IANN Data Exchange Installation Guide

This installation guide provides detailed, step-by-step instructions for setting up the IANN (Intelligent Artificial Neural Network) platform and its associated components. The purpose of this guide is to ensure a smooth and error-free installation process, enabling users to quickly configure the environment and start leveraging the system’s capabilities.

What is IANN?

IANN (Intelligent Artificial Neural Network) is Pragma Edge’s AI-powered unified platform designed to bring intelligence, automation, and predictive analytics into business operations. It combines file tracking, monitoring, and AI-driven insights to ensure end-to-end visibility, operational efficiency, and proactive issue resolution

IANN plays a key role in driving digital transformation across industries by turning traditional data exchanges into intelligent, insight-driven processes.

IANN is built as a modular system with three primary components:

FileGPS – Tracks and monitors file transactions across systems for visibility and SLA compliance.
Monitor – Provides real-time monitoring of processes, system health, and metrics with alerts.

AI – Adds intelligence through predictive analytics, anomaly detection, and GenAI insights.

Who should use this Installation Guide?

This installation guide is designed for a wide range of technical users involved in deploying, maintaining, or supporting IANN solutions. The intended audience includes:

System Administrators / DevOps Engineers

Primary audience.
Responsible for deploying, configuring, and maintaining the software in different environments (development, staging, production).
Use the guide to ensure all prerequisites, system settings, and deployment steps are correctly followed.

IT Support Teams / Technical Support Engineers

Use the guide to troubleshoot installation-related issues reported by end users or internal teams.
May use it to replicate the installation process for issue diagnosis.

Software Developers

Particularly when working in teams or setting up the project locally.
Use the guide to set up their development environments and test deployments.

Customers / End Users (for On-Premises Software)

If the product is delivered for self-hosting, customers’ technical teams use the installation guide.
Often non-developers with technical backgrounds follow these instructions.

Consultants / System Integrators

Third-party professionals who assist organizations in setting up and customizing the product.

QA Engineers / Testers

Use the guide to install and configure the software in test environments to validate features or bug fixes.

What this Installation Guide Covers?

This guide serves as a comprehensive manual for deploying and configuring the IANN platform in various environments (Linux, Windows, OpenShift). It covers the following:

Purpose and Overview of IANN

Clarifies the objective of the document and introduces the IANN FileGPS platform.

System Architecture and Deployment Models

Details the architecture of IANN FileGPS and how it integrates with the broader ecosystem.

Step-by-Step Installation Instructions

Linux Installations: Covers UI, Server, Rest Consumer, and Client Server deployments.
Windows Installations: Includes setup with NSSM, password encryption, component deployments, and validation.
OpenShift Installations: Provides detailed guidance on Helm charts, UI/backend configurations, and deployment steps.

Anomalies Detection Modules

Deployment instructions for File Anomalies and Transaction Anomalies, supporting both Linux and Windows environments.

IANN Monitor Deployment

Instructions for installing IANN Monitor on Linux, Windows, and OpenShift.
Includes pre-requisites, system validation, Helm-based deployments, and anomaly detection features.

IANN File Transaction Search

Covers deployment and configuration of the File Transaction Search module across platforms.

Each section includes detailed prerequisites, component-level configuration, and post-deployment validation steps to ensure successful setup and operation of IANN in production and non-production environments.

IANN AI Installation

i. IANN File Anomalies Deployment

1. Introduction to File Anomalies

IANN File Anomalies is a core component of the IANN FileGPS system, purpose-built monitor and detect irregularities in file transfer activities across enterprise systems. This module plays a critical role in ensuring that files are received as expected, both in terms of time and volume. Irregularities such as missing files, unexpected file arrivals, or abnormal file counts can often signal potential issues that impact data reliability, business continuity, or regulatory compliance.

The File Anomalies module utilizes historical delivery patterns and predictive logic to identify deviations from expected behaviour automatically. This early detection capability empowers teams to act proactively and maintain operational health.

2. Key Benefits of File Anomalies Detection

Timely Identification of Missing or Duplicate Files:
Ensures that no critical data is lost or redundantly processed, which could lead to errors or delays downstream.
Early Resolution of Workflow Disruptions:
Detects anomalies that may disrupt automated pipelines or dependent processes, enabling teams to take corrective action quickly.
Monitoring for Unauthorized or Out-of-Schedule Transfers:
Helps identify files received from unrecognized sources or outside of agreed-upon timeframes, enhancing visibility and security.

By continuously monitoring file activity, the File Anomalies module strengthens the overall reliability of data transfers, supports auditability and compliance, and helps safeguard the performance of file-driven business operations.

3. IANN File Anomalies – Linux Deployment

This section provides step-by-step instructions for installing and configuring the IANN File
Anomalies module on a Linux system. It covers all necessary actions to set up the module, including file extraction, configuration, and execution.

3.1 Linux Deployment Overview

The deployment overview provides steps for the installation and configuration.

Step	Action	Description
1	Create Deployment Directory	Create a target folder (/<Install_dir>/File_Anomalies) using `mkdir` to store and manage all deployment files.
2	Upload Package	Upload File_Anomalies.zip package to the created File_Anomalies directory
3	Extract ZIP File	Use the `unzip` command to extract the contents of the uploaded package inside the deployment folder.
4	Set File Permissions	Use `chmod` to set the correct permissions on all files and directories.
5	Update Configuration File	Edit `config.toml` with your own database credentials and table mappings.
6	Run Pattern Detection	Execute the `file_anomalies_frequency_predictions.sh` shell to generate file delivery patterns
7	Run Daily Anomaly Detection	Execute the `file_anomalies_daily_anomalies.sh` shell to detect missing/unexpected files and irregular counts.

3.2. Pre-requisites

Ensure all prerequisites system, database access, permissions, and the File_Anomalies.zip package are in place before installation.

Category	Requirement (Version -7.0.0)
Operating System	Linux (RHEL 9, CentOS 9)
Python	Version 3.9 or higher
Supported Databases	1. PostgreSQL – Version 15.4 or higher 2. Oracle – Version 19c or higher
Permissions	– Access to install packages and execute binaries – Read/write access to database tables and target directories
Access	Database connection details: – Host name – Port number – DB name – Username – DB Password
Package	File_Anomalies.zip

3.3. Package Contents

The File_Anomalies.zip package includes the following files:

File_Anomalies/

├── config.toml

├── daily_anomalies

├──file_anomalies_frequency_predictions.sh

├──file_anomalies_daily_anomalies.sh

└── File_pattern_prediction

3.4 Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and initiate the File Anomalies module in a server environment

Step 1: Create a Deployment Directory

Before uploading and extracting the application files, you need to create a dedicated directory on the server where the File Anomalies package will reside. This directory will serve as the deployment location for all binaries, configuration files, and logs.

Recommended Location: /<Install_dir>/File_Anomalies

Note: The location where the File_Anomalies directory is created will be referred as <Install_dir> throughout this document

· Run the following command on the Linux server Terminal:

sudo mkdir -p /<Install_dir>/File_Anomalies

<Install_dir>/

├── File_Anomalies

The above command will create a File_Anomalies directory under </Install_dir> directory

Explanation:

Command	Purpose
sudo	Executes the command with superuser privileges (required for /<Install_dir> access)
mkdir	Stands for “make directory”
-p	Ensures that all parent directories in the path are created if not present
/<Install_dir>/File_Anomalies	Target location where the application files will be placed

Step 1.2: Navigate to the Deployment Directory

Once the deployment directory has been successfully created, you must navigate into it before performing any further actions such as uploading the ZIP file or executing shells.

Run the following command on Linux server Terminal:

cd/<Install_dir>/File_Anomalies

Explanation:

Command	Purpose
cd	Stands for change directory—used to move into a specified directory
/<Install_dir>/File_Anomalies	This is the full path to the deployment directory you just created

By running the above command, your terminal session is now working within the deployment directory (File_Anomalies), which ensures:

· All subsequent commands (upload, unzip, install, run) are executed in the correct location

· Files are extracted and generated in an organized and isolated environment

· The application’s binaries, configuration, and logs remain centrally managed

Note: Always confirm that you’re in the correct directory before running the installation or execution of commands. You can check your current directory anytime using below command.

pwd

Step 2: Upload the File_Anomalies.zip Package

1. Upload the File_Anomalies.zip package to the deployment directory created in

Step – 2: /<Install_dir>/File_Anomalies

2. Ensure that the ZIP file is placed directly inside this directory so that subsequent extraction and execution steps occur in a clean and organized environment.

Note: Do not rename or move the ZIP file after uploading. This ensures consistency during the deployment process.

Step 3: Extract the ZIP File on the Server

After successfully uploading the ZIP package to the server, the next step is to extract its contents into the deployment directory.

· Make sure you are inside the correct directory before running the above command:

cd /<Install_dir>/File_Anomalies

· Run the Following Command Inside the Deployment Directory (File_Anomalies):

unzip File_Anomalies.zip

After unzipping the File_Anomalies.zip, the directory looks like below:

File_Anomalies/

├── config.toml

├── daily_anomalies

├──file_anomalies_frequency_predictions.sh

├──file_anomalies_daily_anomalies.sh

└── File_pattern_prediction

These components together enable the full functionality of the IANN FileGPS Anomaly Detection system.

If unzip is Not Installed on the Server
Use the appropriate command based on your Linux distribution to install unzip:

· For RHEL/CentOS-based systems:

sudo yum install unzip

Once the extraction is complete, you can proceed with configuring the application and running the prediction binaries.

Step 4: Set File Permissions

To ensure the deployed application runs smoothly and securely, it’s essential to assign the correct file and folder permissions. Improper permissions can cause execution failures or expose the system to potential security risks.

Command to Set Permissions:

Run the following command to apply read, write, and execute permissions appropriately to all files and subfolders within the deployment directory:

sudo chmod -R 755 /<Install_dir>/File_Anomalies

Step 5: Update the Configuration File

The config.toml file contains essential configuration parameters such as database connection details, table names, and date settings required for the IANN FileGPS Anomalies application.

Location of config.toml:

1. After extracting the ZIP file, the config.toml file will be in the:

/<Install_dir>/File_Anomalies/config.toml

2. Open and Edit the config.toml File:

You can open the configuration file using the vi editor from the terminal:

vi /<Install_dir>/File_Anomalies/config.toml

The above command will open the config.toml file

Update the following details:

[database]
host     = “database-host name”
port     = “database-port number”
dbname   = “databaseb-name”
user     = “database-username”
password = “encrypted-password”

[table_names]
schema_table_name = “database-schema name”
next_date_table_name = “next_date_table” # stores file prediction results
input_table_name = “input_table” # stores input data

output_table_name = “output_table” # stores detected anomalies

2025
date = “YYYY-MM-DD” # (Optional – if not specified, the system date will be used by default)

Save and Exit the File

After making your changes, follow these steps to save and close the file in vi:

1. Press Esc to ensure you’re in command mode

2. Type `:wq!` and press Enter

· `:wq!` stands for write and quit, forcing the save even if the file is marked read-only

Note: Replace all placeholder values with your actual database credentials and table names.

Step 6: Run file_anomalies_frequency_predictions.sh
This step initiates the prediction of expected file delivery patterns by analysing historical input data such as delivery frequency, count ranges, and arrival schedules.

Note: Before running this script make sure historical data is loaded into input_table_name.

Run the Script from the File_Anomalies Directory:

1. Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/File_Anomalies

2. Then execute the pattern prediction script in the background:

./file_anomalies_frequency_predictions.sh

Upon successful execution, a log file named ‘file_pattern_prediction.log’ is generated in the same File_Anomalies directory: /<Install_dir>/File_Anomalies

This log captures:

· Processing steps performed during execution

· Status updates and table creation messages

· Any errors encountered during the run.

Step 7: Run Daily Anomaly Detection
This step performs daily anomaly detection by comparing actual file arrivals against the predicted patterns generated in Step – 6.

It detects:

· Missing files

· Unexpected file arrivals

· File count mismatches

Run the Script from the File_Anomalies Directory

1. Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/File_Anomalies

2. Execute the daily anomaly detection script in the background:

./file_anomalies_daily_anomalies.sh

The script generates a log file named ‘daily_anomalies.log’ This log is created in the /<Install_dir>/File_Anomalies directory.

This log captures:

· Scheduled execution status

· Processing steps

· Errors

What This Does:

· Analyses file delivery for the previous day

· Compares actual file arrivals against expected patterns

· Inserts anomalies into the output table defined in your config.toml

This script is designed to run once per day ideally scheduled using a scheduler to ensure automated, daily anomaly detection without manual execution.

3.5 Troubleshooting Guide – File Anomalies Linux Deployment

This section outlines common issues and their resolutions during the installation and execution of the IANN File Anomalies module.

Issue	Step-by-Step Guidance
Permission denied	Run: `sudo mkdir -p /<Install_dir>/File_Anomalies`
No such file or directory	Confirm directory exists: `cd /<Install_dir>/File_Anomalies`
ZIP file not found	Ensure correct upload location: `ls -l File_Anomalies.zip`
Permission denied when executing scripts	Apply permissions: `sudo chmod -R 755 /<Install_dir>/File_Anomalies`
DB Connection Failure	Confirm DB credentials in config.toml Check network access and DB user permissions
Unable to edit config.toml	Use `sudo vi config.toml`
daily_anomalies.log missing or empty	Review: `tail -n 50 daily_anomalies.log’

4. IANN File Anomalies – Windows Deployment

This guide provides detailed steps to deploy, configure, and run the File Anomalies module on a Windows environment.

4.1 Windows Deployment Overview

The deployment overview provides steps for the installation and configuration.

Steps

Action

Description

Prepare Deployment Directory

Create base deployment folder for application

Upload ZIP Package

Move File_Anomalies.zip into the deployment directory

Extract ZIP File

Unzip using 7-Zip or Windows Explorer

Update Config File

Edit config.toml with environment-specific values

Run File Pattern Prediction

Execute .\File_pattrern_prediction.exe config.toml from cmd

Run Daily Anomalies Prediction

Execute .\Daily_anomalies.exe config.toml from cmd

4.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category	Requirement (Version -7.0.0)
Operating System	Windows 10 / Windows Server 2016 or newer
Python	Version 3.9 or higher
Supported Databases	1. PostgreSQL – Version 12 or higher 2. Oracle – Version 19c or higher
Tools Required	7-Zip or WinRAR, Command Prompt
Database Access	Hostname, Port, DB Name, Username, Password
Permissions	Read/write access to DB and file directories
Package Required	File_Anomalies.zip

4.3 Package Contents

The File_Anomalies.zip package includes the following files:

File_Anomalies/

├── config.toml

├── Daily_anomalies.exe

└── File_pattern_prediction.exe

4.4 Deployment Steps

This section outlines the step-by-step instructions for deploying the File Anomalies module on a Windows system. The deployment includes directory setup, package extraction, configuration.

Step 1: Prepare Deployment Directory

Before installing the application, you need to set up a folder where all the files will be extracted and configured.

Instructions:

Open File Explorer
Create a new folder where you want to install the File Anomalies module.

Example using File Explorer:

- Navigate to your desired location (e.g., C:\).
- Create a new folder named IANN, and inside it, create another folder named File_Anomalies.

Final path (for reference):

C:\IANN\File_Anomalies

Example using Command Prompt:

mkdir C:\IANN\File_Anomalie

Note:

· The path C:\IANN\File_Anomalies is used as an example throughout this guide.

· A different location may be selected based on system configuration or organizational policy.

Step 2: Upload the ZIP Package

After creating the deployment directory, the next step is to upload the application package into it.

Instructions:

1. Locate the File_Anomalies.zip package on your local machine.

2. Copy or move the file into the directory created in Step 1.

Note: The path used in this guide (C:\IANN\File_Anomalies) is for reference only you may use any preferred location on your system.

Example:

C:\IANN\File_Anomalies\File_Anomalies.zip

Important:

Do not rename the ZIP file — the deployment process and extraction scripts are built to work with the filename File_Anomalies.zip.
Make sure the ZIP file is completely transferred before proceeding to extraction.

Step 3: Extract the ZIP File

Once the ZIP package has been uploaded to the deployment directory, extract its contents using one of the methods below.

Use one of the following options to extract the ZIP file:

Option A – Using 7-Zip:

Right-click on the File_Anomalies.zip file.
Navigate to 7-Zip in the context menu.
Select Extract Here to extract the contents into the current directory (C:\IANN\File_Anomalies).

Recommended if you have 7-Zip installed for better control over extraction.

Option B – Using Windows Explorer:

1. Right-click on the File_Anomalies.zip file.

2. Click on Extract All….

3. When prompted, choose the extraction path as:

C:\IANN\File_Anomalies

4. Click Extract to begin unzipping the files.

Note:

Ensure that the files are extracted directly under C:\IANN\File_Anomalies, not into a subfolder like C:\IANN\File_Anomalies\File_Anomalies.

C:\IANN\File_Anomalies\

├── config.toml

├──Daily_anomalies.exe

└── File_pattern_prediction.exe

After extraction, the folder structure should be:

Step 4: Update Configuration File

The application uses a TOML configuration file to load required settings. You need to update this file with appropriate details before running the program.

1. Locate the Configuration File

· Navigate to the following path:

C:\IANN \File_Anomalies\config.toml

2. Open the File

· Open config.toml using a text editor.

3. Update the Configuration Parameters

Update the file with your environment-specific details. Use double quotes ” “ for all values.

[database]
host     = “db-host name”
port     = “db-port number”
dbname   = “db-name”
user     = “db-username”
password = “encrypted-password”

[table_names]
schema_table_name     = “db-schema name”
next_date_table_name = “next_date_table” # stores file prediction results
input_table_name      = “input_table” # stores input data

output_table_name = “output_table” # stores detected anomalies

2025
date = “YYYY-MM-DD” # (Optional – if not specified, the system date will be used by default)

Note:

Always keep double quotes around values (e.g., “2025-07-01”).
Do not modify section headers like [database] or [table_names].

Step 5: Run File_pattern_prediction.exe

This step initiates the frequency-based transaction pattern prediction. It analyzes historical transaction data to detect expected patterns.

Instructions:

1. Open File Explorer (press Windows + E).

2. Navigate to the directory where you extracted the zip file in step 3

3. Click on the address bar at the top of File Explorer, type cmd and press Enter.

4. This opens the Command Prompt directly inside the File_Anomalies folder, where the File_pattern_prediction.exe file is located.

5. Enter the below command in the cmd and press Enter.

.\File_pattrern_prediction.exe config.toml

After Execution:

· The executable will read the configuration details from config.toml and begin analysing transaction frequency patterns.

The script generates a log file named ‘file_pattern_prediction.log’ This log is created in the C:\IANN \File_Anomalies directory and records:

· Scheduled execution status

· Processing steps and errors

Step 6: Run Daily_anomalies.exe

This step triggers the daily anomaly detection module. It checks for missing, unexpected, or abnormal transactions based on the frequency patterns generated in Step 5.

Instructions:

1. In the same Command Prompt window (already open in C:\IANN\File _Anomalies), run the following command:

.\ Daily_anomalies.exe config.toml

2. Press Enter to execute.

After Execution:

· The executable will use the latest pattern data and detect anomalies for the current date.

The script generates a log file named ‘daily_anomalies.log’ This log is created in the C:\IANN \File_Anomalies directory and records:

· Scheduled execution status

· Processing steps

· Errors

Note: This executable is designed to run automatically every 24 hours (once daily)

4.5 Troubleshooting Guide – File Anomalies Windows Deployment

This section provides resolutions for common issues encountered during the installation and execution of the File Anomalies module on Windows systems.

Issue	Step-by-Step Resolution
App Does Not Execute	Run via CMD: .\File_pattern_prediction.exe config.toml .\Daily_anomalies.exe config.toml Avoid double-clicking
*.exe Not Recognized	Ensure correct directory: cd C:\IANN\File_Anomalies List files: dir *.exe
Config Parsing Errors	Ensure config.toml is present and correctly formatted: – Values in double quotes – No trailing commas – Valid section headers like [database]
No Log File Generated	Check for: – Valid config.toml – DB connectivity – Run from CMD to view errors – Directory has write permission
DB Connection Failure	Confirm DB credentials in config.toml Check network access and DB user permissions

ii. IANN Transaction Anomalies Deployment

1. Introduction to Transaction Anomalies

IANN FileGPS Transaction Anomalies is designed to monitor the timely and accurate flow of transactions between systems. In large-scale operations, ensuring that transactions follow expected schedules and volumes is critical for maintaining data integrity and operational continuity.

Irregularities such as missing, unexpected, or abnormal transaction counts may indicate system issues or potential risks. To address this, the system uses anomaly detection to flag deviations and enable timely intervention.

2. Key Benefits of Transaction Anomalies Detection

Ensures Data Integrity: Identifies missing transactions or those occurring outside the expected time windows.
Supports Operational Continuity: Detects anomalies in transaction volumes that could indicate processing issues or delays.
Enhances Security and Compliance: Flags unauthorized, suspicious, or unexpected transaction activity for further investigation.

By proactively detecting deviations in transaction behavior, the IANN FileGPS Transaction Anomalies module helps organizations maintain high levels of reliability and responsiveness. This early warning mechanism reduces the risk of downstream failures, supports compliance with regulatory standards, and improves overall visibility into system performance.

3. IANN Transaction Anomalies – Linux Deployment

This section provides step-by-step instructions for installing and configuring the IANN Transaction Anomalies module on a Linux system. It covers all necessary actions to set up the module, including file extraction, configuration, and execution.

3.1 Linux Deployment Overview

The deployment overview provides steps to the installation and configuration.

Step	Action	Description
1	Create Deployment Directory	Create a target folder `/<Install_dir>/Transaction_Anomalies` using ‘mkdir` to store and manage all deployment files.
2	Upload Package	Upload the Transaction_Anomalies.zip package to the created Transaction_Anomalies directory
3	Extract ZIP File	Use the `unzip` command to extract the contents of the uploaded package inside the deployment folder.
4	Set File Permissions	Use `chmod `to set the correct permissions (e.g., 755) on all files and directories.
5	Update Configuration File	Edit `config.toml` with your own database credentials and table mappings.
6	Run Frequency Detection	Execute the `transaction_anomalies_frequency_prediction.sh` to generate file delivery patterns.
7	Run Daily Anomaly Detection	Execute (transaction_anomalies_daily_anomalies.sh) to detect missing/unexpected files and irregular counts.

3.2 Pre-requisites

Ensure all pre-requisites system, database access, permissions, and the Transaction_Anomalies.zip package are in place before installation.

Category	Requirement (Version -7.0.0)
Operating System	Linux (RHEL 9, CentOS 9)
Python	Version 3.9 or higher
Supported Databases	1. PostgreSQL – Version 15.4 or higher, 2. Oracle – Version 19c or higher
Permissions	– Access to install packages and execute binaries – Read/write access to database tables and target directories
Access	Database connection details: – Host name – Port number – DB name – Username – DB Password
Package	Transaction_Anomalies.zip

3.3 Package Contents

The Transaction_Anomalies.zip package includes the following files

Transaction_Anomalies/

├── config.toml

├── Daily_anomalies_prediction

├── Transaction_Anomalies_Frequency_Prediction

├── transaction_anomalies_frequency_prediction.sh

└── transaction_anomalies_daily_prediction.sh

3.4 Linux Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and initiate the Transaction Anomalies module in a server environment.

Step 1: Create a Deployment Directory

Recommended Location: /<Install_dir>/Transaction_Anomalies

Note: The directory path where Transaction_Anomalies directory is created will be referred to as <Install_dir> throughout this documentation.

Run the following command on Linux server Terminal:

sudo mkdir -p /<Install_dir>/Transaction_Anomalies

The above command will create a Transaction_Anomalies directory under </Install_dir> directory

<Install_dir>/

├── Transaction_Anomalies

Explanation:

Command	Purpose
sudo	Executes the command with superuser privileges (required for /Install_dir access)
mkdir	Stands for “make directory”
-p	Ensures that all parent directories in the path are created if not present
/<Install_dir>/Transaction_Anomalies	Target location where the application files will be placed

Step 1.1: Navigate to the Deployment Directory

Once the deployment directory has been successfully created, you must navigate into it before performing any further actions such as uploading the ZIP file or executing binaries.

Run the following command on Linux server Terminal:

cd /<Install_dir>/Transaction_Anomalies

Explanation:

Command	Purpose
cd	Stands for change directory—used to move into a specified directory
/<Install_dir>/Transaction_Anomalies	This is the full path to the deployment directory you just created

By running this command, your terminal session is now working within the deployment directory (Transaction_Anomalies), which ensures:

· All subsequent commands (upload, unzip, install, run) are executed in the correct location

· Files are extracted and generated in an organized and isolated environment

· The application’s binaries, configuration, and logs remain centrally managed

Note: Always confirm that you’re in the correct directory before running installation or execution of commands. You can check your current directory anytime using below command.

pwd

Step 2: Upload the Transaction_Anomalies.zip Package

· Upload the Transaction_Anomalies.zip package to the deployment directory created in Step –2:
/<Install_dir>/Transaction_Anomalies

· Ensure that the ZIP file is placed directly inside this directory so that subsequent extraction and execution steps occur in a clean and organized environment.

Note: Do not rename or move the ZIP file after uploading. This ensures consistency during the deployment process.

Step 3: Extract the ZIP File on the Server

After successfully uploading the ZIP package to the server, the next step is to extract its contents into the deployment directory.

1. Make sure you are inside the correct directory before running the above command:

cd /<Install_dir>/Transaction_Anomalies

2. Run the Following Command Inside the Deployment Directory:

unzip Transaction_Anomalies.zip

After unzipping the Transaction_Anomalies.zip, the directory looks like below –

Transaction_Anomalies/

├── config.toml

├── Daily_anomalies_prediction

├── Transaction_Anomalies_Frequency_Prediction

├── transaction_anomalies_frequrncy_prediction.sh

└── transaction_anomalies_daily_prediction.sh

These components together enable the full functionality of the IANN FileGPS Anomaly Detection system.

If unzip is Not Installed on the Server

Use the appropriate command based on your Linux distribution to install unzip:

· For RHEL/CentOS-based systems:

sudo yum install unzip

Once the extraction is complete, you can proceed with configuring the application and running the prediction binaries.

Step 4: Set File Permissions

Command to Set Permissions:

Run the following command to apply read, write, and execute permissions appropriately to all files and subfolders within the deployment directory:

sudo chmod -R 755 /<Install_dir>/Transaction_Anomalies

Step 5: Update the Configuration File

The config.toml file contains essential configuration parameters such as database connection details, table names, and date settings required for the IANN FileGPS Anomalies application.

· After extracting the ZIP file, the config.toml file will be located at:

/<Install_dir>/Transaction_Anomalies/config.toml

Open and Edit the config.toml File:

· You can open the configuration file using the vi editor from the terminal:

vi /<Install_dir>/Transaction_Anomalies/config.toml

The above command will open the config.toml file

Inside the config.toml file, update the following fields with the appropriate database connection details and table names as per the target environment configuration.

[database]
host     = “database-host name”
port     = “database-port number”
dbname   = “database-name”
user     = “database-username”
password = “encrypted-password”

[table_names]
schema_table_name     = “database-schema name”
next_date_table_name = “next_date_table” # stores file prediction results
input_table_name      = “input_table” # stores input data

output_table_name = “output_table” # stores detected anomalies

2025
date = “YYYY-MM-DD” # (Optional – if not specified, the system date will be used by default)

Save and Exit the File

After making your changes, follow these steps to save and close the file in vi:

1. Press Esc to ensure you’re in command mode

2. Type `:wq!` and press Enter

a. `:wq!` stands for write and quit, forcing the save even if the file is marked read-only

Note: Replace all placeholder values with your actual database credentials and table names. No code changes are required only update the configuration file.

Step 6: Run transaction_anomalies_frequrncy_prediction.sh

This step initiates the prediction of expected file delivery patterns by analysing historical input data such as delivery frequency, count ranges, and arrival schedules.

Note: Before running this script make sure historical data is loaded into input_table

Run the Script from the Transaction_Anomalies Directory:

· Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/Transaction_Anomalies

· Then execute the pattern prediction script in the background:

./transaction_anomalies_frequency_prediction.sh

The script generates a log file named ‘Transaction_file_pattern_prediction.log’This log is created in the /<Install_dir>/Transaction_Anomalies directory and records:

· Scheduled execution status

· Processing steps and errors

Step 7: Run Daily Anomaly Detection

This step performs daily anomaly detection by comparing actual file arrivals against the predicted patterns generated in Step –6.

It detects:

· Missing files

· Unexpected file arrivals

· File count mismatches

Run the Script from the Transaction_Anomalies Directory

1. Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/Transaction_Anomalies

2. Execute the daily anomaly detection script in the background:

./transaction_anomalies_daily_prediction.sh

Purpose of This Step:

· Analyzes file delivery for the previous day

· Compares actual file arrivals against expected patterns

· Inserts anomalies into the output table defined in your config.toml

· This binary should be scheduled to run daily

· This script is designed to run once per day ideally scheduled using a scheduler to ensure automated, daily anomaly detection without manual execution.

The script generates a log file named ‘Transaction_daily_anomalies.log’This log is created in the /<Install_dir>/Transaction_Anomalies directory and records:

· Scheduled execution status

· Processing steps

· Errors and detected anomalies

3.5 Troubleshooting Guide – Transaction Anomalies Linux Deployment

This section outlines common issues and their resolutions during the installation and execution of the IANN Transaction Anomalies module.

Issue

Step-by-Step Guidance

Permission denied

`sudo mkdir -p /<Install_dir>/Transaction_Anomalies`

No such file or directory

Confirm directory exists: `cd /<Install_dir>/ Transaction _Anomalies`

Permission denied when executing scripts

Apply permissions: `sudo chmod -R 755 /<Install_dir>/ Transaction _Anomalies`

Unable to edit config.toml

Use `sudo vi config.toml`

daily_anomalies.log missing or empty

Review: ‘tail -n 50 daily_anomalies.log’

4. IANN Transaction Anomalies – Windows Deployment

This guide provides detailed steps to deploy, configure, and run the Transaction Anomalies module on a Windows environment.

4.1 Windows Deployment Overview

The deployment overview provides steps for the installation and configuration.

Steps

Action

Description

Prepare Deployment Directory

Create base deployment folder for application

Upload ZIP Package

Move Transaction_Anomalies.zip into the deployment directory

Extract ZIP File

Unzip using 7-Zip or Windows Explorer

Update Config File

Edit config.toml with environment-specific values

Run Frequency Pattern Prediction

Execute Transaction_Anomalies_Frequency_Prediction.exe config.toml from CMD.

Run Daily Anomalies Detection

Execute Transaction_Daily_Anomalies_Prediction.exe config.toml from CMD.

4.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category	Requirement(Version -7.0.0)
Operating System	Windows 10 / Windows Server 2016 or newer
Python	Version 3.9 or higher
Supported Databases	PostgreSQL – Version 15.4 or higher , Oracle – Version 19c or higher
Tools Required	– 7-Zip or WinRAR – Command Prompt
Database Access	Hostname, Port, DB Name, Username, Password
Permissions	Read/write access to DB and file directories
Package Required	Transaction_Anomalies.zip

4.3 Package Contents

The Transaction_Anomalies.zip package includes the following files

Transaction_Anomalies/

├── config.toml

├── Daily_anomalies_prediction.exe

└──Transaction_Anomalies_Frequency_Prediction.exe

4.4 Windows Deployment steps

The Deployment Steps section provides a comprehensive guide to install, configure, and run the Transaction Anomalies module in a Windows environment.

Step 1: Create the Deployment Directory

Before installing the application, you need to set up a folder where all the files will be extracted and configured.

Instructions:

1. Open File Explorer or use Command Prompt / PowerShell.

2. Create a new folder where you want to install the File Anomalies module.

Example using File Explorer:

· Navigate to your desired location (e.g., C:\).

· Create a new folder named IANN, and inside it, create another folder named Transaction_Anomalies.

Final path (for reference):

C:\IANN\Transaction_Anomalies

Example using Command Prompt:

mkdir C:\IANN\Transaction_Anomalie

Note:

The path C:\IANN\Transaction_Anomalies is used as an example throughout this guide.
You may choose a different location based on your system preferences or IT policy.

Step 2: Upload the ZIP Package

After creating the deployment directory, the next step is to upload the application package into it.

Instructions:

3. Locate the File_Anomalies.zip package on your local machine.

4. Copy or move the file into the directory created in Step 1.
The path used in this guide (C:\IANN\Transaction_Anomalies) is for reference only — you may use any preferred location on your system.

Example:

C:\IANN\Transaction_Anomalies\Transaction_Anomalies.zip

Important:

Do not rename the ZIP file — the deployment process and extraction scripts are built to work with the filename Transaction_Anomalies.zip.
Make sure the ZIP file is completely transferred before proceeding to extraction.

Step 3: Extract the ZIP File

Once the ZIP package has been uploaded to the deployment directory, extract its contents using one of the methods below.

Use one of the following options to extract the ZIP file:

Option A – Using 7-Zip:

Right-click on the File_Anomalies.zip file.
Navigate to 7-Zip in the context menu.
Select Extract Here to extract the contents into the current directory (C:\IANN\ Transaction _Anomalies).

Recommended if you have 7-Zip installed for better control over extraction.

Option B – Using Windows Explorer:

1. Right-click on the File_Anomalies.zip file.

2. Click on Extract All….

3. When prompted, choose the extraction path as:

C:\IANN\Transaction _Anomalies

4. Click Extract to begin unzipping the files.

Note:

Ensure that the files are extracted directly under C:\IANN\Transaction_Anomalies, not into a subfolder like C:\IANN\Transaction_Anomalies\Transaction_Anomalies.

Transaction_Anomalies/

├── config.toml

├── Transaction_Daily_Anomalies_Prediction.exe

└── Transaction_Anomalies_Frequency_Prediction.exe

After extraction, the folder structure should be:

Step 4: Update the Configuration File

The application uses a TOML configuration file to load required settings. You need to update this file with appropriate details before running the program.

1. Locate the Configuration File

· Navigate to the following path:

C:\IANN \Transaction_Anomalies\config.toml

2. Open the File

· Open config.toml using a text editor.

3. Update the Configuration Parameters

Update the file with your environment-specific details. Use double quotes ” “ for all values.

[database]
host     = “database-host name”
port     = “database-port number”
dbname   = “database-name”
user     = “database-username”
password = “encrypted-password”

[table_names]
schema_table_name = “database-schema name”
next_date_table_name = “next_date_table” # stores file prediction results
input_table_name = “input_table” # stores input data

output_table_name = “output_table” # stores detected anomalies

2025
date = “YYYY-MM-DD” # (Optional – if not specified, the system date will be used by default)

Note:

Always keep double quotes around values (e.g., “2025-07-01”).
Do not modify section headers like [database] or [table_names].

Step 5: Run Transaction_Anomalies_Frequency_Prediction.exe

This step initiates the frequency-based transaction pattern prediction. It analyzes historical transaction data to detect expected patterns.

Instructions:

1. Open File Explorer (press Windows + E).

2. Navigate to the directory where you extracted the zip file in step 3

3. Click on the address bar at the top of File Explorer, type cmd and press Enter.

4. This opens the Command Prompt directly inside the Transaction_Anomalies folder, where the Transaction_Anomalies_Frequency_Prediction.exe file is located.

5. Enter the below command in the cmd and press Enter.

.\Transaction_Anomalies_Frequency_Prediction.exe config.toml

After Execution:
The script generates a log file named ‘Transaction_file_pattern_prediction.log’This log is created in the C:\IANN\Transaction_Anomalies directory and records:

· Scheduled execution status

· Processing steps and errors

Step 6: Run Transaction_Daily_Anomalies_Prediction.exe

This step triggers the daily anomaly detection module. It checks for missing, unexpected, or abnormal transactions based on the frequency patterns generated in Step 5.

Instructions:

1. In the same Command Prompt window (already open in C:\IANN\Transaction_Anomalies), run the following command:

.\ Transaction_Daily_Anomalies_Prediction.exe config.toml

2. Press Enter to execute.

After Execution:

The script generates a log file named ‘Transaction_Daily_Anomalies.log’This log is created in the C:\IANN\Transaction_Anomalies directory and records:

· Scheduled execution status

· Processing steps

· Errors and detected anomalies

Note: This script is designed to run once per day ideally scheduled using a scheduler to ensure automated, daily anomaly detection without manual execution.

4.5 Troubleshooting Guide – Transaction Anomalies Windows Deployment

This section outlines common issues and their resolutions during the installation and execution of the IANN Transaction Anomalies module.

Issue	Step-by-Step Resolution
App Does Not Execute	Run via CMD: .\Transaction_Anomalies_Frequency_Prediction.exe config.toml .\Transaction_Daily_Anomalies_Prediction.exe config.toml Avoid double-clicking
*.exe Not Recognized	Ensure correct directory: cd C:\IANN\Transcation_Anomalies List files: dir *.exe
Config Parsing Errors	Ensure config.toml is present and correctly formatted: – Values in double quotes – No trailing commas – Valid section headers like [database]
No Log File Generated	Check for: – Valid config.toml – DB connectivity – Run from CMD to view errors – Directory has write permission
DB Connection Failure	Confirm DB credentials in config.toml Check network access and DB user permissions

iii. IANN Monitor Anomalies Deployment

1. Introduction to IANN Monitor Anomalies

IANN Monitor is an advanced self-monitoring analytics solution designed to detect and visualize anomalies from Elasticsearch data streams. It comprises two key components:

Anomalies Engine: Continuously scans and analyses data to identify potential anomalies using configurable logic and thresholds.
Anomaly Preview Interface: A web-based user interface that enables users to review, validate, and investigate detected anomalies in a clear and interactive manner.

2. Key Benefits of IANN Monitor Anomalies

Proactive Anomaly Detection
IANN Monitor enables early identification of irregular patterns or deviations in data, allowing teams to respond promptly and mitigate potential issues before they escalate.

Intuitive Visualization and Validation
With a user-friendly interface, users can easily visualize, interpret, and validate anomalies, ensuring accurate decision-making and reducing the time spent on manual data inspection.
Seamless Integration with Elasticsearch
Designed to work natively with Elasticsearch data streams, IANN Monitor ensures smooth deployment and real-time monitoring without the need for complex configuration or data transformation.

Enhanced Operational Efficiency
By automating anomaly detection and providing clear visual insights, IANN Monitor reduces the burden on engineering and operations teams, allowing them to focus on strategic tasks and system optimization.

By continuously analysing data streams and highlighting irregularities in real time, the IANN Monitor Anomalies module enhances operational visibility, supports faster incident resolution, and reinforces the reliability and integrity of data-driven processes.

3. Pre-requisites

Ensure all prerequisites system, database access, permissions, and the main_iannmonitor_anomalies.zip and IANN_Monitor_Anomalie_preview.zip packages are in place before installation.

Category	Requirement (Version -7.0.0)
Operating System	Linux (RHEL 9, CentOS 9)
Python	Version 3.9 or higher
Supported Databases	1. PostgreSQL – Version 15.4 or higher 2. Oracle – Version 19c or higher
Permissions	– Access to install packages and execute binaries – Read/write access to database tables and target directories
Access	Database connection details: – Host name – Port number – DB name – Username – DB Password
Package	main_iannmonitor_anomalies.zip IANN_Monitor_Anomalie_preview.zip

4. IANN Monitor Anomalies – Linux Deployment

This section provides step-by-step instructions for installing and configuring the IANN Monitor Anomalies module on a Linux system. It covers all necessary actions to set up the module, including file extraction, configuration, and execution.

Step 1: Download Required Files

Ensure you have the following ZIP files:

main_iannmonitor_anomalies.zip
Contains the Anomalies Engine and related configuration for connecting to Elasticsearch.
IANN_Monitor_Anomalie_preview.zip
Provides the executable Preview Interface to display detected anomalies in a web UI.

Step 2: Extract the ZIP Files

After downloading:

Open your terminal.

Navigate to the directory containing the ZIP files.

Run:

unzip main_iannmonitor_anomalies.zip
unzip IANN_Monitor_Anomalie_preview.zip

This will create two new directories containing the binaries required to run the IANN Monitor components.

Package Contents

The IANN_Monitor_Anomalie_preview.zip package includes the following files:

main_iannmonitor_anomalies.zip/

├── config.toml

├──run_anomalies_engine.sh

├──monitor_anomalies_engine.log

The IANN_Monitor_Anomalie_preview.zip package includes the following files:

IANN_Monitor_Anomalie_preview.zip/

├── config.toml

├──IANN_Monitor_Anomalies_preview

├──IANN_Monitor_Anomalies_preview.sh

Step 3: Set Up Configuration (for IANN Monitor Anomalies Engine)

After extracting the main_iannmonitor ZIP file, you’ll need to update the configuration file that the IANN Monitor Anomalies Engine component uses to connect to Elasticsearch and define behaviour.

Update config.ini

Navigate to the extracted main_iannmonitor_anomalies folder.

Open config.ini and update the following fields:

You can do this using a Linux terminal.

Example config.ini Content:

[elasticsearch]

url = http://<elasticsearch-host>:9200

Replace with your actual Elasticsearch endpoint

username = your-username

Elasticsearch username

password = your-encrypted-password

Use Encrypted Elasticsearch password

# Index name to read data from

index_UI = your-index-ui-name

Input index (where your source data is stored)

# Index name to store detected anomalies

index_name = your-anomaly-index

Output index (auto-created if it doesn’t exist)

# Scheduler looks back this many minutes to analyze data

scheduler_time = 1

Time in minutes to fetch and process recent data

Step 4: Installation

Run the Monitor Anomalies Engine:

Once the configuration is complete, you can start the monitor_anomalies_engine using the below steps.

Step 1 – Navigate to the Extracted Folder

Open your terminal and go to the directory where you extracted

main_iannmonitor_anomalies.zip.

For example:

cd <Install_dir> main_iannmonitor_anomalies

Replace <Install_dir>/main_iannmonitor_anomalies with the actual path on your system.

Note: The location where the IANN_Monitor_Anomalies directory is created will be referred as <Install_dir> throughout this document

Step 2 – Start the Application Using the Shell Script

Open your terminal and run the below startup script:

./run_anomalies_engine.sh

This script will:

Start the anomalies engine in the background
Redirect logs to monitor_anomalies_engine.log (or as defined in the script)

Monitor the Logs

A log file named ‘monitor_anomalies_engine.log’ will be created at:
cd <Install_dir>/main_iannmonitor_anomalies directory

To view real-time logs, execute the below script in your terminal

tail -f monitor_anomalies_engine.log

Replace the log file name if a different one is specified in your shell script.

Check if the Process is Running

To verify whether process is running, execute the below script in your terminal

ps -ef | grep main_iannmonitor_anomalies

Stop the Application

If you need to stop the engine, execute the below script in your terminal:

Use ps -ef to get the PID (Process ID)

ps -ef | grep main_iannmonitor_anomalies

Then run kill <PID>

Replace <PID> with the actual process ID

Step 5: Run the Anomalies Preview Interface Service

Note: The service uses config_flask.ini from the preview ZIP. No changes needed unless updating Elasticsearch credentials.

Navigate to the application Location

Open your terminal and move into the directory where the binary was extracted:

cd <Install_dir>/IANN_Monitor_Anomalies_preview

./IANN_Monitor_Anomalies_preview.sh

Note: The location where the IANN_Monitor_Anomalies directory is created will be referred as <Install_dir> throughout this document

Check if Running

ps -ef | grep IANN_Monitor_Anomalies_preview

This will:

Launch the interface in the background
Save output to monitor_preview.log

· A log file named ‘monitor_preview.log’ will be created at:
cd <Install_dir>/IANN_Monitor_Anomalies_preview path

Start the Anomalies Preview Interface:

Run the following command to start the anomalies preview interface in the background:

ps -ef | grep IANN_Monitor_Anomalies_preview

This will:

Launch the application in the background

Save all output and logs to a file named monitor_preview.log in the same folder

To Access the Anomaly Preview UI

Once running, you can open the application in your web browser:

http://<your-server-ip>:<default-port>

Replace <your-server-ip> with the server’s IP address or hostname.

Replace <port> with the correct port number (default is 5000 unless otherwise configured).

Step 6: Enabling IANN Anomalies via YAML Configuration

To enable the IANN Anomalies module, use the application.yml file with a secure passcode.

Step 1:
Locate and update the application.yml file in the application root folder

cd <Install_dir> /IANN_Monitor_Server/

Note: The location where the IANN_Monitor_Anomalies directory is created will be referred as <Install_dir> throughout this document

Step 2:
Open the application.yml file and check for the presence of the apps-enabled key.

If the key is not present, insert the following line just below the dashboard Location key:

If the key already exists, proceed to the next step and update it with the correct value.

Step 3:
The apps-enabled key must be assigned a passcode: this is an xxxxxxxx encoded string.
This passcode is shared with the client via email, along with product details.

Example:

This activates IANN Anomalies module

Passcode-based for controlled feature access

If not set or incorrect:

The system defaults to the standard IANN Monitor module, and IANN Anomalies is disabled.

Step 7: Restart Required After Changing YAML

After editing application.yml:

Stop the existing binary (if running):

ps -ef | grep IANN_Monitor_Anomalies_preview
kill <PID>

Restart the binary:

./IANN_Monitor_Anomalies_preview.sh

Access the application:
After restarting the server, open the application in a browser using:
http://<host>:<port> (replace with actual host and port where the application is deployed), and log in using the valid credentials that were sent via email after the user was created.

Verify Activation:
After successful login, check the side menu. The IANN Anomalies module should now be visible, enabled, and displayed as shown below.

4.1 Troubleshooting Guidance – IANN Monitor Anomalies

Issue	Step-by-step Resolution
run_anomalies_engine.sh not starting	Run: chmod +x run_anomalies_engine.sh
No output in monitor_anomalies_engine.log	Check config.toml for missing/invalid values
Cannot connect to Elasticsearch	Verify url, username, password in config.toml and test connection manually
apps-enabled not activating module	Verify encoded passcode was correctly entered and matches client-provided credentials
Application not reflecting YAML changes	Run kill <PID> and restart using ./IANN_Monitor_Anomalies_preview.sh

5.IANN Monitor Anomalies – Windows Deployment

Step 1: Download Required Files

Please make sure you have the following two ZIP files:

main_iannmonitor_anomalies.zip
Contains the Anomalies Engine and configuration needed to run the Monitor anomalies service, which connects to Elasticsearch, analyses data, and detects anomalies.

IANN_Monitor_Anomalie_preview.zip
Provides the executable Anomaly Preview Interface service, which launches a simple web interface to display to preview the detected anomalies from Elasticsearch.

Place both files in a suitable directory, for example:

C:\IANN\monitor_anomalies_deployment_files\

Step 2: Extract the ZIP Files

Once the required above mentioned files are downloaded, follow these steps to extract them:

Right-click on each ZIP file and choose “Extract All…”.
Extract the contents to:

C:\IANN\monitor_anomalies_deployment_files\

After extraction, two folders will appear:

One for the Anomalies Engine
One for the Anomaly Preview Interface

Step 3: Set Up Configuration (for IANN Monitor Anomalies Engine)

Update config.ini

1. Navigate to the extracted main_iannmonitor_anomalies folder.

2. Open config.ini in a text editor (e.g., Notepad++ or VS Code).

3. Update the following values:

You can do this using a Command Prompt.

Example config.ini Content:

[elasticsearch]

url = http://<elasticsearch-host>:9200

Replace with your actual Elasticsearch endpoint

username = your-username

Elasticsearch username

password = your-encrypted-password

Use Encrypted Elasticsearch password

# Index name to read data from

index_UI = your-index-ui-name

Input index (where your source data is stored)

# Index name to store detected anomalies

index_name = your-anomaly-index

Output index (auto-created if it doesn’t exist)

# Scheduler looks back this many minutes to analyze data

scheduler_time = 1

Time in minutes to fetch and process recent data

Step 4: Installation

Run the Monitor Anomalies Engine:

Open Command Prompt as Administrator.
Navigate to the extracted folder:

cd C:\IANN\monitor_anomalies_deployment_files\main_iannmonitor_anomalies

Run the batch script:

run_anomalies_engine.bat

This will:

· Start the engine in a separate window or background

· Generate logs in a file like monitor_anomalies_engine.log

Monitor the Logs

A log file named ‘monitor_anomalies_engine.log’ will be created at:
cd <Install_dir>/main_iannmonitor_anomalies directory

To view logs, open the log file using a text editor:

notepad monitor_anomalies_engine.log

Check if the Process is Running

ps -ef | grep main_iannmonitor_anomalies

Stop the Application

If you need to stop the engine:

1. Open Task Manager, locate the running process, and end it.

2. Or use the PID (if known) from command line:

taskkill /PID <PID>

Step 5: Run the Anomalies Preview Interface Service

Note: The preview service uses the same config_flask.ini file that was already included in the IANN_Monitor_Anomalie_preview.zip. There’s no need to create a new one just review it if needed to confirm the Elasticsearch connection details are accurate.

1. Open Command Prompt.

2. Navigate to the preview application directory:
CdC:\IANN\monitor_anomalies_deployment_files\IANN_Monitor_Anomalies_preview

3. Run the preview UI using:

IANN_Monitor_Anomalies_preview.bat

This will:

Launch the preview service in the background
Log output to monitor_preview.log

· A log file named ‘monitor_preview.log’ will be created at:
cd <Install_dir>/IANN_Monitor_Anomalies_preview path

To Access the Anomaly Preview UI

Once running, you can open the application in your web browser:

http://<your-server-ip>:<default-port>

Replace <your-server-ip> with the server’s IP address or hostname.

Replace <port> with the correct port number (default is 5000 unless otherwise configured).

Step 6: Enabling IANN Anomalies via YAML Configuration

To enable the IANN Anomalies module, use the application.yml file with a secure passcode.

Step 1:
Locate and update the application.yml file in the application root folder

cd C:\IANN\IANN_Monitor_Server

Step 2:
Open the application.yml file and check for the presence of the apps-enabled key.

If the key is not present, insert the following line just below the dashboardLocation key:

If the key already exists, proceed to the next step and update it with the correct value.

Step 3:
The apps-enabled key must be assigned a passcode: this is an xxxxxxxx encoded string.
This passcode is shared with the client via email, along with product details.

Example:

This activates IANN Anomalies module

Passcode-based for controlled feature access

If not set or incorrect:

The system defaults to the standard IANN Monitor module, and IANN Anomalies is disabled.

Step 7: Restart Required After Changing YAML

After editing application.yml:

Stop the existing binary (if running):

Open Task Manager and search for IANN_Monitor_Anomalies_preview, or run the following command in Command Prompt

tasklist | findstr IANN_Monitor_Anomalies_preview

taskkill /F /IM IANN_Monitor_Anomalies_preview.exe

Restart the binary: Open Command Prompt, navigate to the preview interface folder, and run:

cd C:\path\to\IANN_Monitor_Anomalies_preview

IANN_Monitor_Anomalies_preview.bat

Access the application:
After restarting the server, open the application in a browser using:
http://<host>:<port> (replace with actual host and port where the application is deployed), and log in using the valid credentials that were sent via email after the user was created.

Verify Activation:
After successful login, check the side menu. The IANN Anomalies module should now be visible, enabled, and displayed as shown below.

5.1 Troubleshooting Guidance

This section outlines common issues and their resolutions during the installation and execution of the IANN Monitor Anomalies on Windows.

Issue

Step-by-Step Resolution

run_anomalies_engine.bat not starting

Ensure you are in the correct folder. Right-click > Run as Administrator

monitor_anomalies_engine.log not generated

Check config.ini for correct Elasticsearch settings and valid paths

YAML changes not reflected

Use Task Manager or task kill to stop, then restart the .bat file

IANN_Monitor_Anomalies_preview.exe not stopping

Use Task Manager or task kill /F /IM to force-stop it

Elasticsearch connection fails

Test connectivity using browser or Postman, update config.ini accordingly

6.Use Case & Impact

The Anomalies module introduces an AI-driven layer of intelligence to your monitoring setup by enabling automatic detection of irregular patterns within data streams. This feature is designed to integrate seamlessly into existing environments with minimal disruption and maximum control.

Key Capabilities:

1. Modular Switch

The Anomalies feature is designed with a modular architecture that allows teams to dynamically toggle the anomaly detection functionality on or off via a simple configuration flag (e.g., in the application.yml). This enables seamless switching between:

Standard Monitoring Mode: Operates using traditional log-based or rule-based monitoring mechanisms.
Anomaly Detection Mode: Activates advanced AI models that automatically scan for deviations in data patterns without requiring manual rule definitions.

This modularity allows you to test and gradually roll out the feature in different environments (e.g., staging vs. production) without requiring any code-level changes or redeployments.

2. Secure Activation

To ensure operational safety and compliance, especially in production environments, the Anomalies feature includes built-in controls to restrict unauthorized toggling of its state. These security measures may involve:

Role-based configuration access.
Validation logic that prevents accidental or malicious changes.
Audit readiness by preserving feature state in logs.

This helps safeguard your monitoring workflows from unexpected changes and ensures only authorized personnel can enable or disable anomaly detection in live systems.

3. Backward Compatibility

Introducing AI-based functionality should not disrupt existing setups. The Anomalies feature is designed to preserve all legacy behaviour when it is turned off:

No changes to existing monitoring logic or dashboards.
No impact on current data processing or alerting rules.
Ensures zero regression risk for teams who choose not to opt in immediately.

This makes the feature ideal for enterprises that need stability but want the option to adopt AI monitoring in the future.

4. Flexibility

The feature follows a non-invasive design philosophy, meaning the core monitoring pipeline remains untouched regardless of whether anomaly detection is active. This ensures:

No structural or architectural changes are introduced.
Configuration-based control means no deployment downtime is required.

The system remains maintainable and debuggable without new operational complexity.

iv. IANN File Transaction Search Deployment

1. Introduction to File Transaction Search

The Natural Language SQL Query Generator & Responder is an intelligent interface that empowers users to retrieve insights from enterprise databases using everyday language, eliminating the need for manual query writing or deep technical knowledge. By leveraging IBM Watsonx foundation models through LangChain, this solution converts user questions into accurate PostgreSQL queries, executes them securely, and returns results as natural language answers.

This system is designed to democratize data access, allowing business users, analysts, and non-developers to ask meaningful questions and get data-backed answers instantly. With robust security controls, encrypted credentials, and a modular architecture, it offers a powerful yet user-friendly gateway to enterprise data.

2. Key Benefits of File Transaction Search

Empowers Non-Technical Users with Data Access:
Enables anyone in the organization to extract insights without writing SQL, increasing data-driven decision-making across departments.
Accelerates Insight Discovery
Reduces the time spent on writing, debugging, and validating queries—questions are answered in seconds instead of hours.
Secure & Auditable Data Interaction:

Uses encrypted configurations, HTTP Basic Auth, and controlled model prompts to ensure secure and compliant query access.

Natural Language Output for Business Readability:

Translates raw SQL results into clear, understandable responses, making insights accessible to business stakeholders.

The Natural Language SQL Query Generator & Responder revolutionizes enterprise data access by enabling secure, efficient, and intuitive interaction with complex databases through simple, natural language commands.

3. IANN File Transaction Search – Linux Deployment

This section provides step-by-step instructions for installing and configuring the IANN File Transaction Search module on a Linux system. It covers all necessary actions to set up the module, including file extraction, configuration, and execution.

3.1 Linux Deployment Overview

The deployment overview provides steps for the installation and configuration.

Step	Action	Description
1	Create Deployment Directory	Create a target folder (/<Install_dir>/ File_Transaction_Search) using `mkdir` to store and manage all deployment files.
2	Upload Package	Upload File_Anomalies.zip package to the created File_Transaction_Search directory
3	Extract ZIP File	Use the `unzip` command to extract the contents of the uploaded package inside the deployment folder.
4	Set File Permissions	Use `chmod` to set the permissions on all files and directories.
5	Update Configuration File	Edit `config.toml` with database and table credentials.
6	Run Shell Script	Execute the file_transaction_search.sh shell to generate file delivery patterns

3.2. Pre-requisites

Ensure all prerequisites – system, database access, permissions, and the File_Transaction_Search.zip package are in place before installation.

Category	Requirement (Version -7.0.0)
Operating System	Linux (RHEL 9, CentOS 9)
Python	Version 3.9 or higher
Supported Databases	PostgreSQL – Version 15.4 or higher
Permissions	– Access to install packages and execute binaries – Read/write access to database tables and target directories
Access	Database connection details: – Host name – Port number – Database name – Database Username – Database Password
Package	File_Transaction_Search.zip

3.3. Package Contents

The File_Anomalies.zip package includes the following files:

File_Transaction_Search /

├── config.toml

├── file_transaction_search.sh

└── Flask_app _Filestatus

3.4 Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and initiate the File Anomalies module in a server environment

Step 1: Create a Deployment Directory

Before uploading and extracting the application files, you need to create a dedicated directory on the server where the File Transaction Search package will reside. This directory will serve as the deployment location for all binaries, configuration files, and logs.

Recommended Location: /<Install_dir>/ File_Transaction_Search

Note: The location where the File_Transaction_Search directory is created will be referred as <Install_dir> throughout this document

· Run the following command on the Linux server Terminal:

sudo mkdir -p /<Install_dir>/File_Transaction_Search

<Install_dir>/

├── File_Transaction_Search

The above command will create a File_Transaction_Search directory under </Install_dir> directory

Explanation:

Command	Purpose
sudo	Executes the command with superuser privileges (required for /<Install_dir> access)
mkdir	Stands for “make directory”
-p	Ensures that all parent directories in the path are created if not present
/<Install_dir>/ File_Transaction_Search	Target location where the application files will be placed

Step 1.1: Navigate to the Deployment Directory

Once the deployment directory has been successfully created, you must navigate into it before performing any further actions such as uploading the ZIP file or executing shells.

Run the following command on Linux server Terminal:

cd/<Install_dir>/ File_Transaction_Search

Explanation:

Command	Purpose
cd	Stands for change directory—used to move into a specified directory
/<Install_dir>/ File_Transaction_Search	This is the full path to the deployment directory you just created

By running the above command, your terminal session is now working within the deployment directory (File_Transaction_Search), which ensures:

· All subsequent commands (upload, unzip, install, run) are executed in the correct location

· Files are extracted and generated in an organized and isolated environment

· The application’s binaries, configuration, and logs remain centrally managed

Note: Always confirm that you’re in the correct directory before running the installation or execution of commands. You can check your current directory anytime using below command.

pwd

Step 2: Upload the File_Transaction_Search.zip Package

1. Upload the File_Transaction_Search.zip package to the deployment directory created in

Step – 2: /<Install_dir>/ File_Transaction_Search

2. Ensure that the ZIP file is placed directly inside this directory so that subsequent extraction and execution steps occur in a clean and organized environment.

Note: Do not rename or move the ZIP file after uploading. This ensures consistency during the deployment process.

Step 3: Extract the ZIP File on the Server

After successfully uploading the ZIP package to the server, the next step is to extract its contents into the deployment directory.

· Make sure you are inside the correct directory before running the above command:

cd /<Install_dir>/ File_Transaction_Search

· Run the Following Command Inside the Deployment Directory (File_Anomalies):

unzip File_Transaction_Search.zip

After unzipping the File_Transaction_Search.zip, the directory looks like below:

File_Transaction_Search /

├── config.toml

├──file_transaction_search.sh

└── Flask_app_Filestatus

These components together enable the full functionality of the IANN File Transaction Search Detection system.

If unzip is Not Installed on the Server
Use the appropriate command based on your Linux distribution to install unzip:

· For RHEL/CentOS-based systems:

sudo yum install unzip

Once the extraction is complete, you can proceed with configuring the application and running the prediction binaries.

Step 4: Set File Permissions

Command to Set Permissions:

Run the following command to apply read, write, and execute permissions appropriately to all files and subfolders within the deployment directory:

Sudo chmod -R 755 /<Install_dir>/File_Transaction_Search

Step 5: Update the Configuration File

The config.toml file contains essential configuration parameters such as database connection details, table names, and date settings required for the IANN File Transaction Search application.

Location of config.toml:

1. After extracting the ZIP file, the config.toml file will be in the:

/<Install_dir>/ File_Transaction_Search/config.toml

2. Open and Edit the config.toml File:

You can open the configuration file using the vi editor from the terminal:

vi /<Install_dir>/File_Transaction_Search /config.toml

The above command will open the config.toml file

Update the following details:

[database]
host = “database-host name“
port = “database-port number”
dbname = “databaseb-name”
user = “database-username”
password = “encrypted-password”

[table_names]
schema_table_name =“database-schema name”
input_table_name = “input_table” # stores input data

[Model]
url = “model url“
api_key = “api key“
project_id = “project id“

[security]
SECURITY = “security“
SECRET_KEY = “secret key“
SALT = “salt“

[user]
username = “username“
password = “password“
port = ‘port number’

Save and Exit the File

After making your changes, follow these steps to save and close the file in vi:

1. Press Esc to ensure you’re in command mode

2. Type `:wq!` and press Enter

· `:wq!` stands for write and quit, forcing the save even if the file is marked read-only

Note: Replace all placeholder values with your actual database credentials and table names. No code changes are required only update the configuration file.

Step 6: Run file_transaction_search.sh

This step initiates the prediction of expected file delivery patterns by analysing historical input data such as delivery frequency, count ranges, and arrival schedules.

Note: Before running this script make sure historical data is loaded into input_table_name.

Run the Script from the File_Transaction_Search Directory:

1. Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/ File_Transaction_Search

2. Then execute the pattern prediction script in the background:

./file_transaction _search.sh

A log file named ‘filetransactionsearch.log’ is generated in the ‘/<Install_dir>/ File_Transaction_Search’ directory to capture execution details, warnings, and errors.

To monitor the script execution in real-time, use the following command:

tail -f filetransactionsearch.log

· This command continuously displays new log entries as they are written, allowing you to track script progress, debug messages, and potential errors live during execution.

· Press Ctrl + C to stop the live log view at any time.

3.6 Troubleshooting Guide: File Transaction Search Module

This section outlines common issues and resolutions related to the installation and execution of the IANN File Transaction Search module.

Issue	Step-by-Step Guidance
Permission denied	`sudo mkdir -p /<Install_dir>/File_Transaction_Search`
No such file or directory	Confirm directory exists: `cd /<Install_dir>/ File_Transaction_Search `
ZIP file not found	Ensure correct upload location: `ls -l File_Transaction_Search.zip`
Permission denied when executing scripts	Apply permissions: `sudo chmod -R 755 /<Install_dir>/ File_Transaction_Search `
DB Connection Failure	Confirm DB credentials in config.toml Check network access and DB user permissions
Unable to edit config.toml	Use `sudo vi config.toml`

4. IANN File Transaction Search – Windows Deployment

This guide provides detailed steps to deploy, configure, and run the File Transaction Search module on a Windows environment.

4.1 Windows Deployment Overview

The deployment overview provides steps for the installation and configuration.

Step

Action

Description

Create Deployment Directory

Create a folder `C:\IANN\ File_Transaction_Search` to store all deployment files.

Upload Package

Upload File_Anomalies.zip package to the created File_Transaction_Search directory

Extract ZIP File

Use 7-Zip or Extract All to extract contents into C:\IANN\ File_Transaction_Search.

Set File Permissions

Ensure the .exe files and batch scripts are not blocked; right-click → Properties → Unblock (if needed).

Update Configuration File

Edit `config.toml` with your own database credentials and table mappings.

Run Shell Script

Execute the file_transaction_search.bat shell to generate file delivery patterns

4.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category

Requirement (Version -7.0.0)

Operating System

Windows 10 / Windows Server 2016 or newer

Python

Version 3.9 or higher

Supported Databases

PostgreSQL – Version 15.4 or higher

Tools Required

– 7-Zip or WinRAR
– Command Prompt / PowerShell
– Notepad / Notepad++

Database Access

Hostname, Port, DB Name, Username, Password

Permissions

Read/write access to DB and file directories

Package Required

File_Transaction_Search.zip

4.3 Package Contents

The File_Anomalies.zip package includes the following files:

File_Transaction_Search /

├── config.toml

├──file_transaction _search.bat

└── Flask_app_Filestatus.exe

4.4 Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and run the File Transaction Search module in a Windows environment.

Step 1: Create the Deployment Directory

Before installing the application, you need to set up a folder where all the files will be extracted and configured.

What to Do:

Open File Explorer or use Command Prompt / PowerShell.
Create a new folder where you want to install the File Anomalies module.

Example using File Explorer:

· Navigate to your desired location (e.g., C:\).

· Create a new folder named IANN, and inside it, create another folder named File_Transaction_Search.

Final path (for reference):

C:\IANN\File_Transaction_Search

Example using Command Prompt:

mkdir C:\IANN\File_Transaction_Search

Note:

The path C:\IANN\File_Transaction_Search is used as an example throughout this guide.
You may choose a different location based on your system preferences or IT policy.

Step 2: Upload the ZIP Package

After creating the deployment directory, the next step is to upload the application package into it.

What to Do:

Locate the File_Anomalies.zip package on your local machine.
Copy or move the file into the directory created in Step 1.
The path used in this guide (C:\IANN\ File_Transaction_Search) is for reference only — you may use any preferred location on your system.

Example:

C:\IANN\ File_Transaction_Search \File_Transaction_Search.zip

Important:

Do not rename the ZIP file — the deployment process and extraction scripts are built to work with the filename File_Transaction_Search.zip.
Make sure the ZIP file is completely transferred before proceeding to extraction.

Step 3: Extract the ZIP File

Once the ZIP package has been uploaded to the deployment directory, extract its contents using one of the methods below.

Use one of the following options to extract the ZIP file:

Option A – Using 7-Zip:

Right-click on the File_Transaction_Search.zip file.
Navigate to 7-Zip in the context menu.
Select Extract Here to extract the contents into the current directory (C:\IANN\ File_Transaction_Search).

Recommended if you have 7-Zip installed for better control over extraction.

Option B – Using Windows Explorer:

Right-click on the File_Transaction_Search.zip file.
Click on Extract All….
When prompted, choose the extraction path as:

C:\IANN\ File_Transaction_Search

Click Extract to begin unzipping the files.

Note:

Ensure that the files are extracted directly under C:\IANN\File_Transaction_Search, not into a subfolder like C:\IANN\File_Transaction_Search\File_Transaction_Search.

C:\IANN\ File_Transaction_Search \

├── config.toml

├── File_Transaction_Search.bat

└── Flask_app_Filestatus.exe

After extraction, the folder structure should be:

Step 4: Install Python and Required Libraries

To run the File Anomalies module, Python and a few supporting libraries must be installed on your system.

1. Check if Python is Installed

Open Command Prompt and run the following command:

python –version

If Python is installed, you’ll see a version number (e.g., Python 3.10.5).

2. If Python Is Not Installed:

Download the latest Python version from the official website:

https://www.python.org/downloads/

During installation:

· Ensure the checkbox “Add Python to PATH” is selected.

· Complete the installation using default settings or customize as needed.

3. Install Required Python Libraries

Once Python is installed, use the pip command to install the necessary libraries.

pip install psycopg2-binary pandas toml

Run the following command in Command Prompt:

This will install:

· psycopg2-binary: for connecting to PostgreSQL (if required in future or other modules)

· pandas: for working with CSV and data analysis

· toml: for reading the configuration file (config.toml)

Note: If your environment does not support PostgreSQL, psycopg2-binary will still install without causing issues and can be safely ignored if unused.

Step 5: Update Configuration File

The application uses a TOML configuration file to load required settings. You need to update this file with appropriate details before running the program.

1. Locate the Configuration File

Navigate to the following path:

C:\IANN\ File_Transaction_Search \config.toml

2. Open the File

· Open config.toml using a text editor like Notepad or Notepad++.

3. Update the Configuration Parameters

Update the file with your environment-specific details. Use double quotes ” “ for all values.

[database]
host = “database-host name“
port = “database-port number”
dbname = “databaseb-name”
user = “database-username”
password = “encrypted-password”

[table_names]
schema_table_name =“database-schema name”
input_table_name = “input_table” # stores input data

[Model]
url = “model url“
api_key = “api key“
project_id = “project id“

[security]
SECURITY = “security“
SECRET_KEY = “secret key“
SALT = “salt“

[user]
username = “username“
password = “password“
port = ‘port number’

Note:

Always keep double quotes around values (e.g., “2025-07-01”).
Do not modify section headers like [database] or [table_names].

Step 6: Run file_transaction _search.bat

Using the Provided Executable and Batch Script

The package includes:

Flask_app_Filestatus.exe — the executable that performs the prediction
file_transaction _search.bat — a batch script that runs the .exe with the correct parameters

Instructions:

Open Command Prompt.
Navigate to the installation directory:

cd C:\IANN\File_Transaction_Search

file_transaction _search.bat

Run the batch script:

What the Batch Script Does:

The script internally executes:

cd C:\IANN\File_Transaction_Search

Flask_app_FileStatus.exe –config config.toml –mode pattern

A log file named ‘filetransactionsearch.log’ is generated in the C:\IANN\File_Transaction_Search directory to capture execution details, warnings, and errors.

4.5 Troubleshooting Guide

This section outlines common issues and their resolutions during the installation and execution of the IANN File Transaction Search module on Windows.

Issue

Step-by-Step Guidance

Executable or scripts not found

Ensure all files are in:
‘C:\IANN\File_Transaction_Search’
Avoid nested folders; keep .exe and config.toml directly inside.

Configuration file syntax error

Open config.toml and check:
• All string values in double quotes
• Section headers like [database], [table_names] are intact

Parsing or syntax errors

Open file using:
‘notepad C:\IANN\File_Transaction_Search\config.toml’
Ensure:
• All values are in double quotes
• Section headers are intact (e.g., [database])

config.toml not found

Ensure current path is correct:
‘cd C:\IANN\File_Transaction_Search’

DB Connection Failure

Confirm DB credentials in config.toml

Check network access and DB user permissions

Log not created after starting service

– Ensure service status is Running
– Reopen Services.msc and check status
– Manually run EXE to observe errors

v. IANN Error Recommendation Installation

1. Introduction to Error Recommendation

The Error Recommendation module is a key component of the IANN FileGPS application, developed under the IANN (Intelligent Artificial Neural Networks) initiative. Its primary objective is to intelligently assist in diagnosing and addressing Managed File Transfer (MFT) errors, which are common yet complex issues in enterprise file exchange systems.

File transfers often encounter a wide range of errors due to system misconfigurations, network issues, or policy violations. Traditionally, resolving these errors requires significant manual effort and technical expertise. To overcome this challenge, the Error Recommendation module leverages advanced Generative AI techniques to analyses error patterns and provide detailed, context-aware recommendations for resolution.

By automatically identifying the type of file transfer error and offering clear troubleshooting guidance, this solution empowers users to handle common MFT issues more effectively, reducing dependency on support teams and accelerating issue resolution. While it currently focuses on the 32+ most frequent file transfer errors observed over the last three months, the module is designed to evolve with future enhancements to cover a broader range of error types

2. Key Benefits of Error Recommendation

Accelerated Error Resolution:
Users receive immediate, AI-generated recommendations tailored to the specific file transfer error, significantly reducing the time required to troubleshoot issues.
Reduced Support Dependency:
By empowering end users with actionable insights, the system minimizes the need for intervention by specialized support teams, improving overall efficiency.
Enhanced Operational Continuity:
Prompt error detection and guidance help prevent delays in critical file transfers, ensuring smoother and more reliable business operations.
Focused Coverage of High-Frequency Errors:
The module targets the 32+ most commonly occurring MFT errors from the past three months, offering high-impact value where it’s most needed.
Improved User Confidence and Autonomy:
With clear explanations and step-by-step recommendations, users can confidently resolve errors independently without relying on trial-and-error methods.
Scalable and Future-Ready Design:
The system is designed to evolve and support additional error types in the future, making it a scalable solution for growing enterprise needs.

3. IANN Error Recommendation – Linux Deployment

This section provides step-by-step instructions for installing and configuring the IANN Error Recommendation module on a Linux system. It covers all necessary actions to set up the module, including file extraction, configuration, and execution.

3.1 Linux Deployment Overview

The deployment overview provides steps for the installation and configuration.

Step	Action	Description
1	Create Deployment Directory	Create a target folder (/<Install_dir>/Error_Recommendation) using `mkdir` to store and manage all deployment files.
2	Upload Package	Upload Error_Recommendation.zip package to the created Error_Recommendation directory
3	Extract ZIP File	Use the `unzip` command to extract the contents of the uploaded package inside the deployment folder.
4	Set File Permissions	Use `chmod` to set the correct permissions on all files and directories.
5	Update Configuration File	Edit `configuration.json` with required details
6	Run Shell Script	Execute the streaming.sh shell script for error recommendations

3.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category	Requirement (Version -7.0.0)
Operating System	Linux (RHEL 9, CentOS 9)
Python	Version 3.11 or higher
Package	Error_Recommendation.zip
IBM Watson Credentials	For LLM-based recommendations

3.3 Package Content

The Error_Recommendation.zip package includes the following files:

Error_Recommendation/

├── Configuration.json

├── Error_info.csv

├──Error_Recommendation.sh

└── streaming

3.4 Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and initiate the Error Recommendation module in a Linux server environment

Step 1: Create a Deployment Directory

Before uploading and extracting the application files, you need to create a dedicated directory on the server where the Error_Recommendation package will reside. This directory will serve as the deployment location for all binaries, configuration files, and logs.

Recommended Location: /<Install_dir>/Error_Recommendation

Note: The location where the Error_Recommendation directory is created will be referred as <Install_dir> throughout this document

· Run the following command on the Linux server Terminal:

sudo mkdir -p /<Install_dir>/ Error_Recommendation

<Install_dir>/

├── Error_Recommendation

The above command will create a Error_Recommendation directory under </Install_dir> directory

Explanation:

Command	Purpose
sudo	Executes the command with superuser privileges (required for /<Install_dir> access)
mkdir	Stands for “make directory”
-p	Ensures that all parent directories in the path are created if not present
/<Install_dir>/ Error_Recommendation	Target location where the application files will be placed

Step 1.2: Navigate to the Deployment Directory

Once the deployment directory has been successfully created, you must navigate into it before performing any further actions such as uploading the ZIP file or executing shells.

Run the following command on Linux server Terminal:

cd/<Install_dir>/ Error_Recommendation

Explanation:

Command	Purpose
cd	Stands for change directory—used to move into a specified directory
/<Install_dir>/ Error_Recommendation	This is the full path to the deployment directory you just created

By running the above command, your terminal session is now working within the deployment directory (Error_Recommendation), which ensures:

· All subsequent commands (upload, unzip, install, run) are executed in the correct location

· Files are extracted and generated in an organized and isolated environment

· The application’s binaries, configuration, and logs remain centrally managed

Note: Always confirm that you’re in the correct directory before running the installation or execution of commands. You can check your current directory anytime using below command.

pwd

Step 2: Upload the Error_Recommendation.zip Package

1. Upload the Error_Recommendation.zip package to the deployment directory created in

Step – 2: /<Install_dir>/ Error_Recommendation

2. Ensure that the ZIP file is placed directly inside this directory so that subsequent extraction and execution steps occur in a clean and organized environment.

Note: Do not rename or move the ZIP file after uploading. This ensures consistency during the deployment process.

Step 3: Extract the ZIP File

After successfully uploading the ZIP package to the server, the next step is to extract its contents into the deployment directory.

· Make sure you are inside the correct directory before running the above command:

cd /<Install_dir>/Error_Recommenadtion

· Run the Following Command Inside the Deployment Directory (Error_Recommendation):

unzip Error_Recommendation.zip

After unzipping the Error_Recommendation.zip, the directory looks like below:

Error_Recommendation/

├── Configuration.json

├── Error_info.csv

├──Error_Recommendation.sh

└── streaming

If unzip is Not Installed on the Server
Use the appropriate command based on your Linux distribution to install unzip:

· For RHEL/CentOS-based systems:

sudo yum install unzip

Once the extraction is complete, you can proceed with configuring the application and running the prediction binaries.

Step 4: Set File Permissions

Command to Set Permissions:
Run the following command to apply read, write, and execute permissions appropriately to all files and subfolders within the deployment directory:

sudo chmod -R 755 /<Install_dir>/Error_Recommendation

Step 5: Update the Configuration File

The Configuration.json file contains essential configuration parameters such as port, username, password , API_Key required for the IANN FileGPS application.

Location of Configuration.json:

1. After extracting the ZIP file, the file Configuration.json will be in the:

<Install_dir>/Error_Recommendation/Configuration.json

2. Open and edit the Configuration.json File:

You can open the configuration file using the vi editor from the terminal:

vi /<Install_dir>/Error_Recommendation/Configuration.json

The above command will open the Configuration.json file

“port”: “port-number”,

“csv_path”: “path to the csv file in the deployment directory”,

“api_key”: “IBM-Watson-LLM-API-Key”,

“project_id”: “IBM-Watson_Project-ID”,

“username_auth”: “username”,

“password_auth”: “user-password”,

“secret_key”: “Secret-Key”,

“salt”: “Salt”

Update the following details:

Save and Exit the File

After making your changes, follow these steps to save and close the file in vi:

1. Press Esc to ensure you’re in command mode

2. Type `:wq!` and press Enter

· `:wq!` stands for write and quit, forcing the save even if the file is marked read-only

Step 6: Execute Error_Recommendation.sh

This step initiates the error recommendation process, which analyses historical file transfer error data from a CSV file to generate intelligent, AI-based troubleshooting suggestions for frequently occurring errors.

Run the Script from the Error_Recommendation Directory:

Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/Error_Recommendation

Then execute the error recommendation script in the background:

./Error_Recommendation.sh

Once execution is complete, the system will process the Error_info.CSV and generate recommended resolutions for the identified error types.

A log file named ‘Error_recommendation_streaming.log’ is created in the /<Install_dir>/Error_Recommendation directory. This log captures execution steps, status messages, and any errors encountered during the process.

4.5 Troubleshooting Guide

This section outlines common issues and their resolutions during the installation and execution of the IANN Error Recommendation module on Linux.

Issue

Step-by-Step Guidance

Executable or scripts not found

Ensure all required files are placed directly in: /<Install_dir>/Error_Recommendation/

CSV file not found (Error_info.csv)

1. Place Error_info.csv in: /<Install_dir>/Error_Recommendation/
2. Do not rename the file
3. Ensure it’s not open in another program (especially via network mounts or Excel)

Script does not execute (Permission Denied)

Run: chmod +x Error_Recommendation.sh
Ensure correct file ownership using chown if needed

Output not generated (no recommendations)

1. Open config using: vi /<Install_dir>/Error_Recommendation/Configuration.json
2. After editing, save using ‘:wq!’
3. Ensure file format is JSON-valid using online validator if needed

DB Connection Failure

Confirm DB credentials in config.toml

Check network access and DB user permissions

4. IANN Error Recommendation – Windows Deployment

This guide provides step-by-step instructions for installing and configuring the IANN Error Recommendation module on a Windows system. The module assists in identifying and resolving Managed File Transfer (MFT) errors using AI-generated recommendations.

4.1 Windows Deployment Overview

The deployment overview provides steps for the installation and configuration.

Steps

Action

Description

Prepare Deployment Directory

Create base deployment folder for application

Upload ZIP Package

Move Error_Recommendation.zip into the deployment directory

Extract ZIP File

Unzip using 7-Zip or Windows Explorer

Update Config File

Edit configuration.json with environment-specific values

Launch CMD in NSSM Directory

Open command prompt from nssm.exe directory

Install Error_Recommendation Service (CMD)

Run NSSM install for Error_Recommendation

Configure NSSM Fields

Populate required fields: Path, Startup Dir, Args

Install the Service

Finalize service registration

Start the Service

Begin background execution of the module

4.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category	Requirement (Version -7.0.0)
Operating System	Windows 10 or higher (64-bit)
Python	Version 3.11 or higher
Tools Required	7-Zip or WinRAR, Command Prompt, NSSM (Non-Sucking-Service-Manager)
Package	Error_Recommendation.zip
IBM Watson API Key	For LLM-based recommendations

4.3 Package Contents

The Error_Recommendation.zip package includes the following files:

Error_Recommendation/

├── Configuration.json

├── Error_info.csv

└── streaming.exe

4.4 Deployment Steps

This section outlines the complete, step-by-step process to deploy the Error Recommendation Module on a Windows machine.

Step 1: Prepare Deployment Directory

Before installing the application, you need to set up a folder where all the files will be extracted and configured.

Instructions:

Open File Explorer
Create a new folder where you want to install the Error_Recommendation module.

Example using File Explorer:

· Navigate to your desired location (e.g., C:\).

· Create a new folder named IANN, and inside it, create another folder named Error_Recommendation.

Final path (for reference):

C:\IANN\Error_Recommendation

Example using Command Prompt:

mkdir C:\IANN\ Error_Recommendation

Note:

· The path C:\IANN\Error_Recommendation is used as an example throughout this guide.

· A different location may be selected based on system configuration or organizational policy.

Step 2: Upload the Error_Recommendation.ZIP File

Copy or move the provided Error_Recommendation.zip file to the installation directory created in Step 1.

Instructions:

Move the ZIP file to:

C:\IANN\Error_Recommendation\Error_Recommendation.zip

Ensure: The filename remains unchanged and corresponds to the version shared by the development team.

Step 3: Extract the ZIP File

Use either 7-Zip or Windows Explorer to extract the contents of the ZIP package.

Option A: Using 7-Zip

Right-click on Error_Recommendation.zip.
Select 7-Zip > Extract Here.

Option B: Using Windows Explorer

Right-click on Error_Recommendation.zip.
Select Extract All….
Set the destination folder as:

Error_Recommendation/

├── Configuration.json

├── Error_info.csv

└── streaming.exe

After extraction, the folder will look like:

Ensure: All files including configuration files and executables are extracted correctly.

Step 4: Update the Configuration File

The application uses a JSON configuration file to load required settings. You need to update this file with appropriate details before running the program.

1. Locate the Configuration File

· Navigate to the following path:

C:\IANN \Error_Recommendation\config.toml

2. Open the File

· Open Configuration.json using a text editor.

3. Update the Configuration Parameters

Edit the Configuration.json file to provide paths and credentials.

“port”: “port-number”,

“csv_path”: “path to the csv file in the deployment directory”,

“api_key”: “IBM-Watson-LLM-API-Key”,

“project_id”: “IBM-Watson-Project-ID”,

“username_auth”: “username”,

“password_auth”: “user-password”,

“secret_key”: “Secret-Key”,

“salt”: “Salt”

Step 5: Launch Command Prompt in NSSM Directory

1. Open File Explorer (Windows + E).

2. Navigate to the folder where you extracted NSSM (e.g., nssm-2.24).

3. Open the win64 folder

4. Click on the address bar at the top of File Explorer, type cmd and press Enter.

5. This opens the Command Prompt directly inside the NSSM win64 folder, where the nssm.exe file is located.

Step 6: Run the Install Command

1. In the Command Prompt window, type the following:

nssm install Error_Recommendation

2. Then press Enter.

This launches the NSSM Service Installer interface.

Step 7: Fill in Service Details in the NSSM Window

You will now configure 3 main fields:

1. Field 1: Path

· Click the … button next to the Path field.

· Navigate to the streaming.exe file

Example path:

C:\IANN \Error_Recommendation \streaming.exe

· Select streaming.exe and click Open.

2. Field 2: Startup Directory

· Click the … button next to the Startup Directory field.

· Navigate to the Error_Recommendation folder:

Error_Recommendation

Example:

C:\IANN \ Error_Recommendation

3. Field 3: Arguments

In the Arguments field, append the path to the config.toml file and ensure the filename config.toml is included at the end

C:\IANN \ Error_Recommendation \configguration.json

Step 8: Install the Service

· Once all required fields (Path, Startup Directory, and Arguments) have been populated in the NSSM Service Installer window, click the Install service button at the bottom.

· Upon successful installation, a confirmation message will appear:

Service “Error_Recommendation” installed successfully!

· This indicates that the service has been registered with the system but is not yet running. Proceed to the next step to start the service.

Step 9: Start the Error_Recommendation Service

After successfully installing the service, the next step is to start it from the Windows Services Manager.

Instructions:

1. Open the Task Manager

· Press Ctrl + Shift + Esc to launch the Task Manager.

2. Access the Services Manager

· In Task Manager, click on the Services tab.

· At the bottom-right corner, click on Open Services.

· This action will launch the Windows Services Manager (services.msc), where all system services are listed.

3. Locate the Installed Service

· In the Services Manager window, scroll through the list of services.

· Locate the service named:
Error_Recommendation

4. Start the Service

· Right-click on the Error_Recommendation service.

· From the context menu, select Start.

A loading dialog may briefly appear as Windows initializes the service.

5. Verify Service Status

· Once the service starts successfully, the Status column for Error_Recommendation will update to Running.

· This indicates that the application is now actively running in the background as a Windows service.

· Additionally, a log file named ‘Error_recommendation_streaming.log’ will be generated in the configured logs directory.
This file records runtime logs and can be used for monitoring service activity and troubleshooting issues.

Note: The service will now automatically run in the background and can be managed through the Services Manager where you can start, stop, or restart it as needed.

4.5 Troubleshooting Guidance

This section outlines common issues and their resolutions during the installation and execution of the IANN Error Recommendation module on Windows.

Issue

Step-by-Step Guidance

Executable or script not found

Ensure all required files are extracted to: `C:\IANN\Error_Recommendation`

Required files include: streaming.exe, Configuration.json, Error_info.csv, Error_Recommendation.sh

Error_info.csv Not Found

Ensure Error_info.csv is in `C:\IANN\Error_Recommendation` and not open during execution

NSSM Not Recognized

Navigate to `nssm` directory and run command there

Service fails to start from Services Manager

Validate:
– Path: streaming.exe
– Startup directory: Error_Recommendation
– Arguments: correct config file path

Can’t find Error_recommendation_streaming.log

Check configured path in Configuration.json; ensure write access and correct folder structure

vi. IANN Error Reprocessing Installation

1. Introduction to Error Reprocessing

In complex file-based systems, errors during file processing are inevitable and can disrupt business-critical workflows. The Error Reprocessing use case is designed to intelligently and efficiently address such errors through automated, rule-based, or manual remediation strategies.

This solution supports three primary approaches for error resolution:

Rule-based Fix – Predefined rules guide the system in handling known error scenarios with consistent logic.
AI-based Fix – An AI model analyses the error and determines the best course of action using learned behaviour and historical patterns.
Manual Fix – For cases requiring human oversight, errors are flagged for manual intervention with no automated action taken.

To enhance traceability and performance analysis, the system includes an Automated Fix module. This module logs every attempt made by the AI or rule engine to fix errors, providing visibility into the steps taken and tracking success or failure rates over time. For instance, users can monitor how errors like “SSH Known Host Key Error” were resolved and view the detailed activity history from the interface.

The module also allows configuration of fix strategies and retry policies, ensuring robust automation with controlled fallback mechanisms. This comprehensive framework streamlines the error handling process, reduces manual workload, and ensures higher reliability in file transaction workflows.

2. Key Benefits of Error Reprocessing

Reduced Manual Intervention
Automatically resolves common file processing errors using rule-based or AI-driven logic, minimizing the need for human involvement.
Faster Error Resolution
Automating the detection and fix process significantly reduces resolution time, improving overall system efficiency.
Improved System Reliability
Retry mechanisms and intelligent handling ensure higher job success rates, resulting in more stable and predictable file transfers.

3. IANN Error Reprocessing – Linux Deployment

The IANN Error Reprocessing module can be seamlessly deployed on Linux servers to automate the resolution of file processing errors using rule-based, AI-driven, or manual strategies. This section outlines the steps required to set up and configure the module in a Linux environment for reliable and efficient error handling.

3.1 Linux Deployment Overview

The deployment overview provides steps for the installation and configuration.

Step

Action

Description

Create Deployment Directory

Create a target folder (/<Install_dir>/Error_Reprocessing) using `mkdir` to store and manage all deployment files.

Upload Package

Upload Error_Reprocessing.zip package to the created Error_Reprocessing directory

Extract ZIP File

Use the `unzip` command to extract the contents of the uploaded package inside the deployment folder.

Set File Permissions

Use `chmod` to set the correct permissions on all files and directories.

Update Configuration File

Edit `config.ini ` with required details

Run Shell Script

Execute the iann_core_api.sh shell script for error recommendations

3.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category

Requirement (Version -7.0.0)

Operating System

Linux (RHEL 9, CentOS 9)

Python

Version 3.11 or higher

Package

Error_Reprocessing.zip

3.3 Package Content

The Error_Reprocessing.zip package includes the following files:

Error_Reprocessing/

├── Config.ini

├──iann_core_api.sh

└── iann_core_api

3.4 Deployment Steps

The Deployment Steps section provides a comprehensive guide to install, configure, and initiate the Error Reprocessing module in a Linux server environment

Step 1: Create a Deployment Directory

Before uploading and extracting the application files, you need to create a dedicated directory on the server where the Error_Reprocessing package will reside. This directory will serve as the deployment location for all binaries, configuration files, and logs.

Recommended Location: /<Install_dir>/Error_Reprocessing

Note: The location where the Error_Reprocessing directory is created will be referred as <Install_dir> throughout this document

· Run the following command on the Linux server Terminal:

sudo mkdir -p /<Install_dir>/ Error_Reprocessing

The above command will create a Error_Recommendation directory under </Install_dir> directory

Explanation:

Command

Purpose

sudo

Executes the command with superuser privileges (required for /<Install_dir> access)

mkdir

Stands for “make directory”

-p

Ensures that all parent directories in the path are created if not present

/<Install_dir>/ Error_Reprocessing

Target location where the application files will be placed

Step 1.2: Navigate to the Deployment Directory

Once the deployment directory has been successfully created, you must navigate into it before performing any further actions such as uploading the ZIP file or executing shells.
Run the following command on Linux server Terminal:

cd/<Install_dir>/ Error_Reprocessing

Explanation:

Command

Purpose

Stands for change directory—used to move into a specified directory

/<Install_dir>/ Error_Reprocessing

This is the full path to the deployment directory you just created

By running the above command, your terminal session is now working within the deployment directory (Error_Reprocessing), which ensures:

· All subsequent commands (upload, unzip, install, run) are executed in the correct location

· Files are extracted and generated in an organized and isolated environment

· The application’s binaries, configuration, and logs remain centrally managed

<Install_dir>/

├── Error_Reprocessing

Note: Always confirm that you’re in the correct directory before running the installation or execution of commands. You can check your current directory anytime using below command.

pwd

Step 2: Upload the Error_Reprocessing.zip Package

1. Upload the Error_Recommendation.zip package to the deployment directory created in

Step – 2: /<Install_dir>/ Error_Recprocessing

2. Ensure that the ZIP file is placed directly inside this directory so that subsequent extraction and execution steps occur in a clean and organized environment.

Note: Do not rename or move the ZIP file after uploading. This ensures consistency during the deployment process.

Step 3: Extract the ZIP File

After successfully uploading the ZIP package to the server, the next step is to extract its contents into the deployment directory.

· Make sure you are inside the correct directory before running the above command:

cd /<Install_dir>/Error_Reprocessing

· Run the Following Command Inside the Deployment Directory (Error_Reprocessing):

unzip Error_Reprocessing.zip

After unzipping the Error_Reprocessing.zip, the directory looks like below:

Error_Reprocessing/

├── Config.ini

├──iann_core_api.sh

└── iann_core_api

If unzip is Not Installed on the Server
Use the appropriate command based on your Linux distribution to install unzip:

· For RHEL/CentOS-based systems:

sudo yum install unzip

Once the extraction is complete, you can proceed with configuring the application and running the prediction binaries.

Step 4: Set File Permissions

Command to Set Permissions:
Run the following command to apply read, write, and execute permissions appropriately to all files and subfolders within the deployment directory:

sudo chmod -R 755 /<Install_dir>/Error_Reprocessing

Step 5: Update the Configuration File

The Config.ini file contains essential configuration parameters such as Database details, port, username, password, API_Key required for the IANN FileGPS application.

Location of Config.ini:

1. After extracting the ZIP file, the file Config.ini will be in the:

<Install_dir>/Error_Reprocessing/Config.ini

2. Open and edit the Config.ini File:

You can open the configuration file using the vi editor from the terminal:

vi /<Install_dir>/Error_Reprocessing/ Config.ini

The above command will open the Config.ini file

Update the following details:

[postgresql]

database = database-name

host = host-name

username = user-name

password = encryptedpassword

schema = schema-name

port = port-number

driver_name = driver-name

[oracle_db]

jvm_path = jvm-path

jar_file = jar-file-path

db_schema = database-schema-name

java_classname = java-classname

db_url = database-url

db_user = database-user

db_password = database-encrypted-password

db_type = database-type

[logs]

path = logfile-path

[key]

secret_key = secret-key for encryption of passwords

salt = salt for encryption of passwords

[email]

sender = sender-email-address

password = encrypted-email-password

from_email = from-email-address

email_smtp_host = smtp-host

email_smtp_port = smtp-port

[zone_id]

zone_id = America/Chicago

[API]

runJob_url = runjob-url

get_mailboxes = mailbox-url

url_multi_reprocess = multi-reprocess-url

url_reprocess = url-reprocess

url_getPartners_Id = partner_id-url

url_getPartners_Host = partner-host-url

url_getApplication_Host = application-host-url

url_getKnown_Host = known-Host-url

url_createKnown_Host = create-known-host-url

check_service_status = service-status-url

envelopes_url = envelopes-url

application_search_pcm = application-search-pcm-url

mailbox_url = mailbox-url

pcm_application_url = pcm-application-url

pcm_partner_url = pcm-partner-url

workflow_url_template = workfilow-template-url

workflow_update_url = workflow-update-url

application_activity = application-activity-url

partner_activity = partner-activity-url

pcm_mailbox_url = pcm-mailbox-url

partner_search_pcm = partner-search-pcm-url

dataflow_url = dataflow-url

workflow_base_url = workflow-base-url

Getfiledata = getfiledata-url

pcm_base_url = pcm-base-url

username_pcm = pcm-username

password_pcm = encrypted-pcm-password

db_schema = database-schema

db_type = database-type

username_si = sterling integrator-username

password_si = sterling integrator-encrypted-password

username_spe = spe-username

password_spe = spe-password

Runjob_API = username

password_Runjob = encrypted-password

username_filegps = filegps-username

password_filegps = filegps-encrypted-password

port = port-number

Save and Exit the File

After making your changes, follow these steps to save and close the file in vi:

1. Press Esc to ensure you’re in command mode

2. Type `:wq!` and press Enter

· `:wq!` stands for write and quit, forcing the save even if the file is marked read-only

Step 6: Execute Error_Reprocessing.sh

This step initiates the Error Reprocessing workflow, which automatically identifies and processes recent file transfer errors using AI-based or rule-based logic to determine the most suitable resolution approach.

Run the Script from the Error_Reprocessing Directory:

Navigate to the deployment directory if you’re not already there:

cd /<Install_dir>/Error_Reprocessing

2. Execute the error reprocessing script in the background:

./Error_Reprocessing.sh

Once the script runs, the system will analyze the detected file processing errors and attempt automated resolutions based on the configured fix strategy

A new log file named ‘ian_endpoints.log’ will be created in the /<Install_dir>/Error_Reprocessing directory. This log will contain:

Workflow execution details
Detected errors

You can monitor the real-time log using:

tail -f ian_endpoint.log

3.5 Troubleshooting Guide

This section outlines common issues and their resolutions during the installation and execution of the IANN Error Reprocessing module on Windows.

Issue

Step-by-Step Guidance

Deployment directory not found

Ensure correct path and create using mkdir

`sudo mkdir -p /<Install_dir>/Error_Reprocessing`

Permission denied while running script

Assign execution permissions

`sudo chmod -R 755 /<Install_dir>/Error_Reprocessing`

Cannot edit Config.ini

Use `sudo vi Config.ini`

ian_core_api not executable

Verify binary is present and permissions set

`chmod +x iann_core_api`

DB Connection Failure

Confirm DB credentials in config.toml

Check network access and DB user permissions

4. IANN Error Reprocessing – Windows Deployment

The IANN Error Reprocessing module can be seamlessly deployed on Windows systems to automate the resolution of file processing errors using rule-based, AI-driven, or manual strategies.
This section outlines the complete steps to set up and configure the module in a Windows environment, ensuring reliable and efficient error handling through background execution as a Windows service.

4.1 Windows Deployment Overview

The deployment overview provides steps for the installation and configuration.

Steps

Action

Description

Prepare Deployment Directory

Create base deployment folder for application

Upload ZIP Package

Move Error_Recommendation.zip into the deployment directory

Extract ZIP File

Unzip using 7-Zip or Windows Explorer

Update Config File

Edit configuration.json with environment-specific values

Launch CMD in NSSM Directory

Open command prompt from nssm.exe directory

Install Error_Recommendation Service (CMD)

Run NSSM install for Error_Recommendation

Configure NSSM Fields

Populate required fields: Path, Startup Dir, Args

Install the Service

Finalize service registration

Start the Service

Begin background execution of the module

4.2 Pre-requisites

Make sure the following requirements are met before proceeding:

Category

Requirement (Version -7.0.0)

Operating System

Windows 10 or higher (64-bit)

Python

Version 3.11 or higher

Tools Required

7-Zip or WinRAR,
Command Prompt,
NSSM (Non-Sucking-Service-Manager)

Package

Error_Reprocessing.zip

4.3 Package Contents

The Error_Reprocessing.zip package includes the following files:

Error_Reprocessing/

├── Config.ini

└── iann_core_api.exe

4.4 Deployment Steps

This section outlines the complete, step-by-step process to deploy the Error Reprocessing Module on a Windows machine.

Step 1: Prepare Deployment Directory

Before installing the application, you need to set up a folder where all the files will be extracted and configured.

Instructions:

Open File Explorer
Create a new folder where you want to install the Error_Reprocessing module.

Example using File Explorer:

· Navigate to your desired location (e.g., C:\).

· Create a new folder named IANN, and inside it, create another folder named Error_Reprocessing.

Final path (for reference):

C:\IANN\ Error_Reprocessing

Example using Command Prompt:

mkdir C:\IANN\ Error_Reprocessing

Note:

· The path C:\IANN\ Error_Reprocessing is used as an example throughout this guide.

· A different location may be selected based on system configuration or organizational policy.

Step 2: Upload the Error_Reprocessing.ZIP File

Copy or move the provided Error_Reprocessing zip file to the installation directory created in Step 1.

Instructions:

Move the ZIP file to:

C:\IANN\Error_Reprocessing\Error_Reprocessing.zip

Ensure: The filename remains unchanged and corresponds to the version shared by the development team.

Step 3: Extract the ZIP File

Use either 7-Zip or Windows Explorer to extract the contents of the ZIP package.

Option A: Using 7-Zip

Right-click on Error_Reprocessing.zip.
Select 7-Zip > Extract Here.

Option B: Using Windows Explorer

Right-click on Error_Reprocessing.zip.
Select Extract All….
Set the destination folder as:

Error_Reprocessing/

├── Config.ini

└── iann_core_api.exe

Ensure: All files including configuration files and executables are extracted correctly.

After extraction, the folder will look like:

Step 4: Update the Configuration File

The application uses a config.ini file to load required settings. You need to update this file with appropriate details before running the program.

1. Locate the Configuration File

· Navigate to the following path:

C:\IANN \Error_Reprocessing\config.ini

2. Open the File

· Open config.ini using a text editor.

3. Update the Configuration Parameters

Edit the config.ini file to provide paths and credentials.

[postgresql]

database = database-name

host = host-name

username = user-name

password = encryptedpassword

schema = schema-name

port = port-number

driver_name = driver-name

[oracle_db]

jvm_path = jvm-path

jar_file = jar-file-path

db_schema = database-schema-name

java_classname = java-classname

db_url = database-url

db_user = database-user

db_password = database-encrypted-password

db_type = database-type

[logs]

path = logfile-path

[key]

secret_key = secret-key for encryption of passwords

salt = salt for encryption of passwords

[email]

sender = sender-email-address

password = encrypted-email-password

from_email = from-email-address

email_smtp_host = smtp-host

email_smtp_port = smtp-port

[zone_id]

zone_id = America/Chicago

[API]

runJob_url = runjob-url

get_mailboxes = mailbox-url

url_multi_reprocess = multi-reprocess-url

url_reprocess = url-reprocess

url_getPartners_Id = partner_id-url

url_getPartners_Host = partner-host-url

url_getApplication_Host = application-host-url

url_getKnown_Host = known-Host-url

url_createKnown_Host = create-known-host-url

check_service_status = service-status-url

envelopes_url = envelopes-url

application_search_pcm = application-search-pcm-url

mailbox_url = mailbox-url

pcm_application_url = pcm-application-url

pcm_partner_url = pcm-partner-url

workflow_url_template = workfilow-template-url

workflow_update_url = workflow-update-url

application_activity = application-activity-url

partner_activity = partner-activity-url

pcm_mailbox_url = pcm-mailbox-url

partner_search_pcm = partner-search-pcm-url

dataflow_url = dataflow-url

workflow_base_url = workflow-base-url

Getfiledata = getfiledata-url

pcm_base_url = pcm-base-url

username_pcm = pcm-username

password_pcm = encrypted-pcm-password

db_schema = database-schema

db_type = database-type

username_si = sterling integrator-username

password_si = sterling integrator-encrypted-password

username_spe = spe-username

password_spe = spe-password

Runjob_API = username

password_Runjob = encrypted-password

username_filegps = filegps-username

password_filegps = filegps-encrypted-password

port = port-number

Step 5: Launch Command Prompt in NSSM Directory

1. Open File Explorer (Windows + E).

2. Navigate to the folder where you extracted NSSM (e.g., nssm-2.24).

3. Open the win64 folder

4. Click on the address bar at the top of File Explorer, type cmd and press Enter.

5. This opens the Command Prompt directly inside the NSSM win64 folder, where the nssm.exe file is located.

Step 6: Run the Install Command

1. In the Command Prompt window, type the following:

nssm install Error_Reprocessing

2. Then press Enter.

This launches the NSSM Service Installer interface.

Step 7: Fill in Service Details in the NSSM Window

You will now configure 3 main fields:

1. Field 1: Path

· Click the … button next to the Path field.

· Navigate to the streaming.exe file

Example path:

C:\IANN \Error_Reprocessing\ian_core_api.exe

· Select streaming.exe and click Open.

2. Field 2: Startup Directory

· Click the … button next to the Startup Directory field.

· Navigate to the Error_Reprocessing folder:

Error_Reprocessing

Example:

C:\IANN \ Error_Reprocessing

· Select Error_Reprocessing folder and click OK.

3. Field 3: Arguments

In the Arguments field, append the path to the config.ini file and ensure the filename config.ini is included at the end

C:\IANN \ Error_Reprocessing\config.ini

Step 8: Install the Service

· Once all required fields (Path, Startup Directory, and Arguments) have been populated in the NSSM Service Installer window, click the Install service button at the bottom.

· Upon successful installation, a confirmation message will appear:

Service “Error_Reprocessing” installed successfully!

· This indicates that the service has been registered with the system but is not yet running. Proceed to the next step to start the service.

Step 9: Start the Error_Reprocessing Service

After successfully installing the service, the next step is to start it from the Windows Services Manager.

Instructions:

1. Open the Task Manager

· Press Ctrl + Shift + Esc to launch the Task Manager.

2. Access the Services Manager

· In Task Manager, click on the Services tab.

· At the bottom-right corner, click on Open Services.

· This action will launch the Windows Services Manager (services.msc), where all system services are listed.

3. Locate the Installed Service

· In the Services Manager window, scroll through the list of services.

· Locate the service named:
Error_Reprocessing

4. Start the Service

· Right-click on the Error_Reprocessing service.

· From the context menu, select Start.

A loading dialog may briefly appear as Windows initializes the service.

5. Verify Service Status

· Once the service starts successfully, the Status column for Error_Reprocessing will update to Running.

· This indicates that the application is now actively running in the background as a Windows service.

Once the service is running, a log file named ‘ian_endpoints.log’ will be created in the C:\IANN\Error_Reprocessing\ directory path.

This log will contain:

· Workflow execution details

· Detected errors

To monitor the log in real time, use:

C:\IANN\Error_Recommendation\ian_endpoints.log

Note: The service will now automatically run in the background and can be managed through the Services Manager where you can start, stop, or restart it as needed.

4.5 Troubleshooting Guide

This section outlines common issues and their resolutions during the deployment and execution of the Error Reprocessing Module on Windows systems.

Issue

Step-by-Step Guidance

mkdir command fails

Run: mkdir “C:\IANN\Error_Reprocessing” (use quotes to handle spaces)

Service fails to start, or encryption errors in logs

Double-check the config.ini content for missing or incorrect values. Ensure paths are correct and passwords are encrypted.

nssm command not recognized

Navigate to nssm\win64 folder, then type cmd in the address bar to launch command prompt in the correct directory.

Service fails to start

– Check ian_endpoints.log for errors
– Validate DB/API config
– Ensure all dependencies are packaged with the EXE

Log not created after starting service

– Ensure service status is Running
– Reopen Services.msc and check status
– Manually run EXE to observe errors