MSG Data Manager: Streamline Your Message Storage & Retrieval

Quick Start Guide to MSG Data Manager: Installation to Insights

Overview

A concise walkthrough to get MSG Data Manager installed, configured, ingesting data, and producing basic insights within one session.

Prerequisites

• OS: Linux (Ubuntu 20.04+) or Windows Server 2019+
• Disk: 50 GB free (adjust per dataset)
• Memory: 8 GB RAM minimum (16+ GB recommended)
• Network: Outbound TLS access for updates and APIs
• Credentials: Admin access to target data stores and a service account for the application
• Dependencies: Java 11+, Docker (optional), PostgreSQL or supported metadata DB

Installation (Quick)

1. Download package: Obtain the latest release binary or Docker image for MSG Data Manager.
2. Install dependencies: Ensure Java and PostgreSQL (or configured DB) are installed and running.
3. Database setup: Create a dedicated database and user:
   • db name: msgdm
   • user: msgdm_user
   • grant all privileges to the user
4. Configure application: Edit the config file (config.yml or .env):
   • DB_URL=jdbc:postgresql://localhost:5432/msgdm
   • DB_USER=msgdm_user
   • DB_PASS=your_password
   • LISTEN_PORT=8080
   • TLS settings (if enabling HTTPS)
5. Start service:
   • System: run the provided init script or systemd unit.
   • Docker: docker run -d -p 8080:8080 –env-file .env msg-data-manager:latest
6. Verify: Open http://localhost:8080/health or curl the /health endpoint; expect 200 OK.

Initial Configuration

• Create admin account: Use CLI or first-run web UI to set admin credentials.
• Connect data sources: Add connections for message stores (SMTP archives, S3 buckets, IMAP servers, etc.) with credentials and access policies.
• Set ingestion policies: Define schedules, retention, deduplication rules, and parsers for message formats (.msg, EML, JSON).

Ingesting Data

1. Run a sample ingest: Add a small source and run ingestion to validate parsing and mappings.
2. Monitor pipeline: Check ingestion logs and dashboards for parsing errors or missing fields.
3. Adjust parsers: Map headers, body, attachments, and metadata to the schema; add custom extractors if needed.
4. Scale ingestion: Increase worker count or parallelism in config for larger datasets.

Basic Usage & Insights

• Search: Use full-text search across bodies, headers, and attachments. Support for boolean queries and filters (date, sender, recipient).
• Dashboards: Default dashboards show ingest rate, error rate, storage use, and top senders/receivers.
• Exports: Export search results to CSV or JSON; schedule recurring exports.
• Alerts: Configure alerts for ingestion failures, schema drift, or spikes in message volume.

Security & Compliance

• Access control: Configure role-based access (admin, analyst, auditor).
• Encryption: Enable TLS for transport and AES-256 for at-rest storage if supported.
• Audit logs: Ensure audit trail is enabled for searches, exports, and configuration changes.
• Retention policies: Implement automated deletion or archiving per compliance requirements.

Troubleshooting (Common Issues)

• Service won’t start: Check DB connectivity, ports, and Java version. Inspect logs at /var/log/msgdm/*.
• Slow search: Verify indexing is complete; increase JVM heap or add more search nodes.
• Parsing errors: Examine sample messages, update parsers, or add custom regex extractors.

Next Steps (30–90 days)

• Schedule full-scale ingest with staging run.
• Tune indexing and retention for production load.
• Build custom dashboards and saved queries for stakeholders.
• Integrate with SIEM or BI tools for downstream analysis.

Date: February 7, 2026