Stabilizing Global Data Integrity and Performance After a Major Infrastructure Migration
Client
A prominent US IT services provider undergoing a massive global infrastructure and log management migration.
Project Context
The client modernized an enterprise log management infrastructure by remediating critical post-migration issues after a migration from Splunk to Elastic. Resolved severe operational hurdles, including regional data synchronization lag and potential data loss. Successfully stabilized the environment and secured uninterrupted data integrity while transitioning complex monitoring workflows to the new architecture.
Project Objectives
- Resolve reported data loss and enrichment gaps to maintain a reliable source of truth.
- Mitigate root causes of data lag occurring between local agents and the central cluster.
- Replicate legacy dashboard visualizations to ensure consistent business reporting.
- Implement real-time mechanisms to capture and analyze data ingestion failures.
Challenges
- Severe synchronization delays occurred between local agents and the central cluster.
- Post-migration configuration gaps threatened data integrity and a reliable source of truth.
- The system lacked real-time mechanisms to capture and isolate failed records.
- Broken monitoring workflows halted consistent business reporting and dashboard visualizations.
Solution
- Diagnostic Analysis: Analyzed system logs to distinguish between genuine data loss and duplicates caused by configuration filters.
- Resilient Pipelines: Established Dead Letter Queues (DLQ) to isolate failed records and prevent silent data loss.
- Data Enrichment: Developed logic to propagate event headers across multi-line documents, ensuring full traceability.
- Reporting Realignment: Provided specialized transformation configurations to handle complex data consolidation for dashboards.
