The client runs a distributed environment generating large volumes of diverse logs. Their manual log inspection process was slow and inefficient. We delivered a centralized log-analysis platform to automate ingestion, parsing, classification and alerting – enabling quick root-cause analysis and real-time observability.
3DXLens Log Analyzer - Unified Log Monitoring & RCA Platform
Python
Pandas
Streamlit
Grafana
Elastic Search
FastAPI
Overview
Primary Goals
- Consolidate logs across services and infrastructure
- Provide insights into error patterns, latency spikes, and service-level issues
- Seamless integration with the client’s existing monitoring stack
- Automatically parse and classify log entries (errors, warnings, latency, anomalies)
- Enable timely detection and resolution of problems
Solution Delivered
A lightweight, modular log-analysis engine integrated with the client’s log storage backend. The solution ingests logs, normalizes formats, extracts structured data, aggregates key metrics, and triggers alerts on anomalies. It offers dashboards and summary reports for visibility across services.
Outcome / Impact
Incident Resolution Became Faster
Centralized logs, automated parsing, and intelligent error grouping enabled teams to identify issues quickly, improving overall service reliability.
Quantifiable Benefits
- 50% lower observability cost through optimized log ingestion and storage
- 3X faster RCA with automated correlation across services
- Predictive failure alerts reduced outages and service interruptions
- Lower MTTR & faster MTTD thanks to real-time anomaly detection and insights
Conclusion
The Log Analyzer transformed fragmented logging into a unified, automated observability platform - delivering fast, reliable insights and enabling efficient operation across services.
