Real Outcomesfrom Intelligent Execution
Explore how we help enterprises and fast-moving teams solve real-world problems — with measurable results, clean engineering, and scalable platforms.
Self-Healing DevOps Log Intelligence System
Project Overview
Challenge
A global infrastructure operations team struggled with massive log volumes across distributed systems, delays in diagnosing and resolving system failures, manual triaging of known and unknown log errors, and recurring incidents with no long-term resolution memory. Their goal was to automate log intelligence, error resolution, and incident remediation using AI and self-learning logic.
Our Solution
We built a Self-Healing DevOps System using a hybrid of deterministic error mapping and LLM-based remediation suggestions.
Pattern Detection & Classification
Used regex-based log pattern matching for known issues and built classifiers to tag severity, component impact, and error lineage.
LLM-Powered Root Cause Analysis
Integrated Google Gemini LLM via LangChain pipelines. Trained on prior logs and resolutions for zero-shot error resolution and generated remediation steps with contextual reasoning.
Self-Learning Memory System
Appended new error resolutions to a dynamic error-resolution database and created reusable mappings for faster future resolution.
Real-Time Alerting & Notification
Deployed an event-driven alerting layer using PySpark on AWS/GCP and triggered Slack/email alerts with auto-attached RCA reports.
Cloud-Native Deployment
Packaged as Dockerized APIs, integrated with existing CI/CD and observability tools, compatible with AWS, GCP, Azure (multi-cloud).
Results
40% Reduction in Mean Time to Resolution (MTTR)
Significantly reduced the time required to identify, diagnose, and resolve system failures through automated log intelligence.
70% Manual Triaging Effort Reduction
Dramatically reduced manual effort for recurring errors through automated classification and self-learning resolution mapping.
Faster Onboarding for New Engineers
Auto-RCA knowledge base enabled faster onboarding and knowledge transfer for new team members joining the operations team.
Improved Uptime and System Reliability
Proactive error detection and automated remediation suggestions led to improved overall system stability and reliability.
What Our Client Says
This turned reactive firefighting into proactive ops intelligence. Our engineers now solve, learn, and scale faster.