Agentic AI for Infrastructure Monitoring and Resolution

Overview

Transforming Cloud Reliability with Agentic AI

A leading enterprise faced frequent service outages and high operational costs due to the complexity of managing distributed cloud infrastructure. Traditional monitoring tools generated excessive noise, overwhelming Site Reliability Engineers (SREs) and delaying resolution.

We implemented an Agentic AI solution that could monitor infrastructure in real time, detect anomalies, identify root causes, and provide solution to Team. This transformed incident management into a proactive way that reduced downtime and freed Team to focus on innovation.

Services

- agent orchestration - log summarization and RCA - time-series monitoring - (metrics logs and alarms)

Industry Type

- Cloud & IT Infrastructure - Enterprise IT

Challenges

  • - High Alert Noise & Fatigue – Thousands of alerts daily with high false positives overwhelmed teams.
  • - Slow Root Cause Analysis – The lack of unified log and metric correlation delayed troubleshooting.
  • - Delayed Resolution – Team spent hours executing repetitive remediation steps.
  • - Risk of Autonomous Actions – Needed safety mechanisms to prevent cascading failures.

Outcomes

  • - 60% reduction in false positives through intelligent correlation.
  • - 30–40% faster incident resolution.
  • - 25% faster detection from anomaly-based monitoring.
  • - Built a knowledge base of incidents and solutions for continuous improvement.

Technology Stack

AWS CloudWatch AWS CloudWatch
LangChain LangChain
LangGraph LangGraph
LLMs LLMs

Project Solutions

  • • Consolidates logs, metrics, traces.
  • • Applies anomaly detection and filters noise.
  • • Correlates multi-source signals.
  • • Uses LLM-based log summarization to suggest likely causes and solutions.
  • • Build a Knowledge base of the incidents which can be helpful for future references.

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