#AIOps
7 related articles
Nike Builds Self-Healing Telemetry System with MCP and AI Agents
Nike's former observability platform director Panos Tsilopoulos shares how to build a closed-loop telemetry control system with OpAMP, MCP, and AI agents, managing 100K OpenTelemetry Collectors and enabling safe human-AI collaborative operations through code-based guardrails.
How AI Agents Are Automating DevOps: Boosting Both Efficiency and Reliability
AI agents are transforming DevOps: from automating repetitive tasks to predicting failures and accelerating release cycles. This article analyzes core capabilities, solutions from Red Hat and Google Cloud, and the real challenges and future trends of AIOps adoption.
Microsoft Decision Model in Practice: How Probabilistic Output Is Revolutionizing AIOps Root Cause Localization
A practical test of Microsoft's Decision-1 in AIOps: 86% accuracy in HDFS log anomaly detection, 94% in microservice root cause localization, at 1/40 the cost of reasoning models. Structured state engineering and calibrated thresholds are key.
Three-Agent System in Production: Architecture Breakdown Behind a 78% Reduction in Database Diagnosis Time
Cornerstone OnDemand's Orion AI uses a three-agent system on Amazon Bedrock and Strands Agents to cut database diagnosis time by 78%. Deep dive into architecture, state management, and production trade-offs.
AI SRE Arena: An Open-Source Benchmark for Evaluating Kubernetes AI Ops Agents
AI SRE Arena is an open-source benchmark for Kubernetes AI ops agents, measuring real-world fault diagnosis and remediation performance. Learn about its design and significance for AIOps.
AWS DevOps Agent Auto-Remediation in Practice: From Diagnosis to One-Click Approval
AWS DevOps Agent only diagnoses by default. Learn how Lambda Durable Functions, EventBridge, and Bedrock turn investigation summaries into pre-validated fixes for one-click approval.
