Getting Started with OpenObserve
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OpenTelemetry is free, but your observability backend is not. Learn practical strategies for observability cost reduction using sampling, filtering, retention, and backend architecture choices.
Learn how OpenTelemetry's GenAI Semantic Conventions bring production-grade observability to LLM workloads. A complete guide for DevOps and SRE teams covering traces, metrics, logs, and a hands-on RAG instrumentation walkthrough.
Learn how to add distributed tracing to LangChain and LlamaIndex apps using OpenLLMetry and the OpenTelemetry SDK, with traces flowing into OpenObserve.
Discover the essential LLM monitoring best practices to ensure reliability, safety, and performance in production. Learn how to track hallucinations, latency, costs, and more.
What is an MCP gateway? Compare top options and learn how OpenObserve's native MCP server plugs into your AI agent stack for live observability data access.
Complete guide to AI anomaly detection in observability. Discover how machine learning algorithms detect unusual patterns, handle seasonality, and catch issues traditional thresholds miss.
Learn how to set up logs, metrics, and traces for a new microservice in under 30 minutes. A step-by-step guide to achieving full observability quickly and efficiently.
Learn how OpenObserve's RUM module automatically detects rage clicks, dead clicks, and error clicks turning invisible UX pain into actionable signals you can see in session replays, query with SQL, and alert on.
When the OpenChoreo team needed an observability backend for their CNCF sandbox Internal Developer Platform, they chose OpenObserve. Here's why and what it means for Kubernetes teams everywhere.
Learn how to monitor autonomous AI agents in production using observability best practices. Track agent behavior, logs, traces, and performance with tools like OpenTelemetry to ensure reliability, transparency, and control at scale.
Explore how OpenObserve detects anomalies in logs, metrics, and traces to help SREs identify issues early and take action before incidents escalate.
Learn how to implement distributed tracing in a Java Spring Boot microservices application using the OpenTelemetry Java Agent and OpenObserve. Covers zero-code auto-instrumentation, JVM metrics, cross-service trace propagation, flamegraphs, and Gantt charts , with working source code and curl examples.
Learn how AI-assisted monitoring using MCP enhances observability with intelligent alerts, anomaly detection, and automated insights for faster incident response.
Learn how to implement structured logging in production. Improve debugging, searchability, and observability with best practices and real-world examples.
Discover how AI incident management transforms production operations by reducing MTTR by 90%, automating root cause analysis, and cutting alert noise by 80%. Learn how log clustering, trace correlation, and LLM-powered RCA work
Learn how to measure and dramatically reduce Mean Time to Resolution (MTTR) using AI-powered observability. Discover the four phases that inflate MTTR and how modern teams achieve faster incident resolution with intelligent detection, triage, diagnosis, and remediation
Discover how AIOps transforms IT operations with AI-powered anomaly detection, event correlation, and automated remediation. Learn the core capabilities, use cases, and how observability data drives intelligent operations.
We rewrote the XDrain log pattern extraction algorithm in Rust, achieving 40x performance improvements over Python. Learn how we used prefix trees, systematic sampling, and memory-bounded LRU caches to process 361,000 logs/sec in real-time.
Learn what the Prometheus cardinality bomb is, why high-cardinality metrics break your monitoring, and how to detect, prevent, and fix it effectively.
AI Assistant and LLM Observability are now live on OpenObserve Cloud. v0.70.0 brings a rebuilt Service Graph, visual query builder, Incident Timeline, and more.
Learn how to use the OpenTelemetry Collector Contrib distribution to collect, process, and export telemetry data. This guide covers architecture, key components, configuration examples, and practical deployment tips.
AI Observability by OpenObserve
OpenTelemetry-native observability for agents and LLMs.