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The latest News and Information on Log Management, Log Analytics and related technologies.

ISO 27K Without the Bloat: An Open Source Approach

It’s often framed as an enterprise-only exercise: long timelines, expensive tooling, consultants everywhere, and a lot of compliance work that exists mainly to survive an audit. As a ~40-person, engineering-driven SaaS company, we needed the same level of trust and rigor as much larger organizations — but we weren’t willing to accept shelfware, parallel compliance infrastructure, or controls that only exist on paper. We also didn’t stop at ISO 27001.

The Grok-to-AI Evolution: Why Modern SREs Are Moving Beyond Manual Parsing

Grok structures logs. Context engineering connects systems. AI explains behavior. For years, Grok patterns have been the workhorse of the SRE world. Built on regular expressions, Grok helps teams extract structure from unstructured logs. As we explored in "Do You Grok It?", Grok is the key to turning messy log lines into usable fields. It's why our Grok Pattern Reference remains one of our most-visited resources — SREs are hungry for structure.

Tool Consolidation Is Dead. Long Live Agentic AI.

It’s 2026, and developers have more tools at their disposal than at any point in the industry’s history: CI/CD platforms are richer; observability stacks are deeper; security, data, and AI tooling have exploded into crowded, competitive ecosystems. And yet, delivery is still slow, incidents are still noisy, workflows are still brittle. The problem is no longer tool scarcity or feature depth. It’s integration debt.

How does Coralogix go beyond basic migration?

When a team, division or organization is assessing a new vendor, there are some basic questions that must be answered. At Coralogix, we look at migrations in a different way. It isn’t about transporting the current state of play into a new vendor, often called a “lift and shift”. These are the basics. There is a whole new level of onboarding and support that doesn’t just replicate value across platforms – it expands it.

Elastic 9.3: Chat with your data, build custom AI agents, automate everything

Today, we are pleased to announce the general availability of Elastic 9.3 as the latest version of the Elasticsearch Platform — the world’s most popular open source platform for transforming both structured and unstructured data into trusted answers and outcomes. In addition to including new features that help developers with context engineering and agent building, Elastic 9.3 introduces a broad set of new capabilities to Elastic Search & AI, Elastic Observability, and Elastic Security.

OpenTelemetry Instrumentation Best Practices for Microservices Observability

OpenTelemetry instrumentation is the foundation of modern microservices observability, but getting it right in production requires more than just enabling auto-instrumentation. This guide covers production-tested OpenTelemetry best practices that help engineering teams achieve reliable distributed tracing, control observability costs, and extract maximum value from their telemetry data.

How to Implement Distributed Tracing in Microservices with OpenTelemetry Auto-Instrumentation

This guide shows you how to implement OpenTelemetry’s auto-instrumentation for complete distributed tracing across your microservices, from initial setup through production optimization and troubleshooting.

Curating Security Data for the Financial Services Industry

Security is not just an IT priority in financial services. It is the foundation of the entire business. The need to keep financial assets and information safe is why the modern financial services industry exists. Banks, insurers, payment providers, trading firms, and fintech platforms are all built on trust. Customers trust that their money is safe, that their identities are protected, and that transactions will be accurate and available when needed.

How to Build AIPowered Search with Elasticsearch [2 Min Live Demo]

In this demo, we show how Elasticsearch enables production‑ready GenAI and AI‑powered search applications—from indexing and embedding your data to grounding large language models with RAG. You’ll see how developers can go from raw data to a fully functional GenAI search experience—fast Additional Resources.