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

Elastic AI Assistant for Observability

Harness the power of generative AI to turn insights into actions. Powered by the Elasticsearch Relevance Engine™ (ESRE™), Elastic’s AI Assistant (in technical preview for Observability) transforms problem identification and resolution by eliminating manual data chasing across silos to an interactive assistant that delivers accurate and context-aware remediation for SREs.

Best practices for instrumenting OpenTelemetry

OpenTelemetry (OTel) is steadily gaining broad industry adoption. As one of the major Cloud Native Computing Foundation (CNCF) projects, with as many commits as Kubernetes, it is gaining support from major ISVs and cloud providers delivering support for the framework. Many global companies from finance, insurance, tech, and other industries are starting to standardize on OpenTelemetry.

Kubernetes Logging with Filebeat and Elasticsearch Part 1

This is the first post of a 2 part series where we will set up production-grade Kubernetes logging for applications deployed in the cluster and the cluster itself. We will be using Elasticsearch as the logging backend for this. The Elasticsearch setup will be extremely scalable and fault-tolerant. ‍

Kubernetes Logging with Filebeat and Elasticsearch Part 2

In this tutorial, we will learn about configuring Filebeat to run as a DaemonSet in our Kubernetes cluster in order to ship logs to the Elasticsearch backend. We are using Filebeat instead of FluentD or FluentBit because it is an extremely lightweight utility and has a first-class support for Kubernetes. It is best for production-level setups. This blog post is the second in a two-part series. The first post runs through the deployment architecture for the nodes and deploying Kibana and ES-HQ.

Effective Logging in Threaded or Multiprocessing Python Applications

In Python development, logging is not only good practice; it is vital. Logging is critical for understanding the execution flow of an application and helps in debugging potential issues. The importance of logging for developing reliable and maintainable Python applications cannot be overstated. Python provides capabilities for running concurrent operations—either in a threaded (single process) or multiple process environment. But what implications do these different approaches have on logging?

How to Monitor SaaS Environments with Synthetic Monitoring

Today, we bring you a quick and straightforward overview of "How to Monitor SaaS Environments with Synthetic Monitoring." Whether you're a seasoned professional or a beginner in the SaaS world, understanding the basics of synthetics monitoring can give your SaaS environment a significant boost. In this short video, we're cutting through the clutter and going straight to the point. No deep dives, no overwhelming details – just a crisp, concise look at how synthetics monitoring works. Perfect for those just starting out or anyone in need of a quick refresher.