Blogs

Hands-on, insight-driven content about observing your production and development environments using Elastic Observability.

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From averages to any percentile: Elasticsearch ships native exponential histogram support in ES|QL
Elasticsearch Labs

From averages to any percentile: Elasticsearch ships native exponential histogram support in ES|QL

Query any percentile at any time. Elasticsearch natively stores OTel exponential histograms and lets you analyze distributions in ES|QL without fixed buckets or lossy conversions.

Jonas Kunz
Migrate Logstash Pipelines from Azure Event Hubs to OTel Collector Kafka Receiver
Observability Labs

Migrate Logstash Pipelines from Azure Event Hubs to OTel Collector Kafka Receiver

Step-by-step guide to migrating Logstash pipelines from the Azure Event Hubs plugin to the OpenTelemetry Collector Kafka receiver.

Álex Cámara
Investigate Kubernetes infrastructure issues with PromQL in Elasticsearch & Kibana
Observability Labs

Investigate Kubernetes infrastructure issues with PromQL in Elasticsearch & Kibana

Walkthrough of a Kubernetes fleet-wide CPU investigation in Elastic Observability, from cluster to namespace to the noisy pod, using PromQL in Elasticsearch and Kibana.

TLS certificate monitoring with Elastic Workflows, Synthetics, and Osquery: Eliminate manual renewals
Observability Labs

TLS certificate monitoring with Elastic Workflows, Synthetics, and Osquery: Eliminate manual renewals

Automate TLS certificate monitoring with Elastic Workflows, Synthetics, and Osquery. Detect expiring certificates, rotate, and verify without human intervention.

Adrian Chen
From raw logs to system knowledge: the AI context layer observability is missing
Observability Labs

From raw logs to system knowledge: the AI context layer observability is missing

A self-updating knowledge base built from your logs: services, dependencies, and failure modes, so your AI agents always know what they are looking at.

Luca Wintergerst
Fixing Elastic Streams processing failures without dropping data
Observability Labs

Fixing Elastic Streams processing failures without dropping data

When your Streams ingest pipeline breaks, failed documents land in the failure store, not the floor. Here's how to use those exact failures to fix your pipeline without re-ingesting from the source.

Luca Wintergerst
Connecting Cursor to Production Logs via the Elastic MCP Server
Observability Labs

Connecting Cursor to Production Logs via the Elastic MCP Server

Learn how to connect Cursor to your Elastic APM data using the Elastic Agent Builder MCP server, so you can debug production errors and make UI decisions backed by real usage data without leaving your editor.

Jeffrey Rengifo
Migrating Datadog and Grafana dashboards and alerts to Kibana with the Observability Migration Platform
Observability Labs

Migrating Datadog and Grafana dashboards and alerts to Kibana with the Observability Migration Platform

Learn how to migrate supported Datadog and Grafana dashboards and alerts to Kibana with the Observability Migration Platform.

Subham Sarkar
Elastic Ramen: A CLI harness for SRE investigation and remediation
Observability Labs

Elastic Ramen: A CLI harness for SRE investigation and remediation

Exploring Elastic Ramen, a CLI harness that brings Agent Builder conversations, skills, and tools into the terminal so engineers can move from investigation to remediation in a single thread.

Joe Reuter
Agentic Powered Kubernetes Investigations with Elastic Observability and MCP
Observability Labs

Agentic Powered Kubernetes Investigations with Elastic Observability and MCP

See how Elastic's Agentic powered Kubernetes observability uses MCP App, agent skills to let agents investigate clusters, detect anomalies, and automate root cause analysis.

Jesse Miller
Kubernetes Observability from alert to root cause: Dashboards, Alerts, and Anomaly Detection with Elastic
Observability Labs

Kubernetes Observability from alert to root cause: Dashboards, Alerts, and Anomaly Detection with Elastic

Kubernetes observability with Elastic includes dashboards, alert rules, and ML anomaly detection for alerts with root-cause context.

Jesse Miller
Exploring metrics from a new time series data stream in Discover
Observability Labs

Exploring metrics from a new time series data stream in Discover

Discover helps you see and understand the metrics in a time series stream, with no manual work required. Once you see that your metrics data is flowing, you're ready to build dashboards, alerts, SLOs, and more.

Miguel Sánchez Gómez