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

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LLM tracing in Elastic APM: prompts, responses, and token counts in the span view

In a twenty-call agentic trace, you can see which span is using the most tokens and read the prompt that caused it. Both live in Elastic APM, so there is no second tool to run.

Jenny Pavlova

Your AI agent needs an alibi: Observability and audit trails for Agent Builder in Elastic

Elastic 9.5 traces every Agent Builder run as OpenTelemetry spans in your own cluster, so tool calls and token counts are queryable with ES|QL. One workflow step adds the approval record, in a data stream the pipeline cannot rewrite.

Jeffrey Rengifo

From a 582ms latency spike to the team that owns it, using Kibana Discover

Getting there takes a data view, some filter pills, a KQL query and a switch to Lucene query syntax, but the part that actually names the team is one ES|QL LOOKUP JOIN against a service catalog index.

Jeffrey Rengifo

From recommendation to remediation in 4 stages: human-in-the-loop automation with Elastic Workflows

An approval gate that pauses incident response automation before the action and gives the reviewer enough evidence to decide in seconds. Whatever happens next, approved or declined, lands in one auditable record.

Jeffrey Rengifo

From alert to root cause in 3 minutes: automated root cause analysis with Elastic Agent Builder

Automated root cause analysis only works if the agent compares the incident window against the last healthy one. Skip that step and you get a summariser. The read-only skill, the scoped role and the Elastic Workflow are all here.

Jeffrey Rengifo

AI agent observability for Microsoft Foundry: two env vars, no collector

Set up LLM tracing once and every model call, tool execution and handoff from your Foundry agent arrives in Kibana as one queryable trace, with token counts on each span and code for Agent Framework, LangGraph and Node.js.

Greg Crist

Sleep through the 3am page: automated incident response with Elastic on Red Hat OpenShift

Elastic Observability handles three routine incidents on its own: it scales, restarts or rolls back the workload, then confirms the service recovered, all with the reasoning model inside your own cluster.

Matt Isset

OpenTelemetry Java extensions: customize traces without forking the agent

One JAR, loaded at startup by the OpenTelemetry Java agent, lets you filter health checks, rename spans, add resource attributes, and control sampling with no application code changes.

Sylvain Juge

Kubernetes observability: SLO templates that turn alerts into error budgets

Two bad rollouts burned 88% of a 30-day error budget while the SLI still read 99.56%. This post adds four SLO templates that bring burn-rate tracking to the OTel-based alert rules from Part 1, no new instrumentation required.

Agi K Thomas

Elastic Agent now runs as an OpenTelemetry Collector: Less memory overhead, zero config changes

Elastic Agent 9.3 sends logs, metrics and traces through one OTel Collector pipeline, running Beats integrations alongside native OTel sources in a single Fleet-managed agent.

Nima Rezainia

Correlate logs, metrics, and traces in one ES|QL query

Walk through four investigations, from CPU saturation to pod memory pressure, each answered by a single query across signal types.

Vinay Chandrasekhar

vLLM Prometheus metrics for self-hosted LLM tuning: TTFT, KV Cache, and GPU Utilization

Tuning a self-hosted vLLM inference using its Prometheus metrics in Elastic Observability — TTFT, KV cache, prefix caching and DCGM GPU counters

Bahubali Shetti