Category: OpenTelemetry

Articles tagged OpenTelemetry

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Three clicks from alert to error log: breaking down RED metrics by any span attribute in Elastic Observability

See which pod, deployment or version is driving a RED metrics change by breaking down span attributes in Discover, then trace a failing span to the error log behind it.

Roshan Gonsalkorale

From alert to failing dependency in four clicks: Elastic APM's embedded service map

The APM service map is now embedded on alert pages with filters, connection metrics and a service fly-out so you can analyse dependencies and find the root cause without leaving the alert.

Roshan Gonsalkorale

How Elastic cut OpenTelemetry tail sampling memory by 65% with disk-backed trace storage

Elastic contributed two features upstream to the OTel Collector's tail sampling processor. The span-ingest strategy lets sampling decisions happen earlier, and Pebble tail storage moves trace buffering to disk. It costs more CPU, but operators can raise decision_wait and num_traces without OOM kills.

Carson Ip

Common ES|QL queries for Kubernetes monitoring

Copy-paste ES|QL queries for Elasticsearch that turn memory pressure and error spikes into a five-minute diagnosis.

Jeffrey Rengifo

One OTLP endpoint, three teams, zero routing rules: Elasticsearch Streams AI Partitioning

Stop writing log routing rules upfront. See how Streams AI Partitioning reads your data, proposes child streams, and lets you set per-team retention in minutes.

Aleksandar Panov

Elasticsearch: best-in-class for logs, now best-in-class for metrics

Elasticsearch is now best-in-class for metrics: 30× faster than Prometheus, up to 2.5× more storage-efficient, 50% less than Datadog. Learn about all the capabilities we’ve added.

Bahubali Shetti

3 signals, 2 env vars, 0 collectors: OpenTelemetry with Python and Elastic's Managed OTLP Endpoint

Instrument a Flask API with OpenTelemetry and ship traces, metrics, and logs to Elastic Cloud using just 2 environment variables, no collector needed.

Jeffrey Rengifo

Self-Driving Observability: From Stacktraces to Profiling-Derived Metrics

Profiling-derived metrics turn raw stacktraces into time-series KPIs, unlock continuous profiling for every user and lay the foundation for an observability system that detects, investigates, and acts on its own.

Christos Kalkanis

Bringing Fire to Elasticsearch: Adding Native Prometheus API Support

Query Elasticsearch directly from Prometheus-compatible clients via native PromQL, discovery, and metadata endpoints. Send data to Elasticsearch with Prometheus Remote Write.

Felix Barnsteiner

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

ES|QL queries for debugging LLM latency, cost and GPU saturation

Learn how to investigate LLM latency, token cost and GPU saturation using ES|QL against OpenTelemetry traces and get a root cause, not just a symptom.

Jeffrey Rengifo

30x faster than Prometheus: how we rebuilt Elasticsearch as a leading columnar metrics datastore

Elasticsearch now stores OTel metrics at 3.75 bytes per data point and queries them up to 30x faster than Prometheus. Here's how we rebuilt TSDS and ES|QL.

Kostas Krikellas