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DevOps & observability · #datadog
Learn how to turn application error logs into a Datadog log‑based metric using pipelines, with a concrete Python example, verification steps, and key limitations.
Traces appear for some services but distributed traces are broken. Use this diagnostic guide to check sampling, service names, agent health and intake connectivity in Datadog APM for microservices.
Sampling rate controls how many transactions Datadog traces, directly affecting APM costs and your ability to spot rare bugs. This post walks through a practical engineering decision: adjusting the rate at runtime, verifying the change, and avoiding common blind spots.
Add Datadog tracing to a Spring Boot microservice with the Datadog OpenTelemetry exporter. The blog walks through a minimal example, environment setup, verification steps, and trade‑offs for a low‑overhead, end‑to‑end tracing solution.
When some requests produce traces and others don’t, or downstream spans disappear, follow these ordered checks to pinpoint tracer‑Agent connectivity, sampling, retention filters, or propagation issues.
Guidance on picking Datadog Agent v6 or v7 for Kubernetes clusters, with a feature table, trade‑offs, deployment steps, and validation checks.
Learn how to use Datadog custom spans to bridge visibility gaps in asynchronous workflows and enrich your traces with business-specific metadata.
A step‑by‑step guide to add Datadog APM tracing to a Java microservice: install the Agent, drop the dd‑java‑agent jar, set environment variables, verify logs, and confirm traces in the UI.
Learn how Datadog Log Facets index selected log attributes for instant, low‑latency filtering, see a concrete example enabling the http.method facet, and understand the storage trade‑offs for high‑cardinality fields.
opentelemetry
kubernetes
java