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Integrating feature flag context into OpenTelemetry traces enhances observability by recording flag states as span attributes, making it easier to analyze how specific flags influence application behavior. When you toggle a feature flag, you're changing the behavior of your application; sometimes, in subtle ways that are hard to detect through logs or metrics alone. By adding feature flag attributes directly to spans, you can make these changes observable at the trace level.

This guide covers battle-tested chaos experiments for Kubernetes, AWS, Azure, and GCP to help you validate production resilience before real failures happen. Start with low blast radius experiments (pod-level) and gradually progress to higher impact scenarios (node/zone failures), always defining clear hypotheses and using probes to measure results. Building reliable distributed systems isn't just about writing good code. It's about understanding how your systems behave when things go wrong.

Have you ever asked yourself, what is the fastest way to turn a harmless Infrastructure as Code change into a production incident and an awkward postmortem? We did, and found that usually, it's from letting it through without any guardrails. Infrastructure guardrails in Infrastructure as Code (IaC) were once a nice-to-have. Today, they’re essential. Without clear boundaries and safety mechanisms, even well-designed IaC workflows can turn small mistakes into fast-moving, high-impact problems.

Our December Harness AI updates focus specifically on enhancements to Harness AI governance. You can review our Harness AI November updates here.

Harness FME continues its investment in OpenFeature, building on our early support and adoption of the CNCF standard since 2022. Evaluate flags consistently across languages and environments, and integrate them seamlessly into your applications without modifying your code. Feature flags are table stakes for modern software development. They allow teams to ship features safely, test new functionality, and iterate quickly, all without re-deploying their applications.

Harness Dynamic Pipelines offers an option to create pipelines, or pipeline stages, at runtime For a long time, CI/CD has been “configuration as code.” You define a pipeline, commit the YAML, sync it to your CI/CD platform, and run it. That pattern works really well for workflows that are mostly stable. But what happens when the workflow can’t be stable? In all of those cases, forcing teams to pre-save a pipeline definition, either in the UI or in a repo, turns into a bottleneck.