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Why does my Kubernetes deployment roll out but traffic still hits old pods?
When this happens, the service is almost certainly selecting the wrong pods. Kubernetes services don’t care about deployments or rollout status. They route traffic purely based on label selectors. If your new pods have labels that don’t exactly match what the service expects, traffic will continue fRead more
When this happens, the service is almost certainly selecting the wrong pods.
See lessKubernetes services don’t care about deployments or rollout status. They route traffic purely based on label selectors. If your new pods have labels that don’t exactly match what the service expects, traffic will continue flowing to the old ReplicaSet even though the rollout completed successfully.
This often happens after small refactors where labels are renamed or reorganized, and the service definition isn’t updated accordingly.
Takeaway: If traffic isn’t shifting, always check service selectors before blaming the rollout
Why does my CI job randomly fail with timeout errors?
Random CI failures usually aren’t random at all. They often come from shared runner resource limits, slow dependency downloads, or unstable external services. Adding caching and better logging almost always reveals a consistent bottleneck. Takeaway: Intermittent failures usually hide consistent consRead more
Random CI failures usually aren’t random at all.
They often come from shared runner resource limits, slow dependency downloads, or unstable external services. Adding caching and better logging almost always reveals a consistent bottleneck.
Takeaway: Intermittent failures usually hide consistent constraints.
See lessWhy does my monitoring show healthy infrastructure but users still see errors?
Infrastructure metrics don’t reflect user experience. CPU and memory can look perfect while the application returns errors. Without request-level metrics, failures go unnoticed. Takeaway: Monitor user-facing signals, not just system health.
Infrastructure metrics don’t reflect user experience.
CPU and memory can look perfect while the application returns errors. Without request-level metrics, failures go unnoticed.
Takeaway: Monitor user-facing signals, not just system health.
See lessWhy does autoscaling create too many pods during short traffic spikes?
Autoscaling reacts faster than traffic patterns stabilize. Without proper stabilization windows, brief spikes trigger aggressive scale-ups that aren’t needed long-term. Tuning scale-down behavior usually fixes this. Takeaway: Autoscaling needs damping, not just thresholds.
Autoscaling reacts faster than traffic patterns stabilize.
Without proper stabilization windows, brief spikes trigger aggressive scale-ups that aren’t needed long-term. Tuning scale-down behavior usually fixes this.
Takeaway: Autoscaling needs damping, not just thresholds.
See lessTerraform keeps recreating resources even when nothing has changed—why?
Terraform does this when the real infrastructure doesn’t match the configuration exactly, even if the difference seems harmless. Small drifts—like default values set by the provider, manual console changes, or computed fields—can cause Terraform to think a resource needs replacement. This often happRead more
Terraform does this when the real infrastructure doesn’t match the configuration exactly, even if the difference seems harmless.
Small drifts—like default values set by the provider, manual console changes, or computed fields—can cause Terraform to think a resource needs replacement. This often happens after importing existing resources or tweaking things manually outside Terraform.
The plan output usually tells you which attribute is triggering the change, but it’s easy to overlook.
Takeaway: Terraform is strict by design; even small mismatches can cause replacement.
See less