maxUnavailable: 0 does not guarantee that every client request survives a Kubernetes Deployment rollout. It constrains how many Pods the Deployment counts as unavailable; it does not measure successful requests or guarantee that readiness, endpoint updates, application shutdown, and every routing layer remain synchronized. To find the cause, trace one shared timeline from Pod readiness and deletion through EndpointSlice changes, application shutdown, and the ingress or load balancer actually serving traffic.
What maxUnavailable: 0 guarantees—and what it does not
Kubernetes defines maxUnavailable as the maximum number of Pods that may be unavailable during a Deployment’s rolling update. The Deployment controller uses Pod availability to manage rollout progress; this is not a client-request success metric. Kubernetes also documents that terminating Pods are not counted when calculating availableReplicas. A terminating Pod may still consume resources until its terminationGracePeriodSeconds expires. See the Deployment documentation.
With maxUnavailable: 0, the rollout needs a nonzero maxSurge: the two values cannot both be zero. Surge allows temporary Pods above the desired replica count, but those Pods still need enough schedulable capacity and must become ready. If a new Pod cannot schedule or become ready, rollout progression can stall. That is different from proving that the existing Pods will keep serving every request.
Where requests can be lost during a rollout
Readiness does not match real application health
A readiness probe is Kubernetes’ signal that a container can accept traffic. When readiness fails, the EndpointSlice controller removes the Pod IP from EndpointSlices for matching Services. But a probe can pass before the application can handle real requests—for example, before dependencies or caches are ready—or fail under conditions that do not correspond neatly to client-visible health. Inspect what the probe actually checks and correlate its transitions with request failures. Kubernetes describes these mechanics in its probe documentation.
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EndpointSlice state and the serving route differ
EndpointSlice membership is not, by itself, proof of when a particular ingress, proxy, or external load balancer stopped routing to a Pod. The Kubernetes lifecycle includes endpoint processing as Pod deletion proceeds, but the timing and behavior of an external dataplane are specific to that cluster. Compare the EndpointSlice view with the backend state used by the component that actually routes client requests.
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During graceful Pod termination, kubelet normally asks the container runtime to send SIGTERM to the main process. A configured preStop hook runs before that signal and counts within the termination grace period. Kubernetes documents a default terminationGracePeriodSeconds of 30 seconds; if the hook or shutdown work needs longer, configure an appropriate period. At grace-period expiry, remaining processes are killed. The application and any sidecars must handle this sequence: stopping or draining new work, completing or deliberately rejecting in-flight requests, and exiting within the available time. See the Pod lifecycle documentation.
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Surge Pods cannot be scheduled or made ready
A rollout can request additional Pods, but maxSurge does not reserve capacity for them. Check scheduler events and resource availability if replacement Pods remain pending. The Deployment rules describe the permitted counts, not whether a particular cluster has enough capacity to meet them.
Diagnose the failure by following one timeline
Collect timestamps during a reproduction or incident. Compare the following layers rather than relying on availableReplicas alone:
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- Confirm the live rollout settings. Inspect the Deployment’s strategy, desired replica count,
maxUnavailable,maxSurge,minReadySeconds, and rollout conditions. Check whether the rollout is progressing or stalled. The Deployment documentation describes these controls; confirm the applicable API behavior for the Kubernetes release you run. - Record Pod state changes. Capture readiness transitions, deletion and termination timestamps, and when replacement Pods become ready. Include ready, available, and terminating replica counts. Do not treat the available count as evidence that requests were uninterrupted.
- Test the readiness signal against the real request path. Check the probe endpoint alongside the application’s dependencies, cache warmup, and overload behavior. Compare those observations with failed requests and probe transitions.
- Compare endpoint and router state. Inspect the Service’s EndpointSlices, then verify when the actual ingress, proxy, or external load balancer stops routing to a terminating Pod. Record the component’s backend state at the same timestamps.
- Review shutdown behavior. Check application and sidecar logs for
SIGTERMhandling, active-request draining,preStopwork, the grace-period limit, and forced termination at expiry. Compare the time needed to drain with the time actually available. - Check surge scheduling. Review events and resource capacity for the extra Pods allowed by
maxSurge. Determine whether replacements scheduled and became ready when expected.
Interpret the evidence across layers
| Compare | What to establish | Evidence to inspect |
|---|---|---|
| Kubernetes readiness vs. application health | Whether a passing or failing probe accurately represented the application’s ability to serve the affected requests. | Probe results and transitions, request outcomes, dependency or cache state, and overload behavior. |
| EndpointSlice membership vs. router backends | Whether the actual traffic-serving layer stopped sending traffic to the terminating Pod when expected. | EndpointSlice conditions and the ingress, proxy, or load balancer’s backend state. |
| Application drain time vs. termination grace period | Whether shutdown and in-flight work could finish before the grace period expired. | Termination timestamps, application and sidecar logs, preStop duration, and forced-kill evidence. |
| Requested surge vs. schedulable capacity | Whether replacement Pods could be scheduled and made ready during the update. | Pending Pod details, scheduler events, and available cluster resources. |
These are separate layers, so correlate them on the same timeline before attributing the drops to a specific mechanism. The applicable behavior can depend on the Kubernetes release, application, CNI, proxy or ingress, and cloud load balancer. Kubernetes documentation explains the control-plane and Pod-lifecycle mechanisms; without cluster events or traffic traces, it cannot identify which one caused a particular outage.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Configuration defaults are not incident statistics
The Kubernetes Deployment documentation lists 25% as the default for both maxUnavailable and maxSurge for a rolling update. Percentages for maxUnavailable round down; percentages for maxSurge round up. The Pod lifecycle documentation lists 30 seconds as the default termination grace period. These are documented defaults, not measurements of request loss, and exact behavior should be checked against the Kubernetes release in use.
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