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Readiness controls traffic; liveness controls restarts. A failed readiness probe marks a Pod unready so Services stop sending it new requests, but the container keeps running. A failed liveness probe tells the kubelet that the process needs recovery, so the kubelet restarts that container after the configured failure threshold. A startupProbe protects slow initialization by delaying both checks until startup succeeds.
That distinction explains the common mystery of a Pod that is Running but receives no traffic: phase status only says the container process has started. Service routing depends on the Pod’s Ready condition and the endpoints selected by the Service.
The difference in one view
| Probe | Question it answers | When it fails | What it should examine |
|---|---|---|---|
readinessProbe |
Can this container accept useful requests now? | The Pod is marked unready and removed from Service backends. The container is not automatically restarted. | Current ability to serve traffic, including initialization state, deliberate draining, or a required dependency that makes requests impossible to complete. |
livenessProbe |
Is the process unhealthy enough that restarting it is an appropriate recovery action? | After the configured consecutive failures, the kubelet restarts the container. | A cheap, local indication that the process is deadlocked or otherwise unable to make progress. |
startupProbe |
Has initialization completed so normal health checks are safe? | The container is treated as having failed startup when its failure budget is exhausted. | Slow bootstrap work such as loading a large data set, migrations, or configuration initialization. |
Kubernetes can run readiness and liveness checks independently. They are not two names for the same health test: one gates traffic, while the other authorizes a restart.
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How probe results affect traffic and restarts
Readiness changes the Service’s eligible backends
A Service normally routes to ready endpoints. When a readiness check fails, Kubernetes changes the Pod’s readiness condition and removes that Pod from the Service’s endpoint set. Existing connections may finish according to the application and proxy behavior, but new load-balancing decisions should no longer choose that Pod. The process remains alive, allowing it to finish initialization, recover a transient dependency, or complete a drain operation.
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Readiness is evaluated throughout the container lifecycle, not only at startup. A Pod can become unready during a rollout, while draining for shutdown, or when it temporarily cannot provide a correct response. When the check succeeds again, Kubernetes requires the configured number of successful results before restoring readiness.
Liveness authorizes a container restart
The kubelet uses liveness to decide whether a container is stuck or irrecoverably unhealthy from the container’s point of view. Once failures reach failureThreshold, the kubelet terminates and restarts the container, using the applicable termination grace period. A restart can recover a deadlock, but it also interrupts requests and clears in-memory state. If the test is too sensitive, repeated restarts can become a restart storm and reduce the capacity of every remaining Pod.
Running is not the same as Ready
kubectl get pod may show a Pod in the Running phase while its READY count is lower than the number of containers. That means the process exists but at least one readiness condition is false. The authoritative traffic path is the Service selector and its EndpointSlice objects, not the phase alone.
What a readiness probe should check
Design readiness around the sentence: “If this check succeeds, can the application handle a real request now?” A useful readiness endpoint is fast, deterministic, and reflects conditions that make serving impossible or unsafe.
Good readiness conditions
- Application initialization has completed and required in-memory state is loaded.
- The instance is not intentionally draining for a rollout, maintenance operation, or graceful shutdown.
- A dependency that every relevant request requires is currently available, or the application has no safe degraded mode.
- The listener is bound and the request path can be handled by this instance.
When a dependency belongs in readiness
Put a dependency check in readiness when its outage means this Pod cannot successfully serve the traffic it would receive. For example, an API that must read from one database for every request can report unready while that database is unreachable. This drains the Pod without killing it, giving the dependency time to recover.
Do not make readiness depend on every optional integration. If a metrics exporter, cache, recommendation service, or other nonessential component is down but the application can still answer its contractual requests, keeping the Pod ready preserves capacity. An over-broad readiness check can drain all replicas during an unrelated outage and make a rollout appear stuck.
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Readiness endpoint behavior
Use a dedicated, low-cost endpoint rather than a full business transaction. It should return success only when the service’s stated readiness conditions are true and should avoid expensive queries or side effects. Kubernetes recommends a minimal HTTP response body. The handler must listen on the Pod IP and the configured port; binding only to an unexpected interface or port makes the probe fail even when the application works from another address.
What a liveness probe should check
Liveness is a recovery signal, so a failure must justify terminating the process. Check a condition that the process itself can recover from only by restarting, such as a deadlock or a main event loop that has stopped making progress.
Keep liveness local and inexpensive
- Check that the process can execute a small internal health operation.
- Use bounded work with a short, realistic response time.
- Avoid making the result depend on a database, queue, DNS server, or third-party API unless a restart is genuinely the correct response to that dependency’s failure.
- Make the endpoint independent of the code path whose failure you are trying to detect, where practical.
Kubernetes warns that an incorrectly implemented liveness probe can cause cascading failures. Under high load, a check that times out briefly may restart otherwise recoverable containers; those restarts create more work, fail client requests, and leave fewer Pods to serve traffic. A dependency outage should normally be represented by readiness, backoff, or application-level error handling rather than by liveness.
Separate liveness from readiness in the application
It is acceptable for both probes to use the same HTTP server, but they should have distinct semantics. A liveness response should not turn false merely because the database is unavailable if restarting will not repair the database connection. A readiness response can turn false for that condition so traffic drains while the process remains available to reconnect.
How startupProbe protects slow applications
Configure startupProbe when the worst-case initialization time is longer than the normal liveness or readiness budget. While startup has not succeeded, Kubernetes does not begin liveness or readiness probing. The application can perform migrations, restore a large state file, warm a runtime, or initialize configuration without being killed by a liveness check intended for an already-running process.
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Size the startup budget for the slowest expected startup, not the median. The Kubernetes documentation illustrates failureThreshold: 30 with periodSeconds: 10, a 300-second budget (30 × 10 seconds). This is an example configuration, not a benchmark or a universal recommendation. Once startup succeeds, the regular liveness and readiness probes take over.
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A startup probe does not replace readiness. An application can finish booting successfully and later lose a required dependency; readiness must still remove it from traffic. Likewise, startup success does not prove that a deadlock will never occur; liveness remains responsible for post-startup recovery.
Supported probe handlers and endpoint requirements
| Handler | Use it when | Common failure causes |
|---|---|---|
| HTTP | The application exposes a lightweight health path. | Wrong path, port, host binding, status behavior, TLS or protocol assumptions, or an endpoint that performs slow work. |
| TCP | A listening socket is the meaningful minimum signal. | Wrong port, listener not bound to the Pod network, or a socket that accepts connections but cannot actually serve requests. |
| gRPC | The service implements the gRPC health-checking protocol. | Wrong port, wrong health service name, or an unimplemented health protocol. |
| Exec | A local command can reliably test the process without network access. | Incorrect command, missing executable, different environment or permissions, or a command that is too expensive. |
For HTTP, use a dedicated endpoint with a minimal body and ensure the handler listens on the Pod IP and configured port. Kubernetes treats an incorrect port or service name, and an unimplemented gRPC health-checking protocol, as probe failures. A probe that cannot reach the handler is not evidence that the application is intentionally unready; it is usually a configuration or networking defect.
Probe timing fields and their operational effects
| Field | Meaning | Design implication |
|---|---|---|
initialDelaySeconds |
Delay before probing begins, unless a startup probe is gating the later probes. | Use it for a predictable initial delay; use startupProbe when startup duration is variable or long. |
periodSeconds |
Interval between probe attempts. The documented default is 10 seconds and the minimum is 1 second. | Short intervals detect changes faster but add request and logging load. |
timeoutSeconds |
Maximum time allowed for one probe response. | Set it above normal endpoint latency while keeping it short enough to detect a real stall. |
failureThreshold |
Consecutive failures required before the probe’s failure action. | For liveness, this controls how much transient trouble is tolerated before a restart. For readiness, it controls how quickly traffic is drained. |
successThreshold |
Consecutive successes required to become ready again. | Readiness can use this to prevent flapping; liveness normally uses the default behavior and should not be treated as a traffic gate. |
terminationGracePeriodSeconds |
Grace period used when the kubelet terminates a failed container, subject to Kubernetes version and field behavior. | Allow enough time for the process to close listeners and finish or reject work cleanly, without masking a genuine failure for too long. |
Tune these values as a set. A one-second timeout with a one-second period may be appropriate for a tiny local check but is fragile for a loaded runtime. Conversely, a very large failure threshold can leave a broken Pod receiving traffic for too long when used on readiness.
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The following example separates startup, readiness, and liveness semantics on port 8080. The endpoint names are illustrative; your application must implement equivalent handlers.
apiVersion: apps/v1
kind: Deployment
metadata:
name: orders-api
spec:
replicas: 3
selector:
matchLabels:
app: orders-api
template:
metadata:
labels:
app: orders-api
spec:
containers:
- name: api
image: example/orders-api:2.4
ports:
- name: http
containerPort: 8080
startupProbe:
httpGet:
path: /startup
port: http
periodSeconds: 10
timeoutSeconds: 2
failureThreshold: 30
readinessProbe:
httpGet:
path: /ready
port: http
periodSeconds: 5
timeoutSeconds: 2
failureThreshold: 3
successThreshold: 2
livenessProbe:
httpGet:
path: /live
port: http
periodSeconds: 10
timeoutSeconds: 2
failureThreshold: 3
terminationGracePeriodSeconds: 30Here, startup has a documented illustrative maximum of 300 seconds if every attempt is made at the 10-second interval. Readiness requires three consecutive failures to drain traffic and two consecutive successes to re-admit the Pod, which can reduce rapid ready/unready oscillation. Liveness requires three consecutive failures before a restart. Choose values from observed startup and response behavior rather than copying them blindly.
Why a Pod can be Running but receive no traffic
1. The readiness port is wrong
If the probe targets port 8080 but the process listens on 8081, the kubelet cannot obtain a successful result. The container may appear Running, yet the Pod remains unready and the Service has no endpoint for it. Named ports reduce this class of mismatch, but verify that the name resolves to the intended container port.
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2. The readiness path is wrong or has different semantics
A typo such as /healthz versus /ready, a route mounted under a prefix, or an endpoint that returns failure during normal degraded operation can keep a Pod out of the backend set. Confirm the exact path in the live Pod specification and check what the application returns on the Pod IP and port.
3. The protocol or gRPC service name is incorrect
HTTP, TCP, and gRPC probes are not interchangeable. A gRPC probe must use the health-checking protocol implemented by the service and the expected service name. An unimplemented protocol or incorrect service name is a probe failure, even if another application endpoint responds.
4. Readiness checks a nonessential dependency
If readiness fails whenever an optional cache, analytics system, or external API is unavailable, every replica can be drained for an incident that does not prevent core requests. Define the minimum dependency set for a successful request and keep optional integrations out of the readiness decision.
5. Liveness checks a dependency and triggers restarts
A database outage can make a dependency-heavy liveness endpoint fail. The kubelet then restarts containers that could have recovered by reconnecting, potentially creating a restart storm. Move the dependency condition to readiness or application-level handling unless restarting is known to repair the process.
6. There is no startup protection
A slow process can fail liveness during initialization. The kubelet restarts it before it ever becomes ready, producing repeated startup failures. Add a startup probe with a budget covering the worst expected initialization, or adjust the normal timing fields when startup is short and predictable.
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Short timeouts and low thresholds can interpret CPU contention, garbage collection, disk pauses, or temporary queueing as failure. Readiness may flap and repeatedly add and remove endpoints; liveness may restart healthy processes. Examine probe latency under peak conditions and set tolerance deliberately.
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8. The Service does not select the Pod
A healthy readiness result does not help if the Service selector labels do not match the Pod labels, or if the request is sent to a different Service or namespace. This is a routing configuration problem, not a probe implementation problem. Inspect the selector and EndpointSlice objects separately from Pod conditions.
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- Check phase and readiness separately. Run
kubectl get pods -o wideand compare theREADYcolumn withSTATUS. A Running Pod with a lower ready count confirms that traffic eligibility, not process existence, is the immediate issue. - Read the Pod events. Run
kubectl describe pod <pod-name>. Look for probe failure messages, connection-refused errors, timeouts, HTTP path details, and recent container restarts. Events often reveal a wrong port or path faster than application logs. - Inspect the actual probe specification. Run
kubectl get pod <pod-name> -o yamland verify handler type, path, port, gRPC service name, delays, periods, timeouts, and thresholds. Check the rendered Pod, not only the source template, because admission or deployment tooling may have changed it. - Check application logs around the failure time. Use
kubectl logs <pod-name> -c <container-name>. If the container has restarted, add--previousto inspect the prior instance and determine whether liveness failures preceded the restart. - Test the endpoint from the Pod network. Execute an HTTP request or TCP check from inside the Pod, or use a temporary diagnostic container when the image lacks a client. Test the exact Pod IP, port, path, scheme, and protocol used by the probe. A request from your workstation may succeed through an ingress while the kubelet still cannot reach the Pod listener.
- Verify the Service selector. Run
kubectl describe service <service-name>and compare its selector with the Pod labels. A selector mismatch yields no backends even when every probe is passing. - Inspect EndpointSlices. Run
kubectl get endpointslice -l kubernetes.io/service-name=<service-name> -o wide. Confirm that the expected Pod IP appears and that its ready condition is true. If the slice is empty, resolve readiness or selector issues before investigating clients. - Check restart history and startup timing. Use
kubectl get pod <pod-name> -o jsonpath='{.status.containerStatuses[*].restartCount}'and review events. Frequent restarts during boot point to missing startup protection or an undersized startup budget; restarts only under load point toward an overly sensitive liveness check. - Change one cause at a time. Correct the port or path first, then observe a full probe interval and the success threshold. Avoid simultaneously loosening every threshold, because that can hide a real outage and makes the successful fix impossible to identify.
Design patterns that avoid probe-induced incidents
Use three explicit contracts
- Startup contract: initialization is complete and the normal health endpoints can be evaluated.
- Readiness contract: the instance can handle the traffic the Service may send now.
- Liveness contract: the process is making progress and should not be replaced.
Document those contracts next to the Deployment manifest so future changes do not turn a dependency check into a restart trigger.
Make drain behavior intentional
When an instance is draining, make readiness fail before terminating the process. This removes it from new Service traffic while preserving time for connection draining and graceful shutdown. The termination grace period then provides a bounded window for the process to close cleanly.
Design for transient failures
Readiness should tolerate a short-lived dependency interruption according to the application’s recovery behavior, while success thresholds can prevent immediate re-admission after one lucky response. Liveness should be even more conservative: a single slow request should not restart a process that can recover without replacement.
Keep probe handlers observable
Record probe failures without turning the health endpoint into a high-volume logging source. Expose enough metrics to distinguish endpoint latency, dependency failure, and process-progress failure. During an incident, correlate those signals with Pod events, restart counts, and EndpointSlice membership.
Do not confuse application probes with API-server health endpoints
Kubernetes also exposes API-server health endpoints named livez and readyz. livez represents API-server liveness, while readyz represents API-server readiness. The older healthz endpoint is deprecated for this purpose. These endpoints are related to the same operational concepts but are separate from the livenessProbe and readinessProbe fields in an application container specification.
A decision framework for choosing the probe
| Question | If yes | Probe or action |
|---|---|---|
| Would sending a new request to this instance now produce an unusable result? | Keep it out of load balancing until the condition clears. | Readiness failure. |
| Is the process itself deadlocked or unable to make progress, and is restart a suitable repair? | Replace the process. | Liveness failure. |
| Can initialization exceed normal probe timing? | Delay normal checks until initialization finishes. | Startup probe. |
| Is the problem an optional dependency that does not block core requests? | Continue serving core traffic. | Do not fail readiness or liveness solely for that dependency. |
| Does the failure come from a wrong port, path, protocol, selector, or service name? | Fix configuration or routing before changing thresholds. | Inspect the rendered Pod, Service, and EndpointSlices. |
The reliable operating rule is simple: readiness answers whether traffic should arrive, liveness answers whether the process should be restarted, and startup answers whether either decision should wait.
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