Readiness & Liveness
Overview of various probes that we can setup to ensure the service deployment and the availability of the service is ensured automatically.
Last updated
Overview of various probes that we can setup to ensure the service deployment and the availability of the service is ensured automatically.
Last updated
All content on this page by eGov Foundation is licensed under a Creative Commons Attribution 4.0 International License.
On this page:
Determining the state of a service based on readiness, liveness, and startup to detect and deal with unhealthy situations. It may happen that the application needs to initialize some state, make database connections, or load data before handling application logic. This gap in time between when the application is actually ready versus when Kubernetes thinks is ready becomes an issue when the deployment begins to scale and unready applications receive traffic and send back 500 errors.
Many developers assume that when basic pod setup is adequate, especially when the application inside the pod is configured with daemon process managers (e.g. PM2 for Node.js). However, since Kubernetes deems a pod as healthy and ready for requests as soon as all the containers start, the application may receive traffic before it is actually ready.
Kubernetes supports readiness and liveness probes for versions ≤ 1.15. Startup probes were added in 1.16 as an alpha feature and graduated to beta in 1.18 (WARNING: 1.16 deprecated several Kubernetes APIs. Use this to check for compatibility).
All the probes have the following parameters:
initialDelaySeconds : number of seconds to wait before initiating liveness or readiness probes
periodSeconds: how often to check the probe
timeoutSeconds: number of seconds before marking the probe as timing out (failing the health check)
successThreshold : minimum number of consecutive successful checks for the probe to pass
failureThreshold : number of retries before marking the probe as failed. For liveness probes, this will lead to the pod restarting. For readiness probes, this will mark the pod as unready.
Readiness probes are used to let Kubelet know when the application is ready to accept new traffic. If the application needs some time to initialize the state after the process has started, configure the readiness probe to tell Kubernetes to wait before sending new traffic. A primary use case for readiness probes is directing traffic to deployments behind a service.
One important thing to note with readiness probes is that it runs during the pod’s entire lifecycle. This means that readiness probes will run not only at startup but repeatedly throughout as long as the pod is running. This is to deal with situations where the application is temporarily unavailable (i.e. loading large data, waiting on external connections). In this case, we don’t want to necessarily kill the application but wait for it to recover. Readiness probes are used to detect this scenario and not send traffic to these pods until it passes the readiness check again.
Liveness probes are used to restart unhealthy containers. The Kubelet periodically pings the liveness probe, determines the health, and kills the pod if it fails the liveness check.
Liveness checks can help the application recover from a deadlock situation. Without liveness checks, Kubernetes deems a deadlocked pod healthy since the underlying process continues to run from Kubernetes’s perspective. By configuring the liveness probe, the Kubelet can detect that the application is in a bad state and restarts the pod to restore availability.
Startup probes are similar to readiness probes but only executed at startup. They are optimized for slow-starting containers or applications with unpredictable initialization processes. With readiness probes, we can configure the initialDelaySeconds to determine how long to wait before probing for readiness. Now consider an application where it occasionally needs to download large amounts of data or do an expensive operation at the start of the process. Since initialDelaySeconds is a static number, we are forced always to take the worst-case scenario (or extend the failureThreshold one that may affect long-running behaviour) and wait for a long time even when that application does not need to carry out long-running initialization steps. With startup probes, we can instead configure failureThreshold and periodSeconds to model this uncertainty better. For example, setting failureThreshold to 15 and periodSeconds to 5 means the application will get 10 x 5 = 75s to startup before it fails.
Now that we understand the different types of probes, we can examine the three distinct ways to configure each probe.
The Kubelet sends an HTTP GET request to an endpoint and checks for a 2xx or 3xx response. You can reuse an existing HTTP endpoint or set up a lightweight HTTP server for probing purposes (e.g. an Express server with /healthz endpoint).
HTTP probes take in additional parameters:
host : hostname to connect to (default: pod’s IP)
scheme : HTTP (default) or HTTPS
path : path on the HTTP/S server
httpHeaders : custom headers if you need header values for authentication, CORS settings, etc
port : name or number of the port to access the server
To check whether or not a TCP connection can be made, you can specify a TCP probe. The pod is marked healthy if it can establish a TCP connection. Using a TCP probe may be useful for a gRPC or FTP server where HTTP calls may not be suitable.
Finally, a probe can be configured to run a shell command. The check passes if the command returns with exit code 0; otherwise, the pod is marked as unhealthy. This type of probe may be useful if it is not desirable to expose an HTTP server/port or if it is easier to check initialization steps via command (e.g. check if a configuration file has been created, run a CLI command).
The exact parameters for the probes depend on your application, but here are some general best practices to get started:
For older (≤ 1.15) Kubernetes clusters, use a readiness probe with an initial delay to deal with the container startup phase (use p99 times for this). But make this check lightweight since the readiness probe will execute throughout the entire lifecycle of the pod. We don’t want the probe to time out because the readiness check takes a long time to compute.
For newer (≥ 1.16) Kubernetes clusters, use a startup probe for applications with unpredictable or variable startup times. The startup probe may share the same endpoint (e.g. /healthz ) as the readiness and liveness probes, but set the failureThreshold higher than the other probes to account for longer start times, but more reasonable time to failure for liveness and readiness checks.
Readiness and liveness probes may share the same endpoint if the readiness probes aren’t used for other signalling purposes. If there’s only one pod (i.e. using a Vertical Pod Autoscaler), set the readiness probe to address the startup behaviour and use the liveness probe to determine health. In this case, marking the pod unhealthy means downtime.
Readiness checks can be used in various ways to signal system degradation. For example, if the application loses connection to the database, readiness probes may be used to temporarily block new requests and allow the system to reconnect. It can also be used to load balance work to other pods by marking busy pods as not ready.
In short, well-defined probes generally lead to better resilience and availability. Be sure to observe the startup times and system behaviour to tweak the probe settings as the applications change.
Considering the significance of Kubernetes probes, you can utilize a Kubernetes resource analysis tool to identify any missing probes. These tools can be executed against existing clusters or integrated into the CI/CD pipeline to automatically reject workloads that don't have properly configured resources.
: a resource analysis tool with a nice dashboard that can also be used as a validating webhook or CLI tool.
: a static code analysis tool that works with Helm, Kustomize, and standard YAML files.
: read-only utility tool that scans Kubernetes clusters and reports potential issues with configurations.
