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What you need to decide first
OpenShift does not prescribe one universal Spring Boot build-and-deploy path. The right workflow depends on the target release, cluster policy, registry access, and whether your organization builds images in the cluster or in CI. Red Hat’s OpenShift Container Platform 4.19 documentation organizes platform guidance across areas such as builds, images, ingress, security, configuration, and health monitoring; it is an overview, not a Spring Boot deployment recipe.
- Record the Java and Spring Boot versions used by the application, and the OpenShift release running the target cluster.
- Determine how images must be built, scanned, stored, and supplied to the cluster. Check registry access and any organizational base-image or supply-chain requirements.
- Choose whether image creation belongs in CI or an approved in-cluster build workflow. Compare ownership of base-image updates, reproducibility controls, cluster security compatibility, registry flow, and fit with the team’s release process.
- Confirm the cluster’s supported workload, service, route or ingress, configuration, security, and health-check practices in documentation for that exact release.
Build an OCI-compatible application image
One documented option is the Spring Boot Maven Plugin’s build-image goal. Its configuration includes options such as whether to publish the image and which run image to use. Review the plugin documentation for the version matching your project and the requirements of your target environment: Spring Boot Maven Plugin: build-image.
Use the image-building path your platform team supports. A locally or CI-built image must be available from a registry the cluster can access, while an in-cluster workflow must comply with the cluster’s build and security policies. The available platform overview does not establish one exact command sequence or manifest for every OpenShift installation, so do not copy a deployment recipe from a different release without checking it against your cluster.
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Deploy the image and configure access
Deploy the image as an application workload using the resource types and image-pull approach supported by your OpenShift release. Then configure an internal Service and, when users outside the cluster need access, the cluster’s supported Route or ingress mechanism. The precise resource definitions and commands depend on the release and cluster policy; use the corresponding sections of the OpenShift 4.19 documentation or the documentation for your actual target version.
Keep environment-specific settings outside the built image. Supply non-secret configuration through the mechanism approved for your cluster, and store credentials using its approved Secret and access-control practices. Avoid embedding live credentials in image layers, source control, or example manifests.
Configure health probes that reflect application health
With Spring Boot Actuator, Kubernetes-style health groups are available at /actuator/health/liveness and /actuator/health/readiness. Spring Boot bases these states on application availability. Liveness asks whether the process can recover internally; readiness asks whether this instance should receive traffic. See the Spring Boot 4.2 reference on Actuator endpoints and Kubernetes probes and the SpringApplication availability reference.
Liveness: avoid turning dependency outages into restart storms
Keep liveness independent of external services. Spring Boot states: “The “Liveness” probe should not depend on health checks for external systems.” If a shared database or API fails, marking every application instance as not live can cause restarts without fixing the dependency problem and can make an outage worse.
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Spring Boot does not include external dependency checks in readiness by default. Add one only when refusing traffic to this particular instance is useful—for example, when a required dependency failure is specific to that instance. A dependency shared by all replicas may call for a different response than an instance-local failure.
Point probes at a meaningful application port
Probe the port where the relevant Actuator endpoints are actually available. If management endpoints run on a separate server context or port, a successful management probe may not prove that the main application server can serve requests. Spring Boot documents adding probe paths on the main port as one option. Check the reference for your Spring Boot version and configure the OpenShift probe to match the chosen arrangement.
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Coordinate termination with traffic draining
During pod deletion, shutdown hooks, load-balancer removal, and other lifecycle actions can happen concurrently. Spring Boot describes using a pre-stop delay to allow routing to settle, followed by SIGTERM and graceful shutdown. Set the delay according to the deployment’s traffic-draining behavior and account for in-flight requests; then make the termination grace period long enough for the application’s configured shutdown to complete. Spring Boot’s cloud deployment guidance cites Kubernetes’ default grace period as 30 seconds, but verify the applicable setting on your target platform rather than assuming that value applies unchanged: Spring Boot cloud deployment and container lifecycle.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Verify the workload on the target cluster
After deployment, check the application in the context of the cluster rather than relying only on a successful image build.
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Quick Recap
- Confirm the workload starts and the expected image is pulled.
- Inspect application logs for startup errors and configuration problems.
- Check that liveness and readiness probes reach the intended endpoints and port, and that readiness changes appropriately when the application is unable to serve traffic.
- Test access through the internal Service and, if configured, the external Route or ingress path.
- Exercise termination during an appropriate test or release window. Observe traffic draining, in-flight requests, and whether shutdown completes within the configured grace period.
- Set CPU and memory requests, limits, and scaling behavior from measurements of this application under its expected workload. No sizing or performance figures are established by the cited documentation.
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