Before a Spring Boot MVP goes live, verify the exact artifact, configuration, access rules, data behavior, and operational checks that the first deployment will use. A successful developer-machine run is not enough: readiness depends on your Spring Boot and Java versions, database, platform, and the security and reliability your users need.
1. Are your Spring Boot and Java versions supported?
Record the Spring Boot and Java versions used to build the release artifact. Check the current Spring Boot supported-version information and the framework’s compatibility requirements before changing either version. At the documentation check dated October 7, 2026, the Spring Boot homepage listed 4.1.1 among its stable versions; that is a dated snapshot, not a recommendation to upgrade every existing application to that release.
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- Confirm the runtime used by the deployment platform is compatible with the application’s Spring Boot version.
- Make the versions visible in your release notes or deployment record so an incident can be tied to the code and runtime that produced it.
2. Does the release build pass the tests that matter?
Run the automated tests against the same build you intend to ship. Cover the user-visible promises of the MVP and important failure paths, such as rejected input or an unavailable dependency. Spring Boot’s test starter includes common test support, including JUnit Jupiter and assertion libraries.
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- Check that the release build, rather than only an IDE or development run, completes the test suite.
- Choose test depth for the application’s risks; there is no universal coverage percentage that makes an MVP ready.
3. Does the deployed app receive the right configuration?
Check the effective values the application will use for its database, external services, URLs, and feature toggles. Spring Boot can read configuration from files, environment variables, and command-line arguments; property-source order means a later source can override an earlier one.
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- Compare the expected production values with the values supplied by the deployment environment.
- Check which source wins when the same property appears in more than one place.
- Inspect configuration safely, without exposing credentials in logs, screenshots, or release records.
4. Are production secrets kept out of the code and logs?
Verify that production credentials come from the deployment’s secret or configuration mechanism, not committed application defaults. Check that startup messages, errors, and diagnostic output do not reveal them. Spring Boot’s configuration documentation describes configuration sources, but it does not prescribe a particular secret-management product.
5. Do authentication and authorization behave correctly?
For each important route, test both the permitted request and a request that should be denied, using the intended production security configuration. Spring Security affects unauthenticated request behavior when present, but adding the dependency alone does not prove that application-specific authorization rules are correct.
- Test routes that expose user data or change application state.
- Verify the identity and permissions expected for each allowed action, along with the response for an unauthorized or unauthenticated request.
6. Which management endpoints are reachable?
Review which Actuator endpoints are available and which are exposed to the network. Spring Boot documents separate controls for endpoint access and exposure. Keep remotely reachable endpoints limited to what the deployment needs, and make access intentional: operational endpoints can reveal application configuration or other details, not just health status.
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Confirm that the platform’s health check reaches the intended health endpoint and that the team can see the health and metrics it needs to operate the service. Spring Boot presents Actuator as its production monitoring and management feature set, including health, auditing, and metrics capabilities; those features still need to be configured and used.
- Check the configured health-check address from the platform’s point of view.
- Verify that the team knows where to look when a health check fails or a metric changes.
8. Will application data survive a restart?
Verify the production database connection and the persistence behavior the application requires. An embedded in-memory database can be useful for development or tests, but Spring Boot’s SQL database documentation states: “Obviously, in-memory databases do not provide persistent storage.” Its data is discarded when the application ends, so it is not a substitute for durable production storage.
9. How will a schema change be applied and recovered?
Decide how this release applies schema changes, how you will verify the resulting schema, and what you will do if a change fails. The right plan depends on the project’s database and migration approach; Spring Boot’s database and Actuator references describe support and optional migration visibility, but do not make one migration tool a universal requirement.
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- Identify the release step that applies the change and the check that confirms it succeeded.
- Determine whether recovery means retrying, rolling back application code, restoring data, or another action appropriate to the change.
10. Have you reviewed dependency vulnerability alerts?
Review the project’s dependency alerts and assess vulnerable components before release. GitHub describes Dependabot alerts as a way to find and fix vulnerable dependencies; an alert can include severity and fixed-version information when available. Alerts are a useful input, not a guarantee that every vulnerability will be detected or resolved.
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- Assign someone to assess relevant alerts and decide whether to update, mitigate, or document the risk.
- Check that an update is compatible with the application and its tests before shipping it.
11. Can you diagnose failures without leaking sensitive data?
Check that failures produce enough diagnostic information for the team to investigate, while excluding sensitive data. Spring Boot Actuator includes endpoints for logger configuration and application information, but the logging content, retention, and redaction rules depend on the application and the data it handles.
- Review representative startup and error output for useful context and accidental secrets.
- Know where production logs are available to the people responsible for support.
12. Does the packaged application start in deployment-like conditions?
Start the packaged release artifact using the run mode and environment assumptions expected in production. Spring Boot supports executable JARs and other deployment forms. A successful local development run does not establish that the packaged artifact will start correctly with the deployed runtime and configuration.
- Use the artifact produced by the release build, not a separate development output.
- Confirm that startup completes with the production-like configuration and that the process remains available for the platform to manage.
13. If you ship a container, have you tested the actual image?
Build and start the container image you plan to deploy. Spring Boot supports Docker-compatible images through Cloud Native Buildpacks and provides Dockerfile guidance, including layered JAR layouts. Neither approach is universally best; weigh operational simplicity, compatibility with the target platform, build reproducibility, and how the runtime will be updated.
- Build the image from the release artifact and confirm it starts with the expected environment settings.
- Choose the build approach that fits the team’s platform and update process, rather than treating a local container build as proof of production compatibility.
14. Who owns deployment recovery and data restoration?
Identify who can diagnose a failed deployment, restore data, or roll back an application release. Verify that the necessary steps exist for the selected platform and that the responsible people can carry them out. The exact recovery actions depend on the infrastructure and data requirements; Spring Boot does not provide a universal recovery procedure for every deployment.
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After deployment, exercise the user-critical path in the actual environment. Check expected response behavior, health visibility, and the configuration the running application receives. The smoke test should reflect the MVP’s user journey and infrastructure, not a generic endpoint checklist.
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- Perform the smallest end-to-end action that represents the application’s core user promise.
- Confirm the response or resulting state is what the application is meant to produce.
- Check that the deployed service is visible to the platform’s health monitoring and that its effective environment configuration is correct.
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