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Before a Spring Boot MVP goes live, check the exact artifact and configuration you plan to deploy—not just whether the application runs on a developer machine. The checks below cover framework support, tests, configuration, access controls, persistence, operations, and post-deployment verification. Which checks need the most depth depends on your Spring Boot and Java versions, database, platform, and the risks your MVP must handle.
1. Confirm Spring Boot and Java support
Record the Spring Boot and Java versions used to build the release, and verify that the framework version is supported and compatible with the Java runtime. The Spring Boot project page lists 4.1.1 among its stable versions, but that is a changing snapshot, not a reason to upgrade an existing application without checking its compatibility requirements. Spring Boot describes its purpose this way: “Spring Boot helps you to create stand-alone, production-grade Spring-based applications that you can run.”
2. Build and test the release candidate
Run the automated tests against the same release build you intend to ship. Cover the user-visible promises and important failure paths—for example, what happens when a required external service is unavailable. Choose test depth for your application; there is no universal coverage percentage that establishes readiness. Spring Boot’s testing reference describes the test starter and its common support, including JUnit Jupiter and assertion libraries.
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Check what the deployed process actually receives for database connections, external services, URLs, and feature toggles. Spring Boot accepts configuration through files, environment variables, and command-line arguments. Property-source precedence means a later source can override an earlier one, so reviewing a local configuration file alone may miss the value that takes effect in production. See the externalized configuration reference.
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4. Keep credentials out of code and logs
Confirm that production credentials are supplied through the deployment’s configuration or secret mechanism rather than committed as application defaults. Check that startup errors and diagnostic logs do not expose credentials. The right mechanism depends on the deployment platform; Spring Boot’s configuration documentation describes configuration sources, but does not prescribe a particular secret manager.
5. Test authentication and authorization on important routes
For each route that matters, test both the intended access and a denied request using the production security configuration. If Spring Security is present, it changes how unauthenticated requests are handled, but the dependency alone does not prove that application-specific authorization rules are correct. The Spring Security getting-started guide explains the framework’s initial behavior; verify your own route rules explicitly.
6. Review Actuator endpoint access and exposure
Inventory the management endpoints your application makes available and which ones it exposes. Keep the remotely reachable surface limited to what the deployment needs, and decide deliberately who can access it. Health information is not the only concern: operational endpoints can reveal application or configuration details. Spring Boot documents separate controls for endpoint access and exposure.
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Verify that the platform’s health check reaches the intended health endpoint and that someone on the team can see service health and relevant metrics. Spring Boot’s Actuator feature set includes production-oriented health, auditing, metrics, and management capabilities. Those features still need to be configured and used in the deployed system.
8. Confirm that production data is durable
Test the production database connection and confirm that application data behaves as intended across a process restart. An embedded in-memory database can be useful for development or tests, but it is not durable production storage: Spring Boot’s SQL database reference states, “Obviously, in-memory databases do not provide persistent storage.” Treat the database choice, backup plan, and recovery needs as related decisions rather than assuming a development setup carries over.
9. Decide how schema changes are applied and recovered
Before release, determine how the deployment applies schema changes, how you will verify they succeeded, and what you will do if a change fails. The right plan depends on the database and migration approach you actually use; Spring Boot does not make one migration framework a universal requirement. Include the recovery path in the release procedure rather than discovering it during a failed rollout.
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10. Review dependency vulnerability alerts
Check the project’s dependency alerts and assess whether vulnerable components should be updated before release. GitHub Dependabot alerts can identify vulnerable dependencies and may include severity and fixed-version information when available. Alerts help surface known issues; they do not guarantee that every vulnerability is detected or that an update is safe without testing.
11. Make failures diagnosable without leaking sensitive data
Review representative error paths and confirm that logs provide enough context for the team to investigate while excluding secrets and sensitive user data. Decide how logs are retained and who can access them. Actuator also provides logger-configuration and application-information endpoints, but the content, redaction, and retention rules remain system-specific.
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Run the packaged release using the same mode and environmental assumptions the deployment will use. Spring Boot supports executable JARs and other deployment forms; a successful run from an IDE does not show that the packaged artifact starts correctly with production-like settings. The deployment reference describes supported deployment options.
13. If using containers, test the actual image
Build and start the image you intend to deploy, not just the application outside the container. Check that the image works with the target platform and that the team has a reproducible way to rebuild and update its runtime. Spring Boot supports Docker-compatible images through Cloud Native Buildpacks and also provides Dockerfile guidance, including layered JAR layouts. Neither approach is universally best; choose according to build workflow and platform compatibility.
14. Assign operational and recovery ownership
Make clear who will diagnose a failed deployment, restore data, or roll back an application release. Verify that the relevant instructions and permissions exist for your platform, database, and team. The exact recovery actions depend on your infrastructure and data requirements; Spring Boot does not provide a universal rollback or restore procedure.
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After deployment, verify the user-critical path and expected response behavior in the real environment. Also confirm that health information is visible to the team and that the application is using the intended configuration. Define the smoke test around the MVP’s actual user journey and infrastructure, rather than relying on a generic endpoint check alone.
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