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Capacity, cache and health boundaries

Spring operational components expose health, task admission and cache behavior under explicit application policies.

Learning roadmap

Read the contract, run the source-kit checks, and inspect a rejected input before extending the application. This subject covers Spring and Spring Boot together; Java language lessons remain in their own subject.

Prerequisites

Use Java object ownership, interfaces, exceptions and Maven builds before the framework-specific lessons.

Section lessons

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Boot Foundations, Spring Core, Web APIs, Data & Transactions, Security, Testing, Exercises, Quizzes, Projects.

Curriculum

Inspect the contract and its failure cases.

  1. 1Spring Boot Actuator health: public liveness without public diagnostics
  2. 2Spring task executors: capacity, rejection and lost context
  3. 3Spring cache keys: separate tenants and test the loader count

Inspect the state boundary and run its checked fixture.

  1. 1Spring Boot metrics: bound tag values instead of tracking each receipt

Follow the input contract, inspect failures and run the checked source.

  1. 1Spring cache eviction: invalidate the same tenant key used by the read

Run the source-kit fixture and inspect its rejected boundary.

  1. 1Spring readiness: report an unavailable dependency without forcing liveness failure

Run the source-kit test and inspect the rejected case.

  1. 1Spring @Cacheable sync: collapse a local same-key cache miss

Run the local fixture and inspect the retained state.

  1. 1At-least-once delivery: where Spring outbox retries can duplicate work

Check byte, storage and operational health boundaries.

  1. 1Spring Boot readiness health group: withdraw traffic on a required dependency failure
  2. 2Spring Boot liveness versus readiness: do not restart on every dependency outage

Trace ownership, retry and duplicate delivery boundaries.

  1. 1Spring outbox retries: due time, delay cap, and attempt accounting
  2. 2Spring outbox retry budget: park a poison event for inspection

Trace scheduled claims, retries and duplicate-safe completion.

  1. 1Spring outbox polling: cap work per tick and measure backlog age
  2. 2Spring scheduled retries: leave failed work pending until its due time
  3. 3Spring relay metrics: measure backlog without event-ID labels

Follow the boundary from local fixtures to a release test.

  1. 1Spring Boot graceful shutdown: finish accepted requests within a deadline
  2. 2Spring worker shutdown: release admission before a lease expires
  3. 3Spring readiness during termination: stop routing before stopping dependencies
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