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- Compilation And Inlining LogsReading what the JIT actually did: the columns of -XX:+PrintCompilation and its flag characters, -XX:+PrintInlining and its verdict strings, -XX:+LogCompilation with JITWatch, the -Xlog:jit+compilation and JFR forms, targeted compiler directives, and turning a refusal into a code change. Use when a hot method is suspected of not reaching tier 4, when a call site shows "too big" or another inlining refusal, when a method never appears in the compilation log at all, when someone prescribes -XX:...Votes: 0GitHub stars: 2
- Collaborative Feature DefinitionCo-authoring Product Features and Tech Features through focused question-and-revision rounds. For a Product Feature, separates the business definition from an optional engineering analysis owned by an architect or senior engineer, including PoCs, ADRs, contracts, and engineering premises. Use when an idea needs an agreed feature brief or an evidenced decision not to proceed, not implementation. Accepted features go to feature-engineering for validation and execution planning.Votes: 0GitHub stars: 2
- Coding Agent DisciplineThe reporting and restraint rules for an AI agent changing someone's codebase: never claiming a result that was not observed, saying which commands ran and what they printed, reporting what could not be verified rather than omitting it, keeping the diff to what was asked, preserving behaviour that was not in scope, checking APIs against the versions the project actually depends on, and refusing to make a test pass by weakening it. Use before reporting that work is complete, when about to writ...Votes: 0GitHub stars: 2
- Code ReviewReviewing a change as an engineering activity: setting review depth from the change's risk rather than its size, looking in the order that finds the expensive defects first, refusing to spend human attention on what a formatter or linter should own, writing a finding that can be acted on, separating blocking objections from preferences, and receiving review without either capitulating or defending. Use when reviewing a pull request or a diff, when a review has become a list of style comments,...Votes: 0GitHub stars: 2
- Code Cache SegmentsThe JDK 17-25 segmented code cache, GC-driven unloading, fragmentation, segment sizing, and jcmd Compiler.codecache/CodeHeap_Analytics. Use when aggregate usage looks healthy but one CodeHeap is exhausted, compilation stops or restarts, GC logs show a CodeCache cause, startup rejects manual heap sizes, an OutOfMemoryError reports "Out of space in CodeCache", or a long-running service degrades while aggregate free space remains. Covers runtime-shape discovery so tools do not assume exactly thr...Votes: 0GitHub stars: 2
- Clean Delivery WorkflowThe order of work for a change, and how much of that order a given change actually warrants: understanding before editing, clarifying what is ambiguous, deciding the test approach, implementing in reversible steps, separating refactoring from behaviour where independently valid, running the gates the risk deserves, and verifying before declaring done. Also the entry point that routes a situation to the skill that owns it. Use when starting a change and the order is not obvious, when a change ...Votes: 0GitHub stars: 2
- Circuit BreakersThe breaker as a state machine that stops calling a failing dependency: closed, open and half-open; choosing rate windows versus consecutive failures; recovery probe limits and in-flight work across state transitions; the failure predicate—classifying correlated dependency failures rather than blindly counting status classes—and the distinction between protecting caller resources by failing fast and providing a semantically valid fallback. Use when a breaker trips on consecutive failures, whe...Votes: 0GitHub stars: 2
- Cascading FailuresHow one slow dependency becomes a total outage: the amplification loop and the four points that close it — retry storms, unbounded queues, thread and connection exhaustion, an inner timeout longer than the outer one. Covers why cutting offered work is usually the first stabilization step in a cascade, metastability sustained by backlog, recovery herds and criticality separation. Use when one dependency's latency rise took down services that never call it, when the dependency recovered and the...Votes: 0GitHub stars: 2
- Capacity PlanningEvidence-based capacity decisions for Java services: defining demand and failure scenarios, measuring feasible capacity envelopes, selecting replica and resource configurations, forecasting exhaustion with uncertainty, designing autoscaling headroom, and comparing cost per successful unit of work. Use when deciding pod or instance counts, minimum replicas, scaling signals, saturation dates, infrastructure budgets, rollout or failure-domain headroom, and downstream capacity constraints. Does n...Votes: 0GitHub stars: 2
- Cancellation And InterruptionDesigning cooperative cancellation in Java across interruption, Future/CompletableFuture, executor/scope shutdown, deadlines, resource close/abort, CPU loops, blocking APIs, native calls, partial side effects and cleanup. Covers multiple cancellation sources, signal ownership, propagation/translation/restoration, noninterruptible regions, residual work, idempotency and bounded termination tests. Use when timeout/cancel returns but work or resources remain, or when `InterruptedException` handl...Votes: 0GitHub stars: 2
- Caching StrategiesDeciding whether to cache, then doing it safely: saved origin work and latency, bounded size or weight, TTL and jitter, stampede and its four distinct scopes, cache-aside versus refreshAfterWrite, immutable DTOs rather than JPA entities, invalidation across instances, Redis serialisation, and why hit rate alone is a misleading metric. Use when a cache is being added or reviewed, when @Cacheable is called from within the same bean, when a cache has no size limit or no TTL, when entries are pre...Votes: 0GitHub stars: 2
- Cache Sharding And ReplicationTopology for a cache that no longer fits one node: client-side sharded, proxy-fronted, clustered, and fully replicated, compared on failure behaviour, cost and client complexity; and why a read after a write on a replicated cache is not read-your-writes. Estimates origin load when a cache node fails from its measured request share and the surviving copies, routing and capacity — mitigated by replication, warming, coalescing and admission control. Use when choosing between client sharding, a p...Votes: 0GitHub stars: 2
- C2 Sea Of NodesHow HotSpot actually executes and compiles: the runtime-generated template interpreter, C2's sea-of-nodes IR, a release-scoped diagnostic map of compilation phases, and why a given transformation fired or did not. Use when a method is believed to be "not optimised", when an allocation that looks eliminable still shows up in allocation profiling, when a hot call site reports `too large` or stays non-inlined, when `made not entrant` repeats on the same method, when someone prescribes `-XX:Compi...Votes: 0GitHub stars: 2
- Blocking And Nonblocking IoFour things routinely conflated into one: a blocking API, a blocked OS thread, non-blocking I/O at the syscall, and an asynchronous programming model. Covers which JDK operations unmount a virtual thread and which capture the carrier, the difference between capture-with-compensation and pinning, the socket poller behind blocking socket calls, file I/O as the case Loom does not fix, and what blocking an event loop costs. Use when someone says virtual threads make I/O non-blocking, when a file-...Votes: 0GitHub stars: 2
- Async Profiler AdvancedConfigure and validate async-profiler when recordings are empty, idle-heavy, truncated, permission-blocked, containerized, multi-event, or version-sensitive. Choose event weights and engines, bound collection overhead, diagnose missing stacks, and verify conversions and differentials. Does not own initial profiler selection (jfr-and-async-profiler), visual interpretation (flame-graph-analysis), or JDK Flight Recorder configuration.Votes: 0GitHub stars: 2
- Architecture Trade Off AnalysisCompare architectural alternatives when quality goals conflict, a scorecard or case study is being used as a verdict, options mix abstraction levels, advocates disagree, or a benchmark needs a decision rule. Build comparable options, separate constraints from preferences, test domain scenarios and uncertainty, and recommend a choice or a bounded next step. Excludes ADR lifecycle (architecture-decision-making), quality-driver elicitation (architecture-characteristics), domain pattern selection...Votes: 0GitHub stars: 2
- Architecture TestingWrite or review tests for architectural promises: dependency boundaries, transaction atomicity, persistence mappings, stale-write detection, query budgets and API/event compatibility. Use when green tests missed a lost update or N+1, a boundary exists only in documentation, or an integration test may hide the behavior it claims to verify. Does not choose the architecture or governance thresholds (architecture-fitness-functions), replace general unit-test design, or establish production capaci...Votes: 0GitHub stars: 2
- Architecture Refactoring PathsSequence a chosen enterprise architecture change into compatible, testable checkpoints: domain and persistence refactoring, remote boundaries, session state, locking or events. Use when old and new paths must coexist, a migration has stalled, code and data changes interact, consumers cannot upgrade together, or rollback and safe pause points are unclear. Does not select target patterns, diagnose the need for change (enterprise-architecture-smells), plan a whole modernization programme (legacy...Votes: 0GitHub stars: 2
- Architecture Fitness FunctionsDefine or review checks that preserve architectural qualities when a green pipeline misses incidents, inherited rules are skipped or unexplained, a characteristic lacks evidence, or a metric is being promoted to a blocking gate. Choose the measurement or rubric, threshold, execution site, owner and response policy; expose proxy limits and coverage gaps. Excludes selecting quality drivers (architecture-characteristics), implementing application tests (architecture-testing), pipeline compositio...Votes: 0GitHub stars: 2
- Architecture Decision MakingWrite, review, reconstruct or supersede architecture decision records when rationale is missing, a decision is repeatedly reopened, a proposal needs an explicit outcome, or an accepted choice changes. Decide how much record is warranted; preserve evidence, alternatives, consequences, decision authority and revisit conditions. Covers ADR scope, lifecycle and traceability; option comparison belongs to architecture-trade-off-analysis, quality-driver elicitation to architecture-characteristics, a...Votes: 0GitHub stars: 2
- Architecture Coupling And QuantaMap release and runtime coupling when services ship together, event-driven components still require coordinated changes, shared data obscures ownership, or a proposed architecture quantum boundary cannot be justified. Distinguish structural dependencies, workflow completion and connascence using contracts, deployment evidence and failure behavior. Does not choose service extractions (distribution-boundaries), diagnose architecture smells (enterprise-architecture-smells), or refactor package d...Votes: 0GitHub stars: 2
- Architecture CharacteristicsDerive and prioritize architectural quality drivers when requirements say only scalable or reliable, too many qualities are called top priority, stakeholders disagree on their meaning, or one list is applied across unrelated services. Define scope, sources, observable scenarios, baseline obligations and reasons for deferring candidates. Covers terminology and quality-model interpretation; excludes choosing design options (architecture-trade-off-analysis), recording ADRs (architecture-decision...Votes: 0GitHub stars: 2
- Architecture And PerformanceAttribute endpoint latency and throughput limits to architectural choices when query counts grow with result size, remote calls are chatty, connections are held across other work, or a cache, layer removal or service extraction is proposed as a performance fix. Compare fetching, call topology, resource occupancy and data movement across the whole request path. Does not replace investigation methodology (performance-methodology), profiling (jfr-and-async-profiler), individual SQL tuning (sql-q...Votes: 0GitHub stars: 2
- Ambassador PatternChoose or review a local outbound proxy when discovery or routing changes require client releases, a canary or shadow needs routing outside the app, or retries overlap across app, proxy and mesh. Define the listener, policy ownership, deadlines and failure behavior. Covers shard-map consumption and experiment routing, not shard algorithms (sharding-and-partitioning), container lifecycle (sidecar-pattern), or output normalization (adapter-sidecar-pattern).Votes: 0GitHub stars: 2