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Programming, frameworks, implementation, frontend, backend, and app development
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- Mvc And Request HandlingHow a web request is routed and handled: MVC's actual division of responsibilities, Page Controller versus Front Controller, and Application Controller for flows whose next step is a decision. Use when controllers contain business rules or persistence calls, when the same cross-cutting concern is copied into every handler, when a wizard's navigation logic is spread across handlers as if-chains, when a filter, interceptor and handler contend for one concern, when a controller is tested by star...Votes: 0GitHub stars: 2
- Metrics And CardinalityDesigning bounded, decision-oriented metrics for Java services: selecting counters, gauges and histogram forms; defining RED, USE and business outcomes; budgeting active series and ingestion/query cost; controlling caller-driven dimensions; and planning schema migrations, overflow behavior and exemplars. Use when adding labels, routes, histograms or business metrics, diagnosing series growth or missing gauges, reviewing Micrometer/Prometheus instrumentation, or choosing between classic/native...Votes: 0GitHub stars: 2
- Metaspace InternalsMetaspace internals on JDK 16+: chunk and arena allocation per ClassLoaderData, the compressed class space and its separately configured reservation/limit, chunk waste and fragmentation, when memory is actually returned to the OS, and reading `jcmd VM.metaspace` and the nested `VM.native_memory` output. Use when `OutOfMemoryError: Metaspace` or `Compressed class space` is thrown, when a container is OOMKilled with a healthy heap, when metaspace committed grows monotonically, when `MaxMetaspac...Votes: 0GitHub stars: 2
- Metadata MappingExpressing the object-to-schema mapping as metadata rather than hand-written code: where the mapping lives (annotations, external XML, programmatic), what reflection costs versus generated code, and how metadata drifts from the schema it describes. Use when persistence annotations accumulate on a domain class that is supposed to be framework-free, when the same mapping is expressed twice, when a schema change is discovered at runtime instead of at startup, when ddl-auto generates a schema in ...Votes: 0GitHub stars: 2
- Message Ordering And PartitioningOrdering guarantees and their exact scope/stage: common logs order per partition while a global total order requires a serialized sequencer; per-key ordering depends on key-to-partition mapping remaining stable; why the partition count is nearly a one-way door; what silently breaks order in a consumer or producer; and whether ordering is required at all — version guards, commutative handlers, state-machine guards. Use when a design says messages are processed in order with no scope, when part...Votes: 0GitHub stars: 2
- Low Latency JvmDesigning and validating JVM systems whose primary objective is bounded jitter rather than low average latency: latency-distribution budgets, allocation strategy, GC choice, warm-up and deoptimization, CPU/NUMA placement, busy-spin cost and evidence for kernel bypass. Use when p99.99-to-p50 spread matters, a trading or real-time path claims to be GC-free, CPUs are isolated, Epsilon or busy waiting is proposed, or an optimization shifts jitter between JVM, OS and network. General tail diagnosi...Votes: 0GitHub stars: 2
- Lock InflationDiagnosing and engineering Java intrinsic-monitor contention across fast and inflated monitor states without freezing one HotSpot release's internals. Covers ownership, recursion, wait sets, entry queues, inflation/deflation, virtual-thread behavior, JFR/thread-dump evidence, threshold/censoring, convoys, fairness, lock graphs, critical-section redesign, partitioning and validation. Use when `synchronized` wait/hold time is suspected; JMM correctness, explicit locks, false sharing and lock-fr...Votes: 0GitHub stars: 2
- Lock Free PatternsDesigning and reviewing nonblocking Java algorithms: linearization points, lock-free, wait-free and obstruction-free progress, CAS/RMW loops, success/failure ordering, contention collapse, backoff/helping, ABA/version wrap, node reuse and reclamation, publication, linearizability, starvation and shutdown. For custom implementations or performance claims, compare JDK/library and lock-based alternatives; measure retry and topology effects when relevant. Use when implementing or diagnosing atomi...Votes: 0GitHub stars: 2
- Load TestingDesigning valid service load experiments: choosing open or closed workload models, defining offered, admitted and successful work, controlling generator and environment bias, representative workload and data, state-based warmup, run validity, uncertainty, and reproducible evidence. Use when designing or reviewing k6, Gatling, JMeter or similar tests, diagnosing a throughput plateau, validating a baseline, or deciding whether a run measured the target rather than the generator. Profile selecti...Votes: 0GitHub stars: 2
- Load Testing AdvancedSelecting and executing advanced load profiles—baseline, capacity-envelope, breakpoint, stress, spike, ramp, soak and recovery—using bracketed boundaries, scenario-specific validity, phase isolation and server-side evidence. Use when one steady run is presented as capacity, when overload and SLO boundaries are conflated, when burst/recovery or long-duration resource retention must be tested, or when automation parses generator output. Basic workload validity belongs to load-testing; coordinat...Votes: 0GitHub stars: 2
- Load Balancing And RoutingGetting a request to a replica that can serve it: L4 versus L7 by capability rather than layer number, why an L4 balancer in front of long-lived HTTP/2 or gRPC connections balances connections instead of requests and pins each flow to one replica, the balancing algorithms and what each optimises, power-of-two-choices, health checking and outlier ejection with the fleet-ejection hazard, and connection draining. Use when per-pod request rate is skewed while connection counts look even, when one...Votes: 0GitHub stars: 2
- Littles Law And QueueingConservation checks from Little's Law (`L = λW`) and queueing decisions: measurement boundaries, service demand versus residence time, utilisation curves, thread pool and executor sizing, bounded queues and rejection policy. Use when choosing a pool size, when latency is high while CPU is low, when latency grows over the duration of a run, when someone proposes adding threads to a CPU-bound path, or when a ThreadPoolExecutor is not growing past its core size. Does not cover the statistics of ...Votes: 0GitHub stars: 2
- Linux For JvmThe Linux side of a JVM incident: RSS versus virtual memory, page faults and swap, AlwaysPreTouch, transparent huge pages, cgroup CPU throttling, the two OOM killers, file-descriptor and process limits, signals and graceful shutdown, and PSI as a direct stall signal. Use when a process dies with exit code 137 or no log at all, when a GC pause in the log does not match the pause the client felt, when "too many open files" or "unable to create native thread" appears, when THP or swappiness is b...Votes: 0GitHub stars: 2
- Legacy Enterprise ModernizationModernising an enterprise application that is in production and cannot stop: understanding a system nobody fully knows, pinning behaviour before changing it, strangling functionality out incrementally, and defending a new model with an anti-corruption layer. Use when a rewrite is proposed for a system that still earns money, when a shared database has several writers, when business rules live in stored procedures and triggers, when there are no tests and no specification, when a strangler mig...Votes: 0GitHub stars: 2
- Leader ElectionElecting one active instance for work that must not run concurrently: the lease renewal model and the rule that failed renewal never extends the leader's conservative deadline; split-brain and resource-side fencing/idempotency; failover time as detection, election and warm-up; coordination-store leases, Kubernetes Lease objects and ShedLock rows, and what each is adequate for; and when not to elect. Use when a @Scheduled job runs once per replica after scaling out, when two instances both bel...Votes: 0GitHub stars: 2
- Layering And BoundariesDeciding where an enterprise application's boundaries go and which direction dependencies cross them: the classical presentation / domain / data-source split, the styles that reorganise it (hexagonal, clean, modular monolith, vertical slices), and how a boundary is enforced rather than documented. Use when a package structure is argued about, when a controller contains business rules, when an entity or DTO travels end to end, when a service layer only forwards, when hexagonal is adopted witho...Votes: 0GitHub stars: 2
- Latency StatisticsThe statistics of latency measurement: estimands, means and quantiles, histogram aggregation, uncertainty, censoring, dependence, and coordinated omission. Use when an SLO or dashboard reports mean latency, when p99 values are averaged across instances or time windows, when a percentile is quoted without its sample count, when Prometheus buckets are the default set, or when deciding whether two measurements actually differ. Does not cover generating the load (load-testing), sizing systems fro...Votes: 0GitHub stars: 2
- Kubernetes Service LifecycleA Java service at the edges of its life under Kubernetes: liveness, readiness and startup probes as three different questions, probe timing arithmetic, graceful shutdown as a sequence where endpoint removal races SIGTERM, terminationGracePeriodSeconds as a budget, draining non-HTTP work such as Kafka consumers and scheduled jobs, PodDisruptionBudgets, and limits as availability decisions. Use when 502s appear only during a rolling update, when a liveness probe checks a database and a blip res...Votes: 0GitHub stars: 2
- Kafka Consumers In JavaOperating a Kafka consumer from Java: the log-not-a-queue model where consumption removes nothing and position is an offset; the rebalance as the central operational event, with assignment and membership choices that can reduce disruption and where duplicates enter; processing-interval versus heartbeat/session failures; pause/resume for slow work; commit strategies; auto.offset.reset as a data-loss-or-reprocessing decision; and lag as record, byte, time and catch-up signals. Use when a group ...Votes: 0GitHub stars: 2
- Jvm Performance ReviewAuditing JVM configuration evidence across the supplied command, effective runtime flags, target JDK build, container/cgroup envelope, workload lifecycle, and stated SLO. Classifies flags by support and origin, detects masking, duplicates and ergonomic interactions, prices heap/non-heap/CPU/startup trade-offs, and emits prioritized falsifiable findings rather than folklore flag lists. Use for JVM options, Kubernetes manifests, JDK upgrades, collector/heap proposals, or claims that a flag fixe...Votes: 0GitHub stars: 2
- Jvm Ml InferenceEngineering CPU and accelerator-backed ML inference from JVM applications: choosing in-process versus remote serving, bounding native sessions and predictors, coordinating engine and request parallelism, batching under a latency deadline, reusing direct buffers, warming deployments and diagnosing native memory outside NMT. Use when DJL, ONNX Runtime or another native inference engine loses throughput as concurrency rises, leaks RSS, overloads a model pool or needs graceful degradation. Traini...Votes: 0GitHub stars: 2
- Jvm Memory RegionsThe major memory-accounting domains of a JVM process — heap, Metaspace/class space, code cache, thread stacks, direct/native/JVM-internal memory and mapped/file-backed pages — and how to budget them against a container limit. Use when a pod is OOMKilled with no Java exception, when an OutOfMemoryError names something other than "Java heap space", when -Xmx is set equal to the container limit, when RSS exceeds the heap by more than expected, when a heap above 32 GB is proposed, or when sizing ...Votes: 0GitHub stars: 2
- Jvm Gc TuningDeciding whether GC is the actual bottleneck, then choosing a collector and sizing the heap. Use when GC pauses appear on the critical path of a latency profile, when full collections show up, when the heap grows toward its limit, when sizing a JVM for a container, or when a collector change is being proposed. Start from java-performance instead when the symptom is latency or CPU and GC has not been confirmed as the cause. Does not cover how collectors work internally (gc-fundamentals), confi...Votes: 0GitHub stars: 2
- Jvm Class LoadingClass loading, class identity and classloader leaks: parent-first delegation, {defining loader, binary name} identity, loading versus linking versus initialisation, Metaspace retention, and CDS/AOT cache for startup. Use when a ClassCastException reports identical type names on both sides, when Metaspace grows monotonically across redeploys or plugin reloads, when ClassNotFoundException and NoClassDefFoundError need to be told apart, when IllegalAccessError mentions "does not export" or Inacc...Votes: 0GitHub stars: 2