Development

Programming, frameworks, implementation, frontend, backend, and app development

skills in category: 74,091
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Showing 22,297–22,320 of 74,091 skills

Low Latency JvmADesigning 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...developmentjavaVotes: 0GitHub stars: 2
Lock InflationADiagnosing 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...developmentgojavaVotes: 0GitHub stars: 2
Lock Free PatternsADesigning 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...developmentgojavaVotes: 0GitHub stars: 2
Load TestingADesigning 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...developmentgojavaVotes: 0GitHub stars: 2
Load Testing AdvancedASelecting 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...developmentjavascriptgoVotes: 0GitHub stars: 2
Load Balancing And RoutingAGetting 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...developmentrustgoVotes: 0GitHub stars: 2
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Littles Law And QueueingAConservation 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 ...developmentjavaapiVotes: 0GitHub stars: 2
Linux For JvmAThe 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...developmentgojavaVotes: 0GitHub stars: 2
Legacy Enterprise ModernizationAModernising 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...developmentgojavaVotes: 0GitHub stars: 2
Leader ElectionAElecting 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...developmentjavareactVotes: 0GitHub stars: 2
Layering And BoundariesADeciding 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...developmentrustgoVotes: 0GitHub stars: 2
Latency StatisticsAThe 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...developmentjavarailsVotes: 0GitHub stars: 2
Kubernetes Service LifecycleAA 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...developmentgojavaVotes: 0GitHub stars: 2
Kafka Consumers In JavaAOperating 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 ...developmentjavaspringVotes: 0GitHub stars: 2
Jvm Performance ReviewAAuditing 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...developmentrustgoVotes: 0GitHub stars: 2
Jvm Ml InferenceAEngineering 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...developmentgojavaVotes: 0GitHub stars: 2
Jvm Memory RegionsAThe 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 ...developmentgojavaVotes: 0GitHub stars: 2
Jvm Gc TuningADeciding 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...developmentgojavaVotes: 0GitHub stars: 2
Jvm Class LoadingAClass 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...developmentrustjavaVotes: 0GitHub stars: 2
Jvm BytecodeAReading and reasoning about JVM bytecode: javap -c -p -v, operand stack and local slots, the constant pool and resolution timing, descriptors versus Signature, the invoke* family with invokedynamic and inline caching, verification and the StackMapTable, the class-file limits, what javac desugars, and what bytecode does and does not say about performance. Use when a VerifyError appears after instrumentation by an agent, proxy or mock library, when UnsupportedClassVersionError names two class f...developmentrustgoVotes: 0GitHub stars: 2
Jni And FfmACrossing into native code: JNI call overhead, critical sections and what they block, the FFM downcall and upcall path, `Linker` and method handles, why a native frame pins a virtual thread, and measuring the boundary cost. Use when a native call sits inside a tight loop, when someone proposes migrating JNI to Panama to fix pinning, when `Linker.Option.critical()` is applied without a measured duration, when `jdk.VirtualThreadPinned` events point at a `native` method or `MethodHandle.invokeExa...developmentgojavaVotes: 0GitHub stars: 2
Jmh MicrobenchmarksADesigning and auditing JVM microbenchmarks whose workload, observation boundary, compiler context, state topology, lifecycle, units, and statistical comparison match the engineering question. Covers dead-code elimination, constant folding, Blackhole/return values, forks, warm-up, fixture levels, inputs, operations-per-invocation, allocation counters, experimental units, uncertainty, paired comparisons, negative controls, and production extrapolation. Use before trusting a JMH score or replaci...developmentrustgoVotes: 0GitHub stars: 2
Jmh AdvancedADesigning advanced JMH experiments: shared and asymmetric state topologies, groups, parameter matrices, auxiliary counters, fixture arbitration, fork/JVM controls, profilers, hardware counters, annotated assembly, compiler controls, cold-state protocols, and multi-modal variance diagnosis. Uses runtime capability discovery and separates diagnostic profiled runs from decision runs. Use when a benchmark is concurrent, fork-dependent, profiler-sensitive, cold/startup-oriented, or produces unexpl...developmentrustgoVotes: 0GitHub stars: 2
Jit Inlining And Escape AnalysisAInlining and escape analysis in C2: inlining as the multiplier, scalar replacement versus "stack allocation", flow-insensitivity, turning a PrintInlining verdict into a code change, and measuring with gc.alloc.rate.norm. Use when allocation rate is high on a hot path, when a hot call is refused inlining and the fix is unclear, when an object pool for small objects, @ForceInline on application code or a higher FreqInlineSize is proposed, when an interface gains a third implementation on a crit...developmentgojavaVotes: 0GitHub stars: 2