Guide 1 / fanout
Bound Java Harness Fan-Out Before Virtual Threads Overload Tools
Put admission limits around Java tool calls, distinguish virtual-thread scheduling from dependency capacity, and test permit ownership with a controlled burst.
From harness ownership to JVM evidence
Follow six concrete failure cases: admitting too much dependency work, timing out only the caller, retaining an unbounded queue, publishing mutable checkpoint data, overlooking process memory and tuning G1 without classifying the symptom. Each guide has an original runnable Java example and a companion browser model.
The examples use Java 21 APIs and were run locally on HotSpot JDK 23.0.2. Browser labs are explicitly synthetic; no model training, serving or performance benchmark is claimed. The current AICassindra design is retained.
Guide 2 / cancellation
Stop Java Harness Timeouts From Leaving Tool Work Running
Separate a caller deadline from worker termination, compare CompletableFuture timeouts with owned Future cancellation, and inspect late synthetic effects.
Guide 3 / queue
Keep Bounded Java Executor Queues From Hiding Harness Overload
Model a harness executor under sustained arrivals, bound queued work, and turn rejected submissions into explicit outcomes instead of hidden latency.
Guide 4 / snapshot
Publish Stable Java Harness Checkpoints Without Sharing Mutable State
Copy nested checkpoint data before publication, use an atomic reference for version transitions, and distinguish visibility from immutability and durability.
Guide 5 / memory
Budget JVM Memory Beyond the Heap Before Increasing Concurrency
Plan heap, direct buffers, platform-thread stacks and native headroom together, then use process measurements to replace hypothetical allowances.
Guide 6 / gc
Tune Java G1 From Allocation Evidence Before Changing JVM Flags
Distinguish allocation churn, retained growth and non-GC stalls using synthetic evidence, then design a controlled G1 and Flight Recorder investigation.
Keep the evidence labels separate
A browser calculation explains a policy. A Java fixture checks a narrow implementation invariant. A real JVM workload and inspected diagnostics answer different performance questions. Read each limitation before transferring a model result to a deployed harness.
Views are my own and do not represent any employer, past or present.