This article details a systematic approach to diagnosing and resolving CPU and memory spikes when an Agent processes large document batches, covering backpressure propagation, concurrency budgeting, runtime profiling, and pipeline design to prevent OOM kills and throttling.
When a MySQL‑driven application shows sudden CPU spikes, this guide walks through a step‑by‑step process—using top/htop, SHOW PROCESSLIST, enabling slow‑query logs, analyzing EXPLAIN output, killing offending queries, adding appropriate indexes, rewriting joins, and establishing preventive monitoring—to quickly identify and fix the root cause.
A temporary test server on Tianyi Cloud was compromised by a malicious XMRig miner masquerading as fail2ban, causing CPU usage to skyrocket; the article details how the intrusion was discovered, the forensic steps taken, and a comprehensive remediation and hardening guide to prevent similar attacks.
The article examines a nightly Redis CPU‑100% alert caused by massive simultaneous key expirations, analyzes the active and slow expire cycles, and presents two practical redesigns—randomized expiration with real timestamps and time‑suffix keys—that eliminated the spike.
After receiving an alarm that a production container’s CPU usage surged past 90%, I investigated the JVM metrics, discovered excessive young and full GCs in a single pod, and walked through the detailed troubleshooting steps—including top, thread analysis, jstack, and code fixes—that resolved the issue.
When a production container suddenly hit 90% CPU, the author traced the issue to abnormal JVM garbage‑collection activity, captured the problematic GC graphs, and used Linux tools, jstack, and code inspection to pinpoint a faulty Excel export loop that caused excessive GC and full‑GC cycles.
This article explains how a JDK bug in ScheduledExecutorService can cause a thread pool with coreSize 0 to enter a tight loop, driving CPU usage to 100 %, and shows the fixes introduced in JDK 9 as well as a related bug in scheduleWithFixedDelay.
The article investigates a CPU load spike caused by a red‑black tree cycle inside Java's HashMap after JDK 8, detailing monitoring steps, stack‑trace analysis, heap dump inspection, and concluding with a recommendation to replace HashMap with ConcurrentHashMap in concurrent scenarios.
