Tuning

Executive Summary Performance baseline = safe defaults that work for most workloads, with clear tuning for specific scenarios. This guide covers: sysctl: Kernel parameters (network, filesystem, VM) with production-safe values ulimits: Resource limits (open files, processes, memory locks) CPU Governor: Frequency scaling & power management on servers NUMA: Awareness for multi-socket systems (big apps, databases) I/O Scheduler: NVMe/SSD vs. spinning disk tuning 1. sysctl Kernel Parameters Why sysctl Matters Problem: Default kernel parameters are conservative (fit laptops, embedded systems) Solution: Tune for your workload (databases, web servers, HPC) Trade-off: More throughput vs. latency / memory vs. stability …

Introduction Kafka Producer is a key component for sending messages to a Kafka cluster. Proper producer configuration is critical for achieving high performance and system reliability. Key tuning parameters 1. Batching and Compression # Increase batch size for better throughput batch.size=32768 linger.ms=5 # Enable compression to save bandwidth compression.type=lz4 2. Memory and Buffer # Buffer configuration buffer.memory=67108864 max.block.ms=60000 3. Acknowledgments and Durability # For high reliability acks=all retries=2147483647 enable.idempotence=true Real-world examples High Throughput Scenario For high volume data scenarios: …