⚡ Performance Engineering

Profiling • Benchmarking • Optimization • Scalability • Observability • Low-Latency

Master the art of making systems faster — from CPU/GPU optimization and memory analysis to distributed tracing and real-time performance tuning.

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Performance Engineering Concepts & Techniques

Beginner

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Performance Basics

Latency, throughput, utilization, bottlenecks.

Measurement Fundamentals

Metrics, counters, sampling, instrumentation.

CPU Profiling

Sampling, instrumentation, flamegraphs.

Memory Profiling

Heap, allocations, leaks, fragmentation.

I/O Profiling

Disk, network, filesystem, latency.

Async & Off-CPU Profiling

Off-CPU analysis, wait events, scheduler.

Benchmarking

Micro-benchmarks, macro, statistical analysis.

Statistical Benchmarking

Confidence intervals, A/B testing.

Code Optimization

Compiler flags, loop unrolling, inlining.

Cache Optimization

Data locality, prefetching, cache misses.

SIMD & Vectorization

AVX, NEON, auto-vectorization.

Parallel Optimization

OpenMP, TBB, async, lock-free.

GPU Optimization

CUDA, OpenCL, kernel tuning, memory.

Memory Hierarchy

Registers, L1/L2/L3, DRAM, SSD, NUMA.

Caching Strategies

LRU, LFU, Redis, CDN, cache invalidation.

NUMA Optimization

Affinity, first-touch, interleaving.

Logging & Telemetry

Structured logging, log aggregation.

Metrics & Monitoring

Prometheus, Grafana, dashboards.

Distributed Tracing

Jaeger, Zipkin, OpenTelemetry.

eBPF for Performance

Dynamic tracing, observability, security.

Scalability

Vertical, horizontal, scaling laws.

Capacity Planning

Forecasting, provisioning, auto-scaling.

Low-Latency Systems

Kernel bypass, DPDK, RTOS, lock-free.

Real-Time Performance

Worst-case execution, determinism.

Low-Latency

Intermediate

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Performance Tools

perf, VTune, gprof, strace, ltrace.

Flamegraphs & Visualisation

Flame charts, heatmaps, waterfall.

Profiler Internals

Sampling vs instrumentation, unwinding.

Network Performance

Latency, bandwidth, TCP tuning, QUIC.

Load Balancing

Algorithms, consistent hashing, health checks.

Web Performance

Core Web Vitals, LCP, FID, CLS, CDN.

Backend Performance

Database, caching, API, microservices.

Database Performance

Query optimization, indexing, partitioning.

Distributed DB Performance

Sharding, replication, consistency.

Storage Performance

SSD, HDD, RAID, I/O scheduling.

Filesystem Performance

Journaling, ext4, XFS, ZFS, Btrfs.

Cloud Performance

Instance types, networking, cost/performance.

Container Performance

Docker, Kubernetes, resource limits, cgroups.

ML Model Performance

Inference, training, throughput, latency.

AI Accelerators

TPU, GPU, NPU, model optimization.

AI/ML

Hardware