My Performance Engineering Roadmap

How I grow as a Performance Engineer. From running load tests to thinking in systems. A roadmap that helps me connect tools, theory, and real impact.

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Introduction

🌟 This roadmap is my personal growth plan as a Performance Engineer.

A clear path from running simple tests to understanding and improving whole systems. It’s not just about tools or metrics. It’s about learning how systems behave, how users experience them, and how to make everything faster, more stable, and easier to scale.

I’ve already learned a lot of this through real projects and problem-solving, but there’s always more to understand. My goal is to organize what I know, fill the gaps, and keep growing step by step. Even when I revisit familiar topics, I want to go deeper — to know why things work, not just how.

This roadmap isn’t static. It will change as I learn and as technology evolves. Every few months, I’ll review it, add new insights, and update tools or approaches.

Each section explains the core skills to learn and what they mean at different experience levels. From Junior to Architect.

Quick Overview

🧩 Foundations — systems, architecture, scalability laws.
→ From basics to designing scalable systems.

⚙️ Performance Testing — load, metrics, realistic modeling.
→ From running tests to setting strategy.

📈 Analysis & Monitoring — observability, dashboards, SLOs.
→ From reading graphs to finding insights.

🔍 Root Cause Analysis — profiling, memory, database tuning.
→ From spotting issues to leading RCA.

🔧 Optimization — backend, DB, and frontend tuning.
→ From small fixes to system-wide efficiency.

🔄 DevOps Integration — CI/CD, Infrastructure as Code, automation.
→ From adding checks to full performance pipelines.

🏗️ System Thinking — scale, resilience, trade-offs.
→ From design awareness to defining standards.

💬 Leadership & Culture — mentoring, communication, performance mindset.
→ From helping peers to shaping culture.

🌟 Personal Brand & Innovation — writing, talks, open-source, research.
→ From sharing lessons to influencing the industry.

🧩 Foundations — Understand how systems work

Core Topics

• Operating systems: threads, processes, CPU scheduling, memory basics.
• Networking: TCP/IP, TLS, HTTP lifecycle, latency and bandwidth.
• Concurrency: async programming, synchronization, multi-threading.
• Data structures: algorithm complexity (O(n)).
• System architecture: monoliths, microservices, caching, CDNs, event-driven systems.
• Performance theory: Little’s Law, Amdahl’s Law, scalability, SLOs/SLIs.

Levels

• Junior: learns OS and networking basics, uses monitoring tools.
• Mid: understands concurrency, async, and how code choices affect speed.
• Senior: connects architecture and resource limits to performance.
• Lead+: explains scalability to others and models system behavior.

⚙️ Performance Testing — Tools are replaceable, skills are not

Core Topics

• Tools: k6, JMeter, Gatling, Locust, Artillery.
• Workload modeling: user flows, pacing, data correlation.
• Test types: baseline, load, capacity, soak, stress, spike.
• Distributed execution: Kubernetes, Taurus, CI/CD automation.

Levels

• Junior: runs ready-made tests, reads response times.
• Mid: builds realistic load models, automates runs.
• Senior: integrates performance testing into CI/CD, tracks trends and regressions.
• Lead+: defines performance strategy, gates, and best practices across teams.

Notes

• What is Performance Testing
• Performance Testing Process: from Requirements to Optimization
• Performance Starts with Requirements
• Choosing the Right Tool for Performance Testing
• Types of Performance Tests
• Testing My Pet Project. Just Because I Can

📈 Analysis & Monitoring — Turn data into insight

Core Topics

• Logs, metrics, traces — how to connect them.
• RED/USE methods and key metrics: latency, errors, traffic, saturation.
• Tools: Prometheus, Grafana, Dynatrace, Datadog, OpenTelemetry.
• Building and maintaining SLO dashboards.

Levels

• Junior: reads dashboards, understands latency and errors.
• Mid: builds dashboards, defines alerts and thresholds.
• Senior: links logs, metrics, and traces to find bottlenecks.
• Lead+: creates monitoring strategy and trains teams.

🔍 Root Cause Analysis — Find the why

Core Topics

• Profiling: JFR, AsyncProfiler, PySpy, VisualVM.
• Memory and thread dumps, GC tuning.
• Flamegraphs: CPU and memory usage.
• Database profiling: EXPLAIN ANALYZE, Query Store, slow query logs.

Levels

• Junior: spots issues like high CPU or memory usage.
• Mid: uses profilers and GC logs to find slow spots.
• Senior: leads RCA sessions, connects app and infra data.
• Lead+: creates RCA playbooks and teaches teams how to use them.

Notes

• Java Thread Leak: Finding the Root Cause and Fixing It

🔧 Optimization — Make it faster and smarter

Core Topics

• Backend: caching, async I/O, batching, thread pools.
• Database: indexing, partitioning, query tuning.
• Frontend: Core Web Vitals, Lighthouse, bundle optimization.
• Cloud: right-sizing, autoscaling, FinOps awareness.

Levels

• Junior: applies simple caching or indexing.
• Mid: tests optimization impact with metrics.
• Senior: balances performance and cost, adds async or caching layers.
• Lead+: drives efficiency across architecture and teams.

🔄 DevOps Integration — Performance in CI/CD

Core Topics

• GitHub Actions, Jenkins, GitLab CI integration.
• Performance gates and automated comparisons.
• Terraform, Helm, Kubernetes scaling.
• Reporting: Grafana, Slack/Teams, Power BI.

Levels

• Mid: adds automated performance tests to pipelines.
• Senior: builds templates for CI/CD performance.
• Lead: defines org-wide validation processes.
• Principal: builds frameworks and governance around performance.

Notes

• AI in Performance Testing: Hype vs. Common Sense

🏗️ System Thinking — Design for scale and reliability

Core Topics

• Architecture patterns: retries, circuit breakers, CQRS, bulkheads.
• Scalability: autoscaling, graceful degradation, capacity planning.
• Balancing performance, reliability, and cost.

Levels

• Mid: understands how design affects latency and load.
• Senior: reviews and models system scalability.
• Lead: drives design choices for scalable systems.
• Principal / Architect: defines performance standards across platforms.

Notes

• Testing My Pet Project. Just Because I Can

💬 Leadership & Culture — Make performance everyone’s job

Core Topics

• Mentoring, feedback, and knowledge sharing.
• Communicating results and insights clearly.
• Building performance communities and review habits.

Levels

• Senior: mentors others, helps with analysis.
• Lead: drives collaboration and process improvement.
• Principal: builds culture around performance excellence.
• Evangelist: spreads awareness across the industry.

Notes

• Interviews Where Thinking Matters More Than Memory

🌟 Personal Brand & Innovation — Share and inspire

Core Topics

• Writing, public speaking, open-source contributions.
• Research: AI-based monitoring, chaos engineering, predictive analysis.
• Mentoring and community involvement.

Levels

• Lead: shares lessons inside the company.
• Principal: speaks at conferences, writes case studies.
• Evangelist: mentors globally, creates learning content, drives innovation.

🎯 Why I’m Doing This

This roadmap is my north star. A guide that helps me track progress, challenge myself, and keep improving. I’ll update it regularly, remove outdated ideas, and add new areas like AI-powered testing, cost-efficient scaling, and sustainable performance design.

By mapping everything here, I can see how skills connect — from code to business value and how each part builds on the previous one.

If you’re building your own roadmap, share it with me. I’d love to see how others approach performance growth.