How to Create Systems for Engineering Success

One of the best perks of working at Google? You get to learn from some of the most talented engineers in the world.  Here’s the advice that changed how I approached system design:  ○ 1. Start with the Systems You Already Work On  You don’t need to build the next Google-scale system to learn system design. Start with what’s in front of you. - Study the architecture of the systems your team maintains.   - Ask senior engineers why certain design decisions were made.   - Try to understand trade-offs, +why was SQL chosen over NoSQL?  +Why is there a cache?  ○ 2. Get Involved in Design Discussions  Even if you’re not leading the discussions, listen, observe, and ask questions.  - How does the team decide on a database?   - What factors go into choosing between microservices vs. a monolith?   - What happens when something fails, and how is it mitigated?  ○ 3. Learn to Think in Trade-offs  System design is never about finding a perfect solution, it’s about understanding trade-offs.  - High availability vs. consistency   - Performance vs. cost   - Scalability vs. simplicity  Engineers who understand why something works a certain way are the ones who stand out.  ○ 4. Read and Reverse-Engineer Real Systems  Reading about distributed systems is great, but reverse-engineering existing architectures is even better.   - Read engineering blogs from Netflix, Meta, Uber, and Stripe.   - Study open-source projects to understand their system design.   - Look at case studies of real-world scaling challenges.  ○ 5. Build Small Projects and Simulate Failures  Designing a system on paper is one thing, running one is another.    - Try deploying your own API and scaling it.   - Experiment with load balancing, caching, and database sharding.   - Simulate failures: What happens if a server crashes? How does the system recover?  ○ 6. Teach Others What You Learn   The fastest way to internalize system design concepts? Explain them to others.  - Write blog posts breaking down technical concepts.   - Mentor junior engineers and help them understand architecture decisions.   - Share what you learn with your team in tech talks or discussions.  You don’t gain experience in system design by just watching YouTube videos or reading books.   You gain it by getting involved, asking questions, experimenting, and building. 

System Design isn't just for senior engineers. It's for anyone who wants to think like a real engineer — someone who builds reliable, scalable, and user-friendly systems. Whether you're preparing for your first job or aiming for a staff-level position, understanding System Design will 10x your thinking. If you're a fresher, start here: Basic Concepts: • What happens when you enter a URL in your browser? • What is DNS and how does it work? • How does Google Docs support real-time editing? • How does WhatsApp deliver messages instantly? • What is caching and how does it help? • How do logins and sessions work? • Design a URL shortener (like bit.ly) • Design a file upload service • Design a basic e-commerce cart If you're at an intermediate level: Build for Scale: • Design Instagram feed • Design a scalable chat app like Slack or Discord • Design an online code editor (like LeetCode or Replit) • Design a notification system (push/email/SMS) • How would you implement pagination and infinite scroll? • Design a rate limiter • Design a ride-booking system like Uber • How would you scale a database for millions of users? If you're experienced: Think Distributed & Fault-Tolerant: • Design a distributed caching system (like Redis or Memcached at scale) • Design a recommendation system like Netflix or YouTube • Design a payment system with retries, fraud detection, and idempotency • Design a logging and monitoring system like Datadog • Design a scalable search engine • How would you handle global data replication? • How would you design LinkedIn endorsements? • How to handle eventual consistency in distributed systems? Resources to Learn: • System Design Primer (GitHub): https://lnkd.in/gtS7wkEM • ByteByteGo Newsletter & YouTube • Gaurav Sen’s System Design Playlist (YouTube) • Designing Data-Intensive Applications – Martin Kleppmann • High Scalability Blog • Hussein Nasser’s System Design Series • Grokking the System Design Interview (Educative) • Alex Xu’s System Design Interview books Final Thought: Solving 300 Leetcode problems won’t help if you panic when asked, “How would you scale this?” System Design is the art of balancing trade-offs: latency vs throughput, consistency vs availability, speed vs accuracy. Don’t ignore it. Learn it early. #systemdesign #softwareengineering

An engineering leader recently told us that they had to re-validate half their product for a two-line fix. Teams want to ship daily, but when validation effort outpaces the actual code change by orders of magnitude, it feels completely out of reach. The frustration is real, but so is the responsibility to partners and patients. So how do we design systems that deliver both speed and safety? The way out isn’t brute force. It’s design. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗮𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝘁𝗵𝗮𝘁 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝘀 𝗰𝗵𝗮𝗻𝗴𝗲. Modular, component-driven systems let teams isolate impact, contain risk, and limit validation to only the parts actually affected by a small update. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗳𝗿𝗼𝗺 𝘆𝗼𝘂𝗿 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀. Treat your Jira tickets, commits, test runs, and CI/CD outputs as the source of truth. Instead of writing validation documents after the fact, let evidence generate itself as developers work. 𝗣𝗹𝗮𝗻 𝗳𝗼𝗿 𝗰𝗵𝗮𝗻𝗴𝗲 𝘂𝗽 𝗳𝗿𝗼𝗻𝘁. You can’t skip validation, but you can predefine impact boundaries, acceptance criteria, and change categories. When every update follows a predictable validation path, velocity becomes repeatable instead of chaotic. When validation feels bigger than the change itself, it’s usually not a compliance issue. It’s a system design issue. The right systems make speed and safety compatible.

The one thing I wish I knew about system design interviews before my first FAANG offer. Stop designing for perfection. Design for failure. I bombed my first Amazon system design interview spectacularly. Drew beautiful diagrams. Perfect load balancers. Elegant microservices. Textbook caching layers. The interviewer asked one question that killed me: "What happens when your whole region goes down?" I froze. "Well... we'd have backups?" Wrong answer. Here's what I learned after failing that interview and eventually getting offers from Microsoft, Amazon, and Oracle: What most engineers do in system design: ❌ Design the happy path first ❌ Add failure handling as an afterthought ❌ Focus on scaling to billions (when asked about thousands) ❌ Memorize architecture patterns What actually gets you hired: ✅ Start with "What could go wrong?" ✅ Design for the disaster scenario (expect the improbable) ✅ Show you've dealt with real production fires ✅ Think like someone who's been paged at midnight The mental shift that changed everything: 🎯 Every component you draw will fail. Now what? When I redid that Amazon interview months later, I started differently: "Before we scale this, let's talk about failure modes. Database goes down? Here's our fallback. Network partition? This is how we handle split-brain. Region outage? Let me show you our DR strategy." The interviewer's eyes lit up. Because here's the truth: Anyone can design a system that works when everything's perfect. FAANG companies need engineers who can design systems that work when everything's on fire. My framework for system design interviews now: 1. Start with failure scenarios "What are the top 3 ways this system could fail?" 2. Design in degraded mode "If we lose 50% capacity, what features do we sacrifice?" 3. Make failure visible "How do we know something's wrong before customers complain?" 4. Plan for recovery "When things break, how fast can we recover?" That shift in thinking took me from rejection to multiple FAANG offers. Stop memorizing architecture patterns. Start thinking about what happens at midnight when everything breaks. Because in production, everything eventually does. --- Want to master the system design interview mindset that actually gets offers? Let's talk.

Adopt a systems approach to engineering design before your next capital project slips.     The pain you live with, disconnected people, processes, and data, shows up as late surprises, change chaos, and compliance gaps. In large capital assets, that fragmentation has a real price: average projects see cost overruns near $1.2 billion with delays from six months to two years, while construction productivity has inched around 1% over two decades compared to 3.6% in manufacturing. Add the push toward modular construction (about $175 billion by 2025) and a once-in-a-generation surge in capital spending through 2027, and the stakes could not be higher.     Systems-driven design is the discipline that closes the loop. It moves requirements from scattered docs into a single source of truth connected to every design domain, electrical, mechanical, software, so changes propagate in real time and compliance can be checked as decisions are made, not after the fact. It brings end-to-end traceability, the voice of the customer baked into each step, and a repeatable way to manage change as regulations evolve.     Try this simple play on your next project:  • Make requirements your single source of truth across plant, process, and equipment data.  • Connect requirements to every design activity and validate continuously as changes flow.  • Classify and reuse sub-systems, requirements, history, and change included, to cut rework.     When this approach is in place, hidden design issues surface early, cross-functional collaboration improves, and re-invention gives way to reuse. That’s how assets are more likely to work the first time with minimal rework later. 

Follow This Roadmap to Achieve System Design Mastery! System design is a crucial skill for any software engineer, enabling you to build scalable, reliable, and efficient systems. Here’s a comprehensive roadmap to guide you through learning system design, covering both functional and non-functional requirements: 1. Understand the Basics • Start with the fundamental concepts: scalability, reliability, availability, fault tolerance, concurrency, and more. • Familiarize yourself with different types of databases, API design principles, and basic networking protocols. 2. Dive into Functional Requirements ▶️ Backend Infrastructure: • Databases: Learn about SQL, NoSQL, indexing, and transactions. • API Design: Understand RESTful APIs, GraphQL, and best practices. • Caching: Explore caching mechanisms like Redis, Memcached, and strategies for cache invalidation. • Rate Limiting: Implement rate limiting to protect your system from excessive requests. • Data Partitioning: Study techniques like sharding and partitioning for managing large datasets. • Message Queue: Learn about message brokers like Kafka, RabbitMQ, and their use cases. ▶️ System Operations: • Security: Implement authentication, authorization, and encryption. • Monitoring: Set up monitoring tools like Prometheus, Grafana, and learn about observability. • Connecting Protocols: Understand HTTP, HTTPS, WebSockets, and other communication protocols. • Microservices: Learn about microservices architecture, Docker, Kubernetes, and service orchestration. 3. Master Non-Functional Requirements ▶️ Performance and Reliability: • Scalability: Design systems that scale horizontally and vertically. • Reliability: Ensure your system can recover from failures quickly. • Availability: Aim for high availability with techniques like load balancing and failover. • Fault Tolerance: Build systems that can withstand component failures. • Concurrency: Manage concurrent processes and data consistency. ▶️ Security and Cost Management: • Authentication: Implement robust authentication mechanisms. • Authorization: Ensure secure access control to resources. • Cost Optimization: Optimize your infrastructure and resources for cost-efficiency. • Compliance: Adhere to regulatory standards and compliance requirements. • Auditability: Implement logging and auditing to track system activities. • Privacy: Ensure data privacy and protection for users. Follow me for Insights on Leadership, System Design & Career Growth.

If I had a system design interview tomorrow at Google, this is exactly how I’d approach it.   (This framework helped me crack 3 FAANG+ companies in the past, including Amazon.)  Most engineers fail system design interviews not because they lack knowledge but because they lack structure.  You don’t need to memorize 100 architectures. You need a structured and easy-to-apply approach that works every time.  Here’s how I break it down:   1/ Clarify the Problem Before Writing Anything   - System design interviews aren’t about throwing buzzwords—they’re about trade-offs.   - Start with scoping → Are we designing just one feature or the entire system?   - Ask constraints upfront → How many users? Read/write ratio? Latency requirements?   - Define success criteria → What matters most? Scalability? Cost? Low-latency?  Most candidates assume things and jump into solutions.   I make sure I know what we’re solving before I even start.   2/ Define Functional & Non-Functional Requirements Clearly   - Functional: What features does the system need?   - Non-functional: What are the performance expectations?   - What’s the biggest technical challenge? (This helps guide the discussion.)  Example: If we’re designing YouTube, is the focus on video uploads, recommendations, or live streaming?   Each has a different set of constraints.   3/ Estimate the Scale & Plan Capacity Like an Engineer   - Users per second? Requests per second?   - Storage needs? If we store 10MB per user and have 100M users, what does that mean?   - Throughput? Can a single database handle the load, or do we need sharding?  Most candidates throw random numbers.   I do quick, back-of-the-envelope calculations to validate my assumptions.   4/ Break the System into Core Components (High-Level Design)   - Define the major building blocks → API Gateway, Load Balancer, Service Layers, Databases.   - Don’t overcomplicate. Simple and scalable always wins.   - Clearly define the interactions between services.  If I’m designing a messaging app, I break it down into:   — User Service (auth, profiles)   — Messaging Service (storing chats)   — Notification Service (real-time updates)   — Media Storage (for images, videos)  Each has different constraints, so I build around what’s most important.  Continued Here: https://lnkd.in/eiHQs-qT P.S. If you’re preparing for tech interviews or appearing soon for one as a SWE. Check out my book Awesome Tech Interviews. It will help you: — Learn techniques to win behavioral interviews — Learn DSA with a detailed 6-month roadmap — Build your foundations of System Design - all in one place. Along with 300+ free online resources. Digital copy: https://lnkd.in/efc7u85w Paperback (Available on Amazon internationally): https://lnkd.in/ePWCr74g

System design isn’t just about building systems. It’s about making trade-offs and you can’t make good trade-offs without a broad knowledge base. That’s where this System Design Topic Map comes in. Here are the 6 core categories every engineer should master for real-world system design 👇 1. Application Layer • Covers the fundamentals of designing maintainable, scalable architectures: • Availability, Scalability, Reliability (NFRs) • OOP (Object-Oriented Programming) • Domain-Driven Design (DDD) • Clean Architecture • Microservices vs Modular Monoliths 2. Network & Communication • Focuses on how services talk to each other: • HTTP/HTTPS, WebSockets, gRPC, SSE • Service integration & inter-process communication • Messaging systems (AMQP, Kafka) • Real-time & event-driven architecture 3. Data Layer • Master the foundation of data management and distributed databases: • Schema design, indexing, transactions • SQL vs NoSQL vs NewSQL • Database types and storage engines • Replication, sharding, leader election • Consistency models (CAP/PACELC) 4. Scalability & Reliability • Build systems that perform under pressure: • Horizontal scaling, stateless services • Auto-scaling, caching, partitioning • Load balancing, rate limiting • Fault tolerance and failover 5. Security & Observability • Cover your blind spots and protect your stack: • Auth & AuthZ: OAuth 2.0, JWT, PASETO, Sessions, Cookies • RBAC vs ABAC • Security threats: XSS, CSRF, MITM, SQL Injection • Logging, monitoring, tracing, metrics 6. Infrastructure & Deployments • Automate everything and keep things running: • Docker, Kubernetes, CI/CD pipelines • IaC tools: Terraform, CloudFormation, Ansible • Serverless architecture • Disaster recovery and rollback strategies I help technical professionals build impactful career brands on LinkedIn. : Check in Comment below 👇 Create LinkedIn Diagrams for FREE using AI! Join waitlist : Check in Comment below 👇 Follow Ashish Sahu for more tech content

System Design isn’t a one-step leap — it’s a staircase. Whether you're preparing for FAANG interviews or designing real-world distributed systems, having a structured path is crucial. This visual breaks it down into three clear stages: 🔸 Basic: Start with fundamentals like Load Balancers, API Gateways, and CDNs. These are the building blocks of web-scale infrastructure. 🔹 Intermediate: Understand caching, rate limiting, replication, and sharding. These help you scale and maintain performance as systems grow. 🔺 Advanced: Dive into the real magic — CAP Theorem, eventual consistency, distributed transactions, consensus algorithms, service discovery, and observability. This is where large-scale, resilient systems are born. Each concept here isn't just theory — it's used by the best engineering teams in the world. 🧠 Save this roadmap. Reflect on where you are today. And pick the next step in your journey to mastering system design.

Most engineers fail system design interviews in the first 10 minutes. Not because they can't design systems. Not because they haven't scaled systems. But because they start building before thinking. I've seen it happen with very senior engineers too. I once watched an experienced engineer walk into a system design interview and immediately say: “We’ll run this on Kubernetes with autoscaling across regions, put an SQS queue in front, use Redis for caching, and shard the database…” I paused and asked: “How many users does this system serve?” Silence. They were designing for internet-scale when the question was about a small internal tool for ~100 users. Here’s the secret about system design interviews nobody tells you: → It's not about how fast you can say “Kubernetes, Kafka, Redis.” → It's about whether you can think like an engineer. When designing real systems, we don’t dive straight into solutions. We clarify the problem first. And system design interviews should be no different. So in your next system design interview, try this simple framework: [1] Clarify the problem (don't skip this please) → What problem are we solving? → Who are the users and how many? → Read/write patterns and constraints? → Latency and availability requirements? → What’s in scope vs out of scope? [2] Define requirements → Functional: what the system must do → Non-functional: SLA, scalability, latency, availability, durability, security, cost constraints, compliance [3] Propose a high-level design → Keep it simple → Walk through the core data flow and use cases of the system. → Discuss trade-offs throughout → Get alignment from your interview before diving deep (so important). [4] Dive deep on the important parts of system → Confirm the focus area with the interviewer. → This may include: Data models & storage, API design, consistency model, scaling, security → Explain trade-offs clearly [5] Improve & wrap up → Call out bottlenecks and failure modes. → Discuss how you'd implement observability across your system. → Deployments, CI/CD → Summarise the design and decisions. → Tie your solution back to the requirements, this is super crucial. System design isn’t about sounding smart. It’s about solving the right problem in the right way. Slow down. Ask first. Design second. Save this for your next interview, and refer back to it before you walk into the room. P.S. Sharing Neo Kim’s System Design red flags list as well, it's incredibly helpful for interview prep. #softwareengineering #interviews