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About Logeshwaran
I am an experienced AWS Full Stack Developer with expertise in building scalable, cloud-native applications using a wide range of technologies, including AWS, Angular, Java, Node.js, Python, Terraform, Docker, and TypeScript. With a strong focus on delivering high-performance solutions, I specialize in leveraging AWS services for cloud architecture, creating dynamic front-end interfaces, and building efficient back-end systems. I have hands-on experience in automating infrastructure with Terraform, containerizing applications using Docker, and implementing DevOps best practices.
System Design Interview Cheat Sheet: The Framework That Gets You Hired at FAANG
Posted inSystem Design

System Design Interview Cheat Sheet: The Framework That Gets You Hired at FAANG

The system design interview framework that consistently gets offers at FAANG — requirements scoping, capacity estimation, API design, component breakdown, database selection, and scaling. With worked examples.
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Rust for JavaScript and Python Developers: Why It Is Worth the Learning Curve
Posted inSystem Design

Rust for JavaScript and Python Developers: Why It Is Worth the Learning Curve

Rust is the most admired language for four years running, but most JS and Python developers do not know where to start. This guide explains ownership with analogies, when Rust is the right tool, and the use cases where it beats everything else.
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REST API Design Best Practices: The Patterns That Make APIs a Joy to Use
Posted inSystem Design

REST API Design Best Practices: The Patterns That Make APIs a Joy to Use

The REST API design decisions that make or break developer experience — versioning strategy, error format, pagination, idempotency keys, rate limiting headers, and the spec-first workflow that prevents breaking changes.
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Docker Best Practices: Build Smaller, Faster, More Secure Images in Production
Posted inDebugging

Docker Best Practices: Build Smaller, Faster, More Secure Images in Production

Docker image problems cost teams hours of CI time and create security vulnerabilities. Multi-stage builds, layer caching strategy, non-root users, and minimal base images fix both — with real before/after comparisons.
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Git Mastery: The Commands and Workflows That Senior Engineers Actually Use
Posted inDebugging

Git Mastery: The Commands and Workflows That Senior Engineers Actually Use

Beyond git add, commit, push — the git commands and workflows senior engineers reach for daily. Interactive rebase, bisect, reflog, worktrees, and the aliases that save hours every week.
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React Performance Optimization: Every Technique From memo to Virtualization
Posted inJavaScript

React Performance Optimization: Every Technique From memo to Virtualization

React apps slow down for predictable reasons: unnecessary re-renders, missing memoization, unvirtualized long lists, and oversized bundles. Every technique to fix them — with when to use each.
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Go Concurrency Patterns: Goroutines, Channels, and the Patterns Senior Engineers Use
Posted inSystem Design

Go Concurrency Patterns: Goroutines, Channels, and the Patterns Senior Engineers Use

Go concurrency is powerful and dangerous in equal measure. These goroutine and channel patterns — worker pools, fan-out/fan-in, context cancellation, errgroup — are what senior Go engineers actually use in production.
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JavaScript Async/Await: Every Pattern, Pitfall, and Performance Trick
Posted inJavaScript

JavaScript Async/Await: Every Pattern, Pitfall, and Performance Trick

Async/await looks simple but hides deadly traps — sequential execution when you meant parallel, uncaught rejections, missing AbortController, await in forEach. Every pattern and pitfall covered.
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SQL Query Optimization: 15 Techniques That Turn Slow Queries Into Fast Ones
Posted inDebugging

SQL Query Optimization: 15 Techniques That Turn Slow Queries Into Fast Ones

These 15 SQL optimization techniques are the difference between a 30-second report and a 200ms one — from reading EXPLAIN ANALYZE to covering indexes to replacing self-joins with window functions.
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Python Performance Secrets: 20 Techniques to Make Your Code 10x Faster
Posted inPython

Python Performance Secrets: 20 Techniques to Make Your Code 10x Faster

Python is slow only when you write it slowly. These 20 production-tested techniques make your Python code dramatically faster — from profiling to vectorization to multiprocessing.
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