Engineering Logs
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- Virtual Memory and Lazy Allocation: Why RSS Matters More Than malloc()
How virtual memory promises work, why malloc() doesn't equal RAM, what page faults do, how lazy allocation overbooks memory, and why OOM kills by RSS.
- Cuckoo Filters: Cache-Friendly Membership Checks With Deletions
How Cuckoo filters work: fingerprints, two-bucket lookups, kick-out insertions, why they stay cache-friendly, and the real tradeoff of insertion failure.
- Bloom Filters vs Counting Bloom Filters: When Deletions Kill Performance
Why counting (deletable) Bloom filters often lose in production: cache misses, random memory access, and better alternatives like hash tables or Cuckoo filters.
- Pagination at Scale: Why OFFSET and SKIP Will Eventually Break Your API
Why OFFSET/SKIP pagination degrades linearly with depth, how cursor-based pagination keeps latency flat, and when to switch before production bites back.
- The RUM Conjecture: You Cannot Optimize Reads, Updates, and Memory at Once
How the RUM Conjecture explains real-world database trade-offs between read latency, write throughput, and memory overhead across B-Trees, LSM-Trees, and hash indexes.
- Why UUID Primary Keys Quietly Destroy Database Performance
How random UUID primary keys break clustered indexes, cause page splits and buffer pool churn, and what to use instead for mechanically sympathetic database design.
- Designing Resilient APIs: Failure-Handling Patterns for Distributed Systems
Practical resilience patterns for distributed APIs: fail-fast, retries with backoff, circuit breakers, bulkheads, fallbacks, rate limiting, failover, and observability.
- Microservices Deep Dive: Architecting for Scalability and Resilience
How to design, operate, and scale microservices: core principles, when to use them, key patterns, and how to manage complexity in distributed systems.
- Consistency Models in Azure Cosmos DB: From Strong to Eventual
How Azure Cosmos DB's five consistency levels map onto PACELC tradeoffs, what each level guarantees, and how to choose the right consistency for your workload.
- Zero Trust Architecture: From Perimeter Walls to "Never Trust, Always Verify"
How Zero Trust Architecture replaces perimeter-based security: core principles, differences from traditional models and ZTNA, enabling technologies, and real-world implementations.
- Transitioning from REST to gRPC: System Design and Tradeoffs
How gRPC changes API design versus REST: protocol model, protobuf schemas, service interfaces, streaming patterns, and when gRPC or REST is the right architectural choice.
- HTTP/2 System Design: How It Fixes HTTP/1.1
Deep dive into HTTP/2: why HTTP/1.1 hit scaling limits, how multiplexing, server push, binary framing, and prioritization work, and why it matters for web performance.
- How Shazam's Music Recognition System Design Actually Works
Inside Shazam's music recognition system design: audio fingerprinting, spectrogram peaks, NoSQL and SQL databases, and scaling search across millions of tracks.
- Mastering Event-Driven Architecture with Apache Kafka
How to design scalable, resilient systems using event-driven architecture and Apache Kafka for high-throughput, real-time data processing.
- System Migration: Minimize Downtime, Maximize Efficiency
A practical blueprint for system migration: isolated env, sync/async flows, bridge layer, traffic leakage, backup sync, and monitoring.
- System Design: Principles for Maintainability, Scalability, and Reliability
Data building blocks, fault tolerance, latency vs response time, scaling strategies, and the operability-simplicity-evolvability triad for durable systems.
- Time Management for Software Engineers: A Toolkit That Scales
How to get better at delivery and focus: planning, prioritization, delegation, and guarding deep work.