Mathias Paulenko
Software Engineer & Founder of StackPractices
Mathias Paulenko
Software Engineer
Software engineer with 12+ years of experience building production systems across Python, JavaScript, React, and DevOps. I have contributed to enterprise projects spanning CI/CD pipelines, API design, cloud infrastructure, and full-stack development.
StackPractices is my personal project, born from a simple belief: great documentation should be copy-paste ready. Every recipe, pattern, and guide on this site is designed to save you time and help you ship faster.
Published Works (1032)
Caching Strategies: From Browser to Database, a Complete
A practical guide to caching strategies: browser caching, CDN edge caching, application caching with Redis, and database query caching....
Connection Pooling: Optimize Database Connections for Scale
A practical guide to database connection pooling: sizing pools, handling idle timeouts, detecting leaks, and configuring HikariCP,...
Data Migration: Zero-Downtime Strategies That Work
A practical guide to data migration: planning, dual-write patterns, backfill strategies, schema evolution, validation, and rollback...
Database Sharding: Horizontal Partitioning in Practice
A practical guide to database sharding: choosing shard keys, routing queries, rebalancing data, and avoiding common pitfalls when scaling...
ETL Pipelines: Extract, Transform, Load for Data Engineers
A practical guide to ETL pipelines: extracting data from multiple sources, transforming with validation and business logic, and loading...
Full-Text Search — Implement Search That Actually Works
A practical guide to full-text search: PostgreSQL tsvector, Elasticsearch indexing, query design, relevance tuning, and building search...
Read Replicas: Scale Reads Without Changing Application
A practical guide to read replicas: setting up replication, routing read queries, handling replication lag, and scaling read-heavy...
Real-Time Analytics: From Events to Dashboards in Seconds
A practical guide to real-time analytics: event collection, stream processing, data warehousing, and building sub-second dashboards with...
Stream Processing: Event-Driven Data Pipelines with
A practical guide to stream processing: choosing between Kafka Streams, Flink, and Spark Streaming, designing event schemas, handling...
Database Denormalization
A practical guide to database denormalization: when to trade storage for read performance, common patterns, and how to keep derived data...
Graph Databases — Neo4j and Property Graph Modeling
A practical guide to graph databases: property graph model, Cypher query language, modeling patterns, and when to choose Neo4j over...
NoSQL Data Modeling Patterns
A practical guide to NoSQL data modeling: embedding vs referencing, access pattern-driven design, and patterns for MongoDB, DynamoDB,...
SQL CTEs — Common Table Expressions Explained
A practical guide to SQL Common Table Expressions (CTEs): non-recursive and recursive CTEs, readability, performance, and when to use them...
SQL Window Functions — Complete Guide
A practical guide to SQL window functions: ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG, SUM, AVG over partitions, and real-world analytics use...
Time-Series Databases — InfluxDB, TimescaleDB
A practical guide to time-series databases: when to use a specialized TSDB, data model, retention policies, and choosing between InfluxDB,...
Vector Databases — AI/ML Embeddings and Similarity Search
A practical guide to vector databases: embeddings, similarity search, approximate nearest neighbors, and choosing between Pinecone,...
A/B Testing: Experimentation Frameworks for Data-Driven
A practical guide to A/B testing: experiment design, statistical significance, sample sizing, avoiding pitfalls, and building an...
Blue-Green Deployment
A practical guide to blue-green deployments: architecture, traffic switching strategies, database migrations, and achieving zero-downtime...
Canary Deployment: Gradual Rollouts with Safety Controls
A practical guide to canary deployments: traffic splitting strategies, automated promotion, rollback triggers, and safely rolling out new...
CI/CD Security: Harden Your Pipelines and Prevent Supply
A practical guide to securing CI/CD pipelines: secrets management, least-privilege runners, artifact signing, dependency scanning, and...
Feature Flags: Progressive Release and Safe Experimentation
A practical guide to feature flags: implementation patterns, progressive rollouts, kill switches, A/B testing integration, and managing...
Chaos Engineering — Principles, Tools, and Safe Experiments
A practical guide to chaos engineering: build resilient systems by intentionally injecting failures. Learn the five principles, Litmus,...
FinOps — Cloud Cost Optimization and Financial Operations
A practical guide to FinOps: visibility, optimization, and governance of cloud spending. Learn tagging strategies, right-sizing, reserved...
Multi-Cloud Strategies — Benefits, Pitfalls
A practical guide to multi-cloud architecture: when to adopt it, workload placement strategies, data gravity, portability, and avoiding...