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)
Deployment Ring Pattern
Roll out changes progressively in rings of increasing size. Start with a small group, verify health, then expand to larger rings before...
Geode Pattern
Distribute data across nodes with partitioning so each node owns a shard. Horizontal scaling without shared state, with locality and fault...
Graceful Degradation Pattern
Degrade functionality instead of failing when dependencies are unavailable. Serve partial results, cached data, or fallback features to...
Read-Through Cache Pattern
A transparent cache layer that intercepts read requests, fetches from the data source on miss, and populates the cache automatically.
Refresh-Ahead Cache Pattern
Proactively refresh cache entries before they expire to eliminate cache misses on hot keys and maintain consistent read latency.
Serverless Event Sourcing Pattern
Store function state as an append-only event log so workflows can be replayed, audited, and recovered without a persistent database.
Serverless Fanout Pattern
Broadcast a single event to multiple independent consumers via SNS, EventBridge, or SQS so each consumer processes the event without...
Serverless Function Composition Pattern
Chain serverless functions via Step Functions or orchestration layers to build multi-step workflows with retries, branching, and state...
Serverless Throttling Pattern
Handle backpressure in serverless by using SQS, token buckets, and concurrency limits to protect downstream services from burst traffic.
Serverless Warm Pool Pattern
Keep Lambda functions warm by sending periodic ping events to reduce cold start latency for latency-sensitive workloads.
Shed Load Pattern
Drop requests proactively under extreme load to protect the system. Reject excess traffic before it consumes resources and causes cascading...
Two-Level Cache Pattern
Combine an L1 in-memory cache with an L2 distributed cache to reduce latency for hot keys while maintaining cache consistency across...
Write-Behind Cache Pattern
Write to cache synchronously and persist to the database asynchronously for high-throughput write workloads with eventual consistency.
Write-Through Cache Pattern
Synchronously write to both cache and backing store so the cache always has the latest data without TTL-based invalidation.
GraphQL Batched Resolver Pattern
Resolve nested GraphQL fields in a single batched request to eliminate N+1 queries and reduce database load.
GraphQL Connection Pagination Pattern
Implement Relay-style cursor-based pagination with edges, nodes, and pageInfo for stable GraphQL list queries.
GraphQL DataLoader Pattern
Coalesce individual load requests into batched calls with per-request caching to prevent N+1 queries and redundant fetches.
GraphQL Error Extension Pattern
Attach structured metadata to GraphQL errors using extension codes for predictable client-side error handling.
GraphQL Federated Entity Pattern
Share entity types across federated GraphQL services so the gateway can resolve fields from multiple subgraphs transparently.
GraphQL Interface Polymorphism Pattern
Model polymorphic types with GraphQL interfaces to share field contracts across different object types while keeping resolvers...
GraphQL Mutation Validation Pattern
Centralize input validation for GraphQL mutations using custom validators, schema directives, and structured error responses.
GraphQL Schema Stitching Pattern
Merge multiple independent GraphQL schemas into a single unified schema that clients can query as one graph.
Build Stateful AI Agents with LangGraph State Machines
Create multi-step AI agents with LangGraph using state machines, conditional edges, tool calling, and human-in-the-loop checkpoints for...
Fine-Tune and Deploy Text Classifiers with Hugging Face
Fine-tune a pre-trained transformer model for text classification using Hugging Face Trainer, tokenize datasets, evaluate metrics, and...