Blog — Page 2 of 53
Browsing page 2 of 53 — 634 articles and counting.
How Valkey Works Internally: Multi-Threaded I/O, RDMA Networking, and the Fork That Is Replacing Redis in Production
A deep-dive into Valkey internals for senior engineers. Covers the Linux Foundation fork origin, the multi-threaded I/O pipeline diverging from Redis 7's model, RDMA networking for data center deployments, cluster slot migration improvements, RESP protocol compatibility, and a production migration guide with tradeoffs against Redis, Dragonfly, KeyDB, and Memcached.
How FoundationDB Works Internally: Ordered Key-Value Storage, Serializable Transactions, and the Simulation Testing Framework That Proves Correctness
A deep-dive into FoundationDB internals for senior engineers. Covers the five-role cluster architecture, the optimistic concurrency control protocol driven by the Sequencer, the log-structured storage engine, multi-Paxos coordination, the deterministic simulation testing framework that found hundreds of bugs before release, the layer concept for higher-level data models, and production considerations.
How Supabase Works Internally: PostgREST, GoTrue Auth, Realtime Subscriptions, and the PostgreSQL Platform Architecture
A deep dive into how Supabase stitches together PostgREST, GoTrue, a Realtime server, S3-compatible storage, Deno Edge Functions, and Kong into a coherent backend platform on top of PostgreSQL.
How gRPC Works: Protocol Buffers, HTTP/2 Multiplexing, and Bidirectional Streaming From Service Definition to Wire Format
A deep dive into gRPC internals: Protocol Buffer IDL and the buf codegen pipeline, HTTP/2 stream multiplexing and HPACK header compression, all four RPC patterns with TypeScript, channel management, deadline propagation, interceptors, load balancing from pick-first to xDS, the health checking protocol, and production tradeoffs vs REST and GraphQL.
How Amazon SQS Works Internally: Distributed Message Storage, Visibility Timeouts, and the Architecture Behind the Most Widely Deployed Message Queue
A deep dive into SQS internals covering distributed redundant message storage across availability zones, the visibility timeout mechanism and consumer semantics, standard vs FIFO queue architectures with deduplication and ordering, long polling mechanics, dead-letter queues, the full SendMessage-to-DeleteMessage lifecycle, batching APIs, delay queues, server-side encryption, and a tradeoffs comparison against Kafka, RabbitMQ, NATS JetStream, and Redpanda.
How Dragonfly Works Internally: Shared-Nothing Multi-Threading, Dash Hash Tables, and the Architecture That Outperforms Redis on a Single Node
A deep-dive into Dragonfly internals for senior engineers. Covers the io_uring event loop with shared-nothing thread-per-core architecture, the Dash hash table with lock-free concurrent access, mimalloc per-shard memory management, fork-free snapshot persistence via fiber serialization, multi-shard transaction coordination, and production tradeoffs vs Redis, Valkey, KeyDB, and Memcached.
How Redis Works Internally: Single-Threaded Event Loop, Data Structures, Persistence, and Replication
A deep-dive into Redis internals for senior engineers. Covers the single-threaded event loop with epoll/kqueue multiplexing, the actual in-memory data structures behind each Redis type, RDB and AOF persistence mechanics, replication with partial resync, Redis Cluster with hash slots and MOVED/ASK redirections, and production tuning for memory and eviction.
AI Agent Frameworks Compared: CrewAI, LangGraph, AutoGen, and Mastra for Production Systems
A practical comparison of CrewAI, LangGraph, AutoGen, and Mastra for building production AI agent systems. Covers architecture philosophy, state management, tool integration, observability, and deployment patterns with TypeScript code examples.
Google's Agent2Agent Protocol: How A2A Enables Cross-Framework Agent Communication in Production Systems
A deep dive into Google's Agent2Agent (A2A) protocol covering agent cards, task lifecycle, message parts, streaming via SSE, push notifications, and how A2A complements MCP. Includes TypeScript implementation examples, comparison with MCP and direct API integration, and production deployment patterns for multi-vendor agent ecosystems.
How ScyllaDB Works Internally: Shard-Per-Core Architecture, LSM Storage, and the C++ Engine That Outperforms Cassandra
A deep dive into ScyllaDB internals covering the shard-per-core thread model built on the Seastar framework, shared-nothing design that eliminates cross-core locking, LSM-tree storage with size-tiered and leveled compaction, CQL compatibility with Cassandra, gossip-based cluster membership and consistent hashing, lightweight transactions via Raft consensus, I/O scheduling and memory allocation, streaming and repair, and a tradeoffs comparison table across ScyllaDB, Apache Cassandra, Amazon DynamoDB, CockroachDB, and FoundationDB.
How Grafana Loki Works Internally: Label-Based Indexing, Log Chunk Storage, and the Cost-Efficient Architecture That Stores Logs Like Prometheus Stores Metrics
A deep dive into Loki's internal architecture covering label-based indexing that avoids full-text inversion, the write path through distributors and ingesters with WAL-backed chunk buffering, the read path through query frontends and queriers with LogQL execution, the boltdb-shipper and TSDB index backends, compaction and retention mechanics, and tradeoffs against Elasticsearch, Datadog, and Splunk.
How Prometheus Works Internally: Pull-Based Scraping, the TSDB Storage Engine, and PromQL Query Execution
A deep dive into Prometheus internals for senior engineers. Covers the pull-based scraping model, service discovery integration, the custom TSDB with head block and compacted blocks, WAL-based crash recovery, PromQL evaluation from parse tree to result, recording rules, the Alertmanager pipeline, federation, and production considerations including cardinality management, retention tuning, and remote write for long-term storage.