With over 52,000 GitHub stars and its role as the foundation of every Kubernetes cluster worldwide, etcd is the distributed key-value store that handles the most critical data in modern infrastructure — cluster state, configuration, service discovery, and distributed coordination. Built in Go and graduated from the CNCF, etcd uses the Raft consensus algorithm to maintain a strongly-consistent, highly-available replicated log across a cluster of machines, gracefully handling leader elections during network partitions and tolerating machine failure including the leader node. The gRPC API provides atomic key-value operations including put, get, delete, and transactions with multi-key compare-and-swap semantics, enabling distributed locking, leader election, and configuration management without external coordination. Watch operations stream real-time change notifications for specific keys or key ranges, powering reactive architectures that respond immediately to configuration updates. Version 3.7 introduces RangeStream for streaming large result sets in chunks, keys-only range requests for faster metadata queries, and bootstraps entirely from v3store after eliminating the legacy v2 store dependency. Automatic TLS encryption with optional client certificate authentication secures all cluster communication, while role-based access control restricts key access per user. The embedded bbolt B+ tree storage engine provides consistent reads and writes with configurable compaction policies. Benchmarked at 10,000 writes per second per instance with linearizable reads, etcd supports clusters of 3, 5, or 7 members for fault tolerance. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Processing over one billion tasks per month on Hatchet Cloud and holding 7,600+ GitHub stars, Hatchet is the open-source orchestration engine that replaces fragile legacy queues with durable, fault-tolerant task execution built entirely on PostgreSQL — no Redis, RabbitMQ, or Kafka required. Born from the creators' experience scaling Uber's Cadence-inspired patterns, the v1 engine achieves 10,000 tasks per second sustained throughput with 20ms average queue latency through dynamic buffer flushing and batch insert optimization. Define tasks, durable workflows, and DAG pipelines as code using native SDKs for Python, TypeScript, Go, and Ruby — every function gets automatic retries with configurable backoff, concurrency control with group round robin or cancellation policies, priority queuing, and dynamic rate limiting for third-party API protection. Durable execution persists the complete history of every task and state transition, enabling replay from failure, debugging via full event timelines, and complex pause/resume conditions using durable sleep and event waits. The real-time web dashboard provides workflow run visualization with DAG timeline rendering, worker health monitoring with slot utilization, queue depth metrics, task throughput charts, and error rate tracking — all filterable by status, workflow, or time window. OpenTelemetry integration and Prometheus metrics export enable advanced observability. Multi-tenant by default with users, roles, and namespace isolation. Self-host via Docker Compose with PostgreSQL and optional RabbitMQ, or use the single-container Hatchet Lite image for development. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Powering mission-critical infrastructure at OpenAI, Cursor, Replit, Lovable, Retool, and Snap with over 22,000 GitHub stars, Temporal is the durable execution platform that originated from Uber's Cadence project — built by the creators of AWS SQS, AWS SWF, and Azure Durable Functions with nine years of production-proven reliability. The workflow-as-code model lets developers write business logic in Go, Java, Python, TypeScript, .NET, PHP, or Ruby using native SDKs, while the Temporal Server automatically persists state at every step, replays from failures, retries activities with configurable backoff policies, and manages task queues without developers writing reconciliation logic. Workflows support signals for external event injection, timers for scheduled delays, child workflows for decomposition, and queries for real-time state inspection — all backed by deterministic replay over an event-sourced history that guarantees exactly-once semantics. The Web UI provides visual workflow execution inspection with event timelines, pending activity monitoring, namespace management, and worker health dashboards. Persistence supports PostgreSQL, MySQL, or Apache Cassandra for horizontal scalability, with Elasticsearch or OpenSearch for advanced workflow visibility queries. Multi-cluster replication enables global failover across data centers. The self-hosted stack deploys via Docker Compose with the auto-setup image, PostgreSQL, Web UI, and admin tools — operational within 30 minutes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.