One OpenAI-compatible API fronts more than 250 models across 40 providers in LLM Gateway, with routing, cost analytics, and key management in a single dashboard. Existing OpenAI SDK code keeps working: change the base URL and model name to reach OpenAI, Anthropic, Google, xAI, DeepSeek, Groq, and dozens more. Every request lands in an activity log with its model, cache status, token counts, duration, and cost, and opening a request shows time to first token, throughput, and cached token usage. Spend splits by model, provider, project, and API key over 7 or 30 days, so the expensive endpoint stops hiding inside one monthly invoice. Scoped API keys carry spend caps and recurring limits, and requests stop automatically at the cap. Provider errors, timeouts, and rate limits trigger a retry on another provider for the same model before the caller hears about it. Coding agents and automation tools get their own usage views with requests, tokens, and spend per tool. Self-hosting runs the unified Docker image or a Kubernetes Helm chart on your own network. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With over 11,000 GitHub stars and now backed by Datadog while remaining fully Apache 2.0 licensed, Quickwit delivers the search performance Elasticsearch users expect at a fraction of the infrastructure cost by moving the index to object storage instead of expensive local SSDs. The Rust-based engine, built on the Tantivy search library with SIMD-accelerated vectorized processing and zero garbage collection overhead, achieves sub-second search latency directly against Amazon S3, Azure Blob Storage, Google Cloud Storage, or any S3-compatible backend like MinIO and Ceph. The Elasticsearch-compatible REST API covers ingest, search, query DSL, and aggregations, enabling existing log shippers including Vector, Fluent Bit, and Syslog to migrate without rewriting configurations. Native OpenTelemetry Protocol endpoints accept logs and traces via gRPC, while Jaeger integration provides a drop-in distributed tracing backend. Ingestion from Apache Kafka, Amazon Kinesis, and Apache Pulsar supports streaming pipelines with multi-index partitioning, and the schemaless JSON indexing mode eliminates the need for upfront schema definitions. Stateless searchers and indexers scale horizontally on Kubernetes or bare metal, with a control plane that distributes indexing tasks and a janitor that manages retention policies and GDPR-compliant deletions. The built-in web UI displays search results and cluster state, while the official Grafana data source enables log exploration dashboards. 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.

ClickStack is an open-source observability platform that unifies logs, metrics, traces, session replays, and errors in one searchable interface, so engineers can move from an alert to the exact request that broke in minutes. Search uses an intuitive full-text and property syntax (for example level:err), with SQL available when a question needs full analytical power. Live tail streams fresh logs and traces as they arrive, and event deltas surface anomalies by comparing current behavior against earlier windows. Dashboards chart high-cardinality events without a complex query language, and alerts can be created in a few clicks from any search or chart. Session replays connect a user's browser experience to the backend traces and database queries behind it, giving full-stack visibility from click to query. Native JSON string querying handles nested payloads, and the schema-agnostic design works on top of an existing ClickHouse schema instead of forcing a new one. OpenTelemetry is supported out of the box, with SDKs and collectors for Kubernetes, JavaScript, Python, Java, Go, Ruby, PHP, .NET, Elixir, and Rust. The all-in-one Docker image bundles the interface, ClickHouse, the OpenTelemetry Collector, and supporting services on port 8080, and a terminal CLI serves engineers who prefer the shell. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Consolidate application hosting, web analytics, error tracking, and performance monitoring into Temps, an open-source developer platform that replaces disparate SaaS subscriptions with a single compiled Rust binary. Engineering teams deploy full-stack web applications, background daemons, and microservices directly from Git repositories with automated TLS certificate provisioning powered by an embedded Cloudflare Pingora reverse proxy. The centralized web console unifies real-time visitor analytics, conversion funnels, and rrweb-powered session replay recordings without third-party tracking scripts. Integrated error monitoring ingests runtime exceptions with full stack traces and source map resolution, while continuous health checks evaluate container CPU utilization, memory thresholds, and network throughput across custom alerting rules. Developers manage infrastructure through an extensive command line interface containing over 440 operations across 69 command groups, or deploy drop-in skill files that allow AI coding assistants like Claude Code and Codex to provision preview environments autonomously. The platform also provides serverless key-value storage, S3-compatible blob buckets, and native transactional email routing with custom DKIM validation. 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.

All-In-One Free SEO Tool packs site audits, rank tracking, keyword research, AI-search visibility checks, and client reporting into one self-hosted workspace that stands in for a stack of monthly SEO subscriptions. Every client opens on a ranked to-do list that separates work the agent can finish unattended from decisions that need a person, with time estimates attached. The crawler runs dozens of on-page checks, and over ninety single-purpose tools cover schema, Core Web Vitals, hreflang, robots.txt, redirects, and server logs. Rank tracking follows keywords by device and by city. The AI visibility tools record when ChatGPT, Perplexity, Gemini, or Google AI Overviews cite your domain. Agencies generate every client's white-label PDF in one run, review the drafts, and send only what they approve. An embeddable audit widget collects leads, and proposals are built from real findings. Four autonomy levels range from suggest-only to full autopilot, and every change the agent applies can be undone. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Product catalogs, help centers, and document archives all fail the same way: visitors type a few words, get the wrong results, and leave. Apache Solr is the search platform behind fast, relevant answers, returning ranked matches with faceted filters, highlighted snippets, spell suggestions, and geospatial distance in a single query. Index documents through HTTP updates or data import handlers, shape fields in the schema, and watch changes appear through near-real-time indexing without rebuilding the corpus. SolrCloud turns one index into a distributed collection: shards split large corpora across nodes, replicas copy each shard for failover and query load, and ZooKeeper coordinates configuration so every node serves the same schema. Dense vector fields store embeddings beside your text, and the KNN parser retrieves nearest neighbors through HNSW graphs, so semantic search runs in the same engine as keyword search instead of a second system. A combined query handler merges keyword and vector rankings with reciprocal rank fusion, and an enrichment processor can call language models at index time to tag or summarize documents as they arrive. Streaming expressions add analytics over results, from rollups and percentiles to joins across collections, while JWT authentication and authorization rules protect the admin console and APIs. 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.

With 5,600+ GitHub stars and deep dbt integration, Lightdash is the open-source Agentic BI platform that treats analytics like software — defining metrics, dimensions, joins, permissions, and caching in a governed context layer that powers dashboards, AI agents, data apps, embedded analytics, and MCP server endpoints simultaneously. The dbt Write-Back feature lets business users create custom metrics and models in the UI, then automatically generates pull requests in GitHub or GitLab so every change flows through code review and CI validation before reaching production. Context-specific AI analysts automatically select relevant models and metrics, build queries, and present insights in plain English, while row-level security, user attributes, and customer-facing permissions ensure data governance at every layer. The platform connects to BigQuery, Snowflake, Redshift, Databricks, PostgreSQL, Trino, and ClickHouse through warehouse adapters, with the TypeScript monorepo built on React, Mantine, Vite, and TanStack Query on the frontend plus Node.js, Express, Knex, and PostgreSQL on the backend. Data teams build analytics with coding agents, preview changes from the CLI, validate in CI pipelines, and review charts and dashboards in pull requests — making the entire analytics lifecycle version-controlled and reproducible. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Used by over 3,000 organizations including Dropbox, Khan Academy, Sony, Pepsi, Wikipedia, and Mistral, GrowthBook is the open-source experimentation platform that handles over 100 billion feature flag evaluations daily across its cloud and self-hosted deployments. Feature flags support advanced targeting with user attributes, gradual percentage rollouts, prerequisite dependencies, and scheduled launches, with both client and server SDKs evaluating flags locally from a cached payload for sub-millisecond performance with zero network calls per check. The warehouse-native architecture queries experiment results directly from 11 data sources including BigQuery, Snowflake, Databricks, Redshift, ClickHouse, Mixpanel, and PostgreSQL, eliminating duplicate data pipelines. The statistics engine implements CUPED variance reduction, sequential testing, Bayesian analysis, post-stratification, multi-armed bandits, and sample ratio mismatch checks with fully open-source methodology. Product analytics provides dashboards with funnels, retention cohorts, and event-based tracking shareable across teams. Twenty-four SDKs cover React, Next.js, Node.js, Python, Go, Ruby, PHP, Java/Kotlin, Swift, C#/.NET, Rust, Elixir, Angular, and edge runtimes including Cloudflare Workers, Fastly Compute, and Lambda@Edge. The MCP server and REST API enable AI coding agents to create features, start experiments, and manage stale flags programmatically. Self-hosting deploys via Docker Compose with MongoDB, or via Helm charts on Kubernetes, with the same codebase powering both open-source and managed cloud offerings. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Your analysts write the context once, and everyone else just asks questions: nao turns your warehouse into an analytics agent that answers in plain English, showing the SQL and source files behind every answer. The data team builds the context layer by syncing warehouse schemas, dbt projects, documentation, and business rules into files the agent reads, then tests key questions offline against expected SQL before any change ships. Colleagues ask from the web chat, Slack, Teams, or any MCP client, and turn good answers into live dashboards, data apps, and slide stories they share with their team. Every conversation can be replayed, and when an answer earns a downvote, context recommendations turn the mistake into a fix that arrives as a pull request. You bring your own model key from any provider, sign people in with Google, GitHub, or GitLab, and keep warehouse permissions intact as queries run. Dashboards from Metabase or Tableau migrate over instead of starting blank. 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.

Point your routers at Akvorado and every NetFlow, IPFIX, and sFlow record crossing your network becomes a chart you can interrogate. The web console opens on a live summary of flows per second, exporter count, and traffic split by autonomous system, port, protocol, country, and address family. From there, the visualize page turns stored flows into stacked, line, grid, and heatmap time series, plus Sankey diagrams that show how traffic moves between networks, interfaces, and countries. Filters use a simple SQL-like syntax, so a question like which customers pulled traffic over a transit link last night becomes a query, not a support ticket to your future self. Because the outlet polls each exporter with SNMP or gNMI, flows arrive wearing real interface names, descriptions, and speeds instead of raw ifIndex numbers nobody can read. GeoIP lookups attach country and city to addresses, classification rules tag providers, peers, and connectivity types, and optional BMP sessions add AS paths and BGP communities to every flow. Retention is tiered: raw flows keep full detail for recent days while one-minute, five-minute, and hourly rollups stretch summaries across a year of history. A Grafana plugin is available too, so the same flow data can sit on the dashboards your team already watches. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

When a buyer asks ChatGPT which company to call, your brand is either inside the answer or invisible: Canonry tracks those mentions and citations across ChatGPT, Claude, Gemini, Meta Muse, and Perplexity, then joins them with the search, ads, and traffic data that explains them. You see mention share against named competitors, the exact answers and sources behind every result, and where rivals get cited while you do not. Server-side traffic analysis reads your own logs to show which pages GPTBot, ClaudeBot, and other AI crawlers visit, which pages AI assistants open for users, and who clicks through. Site Health crawls score every page for AI readiness and map the internal links between them, with each finding listing the pages it affects. Keyword volume, difficulty, rankings, and search gaps come from DataForSEO, while the content engine points at the pages to write or improve next and can draft them to WordPress for review. Your connected agent works the same evidence through the REST API, CLI, or MCP: find competitor citations, prepare a fix, publish and submit URLs to Google and Bing, then rerun checks and report what changed. Schedules rerun everything on a clock with alerts to Discord or Slack, and Aero, the built-in analyst, reads the evidence and explains what moved. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Most traders know their balance and almost nothing else, because the patterns that actually cost money hide across hundreds of individual fills. Trading Journal AI rebuilds your round-trip trades from a broker CSV, grouping partial fills, scale-ins and shorts automatically, then tracks win rate, profit factor, expectancy, drawdown, MFE, MAE and exit efficiency for every account. Thinkorswim and Interactive Brokers import directly, seven more brokers including Tradovate, NinjaTrader, Webull and tastytrade are in beta, and a generic template covers any other broker's export. The Leak Finder ranks groups of trades that share something you knew at entry, an entry window, a weekday, a size habit, an emotion from your diary, and shows which of them quietly drain the account, with confidence scored against the rest of your history. Exit Lab replays your completed stock trades on one-minute prices and compares your actual exits against 1R and 2R targets, breakeven rules, trailing stops and VWAP or EMA exits, in R and in dollars. If you add an Anthropic key, Claude reads your trading diary and grades each day on process rather than outcome; without one, every number still works, because the statistics are plain code and never AI. Four interface themes, one SQLite file, no account and no telemetry complete the picture. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Unlimited domains, unlimited keywords, daily Google position checks with stored history and trend charts: SerpBear is an open-source search engine rank tracker. Retrieval works through your choice of third-party SERP APIs - ScrapingAnt, ScrapingRobot, SerpApi, SearchApi, HasData - or your own proxy IP pool, and a flexible scrape-strategy system (Basic, Custom, or Smart, set globally or per domain) works around Google's removal of the 100-results-per-page parameter by choosing how many pages to check per keyword. Google Search Console integration adds real visit counts, impressions, and click-through rates per tracked keyword and surfaces top-performing pages and countries; Google Ads integration supplies monthly search volumes and auto-generates keyword ideas from your site's content. Email notifications report position changes daily, weekly, or monthly, a built-in REST API feeds dashboards and reporting tools, and data exports to CSV. Built with Next.js on SQLite, deployed via Docker, installable as a PWA on mobile - with no per-keyword or monthly SaaS fees.

With nearly 9,000 GitHub stars and adoption by over 60,000 companies across 100 countries, Papermark is the open-source DocSend alternative that turns document sharing into a data-rich conversation between you and your viewers. Every shared document generates page-by-page analytics showing exactly which pages capture attention, how long viewers spend on each section, where they drop off, and whether they return for a second look, with real-time notifications the moment a document is opened. Virtual data rooms support unlimited folders with drag-and-drop organization, bulk uploads, granular per-viewer permissions, dynamic watermarking that stamps each page with the viewer's identity, and NDA gating that requires agreement before access. Custom branding applies your logo, colors, and custom domain to every shared link and download page, while email verification and password protection add authentication layers. The AI Data Room Copilot lets viewers chat with uploaded documents, ask questions, and receive contextual summaries directly within the data room interface. The developer platform exposes 43 REST API operations covering data rooms, documents, folders, links, visitors, and analytics, with an MCP server for AI agent integration and a CLI for automation. Built on Next.js with TypeScript, Prisma ORM, PostgreSQL, NextAuth.js authentication, and shadcn/ui components. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Backed by Y Combinator (S24) and processing traces from thousands of AI agents in production, Laminar is the open-source observability platform that treats agent debugging as a first-class engineering discipline rather than an afterthought. Its OpenTelemetry-native SDK auto-instruments Vercel AI SDK, LangChain, OpenAI, Anthropic, Gemini, Browser Use, Stagehand, Mastra, Pydantic AI, and the OpenAI Agents SDK with a single line of code, capturing every LLM turn, tool call, and sub-agent delegation as nested spans with full input/output data and token costs. The Signals engine lets you describe failures in plain language — "agent is stuck in a loop" or "tool returned empty results" — then reads every trace and alerts via Slack when it detects a match. A built-in debugger records runs and replays them from cache so each iteration takes seconds, designed for Claude Code, Cursor, or Codex to drive the repair loop via the MCP server or CLI. Run code-first evaluations in Python or TypeScript locally or in CI/CD pipelines, build datasets from production traces, and query everything with raw SQL through custom dashboards, the in-app editor, or your coding agent. The Rust backend delivers 20x trace compression, a custom real-time streaming engine, ultra-fast full-text search, and gRPC ingestion, while ClickHouse powers columnar analytics and PostgreSQL stores application state. 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.

With 12,400 GitHub stars and adoption across enterprises processing billions of events daily, Redpanda delivers a complete Kafka wire protocol implementation in C++ that existing Kafka producers, consumers, Kafka Connect connectors, and Kafka Streams applications connect to without code changes — eliminating JVM garbage collection pauses and ZooKeeper coordination overhead through a single binary architecture built on the Seastar framework's thread-per-core model. The integrated schema registry supports Avro, Protobuf, and JSON Schema validation directly within the broker without separate infrastructure. Tiered storage automatically offloads cold data to object storage while maintaining seamless consumer access across the full retention window. Redpanda Console provides a web-based management interface for topic inspection, consumer group monitoring, schema management, and ACL configuration. Redpanda Connect extends the platform with 200+ pre-built connectors for data pipelines between databases, cloud services, and streaming systems. Exactly-once semantics with idempotent producers and transactional guarantees ensure data integrity for financial, healthcare, and compliance workloads. The Adaptable Data Plane in version 26.1 enables per-topic performance profiles balancing throughput, latency, and durability within a single cluster. Deploy via Docker or Kubernetes with official Helm charts — a three-node cluster starts with a single rpk command. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed (converts to Apache 2.0 after four years).

GoAccess processes millions of web log entries in seconds and renders the results as interactive dashboards that update every 200 milliseconds in the terminal or every second via WebSocket-connected HTML reports. Written entirely in C with only ncurses as a dependency, it achieves exceptional performance even on resource-constrained servers, reducing memory usage by approximately 20% and parsing time by 35% in recent releases through optimized in-memory hash tables with on-disk persistence support. The analyzer parses virtually every web log format out of the box (Apache Combined and Common, Nginx, Amazon CloudFront, Amazon S3, AWS Elastic Load Balancing, Google Cloud Storage, Squid, W3C IIS, Caddy JSON, and Traefik) while supporting fully custom log format strings for non-standard configurations. The self-contained HTML dashboard displays 15+ interactive panels covering unique visitors, requested files, static files, 404 errors, referring sites, search keyphrases, geographic location with city-level GeoIP resolution, operating systems, browsers, HTTP status codes, time distribution, and virtual host metrics. WebSocket authentication via JWT provides secure remote access, and incremental log processing ensures data continuity across daemon restarts. Docker deployment requires a single command with volume-mapped access logs. Over 20,800 stars with active development since 2010. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Parseable replaces expensive Elasticsearch clusters and fragmented monitoring stacks with a single Rust binary that ingests, queries, and stores logs, metrics, and traces on commodity object storage at a fraction of the cost. The data lake architecture decouples stateless compute from S3-compatible storage, enabling independent scaling of ingestion throughput and query capacity while cutting storage costs by up to 90% compared to indexed alternatives. OpenTelemetry-native OTLP ingestion accepts telemetry from existing OTel collector pipelines, Prometheus Remote Write endpoints, Kafka consumers, eBPF probes, and popular logging agents including Fluentd, Fluent Bit, and Vector without proprietary format conversions. The SQL-first query interface enables cross-signal analysis across all telemetry types, while native PromQL support with 50+ functions and 12 aggregation operators provides Prometheus-compatible metrics querying that works directly with Grafana dashboards. Built-in features include customizable dashboards, real-time alerting with Webhook, Slack, and Alertmanager targets, role-based access control, OpenID single sign-on integration, LogIQ automatic unstructured-to-structured log transformation, smart caching for frequently accessed data, and retention policies for lifecycle management. AI-powered Keystone Q&A provides natural language to SQL conversion and dataset summarization. All data stored as standard Apache Parquet on object storage remains accessible to any Parquet-compatible engine (DuckDB, Spark, Trino), ensuring zero vendor lock-in. Deploys on AWS S3, Azure Blob, Google Cloud Storage, MinIO, Wasabi, and DigitalOcean Spaces. 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.