With 17,000 GitHub stars, 460+ contributors, and deployments across telecommunications, automotive, and financial services running on over 10,000 CPU cores at the largest known installations, Apache APISIX delivers a fully dynamic API gateway achieving 140,000 QPS on eight cores with sub-millisecond latency through NGINX's event-driven architecture and LuaJIT-compiled plugin execution. The 100+ open-source plugins cover authentication (JWT, OAuth 2.0, OIDC, Keycloak, LDAP), observability (Prometheus, Datadog, SkyWalking, OpenTelemetry), traffic management (rate limiting, circuit breaking, canary releases, traffic splitting), and security (CORS, IP restriction, CSRF protection) — all hot-reloadable without process restarts via etcd-based real-time configuration synchronization. Multi-protocol support handles HTTP, gRPC, MQTT, TCP, UDP, and WebSocket traffic for both north-south API access and east-west service mesh communication. AI gateway capabilities proxy requests to 20+ LLM providers with semantic caching, token-aware rate limiting, provider failover routing, and content moderation. Custom plugins extend the gateway in Lua, Go, Java, Python, or WebAssembly. Radixtree route matching handles 100,000+ routes without performance degradation. Functions as a Kubernetes ingress controller with native service discovery for Consul, Nacos, and Eureka. Deploy via Docker or Helm charts with horizontal scaling through etcd cluster coordination. 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 over 43,000 GitHub stars and adoption by companies including Nasdaq, Samsung, and Expedia, Kong Gateway is the world's most deployed open-source API gateway, processing billions of API requests daily across hybrid-cloud and multi-cloud architectures. Built on the battle-tested NGINX engine with OpenResty's LuaJIT runtime, Kong delivers sub-millisecond proxy latency while supporting REST, gRPC, GraphQL, WebSocket, SOAP, and Kafka protocols. The plugin architecture includes authentication via JWT, Basic Auth, HMAC, key authentication, OAuth 2.0, and LDAP, alongside rate limiting with configurable windows per consumer, IP address, or API key. The AI Proxy plugin provides a universal LLM API that routes across OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure AI, Databricks, Mistral, and Hugging Face through a single standardized interface, while MCP proxy capabilities convert REST APIs into MCP tools and provide traffic governance for AI agents. Kong supports declarative configuration via YAML for GitOps workflows, a RESTful Admin API for dynamic configuration, and decK CLI for version-controlled infrastructure-as-code management. Upstream health checking with active and passive probes enables automatic failover, and the ring balancer distributes traffic across upstream targets with consistent hashing, round-robin, or least-connections algorithms. The Kong Plugin Hub hosts over 100 community and official plugins covering logging, monitoring, transformation, security, and traffic control. 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.

Bifrost is an open-source AI gateway that unifies 23+ LLM providers into a single OpenAI-compatible endpoint with automatic failover, semantic caching, and built-in cost governance, so one provider going down never takes your production AI application with it. Point your existing OpenAI or Anthropic SDK at Bifrost's local endpoint and gain access to OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Groq, Mistral, and Ollama without changing application code. Define fallback chains that automatically switch providers when one returns errors or exceeds latency thresholds, keeping response times stable during outages. The built-in web dashboard at port 8080 lets you configure providers, create virtual API keys, monitor live request traffic, and review analytics without editing configuration files. Semantic caching combines exact hash matching with vector similarity search via Weaviate, serving cached responses for identical or paraphrased prompts in sub-millisecond time to cut costs on repetitive workloads. The MCP gateway connects AI agents to external tools like filesystems, databases, and web APIs, exposing them to clients such as Claude Desktop and Cursor with per-key allow-lists. Four-tier budget hierarchy at customer, team, virtual key, and provider levels enforces spend caps, rate limits, and model restrictions across your organization. Extend functionality through custom Go plugins for analytics, monitoring, or security middleware. Native Prometheus metrics and OpenTelemetry distributed tracing give operations teams full production observability. 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.

Backed by 56,000+ GitHub stars and over 240 million Docker pulls, LiteLLM delivers the open-source AI gateway trusted by Netflix, Lemonade, Rocket Money, and thousands of engineering teams to route every LLM request through one unified API. The Rust-core gateway adds sub-millisecond overhead per request with 8ms P95 latency at 1,000 RPS, 15x throughput improvement and 11x lower memory footprint compared to Python-only proxies. A single OpenAI-compatible endpoint connects to 100+ providers and 1,800+ models spanning OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Vertex AI, Hugging Face, vLLM, Nvidia NIM, Ollama, and Mistral with day-zero support for new model releases. The Auto Router V2 classifies request complexity across four tiers using rule-based scoring, semantic keyword matching, and adaptive Thompson sampling to route each request to the most cost-effective model without API calls or training data. Virtual API keys enable multi-tenant governance with per-team, per-user, and per-project cost tracking, budget caps with automatic fallback rerouting, and role-based access control. Built-in guardrails provide PII masking, prompt injection detection, and model-graded evaluation before requests reach providers. The Agent Gateway extends routing from model calls to agent workflows with MCP server integration. Observability integrates with Langfuse, Arize Phoenix, OpenTelemetry, and MLflow for complete request tracing. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Instead of scattering provider credentials and vendor-specific SDK logic across dozens of microservices, engineering teams route every LLM call through GoModel, an open-source AI gateway that unifies 34 model providers behind OpenAI-compatible and Anthropic-compatible endpoints. Pointing existing OpenAI or Anthropic SDKs at the gateway unlocks chat completions, the Responses API, Anthropic Messages, embeddings, batch jobs, and realtime audio across OpenAI, Anthropic, Gemini, Bedrock, Azure, Groq, DeepSeek, Ollama, and vLLM. Platform operators publish virtual model aliases that distribute traffic via weighted round-robin or lowest-cost routing while rotating multiple API keys per provider and failing over through circuit breakers during upstream outages. Sticky session routing keeps multi-turn agent conversations on the same target to preserve warm prompt caches, while exact-match and vector semantic caching via Qdrant, pgvector, Pinecone, or Weaviate cut duplicate token costs. Versioned workflows and pre-dispatch guardrails enforce prompt injection rules, rate limits, and hard USD spend budgets across hierarchical tenant user paths before requests are dispatched. The built-in admin dashboard offers live audit logs, per-tenant cost analytics, LiteLLM key migration, an interactive request playground, Model Context Protocol tool aggregation, and OpenTelemetry and Prometheus metrics. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Point Claude Code, Codex CLI, Gemini CLI, or any OpenAI, Anthropic, or Gemini SDK at one address and Nyro routes every request to whichever model provider you choose. The gateway translates protocols on the fly, including streaming, reasoning blocks, and tool calls, so a tool built for one API can run on a model from another. Define virtual model names, bind each to one or more providers, and pick weighted load balancing or priority failover; unhealthy targets are skipped and recover automatically. Issue API keys with limits on requests and tokens per minute and per day, and bind each key only to the models it may call. Exact and semantic caching return repeated answers instantly. A request log records provider, model, token counts, latency, and streaming speed, and usage charts break traffic down by model and provider. The Connect page generates ready-to-paste samples in Python, TypeScript, and cURL, plus one-click configuration for popular coding CLIs. Choose an embedded database for a single host or an external PostgreSQL or MySQL server for production, and run the gateway, the admin UI, or both as separate processes. 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.

One endpoint, 130+ models from 90+ providers: KeiRouter is a self-hosted AI gateway, so apps, coding tools, and agents connect once and stop juggling provider keys. Your code speaks OpenAI Chat, OpenAI Responses, Anthropic Messages, or native Gemini, and KeiRouter translates to whichever upstream you want, including AWS Bedrock, Azure AI Foundry, Vertex, Snowflake Cortex, and self-hosted runtimes like Ollama and vLLM. Fallback chains keep requests moving when a provider goes down or hits a rate limit, using priority, round-robin, latency, or cost ordering, so coding sessions do not stop mid-task. Five token savers compress prompts on the way in and trim responses on the way out, with a live dashboard showing savings recovered. A response cache answers repeated prompts instantly for zero marginal cost, with optional semantic matching. Per-key budgets and rate plans set USD, token, RPM, and concurrency limits with auto-cutoff, stopping surprise bills. Guardrails scan for PII, prompt injection, toxicity, and banned topics at global, provider, model, chain, and key scopes, with a monitor showing what got blocked and what it cost. The dashboard tracks usage by provider and model, latency, a live console tracing each request through its fallbacks, and provider health. You can import from 9router or OmniRoute, white-label the portal for your team, and run replicas on Postgres and Redis for high availability. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

One gateway, every AI model: APIPark gives your applications a single, consistent API for OpenAI, Anthropic, Google Gemini, DeepSeek, and 100+ other models, and gives your team a portal to publish and share whatever gets built on top. Standardized request and response formats mean swapping a provider or rewriting a prompt never touches client code. Pair a model with a prompt template and it becomes a ready-made API for sentiment analysis or translation, listed in the developer portal with its own readme and generated API docs. Model Fallback swaps in the highest-priority available model when one misbehaves. API key balancing spreads traffic across several keys for the same provider. Already have REST services? Import an OpenAPI document, file the service under a category and tags, and let consumers subscribe, with optional manual review before anyone gets access. Any service can be switched on as an MCP tool that AI assistants can discover and call, and local open-source models can be deployed and exposed the same way. Usage charts follow requests, traffic, and tokens per service and consumer. Request logs flow out to files, HTTP endpoints, Kafka, NSQ, or Syslog. 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.

One OpenAI-compatible endpoint, 1,600+ models behind it: Portkey Gateway sits between your app and every major LLM provider, deciding in real time where each request should go. When a provider times out or returns errors, automatic retries with exponential backoff kick in, and fallback rules quietly move traffic to your second-choice model before users notice anything. Load balancing spreads calls across multiple API keys and providers by weight, conditional routing sends each request down a different path based on its content or metadata, and per-request timeouts cut off providers that hang. Guardrails inspect inputs and outputs as traffic passes through: block banned words, screen for sensitive content, and enforce the checks your compliance team asked for, with dozens of pre-built rules ready to attach. Text is only the start: the same API shape reaches vision models, speech-to-text, text-to-speech, image generation, and realtime websocket APIs, so multimodal features stop multiplying your integration work. Routing policies live in JSON configs you attach per request or per client, which means experiments, cost controls, and provider migrations ship as configuration changes, not redeploys. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Manifest LLM Gateway is a self-hosted gateway that puts every model you pay for behind one OpenAI- and Anthropic-compatible endpoint. Connect provider API keys, reuse subscriptions like ChatGPT Plus or Claude Max, or point it at Ollama and LM Studio on your own hardware. Send a request with the model set to auto and your routing rules choose the target by model, header, complexity, or task type, with fallbacks that take over the instant a model fails. Each agent or app gets its own harness, a named connection with a private key, spending limits, and notifications when usage climbs. The Requests view logs every call and every retry attempt, with status, cost, tokens, and the full request and response body readable as a conversation. Autofix repairs a malformed request, for example one using a renamed parameter, and resends it before your app ever sees an error. A Playground tests models from the dashboard, a command line tool and MCP server handle setup from a terminal or an AI assistant, and an n8n node plugs it into automations. Over 35 provider connections cover more than 300 models. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

One endpoint, every model you run, and a government-grade paper trail for each request. OpenGateLLM sits in front of your AI infrastructure as the single door: applications call one OpenAI-compatible API, and the gateway decides which backend answers, a self-hosted vLLM cluster, an Ollama box in the corner, a Hugging Face TEI embeddings service, or a hosted provider when you allow one. You publish friendly model names as routers and attach real provider APIs behind them, then load-balance across those backends by shuffle or least-busy so a second GPU node starts earning its keep the moment you register it. Chat completions, embeddings, reranking, OCR, and audio transcription each get their standard endpoint, so existing OpenAI SDK code, LangChain, and LlamaIndex projects point at a new base URL and keep working. Governance is built in rather than bolted on: organizations, users, and roles control who may call which model, API keys authenticate every request, and rate limiting keeps one enthusiastic team from eating the whole cluster. Usage monitoring follows every inference, and carbon footprint estimates attach to models through their hosting zone and parameter counts. Retrieval-augmented generation against Elasticsearch or Qdrant plugs into the same surface. No chat history is stored, which is rather the point when the data is yours. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Give every team, project, and application one governed door to AI models instead of scattering raw provider keys across codebases. TokenHub is an OpenAI-compatible gateway that serves chat completions, responses, embeddings, reranking, and image generation, plus Anthropic Messages endpoints, in front of OpenAI, Azure OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Codex subscriptions, local models, and more than 150 provider templates. Administrators publish a model catalog and write routing policies with priority, weight, failover order, and cost or quality preferences, so a provider outage never reaches client code. Users create project-scoped API keys with quotas and concurrency limits, team leaders manage project spaces and members, and each role gets a workspace that matches its job. Usage analytics and request logs attribute every call to a user, project, team, model, and cost center, and provider reconciliation compares internal usage with upstream bills. Sign in through OAuth or OIDC, control access with RBAC, and keep an audit trail of administrative changes. The console switches between English, Chinese, Japanese, and Russian, and includes an API documentation workspace for developers. 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.

Your apps keep using the OpenAI SDK while Antirion, a self-hosted AI gateway, decides which provider answers, what each team may spend, and what gets logged. Clients speak the OpenAI, Anthropic, Gemini, or Bedrock APIs, and Antirion translates between them, so a Claude deployment can answer an OpenAI-style call, streams included. Add providers such as Amazon Bedrock, Vertex AI, Mistral, Groq, DeepSeek, or a vLLM server, then publish them as named Models. Routing rules send traffic by team or project with fallback chains, weighted splits, least-cost or least-latency targets, retries, hedging, and circuit breakers. Budgets and rate limits in dollars or tokens apply per organization, team, project, and key, with projections and alerts before money runs out. Guardrails check for personal data, secrets, keywords, and regex matches, then block, redact, flag, or divert. Exact and semantic caching answers repeated prompts without calling a provider. The request log records every attempt, route, token count, cost, and guardrail verdict, with Prometheus metrics and OTLP traces. An MCP gateway and A2A proxy put tools and agents behind the same keys. Sign in with OIDC, SAML, or GitHub, provision users with SCIM, and review every change in the audit log. Changes you choose can require a change request or a second person's approval, and the Playground sends requests from the console. 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.

Respan Gateway is a single-binary LLM gateway that lets the SDK you already use call any AI model from any provider, translating between OpenAI, Anthropic, and Gemini API formats on the way through. Point an OpenAI, Anthropic, or Gemini client at it and you reach chat models on sixteen providers, plus any OpenAI-compatible endpoint of your own, with streaming, tools, images, and reasoning translated. Traffic control works the way operators think: name a route, send it to the cheapest or fastest provider, retry on failure, fall back to a second vendor, or hedge a slow call by racing another provider. Models that never had tools get them anyway, because MCP servers and built-in search, browsing, code, document, and memory tools run inside ordinary chat requests behind the gateway. Realtime voice crosses vendors too, with an OpenAI Realtime client able to talk to Gemini Live, alongside images, speech, transcription, embeddings, and video through one endpoint. A live request log in the web UI shows the client key, model, provider, status, tokens, cost, and latency of every call, so runaway agents and surprise bills are visible immediately. Everything is a plugin on one public Rust API, from routing and pricing to tracing, with examples for guardrails, PII masking, and billing. One TOML file configures keys, providers, routes, and tools, validates before it starts, and reloads on signal. 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.

Juggling separate API keys, incompatible payload schemas, and unpredictable rate limits across OpenAI, Anthropic, and Google Gemini slows down every AI workflow, and Octopus solves it by consolidating all your upstream model providers into one self-hosted API gateway. Point Claude Code, OpenAI Codex CLI, or any SDK client at a single gateway URL and translate requests transparently between OpenAI Chat Completions, OpenAI Responses, Anthropic Messages, and Google Gemini endpoints without modifying client code. Group multiple provider channels under a unified model alias so your coding agents automatically fail over to backup providers and shield active tasks from upstream HTTP errors or rate limits. Watch live end-to-end request routing on the interactive topology canvas as prompts flow from client applications through model groups to specific upstream channels. Synchronize available model catalogs directly from connected providers and pull up-to-date token pricing from models.dev, or define custom per-million input, output, and cache-read rates for private deployments. Inspect detailed request logs, monitor token consumption trends, and audit daily API spend across every channel from the web dashboard. 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.

KrakenD processes over 18,000 requests per second on a single instance while consuming under 50MB of RAM at 1,000 concurrent connections, operating as a stateless API gateway that requires no database whatsoever. The Community Edition has earned over 2,600 GitHub stars by outperforming database-dependent alternatives like Kong and Tyk in independent benchmarks. Written entirely in Go, it uses declarative JSON or YAML configuration files that integrate directly into GitOps workflows for version-controlled infrastructure management. The gateway aggregates responses from multiple backend services into a single API call, transforms request and response payloads with field filtering, grouping, and mapping, and applies zero-trust security policies including JWT validation, OAuth 2.0, CORS, HSTS, clickjacking protection, and XSS prevention. Traffic management features include multi-layer rate limiting at both the router and proxy levels, circuit breakers for backend fault isolation, spike arrest policies, and concurrent call support that requests the same data from multiple backends in parallel for improved response times. Telemetry integrates with OpenTelemetry, Prometheus, Grafana dashboards, Datadog, Zipkin, and Jaeger for distributed tracing and metrics collection. The gateway extends through Go plugins, Lua scripting, Martian modifiers, and Google CEL expressions for custom request processing logic. AI workload routing supports OpenAI, Anthropic, Gemini, and other model endpoints with built-in fallback, retries, and load balancing. Deploy via Docker with the devopsfaith/krakend image as a single binary. 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.

Put one governed doorway in front of every service you run: Apache ShenYu is an API gateway that proxies, secures, and manages traffic for HTTP, Dubbo, gRPC, WebSocket, and MQTT backends from a single entry point. Every request flows through an ordered, hot-pluggable plugin chain, so you compose exactly the behavior each route needs instead of accepting a fixed gateway feature set. Selectors give you coarse, service-level routing and rules refine it down to individual methods, matched against headers, paths, and parameters. Authentication and edge security come from JWT, OAuth 2.0, request-signing, and WAF plugins, while rate limiting, circuit breaking, and load balancing protect fragile upstreams from traffic spikes. You reshape calls in flight with request, response, and parameter mapping, and convert protocols so a gRPC or Dubbo service answers ordinary HTTP clients. Newer releases add AI gateway plugins that proxy LLM calls with prompt processing, token limits, and sensitive-word filtering, plus an MCP server plugin for exposing tools to AI agents. The ShenYu Admin console on its own port manages plugins, selectors, rules, users, and permissions, then pushes changes live to every gateway replica over WebSocket, ZooKeeper, Nacos, etcd, or HTTP long polling. Metrics, tracing, and logging plugins stream operational data to Kafka or Elasticsearch, and client SDKs for Java, Go, Python, and .NET let services register themselves automatically. 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.

Doorman puts one controlled front door in front of every API you run, instead of teaching each service to reinvent keys, quotas, and abuse protection. It routes REST, SOAP, GraphQL, gRPC, gRPC-Web, and AI traffic through a single gateway while its control plane handles the surrounding work. Catalog APIs in a visual builder, configure protocols and endpoints, validate schemas, and manage semantic versions with deprecation and sunset dates as interfaces evolve. Control who may call what through users, roles, groups, and subscriptions, then attach credit tiers and quotas so heavy consumers stay inside the plan you sold them. Slow abusive clients with rate limits, throttling, and bandwidth caps, and keep flaky upstreams from cascading through retries and circuit breaking. Follow every request in searchable logs, review security controls and audit activity, and move configuration between environments with import and export. Start in a self-contained in-memory mode for a small deployment, then switch to shared MongoDB and Redis when several gateway instances need the same counters, revocations, and routing 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.

Thirty model providers, one OpenAI-compatible endpoint: Ferro Labs AI Gateway routes every request from your applications to the provider that should answer. Eight routing strategies cover fallback chains, weighted load balancing, lowest latency, lowest cost, content-based rules, A/B tests, and conditional targets, each with retries and circuit breakers. Guardrail plugins filter blocked words, redact personal data, scan for leaked secrets, block prompt injection, validate response schemas, and enforce rate limits and per-key spend budgets. Identical prompts can come back from a response cache, and tool servers connect through MCP so the gateway can run the tool-call loop itself. The console opens with a getting-started checklist, then charts traffic, token throughput, latency percentiles, and cost by model. Providers, routing targets, and plugins each get their own page, a playground sends test chats through the real routing path, and request logs plus an audit trail record who changed what. Scoped admin and read-only keys give every operator separate access, and configuration history allows a rollback. OpenTelemetry traces and Prometheus metrics feed existing 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.

Inference Gateway puts a single OpenAI-compatible API endpoint in front of OpenAI, Anthropic, Groq, Cohere, Ollama, DeepSeek, Google, Mistral, MiniMax, Moonshot, Nvidia, and llama.cpp, so your application code never changes when you switch models or providers. The Go binary starts on port 8080 and normalizes authentication, streaming protocols, and response formats across all backends transparently. Native Model Context Protocol support auto-discovers tools from connected MCP servers and injects them into LLM requests without client-side management, enabling server-side tool execution across any provider that supports function calling. Agent-to-Agent protocol integration allows distributed agent communication through a declarative Agent Definition Language that generates production-ready Go or Rust servers from a single YAML manifest. The dedicated Kubernetes Operator manages Gateway, Agent, MCP, and Orchestrator custom resources with automatic HPA scaling, OIDC authentication, and service discovery that rebuilds MCP configurations when the discovered server set changes. Prometheus metrics and OpenTelemetry tracing provide full request-level observability across the entire inference pipeline. Middleware controls enable per-request provider selection, model routing, and fallback strategies. Official SDKs in Go, Python, TypeScript, and Rust provide typed client interfaces with streaming support. Docker Compose deployment requires only environment variables for API keys. A CNCF Sandbox applicant. 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.