[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"workflow-asset-451ff9c1":3,"seo:featured-workflow:451ff9c1-4ecb-11f1-9bc6-00163e2b0d79:es":81,"workflow-related-asset-451ff9c1-451ff9c1-4ecb-11f1-9bc6-00163e2b0d79":82},{"id":4,"uuid":5,"slug":6,"title":7,"description":8,"author_id":9,"author_name":10,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":12,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":15,"tags":22,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":29,"asset_kind":30,"target_tools":31,"install_mode":35,"entrypoint":19,"risk_profile":36,"dependencies":38,"verification":43,"agent_metadata":46,"agent_fit":59,"trust":70,"provenance":78,"created_at":80,"updated_at":80},3618,"451ff9c1-4ecb-11f1-9bc6-00163e2b0d79","asset-451ff9c1","Nuclio — High-Performance Serverless Framework for Real-Time Data","Nuclio is a serverless framework optimized for real-time and data-intensive workloads, delivering sub-millisecond cold starts and high throughput on Kubernetes, Docker, or bare metal.","8a910e34-3180-11f1-9bc6-00163e2b0d79","Script Depot","https:\u002F\u002Ftokrepo.com\u002Fapple-touch-icon.png",0,"","en",[16],{"id":17,"step_order":18,"title":19,"description":13,"prompt_template":20,"variables":13,"depends_on":21,"expected_output":13},4178,1,"Nuclio Serverless Framework","# Nuclio — High-Performance Serverless Framework for Real-Time Data\n\n## Quick Use\n```bash\n# Install the CLI\n# Deploy a function from a YAML spec\nnuctl deploy my-func \n  --path .\u002Fhandler.py \n  --runtime python \n  --handler handler:handler \n  --platform local\n\n# Invoke it\nnuctl invoke my-func --body '{\"key\": \"value\"}'\n```\n\n## Introduction\nNuclio is built for workloads where latency and throughput matter — event processing, real-time inference, IoT data pipelines. Unlike general-purpose FaaS platforms, it keeps function instances warm and processes events in parallel threads within a single container, eliminating per-invocation cold starts.\n\n## What Nuclio Does\n- Deploys serverless functions on Kubernetes, Docker Swarm, or bare metal\n- Processes events from HTTP, Kafka, Kinesis, MQTT, RabbitMQ, Cron, and more\n- Maintains warm function instances with multi-worker concurrency inside each container\n- Provides a web-based dashboard for deploying, testing, and monitoring functions\n- Supports Python, Go, Java, Node.js, .NET, and shell runtimes\n\n## Architecture Overview\nEach Nuclio function runs in a container with an embedded event processor. The processor listens on configured triggers, decodes events, and dispatches them to worker threads running user code. A controller (on Kubernetes, a CRD operator) manages function lifecycle, scaling, and ingress. This in-process model avoids the overhead of spinning up new containers per event, achieving throughput rates of hundreds of thousands of events per second.\n\n## Self-Hosting & Configuration\n- Deploy on Kubernetes with Helm charts or on Docker with a single docker run command\n- Configure triggers, resources, and scaling via YAML function specs or the dashboard\n- Set min\u002Fmax replicas and target concurrency for autoscaling on Kubernetes\n- Mount volumes, secrets, and config maps for function dependencies\n- GPU support available for ML inference workloads\n\n## Key Features\n- Sub-millisecond warm-start latency with multi-worker parallelism\n- Built-in triggers for Kafka, MQTT, Kinesis, RabbitMQ, and V3IO stream\n- Integrated web dashboard for code editing, deployment, and log viewing\n- GPU-aware scheduling for real-time ML serving functions\n- Versioned function deployments with canary and blue-green support\n\n## Comparison with Similar Tools\n- **AWS Lambda** — managed FaaS with broader integrations; Nuclio is self-hosted and optimized for low-latency data processing\n- **OpenFaaS** — Kubernetes FaaS with simpler architecture; Nuclio offers tighter event-source integrations and higher throughput\n- **Knative Serving** — scales Kubernetes pods per request; Nuclio's in-process workers avoid per-request container overhead\n- **Fission** — fast Kubernetes FaaS with environment pooling; Nuclio adds a dashboard and native streaming triggers\n\n## FAQ\n**Q: How does Nuclio achieve low latency?**\nA: Functions run as persistent processes with multiple worker threads. Events are dispatched in-process, avoiding container startup overhead.\n\n**Q: Can Nuclio run outside Kubernetes?**\nA: Yes. The local Docker platform lets you run Nuclio functions without a Kubernetes cluster.\n\n**Q: Does it support GPU workloads?**\nA: Yes. 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