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Deploying ClearML as a GCP Vertex AI Alternative on Ubuntu

Sanskriti Harmukh 2026年07月08日 05:37 3 次阅读 来源:Dev.to

Google Vertex AI is Google Cloud's managed ML platform with experiment tracking, training jobs, pipelines, a model registry, and endpoints, but it locks you into GCP-specific APIs and per-use billing. ClearML is an open-source MLOps platform that covers the same ground on any Docker host or Kubernetes cluster, capturing training metrics automatically with no code changes and keeping every byte of data on infrastructure you control. This guide deploys ClearML Server with Docker Compose and Traefik, registers an agent, runs an experiment, builds a pipeline, runs a hyperparameter sweep, and deploys a Triton-served model. By the end, you'll have a self-hosted Vertex AI replacement covering the full ML lifecycle. Vertex AI → ClearML Mapping GCP Vertex AI ClearML Equivalent Purpose Vertex AI Workbench ClearML Web UI Browser-based monitoring and configuration Vertex AI Experiments ClearML Experiment Manager Automatic hyperparameter/metric/artifact tracking Vertex AI Training Job ClearML Agent + Tasks Any machine becomes a remote worker via queues Vertex AI Pipelines ClearML Pipelines Python-native DAGs, no separate compile step Vertex AI Model Registry ClearML Model Repository Versioned models with full lineage Vertex AI Endpoints ClearML Serving (Triton) Self-hosted inference with canary/A-B support Cloud Monitoring/Logging ClearML Scalars/Plots Built-in metrics and hardware dashboards Prerequisite: Ubuntu host with Docker + Compose, DNS A records for app.clearml.example.com , api.clearml.example.com , files.clearml.example.com . NVIDIA Container Toolkit if you'll run GPU agents. Deploy the ClearML Server 1. Raise Elasticsearch's virtual memory limit and restart Docker: $ echo "vm.max_map_count=524288" | sudo tee /etc/sysctl.d/99-clearml.conf $ sudo sysctl --system $ sudo systemctl restart docker 2. Create persistent data directories with the correct ownership: $ sudo mkdir -p /opt/clearml/ { data/elastic_7,data/mongo_4/db,data/mongo_4/configdb,data/redis,data/fileserver,

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