MLRun vs Opik

MLRun is an open-source framework for orchestrating machine-learning and generative-AI applications across their lifecycles. It automates data preparation, model tuning, customization, validation, and optimization for ML models and large language models over elastic resources. Its feature store can collect, transform, store, catalog, serve, and monitor data features. MLRun supports multi-cloud, hybrid, and on-premises deployments with built-in observability; documented options include Kubernetes, AWS, Azure AKS, and Iguazio’s managed service. The ecosystem includes storage and data systems such as S3, Google Cloud Storage, BigQuery, Snowflake, Kafka, Spark, and Dask, alongside PyTorch, TensorFlow, XGBoost, and ONNX. CI/CD integrations include GitHub Actions, GitLab CI/CD, Jenkins, and Kubeflow Pipelines. MLRun also lists model registry, experiment tracking, pipeline orchestration, model serving, data versioning, and managed compute. The open-source plan costs nothing and includes community support. Managed MLRun includes LDAP integration, user and group management, service authentication and authorization, secured API-gateway authentication, service monitoring, log management, and 24/7 enterprise support.

Opik helps teams building applications or agents that call an LLM log actions and evaluate behavior across development, testing, and production. It captures and visualizes traces, supports annotation, and provides audit logs. Its evaluation tools include more than 30 metrics for outcomes such as answer relevance, context precision, task completion, and hallucination. In production, Opik can evaluate traces in real time, alert when criteria fail, and track token use and model costs. Test Suites offer pass/fail assertions, an Agent Playground supports end-to-end tests, and a Prompt Optimizer provides six algorithms. Core observability and evaluation features are available as open-source code for local use. Opik includes a REST API and Python client, with Python and TypeScript SDKs listed, and integrations with more than 40 frameworks, model providers, and gateways. Free Cloud allows up to 10 team members, 25,000 spans per month, and 60-day retention. Pro Cloud costs $19 a month and lists up to 50 team members and 100,000 spans monthly.