Orchestrate workflows with Prefect. Build AI applications with Horizon. Open-source foundations, production-ready platforms.
Millions of developers choose our open-source Python frameworks when moving from script to scale. Turn any Python function into a workflow. One decorator. Full observability. No rewrites. Build MCP servers in minutes. Connect AI agents to any system. The standard for context delivery. Same code you wrote. Enterprise scale. SSO, RBAC, governance, and zero infrastructure to manage. Production orchestration without the ops. Autoscaling workers, enterprise auth, and observability that actually helps you debug. Deploy MCP servers with a command. Gateway, registry, and governance for AI agents accessing your business. From fintech to healthcare, teams rely on Prefect to orchestrate their most critical workflows. Faster fraud prevention with enterprise security Tripling production while cutting spend Connecting AI to internal systems Open source to experiment. Cloud and Horizon when you're ready for production. Prefect is used in production at Detailed feature comparison across all tiers Free Hobby tier with full core functionality. Upgrade when you need enterprise features—your workflows always run in your infrastructure. Join an active ecosystem of engineers running Prefect in production who share solutions to common challenges. When failures impact revenue or SLAs, you need more than community support. Enterprise plans include dedicated TAMs and 24/7 coverage. Find step-by-step tutorials, complete API documentation, and troubleshooting guides for every workflow pattern. Every tier includes support options. Begin with free community access and upgrade to SLA-backed coverage when your workflows become mission-critical. Get help from the community. If you're on a paid plan, submit a ticket to our support team. Discuss your requirements, learn about custom pricing, or request a demonstration. Get Prefect news, company information, and media resources. For code related discussions, join our community Slack.
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npm packages
Pricing found: $100 /mo, $100 / user, $100 /mo, $100 / user
[R] How are you managing long-running preprocessing jobs at scale? Curious what's actually working
We're a small ML team for a project and we keep running into the same wall: large preprocessing jobs (think 50–100GB datasets) running on a single machine take hours, and when something fails halfway through, it's painful. We've looked at Prefect, Temporal, and a few others — but they all feel like they require a full-time DevOps person to set up and maintain properly. And most of our team is focused on the models, not the infrastructure. Curious how other teams are handling this: - Are you distributing these jobs across multiple workers, or still running on single machines? - If you are distributing — what are you using and is it actually worth the setup overhead? - Has anyone built something internal to handle this, and was it worth it? - What's the biggest failure point in your current setup? Trying to figure out if we're solving this the wrong way or if this is just a painful problem everyone deals with. Would love to hear what's actually working for people. submitted by /u/krishnatamakuwala [link] [comments]
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Deep analysis of PrefectHQ/prefect — architecture, costs, security, dependencies & more
Yes, Prefect offers a free tier. Pricing found: $100 /mo, $100 / user, $100 /mo, $100 / user
Key features include: Prefect, FastMCP, Prefect Cloud, Prefect Horizon.
