Partner Spotlight: Orchestrating large-scale agent training on Lambda with dstack and RAGEN
Blog post from Lambda
Lambda and dstack provide a streamlined alternative to Kubernetes and Slurm for teams running on Lambda, with native support for training workloads, development environments, and persistent services. By using Lambda's 1-Click Clusters and dstack's orchestration, developers can focus on building rather than setting up their machine learning infrastructure. The RAGEN framework is used for training large language models as reasoning agents in complex, multi-turn environments, introducing fine-grained reward signals to improve agent reliability and performance. With dstack, users can launch a Ray cluster with the RAGEN environment, submit Ray tasks from their local machine, and recover training in case of a failure or cluster restart.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Serverless | 20 | 768 | 210 | 90 | -17% |
| AI Model Fine-tuning | 3 | 508 | 150 | 76 | -36% |
| Kubernetes | 3 | 2,191 | 312 | 96 | +14% |
| Reinforcement learning | 3 | 128 | 48 | 32 | -27% |
| LLM | 1 | 4,437 | 679 | 217 | -3% |
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