dstack vs HTCondor

dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, virtual machines, and bare-metal clusters. YAML configurations define fleets, development environments, tasks, services, presets, and volumes, while dstack handles provisioning and job scheduling, including auto-scaling, port forwarding, and ingress. Supported accelerators include NVIDIA, AMD, TPU, and Tenstorrent. Documented backends include AWS, Azure, GCP, Kubernetes, GPU cloud providers, remote SSH hosts, and experimental Slurm. Tasks can use frameworks such as accelerate, torchrun, Ray, and Spark. Users manage resources through the CLI or HTTP API, and the server can run on a laptop or another environment that can access the clusters in use. Services can publish inference endpoints through gateways with HTTPS, custom domains, auto-scaling, and rate limits. The self-hosted open-source stack is free. Server data and project secrets are stored in plaintext by default unless administrators configure AES-256-GCM encryption. TPU support is limited to single-host instances with up to eight cores. GPU Marketplace usage is prepaid, with prices that vary by GPU and provider and appear in the console before provisioning.

HTCondor is a free high-throughput computing system that coordinates networked machines to run submitted jobs. It finds available machines, matches their resource offers to job requirements and preferences through ClassAds, and can restart a job elsewhere if its current machine becomes unavailable. It is suited to submitting large batches, including thousands of runs across different data sets, and can use otherwise idle machines in a pool. Users do not need login accounts on machines running their jobs; file transfers and split execution support that model. HTCondor can draw on clusters, cloud resources, and international grids, and flocking can connect multiple installations. It supports transfers to and from S3-compatible storage, including Google Cloud Storage through its S3 interoperability API, but not entire buckets or directories. The software is licensed under Apache License 2.0, includes Python bindings, and offers user and administrator guides. Community support is available through a mailing list; paid contract support offers guaranteed resolution and faster turnaround. Security fixes cover current feature and LTS versions, with the previous LTS supported for approximately twelve months after a new LTS release.