ca847a195f
Upon dequeuing an evaluation workers snapshot their state store at the eval's wait index or later. This ensures we process an eval at a point in time after it was created or updated. Processing an eval on an old snapshot could cause any number of problems such as: 1. Since job registration atomically updates an eval and job in a single raft entry, scheduling against indexes before that may not have the eval's job or may have an older version. 2. The older the scheduler's snapshot, the higher the likelihood something has changed in the cluster state which will cause the plan applier to reject the scheduler's plan. This could waste work or even cause eval's to be failed needlessly. However, the workers run in parallel with a new server pulling the cluster state from a peer. During this time, which may be many minutes long, the state store is likely far behind the minimum index required to process evaluations. This PR addresses this by adding an additional long backoff period after an eval is nacked. If the scheduler's indexes catches up within the additional backoff, it will unblock early to dequeue the next eval. When the server shuts down we'll get a `context.Canceled` error from the state store method. We need to bubble this error up so that other callers can detect it. Handle this case separately when waiting after dequeue so that we can warn on shutdown instead of throwing an ambiguous error message with just the text "canceled." While there may be more precise ways to block scheduling until the server catches up, this approach adds little risk and covers additional cases where a server may be temporarily behind due to a spike in load or a saturated network. For testing, we make the `raftSyncLimit` into a parameter on the worker's `run` method so that we can run backoff tests without waiting 30+ seconds. We haven't followed thru and made all the worker globals into worker parameters, because there isn't much use outside of testing, but we can consider that in the future. Co-authored-by: Tim Gross <tgross@hashicorp.com>
Nomad
Nomad is a simple and flexible workload orchestrator to deploy and manage containers (docker, podman), non-containerized applications (executable, Java), and virtual machines (qemu) across on-prem and clouds at scale.
Nomad is supported on Linux, Windows, and macOS. A commercial version of Nomad, Nomad Enterprise, is also available.
- Website: https://nomadproject.io
- Tutorials: HashiCorp Learn
- Forum: Discuss
Nomad provides several key features:
-
Deploy Containers and Legacy Applications: Nomad’s flexibility as an orchestrator enables an organization to run containers, legacy, and batch applications together on the same infrastructure. Nomad brings core orchestration benefits to legacy applications without needing to containerize via pluggable task drivers.
-
Simple & Reliable: Nomad runs as a single binary and is entirely self contained - combining resource management and scheduling into a single system. Nomad does not require any external services for storage or coordination. Nomad automatically handles application, node, and driver failures. Nomad is distributed and resilient, using leader election and state replication to provide high availability in the event of failures.
-
Device Plugins & GPU Support: Nomad offers built-in support for GPU workloads such as machine learning (ML) and artificial intelligence (AI). Nomad uses device plugins to automatically detect and utilize resources from hardware devices such as GPU, FPGAs, and TPUs.
-
Federation for Multi-Region, Multi-Cloud: Nomad was designed to support infrastructure at a global scale. Nomad supports federation out-of-the-box and can deploy applications across multiple regions and clouds.
-
Proven Scalability: Nomad is optimistically concurrent, which increases throughput and reduces latency for workloads. Nomad has been proven to scale to clusters of 10K+ nodes in real-world production environments.
-
HashiCorp Ecosystem: Nomad integrates seamlessly with Terraform, Consul, Vault for provisioning, service discovery, and secrets management.
Quick Start
Testing
See Learn: Getting Started for instructions on setting up a local Nomad cluster for non-production use.
Optionally, find Terraform manifests for bringing up a development Nomad cluster on a public cloud in the terraform directory.
Production
See Learn: Nomad Reference Architecture for recommended practices and a reference architecture for production deployments.
Documentation
Full, comprehensive documentation is available on the Nomad website: https://www.nomadproject.io/docs
Guides are available on HashiCorp Learn.
Contributing
See the contributing directory for more developer documentation.