Comments (7)
I've just pushed the CLI changes to adding support for nextstrain build --aws-batch
: https://github.com/nextstrain/cli/compare/aws-batch.
I would appreciate any review of the code and especially the user interaction/experience. Until I complete some of the ancillary items on the todo list above, it will only work if you have admin access to the lab's AWS account (this means @trvrb and maybe @jameshadfield for now). I will leave another comment when I've arranged wider access so more folks can test if they want, hopefully tomorrow or sometime soon this week.
Note that the remote jobs are currently using the nextstrain/base:branch-aws-batch
image from the aws-branch
of docker-base
: https://github.com/nextstrain/docker-base/compare/aws-batch. Relevant entrypoint code is there.
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Folks in our lab should now be able to try this out more widely.
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Re: compute limits: In our current AWS Batch configuration, each job defaults to 2 vCPUs with 4GB of memory and will be terminated if it does not complete in 4 hours. These are adjustable on a per-job basis, but the cli itself does not change the defaults. (Though an authorized user could.) The Batch compute environment (i.e. managed pool of EC2 instances) is limited to no more than 256 combined vCPUs. Instances are automatically provisioned, including down to zero instances (no cost) running if there are no jobs in the queue.
We should keep an eye on Batch usage and Batch-driven costs to make sure this is functioning as we expect. Only @trvrb (or someone else with access to Billing details) can do this.
If we start submitting large jobs, we should consider increasing the default job resources.
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Re: cost tracking: @trvrb these may be of interest:
https://aws.amazon.com/aws-cost-management/aws-cost-explorer/
https://aws.amazon.com/aws-cost-management/aws-cost-and-usage-reporting/
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Documentation is now at https://github.com/nextstrain/cli/blob/aws-batch/doc/aws-batch.md.
That URL (well, the URL for master
not aws-batch
) is referenced from the output of nextstrain build --help-all
under the AWS Batch section.
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I've bumped the default job resources to 8 vCPUs and (just under) 16GiB of memory, which should cost about 34ยข/hour on a c5.2xlarge. Combined with my augur PR to auto-scale alignment and tree-building parallelism, this should make larger builds run much quicker.
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Merged and released as 1.7.0.
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Related Issues (20)
- CI fails due to change in Python 3.6 deprecation warning from cryptography HOT 1
- Windows: Snakemake arguments with file paths containing backslashes produce file not found errors
- ENH: Print docker image used at beginning of aws-batch jobs HOT 2
- When using `--aws-batch`, the `--image` argument is ignored HOT 2
- BUG: `nextstrain update conda` doesn't seem to update to latest available conda-base HOT 18
- Confusing log message "runtime updated" when nothing was changed HOT 3
- `nextstrain update singularity` throws error about OCI indexes with Singularity 2.6 and 3.5.3 HOT 13
- Add command to self-upgrade HOT 3
- Auto-trigger Docker and Conda runtime builds on CLI releases
- `Your request was too big` error on stock RSV repo build via aws-batch HOT 7
- [build] `--cpus` isn't passed to thru when using `--exec` HOT 5
- Read-only filesystem errors from Snakemake in Singularity runtime HOT 2
- Installation fails when there is a space in the path HOT 1
- Docker runner assumes the Docker Hub (docker.io) registry HOT 4
- ENH: Detect and warn user if their environment deviates from nextstrain-base HOT 1
- Pyright failures with 1.1.309
- `nextstrain update conda` in 7.0.0 can error with "Invalid version" HOT 13
- Improve runtime documentation HOT 1
- pyparsing 3.1.0 causing test failures in Markdown image inlining HOT 4
- [batch] ZIP archive of build dir is stored without compression HOT 1
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