Container Orchestrator for Batch & Cron Jobs
Seamlessly execute scheduled tasks and asynchronous workloads. Daestro let's you run your batch jobs and cron jobs across any cloud or self-hosted hardware.
Job Submit API
curl --request POST
--url https://api.daestro.com/v1/client/job/submit
--header 'authorization: Bearer your_api_key_here'
--header 'content-type: application/json'
--data '{
"job_definition": "my-project::hello-world:1",
"job_queue": "my-project::first-job-queue",
"container_cmd": ["python", "main.py"]
}'
Self-hosted Compute
docker run --name daestro-agent
-e DAESTRO_AUTH_TOKEN="<token>"
-v /var/run/docker.sock:/var/run/docker.sock
-v daestro_agent_data:/var/lib/daestro-agent
--network host
daestro/daestro-agent:latest
Run your batch jobs on any cloud provider and on your own account.
Daestro let's you run jobs on your own servers. Be it your laptop or enterprise servers.
Monitor your jobs in real time with logs and metrics.
Optimize your costs by running your jobs on the cloud providers that are cost effective for your needs.
Set fine grained controls on concurrency, priority and resource usage for your jobs.
Use job queues to make sure high priority jobs get processed first.
Run recurring jobs on specified time.
Schedule jobs to run at later time or date.
Set custom CPU and Memory quota per job definition
How to deploy a workload on Daestro
Deploying a workload on Daestro is a simple process that can be completed in just a few steps.
Cloud Auth
Cloud Auths are the credentials for accessing cloud providers.
Compute Environment
Compute Environments define the compute type and location for jobs.
Job Queue
Job Queues define how and when jobs are executed. They can be used to manage the concurrency and priority of jobs.
Job Definition
Job Definitions are the blueprint for creating jobs. They define the job's behavior and parameters.
Jobs
A runnable instance of the Job definition.
Steps
Cloud Auth: Add your cloud provider credentials (api keys / auth tokens) to Daestro.
Compute Environment: Create a compute environment to run your workload.
Job Queue: Create a job queue and add compute environment to run jobs on.
Job Definition: Create a job definition which describes how a workload should be executed using a docker image.
Run Jobs: You can now run your workload by submitting a job to the job queue with the job definition. You can use either Job Submit form or API.
Comparing With Other Solutions
Other Solutions
- Vendor lock-in
- Setup varies for each cloud provider
- No on-prem option
- Locked into their infrastructure
- Limited by the services they offer
Compute Workloads with Daestro
- Run your jobs on any cloud provider
- Easy and intuitive setup process
- Run it on your own infrastructure
- Run jobs on most suitable infrastructure for your job type
- Scale up and down as needed
Frequently asked questions
Checkout all the FAQs here