Run Compute Workloads Anywhere, Without Limits

Run your compute workloads seamlessly across multiple cloud providers and on-premises infrastructure. Break free from vendor lock-in and optimize costs with our cloud-agnostic platform.

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Daestro provides simple to use Job Submit API to submit a job to Daestro from within your own application. Read more

    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"]
        }'

Multi Cloud

Run your batch jobs on any cloud provider and on your own account.

On-Prem

Run your batch jobs on your own servers. Be it your laptop or enterprise servers.

Monitoring & Logging

Resource monitor and logging your jobs.

Cost Optimization

Optimize your costs by running your jobs on the cloud providers that are cost effective.

Control and Limits

Set fine grained controls on concurrency, priority and resource usage for your jobs.

Job Queues

Use job queues to make sure high priority jobs get processed first.

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.

Docs Get Started

Comparing With Other Solutions

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

Run Compute Workloads Anywhere, Without Limits

How to deploy a workload on Daestro

Steps

Comparing With Other Solutions

Other Solutions

Compute Workloads with Daestro

Frequentlyasked questions

Frequently
asked questions