For Agents
Submit, monitor, and cancel containerised batch jobs across managed compute environments and queues, with support for array jobs, dependencies, and Spot-backed scaling.
Install Jentic One Beta
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AWS Batch, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | shStep 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with AWS Batch API.
Register job definitions that describe the container image, vCPU, memory, environment variables, and IAM role for a batch job
Create managed or unmanaged compute environments backed by EC2 Spot, EC2 On-Demand, or Fargate with min/max vCPU bounds
Create job queues that map to one or more compute environments and apply priority and fair-share scheduling policies
GET STARTED
Use for: I need to submit a containerised batch job, Register a new job definition for my pipeline, Create a Fargate-backed compute environment, Submit an array job with 1,000 children
Not supported: Does not orchestrate Kubernetes pods, run interactive notebook sessions, or manage Spark clusters. Use for managed batch container scheduling on EC2 or Fargate only.
AWS Batch runs containerised batch computing workloads at any scale by dynamically provisioning the right amount and type of compute on EC2 or Fargate. The API lets you register job definitions, create compute environments backed by EC2 Spot, On-Demand, or Fargate capacity, define job queues with priority and scheduling policies, submit jobs with array and dependency support, and inspect or cancel jobs as they run. It is well suited to genomics pipelines, financial Monte Carlo, media transcoding, and other parallel container workloads.
Submit jobs, array jobs (up to 10,000 children), and jobs with dependsOn relationships to other jobs
Cancel or terminate running jobs and inspect their exit reason and CloudWatch Logs stream
Define scheduling policies that allocate share between users or tenants on a shared queue
Update compute environments to change capacity bounds, allocation strategies, or instance types
Patterns agents use AWS Batch API for, with concrete tasks.
★ Massively Parallel Array Job
Run a 5,000-task simulation, transcode, or analytics sweep without managing servers. Register a job definition with the container image and vCPU/memory request, then SubmitJob with arrayProperties.size=5000. AWS Batch fans out 5,000 child jobs onto the compute environment, retries failures based on the retry strategy, and writes per-job logs to CloudWatch Logs. Spot capacity keeps the run cheap.
SubmitJob with jobName=monte-carlo-2026-06-09, jobDefinition=monte-carlo:7, jobQueue=hpc-spot, and arrayProperties={size: 5000}, then poll DescribeJobs every 60 seconds until status=SUCCEEDED.
Pipeline with Job Dependencies
Express a multi-stage pipeline (preprocess to analyse to post-process) by chaining jobs with dependsOn relationships. Each stage's SubmitJob call references the prior stage's job ID; AWS Batch holds dependent jobs in PENDING until the parent reaches SUCCEEDED. Suitable for ETL, genomics, and any directed-acyclic workflow that fits inside Batch's scheduler without needing Step Functions.
Submit job preprocess (returns id A), then submit job analyse with dependsOn=[{jobId: A}], then submit post-process with dependsOn=[{jobId: <analyse-id>}], all into queue analytics-prod.
Cost-Optimised Fargate Spot
Run short-lived containerised batch workloads on Fargate Spot to cut compute spend by up to 70 percent. Create a managed compute environment with type=FARGATE_SPOT and a maxvCpus cap, attach it to a job queue, and submit jobs as normal. AWS Batch handles capacity reclaim by re-queuing interrupted jobs on the next available Fargate Spot capacity.
CreateComputeEnvironment with type=MANAGED, computeResources.type=FARGATE_SPOT, maxvCpus=256, and subnets=[subnet-xxx], then CreateJobQueue mapping to it with priority=1.
Agent-Driven Job Operator
Let an agent take a research request such as 'rerun yesterday's failed sequencing batches with double the retry budget' and translate it into AWS Batch operations. The agent calls Jentic to list failed jobs, derive the array indices that need retry, and submit a new array job pointing at those indices. AWS credentials stay in the Jentic vault.
Search Jentic for 'list failed AWS Batch jobs', execute it filtered to jobQueue=hpc-spot and status=FAILED in the last 24 hours, then SubmitJob with the failed indices and retryStrategy.attempts=4.
24 endpoints — aws batch runs containerised batch computing workloads at any scale by dynamically provisioning the right amount and type of compute on ec2 or fargate.
METHOD
PATH
DESCRIPTION
/v1/submitjob
Submit a job, array job, or dependent job
/v1/describejobs
Describe one or more jobs by ID
/v1/listjobs
List jobs in a queue with filters
/v1/canceljob
Cancel a job that is not yet running
/v1/terminatejob
Terminate a running job
/v1/registerjobdefinition
Register a job definition
/v1/createcomputeenvironment
Create a compute environment
/v1/createjobqueue
Create a job queue
/v1/submitjob
Submit a job, array job, or dependent job
/v1/describejobs
Describe one or more jobs by ID
/v1/listjobs
List jobs in a queue with filters
/v1/canceljob
Cancel a job that is not yet running
/v1/terminatejob
Terminate a running job
Three things that make agents converge on Jentic-routed access.
Credential isolation
AWS access key ID and secret access key for AWS Batch are stored encrypted in the Jentic vault. Agents receive scoped, short-lived signing credentials and the raw IAM secrets never enter the agent context. Jentic computes the AWS Signature Version 4 signature server-side for every request.
Intent-based discovery
Agents search Jentic by intent (for example, 'submit a batch job') and Jentic returns matching AWS Batch operations with their input schemas, the correct AWS service endpoint, and the required IAM action, so the agent can invoke the right call without crawling the AWS docs.
Time to first call
Direct AWS Batch integration: 1-3 days for AWS SDK setup, IAM role configuration, Sigv4 signing, and error handling. Through Jentic: under 1 hour, search, load schema, execute.
Alternatives and complements available in the Jentic catalogue.
Specific to using AWS Batch API through Jentic.
What authentication does the AWS Batch API use?
All requests are signed with AWS Signature Version 4 using an AWS access key ID and secret access key. Through Jentic, the credentials live encrypted in the vault and Jentic performs the signing server-side, so the agent never sees the raw secret.
Can AWS Batch run jobs on Fargate instead of EC2?
Yes. Create a managed compute environment with computeResources.type=FARGATE or FARGATE_SPOT and AWS Batch will run jobs as Fargate tasks instead of EC2 instances. Fargate is well suited to short-lived jobs that need fast start times without the EC2 instance bootstrap delay.
How do I submit a 1,000-task array job through Jentic?
Search Jentic for 'submit an AWS Batch job', load the SubmitJob schema, and execute it with arrayProperties={size: 1000}. The operation maps to POST /v1/submitjob. Jentic returns the parent job ID; each child carries an index in AWS_BATCH_JOB_ARRAY_INDEX so the container can fetch its work shard.
What are the rate limits for the AWS Batch API?
Standard AWS service throttling applies; high SubmitJob rates can return ThrottlingException. AWS recommends batching submissions through array jobs (up to 10,000 children per call) rather than calling SubmitJob in tight loops.
Can I express job dependencies in AWS Batch?
Yes. Pass dependsOn=[{jobId: <parent-id>}] when calling SubmitJob and the new job stays PENDING until the parent reaches SUCCEEDED. This supports linear pipelines and small DAGs natively without needing AWS Step Functions.
Is AWS Batch free to use?
AWS Batch itself has no separate charge. You pay only for the EC2 or Fargate compute, the EBS or ephemeral storage, and the CloudWatch Logs the jobs consume.
/v1/registerjobdefinition
Register a job definition
/v1/createcomputeenvironment
Create a compute environment
/v1/createjobqueue
Create a job queue