AWS Batch Integration
Monitor job queue depth, compute environment utilization, and job duration metrics for your AWS Batch workloads. Get AI-powered hung job detection and queue backlog prediction before SLAs are missed.
How It Works
Create IAM Role for Metric Streams
Provision an IAM role with CloudWatch permissions scoped to the AWS/Batch namespace. TigerOps requires this role to deliver Batch metrics via Kinesis Firehose.
Deploy CloudWatch Metric Streams
Run the TigerOps CloudFormation stack to create a Metric Stream for the AWS/Batch namespace. Job queue, compute environment, and job status metrics begin flowing immediately.
Tag Queues and Compute Environments
Apply team and workload tags to your Batch queues and compute environments. TigerOps uses these tags for cost attribution and per-team alert routing.
Configure Queue Depth Alerts
Set thresholds on pending job counts and RUNNABLE job age. TigerOps predicts queue backlog growth and alerts before job SLA deadlines are at risk.
What You Get Out of the Box
Job Queue Depth Monitoring
Pending, runnable, starting, and running job counts per queue. Track queue depth trends over time and receive alerts when backlogs grow beyond expected thresholds.
Compute Environment Utilization
vCPU and memory utilization across managed and unmanaged compute environments. Identify over-provisioned environments and spot underutilized capacity.
Job Duration Metrics
P50, P90, and P99 job duration per job definition. Detect when specific job types are running significantly longer than historical baselines.
Failed Job Analysis
Track job failure rates by job definition, exit code, and failure reason. TigerOps groups failures by reason category to surface systemic issues quickly.
Spot Instance Interruption Tracking
Monitor spot instance reclamation events in your Batch compute environments. Correlate interruption rates with job retry counts and increased queue depth.
AI Job Duration Anomaly Detection
TigerOps establishes per-job-definition duration baselines and alerts when jobs run significantly longer than expected, catching hung jobs before they block queues.
CloudFormation Stack for AWS Batch Metric Streams
Deploy the TigerOps CloudFormation stack to start streaming Batch job and compute metrics in minutes.
# TigerOps CloudFormation — AWS Batch Metric Streams
# aws cloudformation deploy \
# --template-file tigerops-batch-streams.yaml \
# --stack-name tigerops-batch \
# --capabilities CAPABILITY_IAM
Parameters:
TigerOpsApiKey:
Type: String
NoEcho: true
Resources:
TigerOpsBatchStream:
Type: AWS::CloudWatch::MetricStream
Properties:
Name: tigerops-batch-stream
FirehoseArn: !GetAtt TigerOpsDeliveryStream.Arn
RoleArn: !GetAtt MetricStreamRole.Arn
OutputFormat: opentelemetry0.7
IncludeFilters:
- Namespace: AWS/Batch
StatisticsConfigurations:
- AdditionalStatistics:
- p50
- p90
- p99
IncludeMetrics:
- Namespace: AWS/Batch
MetricName: RunningJobCount
- Namespace: AWS/Batch
MetricName: PendingJobCount
TigerOpsDeliveryStream:
Type: AWS::KinesisFirehose::DeliveryStream
Properties:
HttpEndpointDestinationConfiguration:
EndpointConfiguration:
Url: https://ingest.atatus.net/api/v1/cloudwatch
AccessKey: !Ref TigerOpsApiKey
RequestConfiguration:
CommonAttributes:
- AttributeName: service
AttributeValue: batch
RetryOptions:
DurationInSeconds: 60
# Recommended alert thresholds:
# PendingJobCount > 500 (for queue) → Warning
# FailedJobCount rate > 5% rolling 5m → Critical
# RunningJobCount plateau 2h+ → Hung jobs suspectedCommon Questions
Which AWS Batch metrics does TigerOps collect?
TigerOps collects all AWS/Batch CloudWatch metrics including PendingJobCount, RunnableJobCount, StartingJobCount, RunningJobCount, SucceededJobCount, FailedJobCount, CPUUtilization, and MemoryUtilization per job queue and compute environment.
Can TigerOps monitor Batch on EKS (Amazon EKS) workloads?
Yes. AWS Batch on EKS publishes metrics to the AWS/Batch namespace alongside EC2-based compute environments. TigerOps ingests these metrics and allows filtering by compute environment type for EKS versus EC2 comparisons.
How does TigerOps help with Batch job SLA monitoring?
TigerOps allows you to define maximum acceptable RUNNABLE wait times per job queue. When jobs have been waiting longer than the configured SLA threshold, TigerOps fires an alert with the oldest waiting job age and queue depth context.
Can TigerOps track Batch job costs per workload?
Yes. TigerOps correlates Batch job durations with AWS Cost and Usage Report line items tagged to compute environments. You can build cost-per-job-definition dashboards and track compute spend trends over time.
Does TigerOps support Batch Array jobs?
Yes. Array job child job statuses are tracked individually in CloudWatch. TigerOps aggregates array job completion percentages and flags partial failures where a subset of child jobs fail while others succeed.
Stop Missing Batch Job SLAs Because of Silent Queue Backlogs
Queue depth monitoring, compute utilization, and AI hung job detection. Deploy in 5 minutes.