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CloudCloudWatch Metric Streams + IAM

AWS SQS Integration

Queue depth, message age, DLQ monitoring, and processing rate visibility for Amazon SQS. AI consumer lag analysis correlates queue accumulation with Lambda throttles, ECS task counts, and consumer CPU saturation.

Setup

How It Works

01

Deploy CloudFormation Stack

Launch the TigerOps CloudFormation template to configure Metric Streams for the AWS/SQS namespace and grant the necessary IAM read permissions for queue metadata.

02

Auto-Discover Queues

TigerOps uses the SQS ListQueues API to enumerate all queues in your account. Tag-based filtering lets you scope monitoring to production queues and exclude development queues.

03

Link DLQs to Source Queues

TigerOps reads each queue's RedrivePolicy to map DLQs to their source queues. When a DLQ starts accumulating messages, the alert is enriched with the source queue name and consumer service.

04

Set Queue SLA Alerts

Configure message age and queue depth thresholds per queue. TigerOps computes the current processing rate and projects when the queue will exceed your SLA based on the trend.

Capabilities

What You Get Out of the Box

Queue Depth Tracking

ApproximateNumberOfMessagesVisible tracked per queue with historical trend charts. TigerOps alerts when queue depth exceeds thresholds and predicts breach time based on the accumulation rate.

Message Age Monitoring

ApproximateAgeOfOldestMessage per queue — the most critical SQS SLO metric. TigerOps alerts when the oldest message age approaches your SLA deadline.

DLQ Visibility

Dead letter queue depth monitored alongside source queue metrics. TigerOps alerts immediately on first DLQ message arrival and tracks the DLQ fill rate to prioritise reprocessing urgency.

Processing Rate Analysis

NumberOfMessagesSent vs. NumberOfMessagesDeleted rates show queue throughput and consumer pace. TigerOps detects when consumers fall behind producers and estimates time to queue drain.

FIFO Queue Monitoring

SQS FIFO queue metrics including NumberOfMessageGroupsWithInflightMessages and per-MessageGroupId depth visibility. TigerOps identifies hot message groups causing processing bottlenecks.

AI Consumer Lag Analysis

When SQS queue depth grows, TigerOps AI correlates the accumulation with consumer Lambda throttle rates, ECS task counts, and EC2 CPU saturation to identify the processing bottleneck.

Configuration

SQS Queue Monitoring Setup

Deploy the TigerOps SQS integration and configure per-queue alert thresholds.

sqs-setup.sh
# Deploy TigerOps SQS monitoring stack
aws cloudformation deploy \
  --template-url https://tigerops-cfn.s3.amazonaws.com/sqs-integration.yaml \
  --stack-name tigerops-sqs \
  --capabilities CAPABILITY_IAM \
  --parameter-overrides \
    TigerOpsApiKey=${TIGEROPS_API_KEY} \
    QueueTagKey=Environment \
    QueueTagValue=production

# Tag your SQS queues for auto-discovery
aws sqs tag-queue \
  --queue-url https://sqs.us-east-1.amazonaws.com/123456789/orders-queue \
  --tags Environment=production,Team=payments,Service=order-processor

# Set DLQ for source queue monitoring
aws sqs set-queue-attributes \
  --queue-url https://sqs.us-east-1.amazonaws.com/123456789/orders-queue \
  --attributes '{
    "RedrivePolicy": "{"deadLetterTargetArn":"arn:aws:sqs:us-east-1:123456789:orders-dlq","maxReceiveCount":"3"}"
  }'

# tigerops-sqs-alerts.yaml — alert thresholds per queue
alerts:
  - queueNamePattern: "orders-*"
    messageAgeWarningSeconds: 300    # 5 minutes
    messageAgeCriticalSeconds: 900   # 15 minutes
    queueDepthWarning: 1000
    queueDepthCritical: 10000
    dlqAnyMessageAlert: true         # alert on first DLQ message
FAQ

Common Questions

What is the most important SQS metric to alert on?

ApproximateAgeOfOldestMessage is usually the most critical — it tells you how long the oldest message has been waiting. TigerOps alerts on this metric relative to your processing SLA rather than just queue depth, which can be misleading for high-throughput queues.

How does TigerOps detect when a DLQ starts receiving messages?

TigerOps monitors the ApproximateNumberOfMessagesVisible metric for every DLQ in your account. It alerts on the first non-zero reading (any message in DLQ) and includes the source queue name and the most recent consumer Lambda error from CloudWatch Logs.

Can TigerOps monitor SQS FIFO queues?

Yes. TigerOps supports both standard and FIFO SQS queues. For FIFO queues it monitors the standard metrics plus NumberOfMessageGroupsWithInflightMessages to surface message group bottlenecks.

How does TigerOps correlate SQS queue depth with Lambda consumer metrics?

TigerOps automatically discovers Lambda functions that have SQS event source mappings and links their invocation rate, throttle count, and error rate to the corresponding queue. A queue depth spike with simultaneous Lambda throttles is surfaced as a single correlated incident.

Does TigerOps support monitoring SQS queues across multiple AWS accounts?

Yes. Deploy the TigerOps CloudFormation stack in each AWS account and all queue metrics are aggregated into a unified dashboard. Cross-account DLQ relationships are also resolved so you can trace a message failure across account boundaries.

Get Started

Know When Your Queues Are Falling Behind

Message age alerts, DLQ monitoring, and AI consumer lag analysis. Connect your SQS queues in minutes.