Estimate SQS requests (from messages and retries)

SQS pricing is usually request-driven, so the key input is requests per month. The mistake is to treat “one message” as “one request”. A typical successful message flow is already multiple requests (send, receive, delete), and retries or poison loops can multiply it quickly. This guide gives you a model you can validate with real metrics.

Step 1: estimate messages per month

  • From steady rate: messages/month ≈ messages/sec × 2,592,000 (30-day month)
  • From business events: orders/jobs/events per month × messages per event
  • From upstream: if SNS publishes to SQS, publish volume can approximate queue ingress

Helper: SQS request volume estimator (for steady producers)

Step 2: model baseline requests per successful message

A simple baseline for a successful message:

  • Send: 1 request
  • Receive: 1 request
  • Delete: 1 request
  • Baseline: 3 requests per successful message

Step 3: add the multipliers (where bills blow up)

  • Retries: every retry adds extra receives (and often deletes/visibility changes).
  • Visibility extensions: long processing can trigger ChangeMessageVisibility calls.
  • Empty receives: aggressive polling can generate receive calls even when the queue is empty.
  • Poison loops: bad messages repeatedly reprocessed until DLQ threshold (many receives).

If you’re seeing spikes, start by checking retry rate and poison message behavior before assuming “pricing changed”.

Step 4: compute total monthly requests

  • Total requests/month ≈ messages/month × requests per message
  • Keep two scenarios: baseline and incident (higher retry/poison rate)

Worked examples (structure)

  • Baseline: 100M messages/month × 3 requests/message = 300M requests/month
  • Incident: +20% retry → +0.2 extra receives/message → 320M requests/month
  • Polling tax: 50M empty receives/month adds 50M requests even with zero extra messages

Turn requests into cost

Use AWS SQS cost calculator with your request volume and pricing assumptions.

Related calculators

SQS request volume estimator AWS SQS cost calculator

How to validate with metrics

  • Use a representative week of CloudWatch: NumberOfMessagesSent/Received/Deleted.
  • Compute requests/message = (sent + received + deleted + visibility changes + empty receives) / sent.
  • Use that “real” requests/message number for budgeting and optimization.

Common pitfalls

  • Counting messages but forgetting each successful message is multiple requests.
  • Ignoring empty receives from polling (quiet but expensive at scale).
  • Assuming retries are rare (incidents can dominate monthly variance).
  • Not using a DLQ policy; poison messages loop forever.
  • Budgeting from peak rate for the whole month instead of average + peak scenario.

Related guides

SQS cost optimization SQS pricing Request-based pricing Messaging cost hub

Sources

Related guides

AWS SQS cost optimization (high-leverage fixes)
A practical playbook to reduce SQS costs: reduce requests per successful message with batching and long polling, prevent retry storms and poison loops, and validate savings with sent/received/deleted metrics.
AWS SQS pricing (what to include)
A practical checklist for estimating SQS costs: requests, retries, Receive/Delete patterns, and the common pitfalls that inflate spend.
SQS vs SNS cost: how to compare messaging unit economics
Compare SQS vs SNS cost with a practical checklist: request types, retries, fan-out, payload transfer, and the usage patterns that decide the bill.
SNS pricing: what to model (publishes, deliveries, fan-out)
A practical SNS pricing checklist: publish requests, delivery requests by protocol mix, fan-out after filter policies, and the retry/alert-storm patterns that create surprise delivery volume.
API Gateway cost optimization: reduce requests, bytes, and log spend
A practical playbook to reduce API Gateway spend: identify the dominant driver (requests, transfer, or logs), then apply high-leverage fixes with a validation checklist.
API Gateway pricing: what to model (requests + transfer)
A practical API Gateway pricing checklist: request charges, data transfer, and the add-ons that can show up on the bill.

Related calculators

RPS to Monthly Requests Calculator
Estimate monthly request volume from RPS, hours/day, and utilization.
API Request Cost Calculator
Estimate request-based charges from monthly requests and $ per million.
CDN Request Cost Calculator
Estimate CDN request fees from monthly requests and $ per 10k/1M pricing.

FAQ

What's a good default for requests per message?
Start with 3 (Send + Receive + Delete) for a successful flow. Increase it if you have retries, visibility extensions, empty receives from polling, or DLQ reprocessing loops.
How do retries impact requests?
Retries add more receives and deletes (and often visibility changes). Even a small retry percentage at high volume can materially change total requests.
Why do SQS bills spike during incidents?
Poison messages, consumer failures, and retry storms multiply receives and deletes. Aggressive polling can also create lots of empty receives.
How do I validate the estimate?
Compare against CloudWatch metrics for NumberOfMessagesSent/Received/Deleted for a representative week, then compute requests per successful message and use that for budgeting.
Last updated: 2026-01-27