SES cost optimization (reduce volume, retries, and payload)

SES costs usually scale with emails sent. The best savings come from preventing unnecessary sends and controlling the multipliers: duplicates, retries, and alert storms. This playbook focuses on high-leverage changes that cut spend while protecting deliverability.

SES cost levers

  • Reduce volume: suppress bounces and duplicates.
  • Payload size: compress content and limit attachments.
  • Retries: fix auth and reputation to lower retries.

Step 0: baseline what you’re sending

  • Emails/day by type: transactional vs marketing vs notifications
  • Duplicate/resend rate (how many sends are “not new information”)
  • Incident spikes: identify the top 1–2 events that trigger alert storms
  • Non-prod volume (dev/stage often produces surprising sends)

If you don’t have a baseline yet: estimate email volume

1) Reduce volume by design (batch, digest, and preference controls)

  • Digest notifications: daily/weekly summaries instead of per-event blasts.
  • Preference center: let users opt out of low-value notifications.
  • Batch admin alerts: group events by incident window, not per event.
  • Suppress redundant events: avoid “state changed” loops that email repeatedly.

2) Prevent duplicates (idempotency is a cost control)

  • Use an idempotency key per logical email (user + template + event id).
  • Store send state (sent/pending) to prevent races from creating duplicates.
  • Deduplicate at the queue/job level so retries don’t become extra sends.

3) Control retries (retry storms are both reliability and cost incidents)

  • Use exponential backoff with jitter and a clear max retry limit.
  • Stop retrying when the root cause is persistent (circuit breaker / fail-fast).
  • Separate “send” failures from “template rendering” failures; fix the latter first.

4) Reduce non-prod waste

  • Route dev/stage emails to a sink mailbox or disable external sends entirely.
  • Use smaller test recipient sets and avoid marketing-scale campaigns in staging.
  • Schedule test workloads so they don’t run 730 hours/month.

5) Reduce payload when it matters

  • Prefer links to downloads instead of attachments.
  • Keep templates lean; avoid embedding large images inline.
  • Remove duplicated JSON blobs and debug metadata from templates.

Helper: units converter (for size modeling)

Validate improvements (protect deliverability)

  • Sends/day and sends/user (did volume actually drop?)
  • Duplicate/resend rate (did idempotency stop duplicates?)
  • Bounce and complaint rates (deliverability must remain healthy)
  • Incident behavior: do alert storms stay bounded now?

Tools and next steps

SES cost calculator SES pricing Reduce logging costs Cost checklist

Sources

Related guides

CloudTrail cost optimization (reduce high-volume drivers)
A practical playbook to reduce CloudTrail costs: measure event volume, control data event scope with selectors, reduce automated churn, and avoid downstream storage/query waste.
KMS cost optimization (reduce request volume safely)
A practical AWS KMS cost optimization checklist focused on the real driver: request volume. Learn where KMS calls come from, how to reduce them safely with caching and batching, and how to validate savings.
Route 53 cost optimization (reduce query volume and zone sprawl)
A practical playbook to reduce Route 53 costs: reduce DNS query volume, fix low TTL defaults, and avoid hosted zone sprawl across environments. Includes validation steps and related tools.
SES pricing: what to model (send volume + payload size)
A practical AWS SES pricing checklist: emails sent, optional payload/attachment size assumptions, and the operational patterns (retries, alert storms, duplicates) that create surprise spend.
SNS cost optimization (reduce deliveries and retries)
A high-leverage playbook to reduce SNS costs: reduce fan-out (deliveries), reduce delivery retries by fixing endpoints, and prevent alert storms with dedupe and rate limits — with a validation plan.
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.

Related calculators

Data Egress Cost Calculator
Estimate monthly egress spend from GB transferred and $/GB pricing.
API Response Size Transfer Calculator
Estimate monthly transfer from request volume and average response size.
VPC Data Transfer Cost Calculator
Estimate data transfer spend from GB/month and $/GB assumptions.
Cross-region Transfer Cost Calculator
Estimate monthly cross-region transfer cost from GB transferred and $/GB pricing.
Log Cost Calculator
Estimate total log costs: ingestion, storage, and scan/search.
Log Ingestion Cost Calculator
Estimate monthly log ingestion cost from GB/day or from event rate and $/GB pricing.

FAQ

What's the biggest lever to reduce SES cost?
Reduce send volume and prevent duplicates. Most SES spend is linear in email count, so avoiding unnecessary sends and retries is highest impact.
How do I prevent incident-driven cost spikes?
Dedupe and rate-limit notifications, fix retry loops, and add circuit breakers so failures don't trigger repeated sends.
Do payload size and attachments matter?
They can. If you send large templates or attachments, prefer links to downloads and reduce template bloat. Include payload size in the model only when it’s a meaningful driver.
How do I validate improvements safely?
Track sends/day, retry rate, bounce/complaint rates, and deliverability before/after. Validate that volume reductions don’t remove critical notifications.
Last updated: 2026-02-07