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First Production Integration Checklist

SendPromptly Team
5 min read

Introduction

Getting a test event to work is the easy part. Production is about reducing unknowns:

  • isolating environments (keys, templates, data)
  • preventing duplicates under retries/timeouts
  • validating template payloads before deploy
  • securing inbound webhooks (signature + replay defense)
  • proving you can detect, stop, and recover from failures

This checklist is designed for your first production rollout of SendPromptly. Assume you already have a dev integration working. Now you’re hardening behavior under retries, partial outages, deploys, and real traffic.

0) “Stop-the-bleeding” baseline (do this first)

Before you ship, make sure you can answer these in < 2 minutes:

  1. Where do I see failures? (delivery logs / attempt status)
  2. How do I stop new failures? (pause a project/channel, feature flag, rollback)
  3. How do I recover safely? (fix root cause → replay)
  4. How do I prove it’s fixed? (green deliveries + stable failure rate)

If you don’t have those answers, production incidents turn into guesswork.

1) Create environments and tokens

Treat environments as isolation boundaries, not convenience.

Checklist

  • Create separate environments: dev, stage, prod
  • Generate distinct API tokens per environment
  • Never reuse production tokens in lower environments
  • Store tokens in a secrets manager or CI secrets (not in source control)

Practical rules

  • Name tokens by purpose: prod-app, prod-ci, stage-ci
  • Rotate deliberately: track which deploy/service is on which token
  • Make staging capable of full E2E without touching prod data

Sanity check Your staging should run: event accepted → delivery runs → webhook callback → logs with zero production dependencies.

2) Require idempotency on every send

Retries are normal. Duplicates are optional.

Your app should attach an idempotency key to every business action that triggers messaging. The key should be:

  • stable for the business action
  • deterministic (recomputable)
  • unique enough to avoid collisions

Good keys

  • invoice:123:created:v1
  • order:555:status:shipped
  • user:9981:welcome_email:v2

Bad keys

  • random UUID generated per attempt (every retry becomes “new”)
  • timestamp-only keys (collisions under concurrency)
  • keys based on mutable fields (email/name/status) without a stable identifier

Make it mandatory

  • require idempotency in your internal sendNotification(...) boundary
  • add a test/lint rule that fails builds for missing keys in critical flows
  • log idempotency keys so they’re searchable during incidents

Why this matters Timeouts, queue retries, “retry on 5xx,” and deploy turbulence will eventually happen. Idempotency turns those from “double-send disasters” into “safe retries.”

3) Validate template context before deploy (CI, not production)

Most messaging incidents are boring:

  • a renamed field breaks rendering
  • one edge case missing subscriber.name
  • a template version ships without coverage

SendPromptly failing fast on missing placeholders is good — as long as it fails in CI or staging.

Template test harness checklist

  • Maintain golden payload fixtures per event type:
    • happy path
    • missing optional fields
    • known real-world variants
  • In CI/staging, render templates against fixtures and assert:
    • placeholders resolve
    • conditionals behave
    • formatting looks right (dates/currency)

Safe rollout pattern

  1. Add new fields to payload contract
  2. Deploy app changes
  3. Update templates to use fields
  4. Roll back safely if needed

Rule of thumb Never “edit live” without:

  • a versioning plan
  • a rollback plan
  • test fixtures that cover the change

4) Secure inbound webhooks (signature + replay safety)

If you consume SendPromptly webhooks (delivery results, events, etc.), treat them as an inbound attack surface.

Minimum controls

  • Verify X-SP-Signature using your shared secret
  • Validate X-SP-Timestamp and reject out-of-window requests (skew tolerance)
  • Use constant-time comparison
  • Reject missing/empty required headers
  • Require HTTPS

Replay safety Even valid webhooks can be replayed (or legitimately retried). Protect your consumer:

  • derive or use an event ID/fingerprint
  • store processed IDs for a retention window
  • make webhook handling idempotent

Operational rule Don’t return 200 if you didn’t process it. “Accept-and-drop” hides outages and creates silent data loss.

5) Define retry behavior and failure boundaries

You need two retry layers to behave predictably:

  1. Delivery retries (SendPromptly attempting a destination)
  2. Consumer retries (your app processing inbound webhook payloads)

Checklist

  • Decide which failures are retryable vs permanent
  • Make response codes intentional:
    • 2xx: accepted and processed (or queued safely)
    • 4xx: permanent failure (usually don’t retry)
    • 5xx: transient failure (usually retry)
  • Use a queue boundary for slow work:
    • acknowledge quickly
    • process asynchronously

Anti-pattern Blocking webhook requests while doing heavy DB/API work → timeouts → retry storms → duplicates.

6) Observability: monitor what matters (and alert on it)

Monitoring isn’t dashboards — it’s knowing what you’ll do next.

Track at minimum

  • delivery success rate over time
  • failure rate by channel
  • top failure reasons (auth, timeouts, template rendering, 4xx/5xx)
  • retry volume and retry exhaustion
  • queue depth / job latency (if you enqueue)

Define thresholds

  • “Failure rate > 2% for 10 minutes → alert”
  • “Retries spike 5x baseline → alert”
  • “Webhook consumer latency > N seconds → alert”

Incident actions you should pre-define

  • pause sending (project/env)
  • disable a channel temporarily
  • roll back a template version
  • roll back an app deploy
  • replay only after root cause is fixed

7) Load-test the integration path you actually use

You don’t need enterprise load testing for your first rollout, but you do need proof your system behaves under bursts and failures.

Staging tests

  • burst: 500–5,000 events near peak pattern
  • controlled failure: force timeouts / 5xx to verify retries + idempotency
  • deploy mid-stream: confirm no duplicates and no drops

Validate

  • user-facing requests aren’t blocked on messaging
  • backpressure exists (queueing, rate limits, circuit breakers)
  • delivery logs remain usable under load

8) Production cutover plan (avoid “big bang”)

Safer patterns

  • Shadow mode: send to prod, but route to a safe destination or disable final channel
  • Canary rollout: enable for a small % of users/tenants first
  • Feature flag: deploy code with sending disabled, enable after verification

Before flipping

  • prod tokens correct
  • webhook verification enabled
  • monitoring/alerts active
  • templates tested and versioned
  • rollback path rehearsed

After enabling

  • watch success rate + retries for the first hour
  • manually verify one full E2E flow
  • write down surprises immediately

Post-launch hardening (high ROI)

After the first stable rollout:

  • expand fixtures with real-world edge cases
  • improve correlation IDs across your app ↔ SendPromptly logs
  • add a scheduled “integration health” check
  • rotate tokens on a schedule
  • tune alert thresholds based on baseline behavior