Every SaaS launch has the same failure modes. Auth callbacks pointing at localhost. Stripe webhooks using test-mode secrets. Transactional emails blocked by missing SPF records. DNS propagation not complete. Rate limits set to development defaults. The difference between a smooth launch and a fire drill is whether you verified these before or after real users arrived.
Authentication and authorization
Verify OAuth redirect URIs point at production. Confirm password reset emails deliver and the reset link resolves. Check that session tokens have appropriate expiration. Ensure protected routes reject unauthenticated requests with proper status codes, not silent redirects to broken pages.
Payments and billing
Use restricted Stripe keys with minimum permissions. Verify webhook delivery with signature validation. Test the full checkout loop including the database side effect. Confirm success and cancel URLs resolve on the production domain. Check that subscription lifecycle events (upgrade, downgrade, cancel) update entitlements correctly.
Transactional email and SMS
Send a real email from the production domain and verify it lands in the inbox, not spam. Check SPF, DKIM, and DMARC records are published and aligned. Verify your sending domain is not on any blocklist. For SMS, confirm the provider account is active and the phone number is verified for the target region.
Database and backups
Confirm your production database is not paused (Supabase pauses inactive projects). Verify your backup schedule is active and recent. Run an integrity drill to confirm the database is intact and readable. Check that migrations are in sync between your codebase and the deployed schema.
API security
Enable rate limiting on all public endpoints. Validate and sanitize all user input. Set CORS to allow only your production origins. Return appropriate error codes without leaking stack traces. Rotate any keys that were exposed during development.
Infrastructure and DNS
Verify DNS records are propagated. Confirm SSL certificates are valid and not expiring within 30 days. Check that your CDN is caching static assets correctly. Verify environment variables match between staging and production. Confirm deploy rollback is possible if the launch fails.
Monitoring and alerting
Set up uptime monitoring before launch, not after. Configure alert channels (Slack, Discord, email) and verify delivery. Enable error tracking with enough context to diagnose failures. Plan for the first 24 hours with denser sampling and lower alert thresholds.
Automate the checklist
PreFlight turns this entire checklist into automated probes. Connect your providers, run a check, and get a scored report showing exactly what passed, what failed, and what to fix. No manual verification needed — the system probes your live stack and tells you the truth.
Expanded field note
A current SaaS launch checklist: the practical answer
launch readiness spans product behavior, integrations, security, discoverability, and recovery. This guide is for founders and small product teams. Start by naming the failure you want to prevent and the customer or operator who would notice it first.
The useful scope is whether the release can acquire, convert, serve, and recover customers. That keeps the work concrete: you can choose a URL, provider, route, release, or data operation, observe it, and decide what to do when the observation does not match the expected contract.
What good looks like
a release baseline with critical paths, owners, and timestamps. A result is stronger when it preserves the input, environment, timestamp, expected behavior, observed behavior, and the next action. This lets a different person reproduce the finding without asking the original operator to reconstruct the entire context from memory.
a checklist only matters when it changes a release decision or creates a follow-up owner. Keep the scope visible when sharing the result. A passing outside-in check can prove a reachable behavior at a point in time; it cannot silently become a guarantee about private code, every authenticated role, or every provider failure mode.
Frame the decision before you change anything
founders and small product teams usually do not need another dashboard full of disconnected warnings. They need a defensible answer to a narrower question: is the behavior that matters to the customer working in the environment that is about to change? Start there. If the answer is unclear, make the ambiguity part of the work instead of translating it into a green score.
The first useful boundary is whether the release can acquire, convert, serve, and recover customers. Write it down in the same language the team will use during the fix. Name the route, provider, release, role, data object, or browser action involved. Then write the expected behavior as a sentence that could be checked by another person. This turns a broad topic into a small contract and makes it easier to tell whether a failure is reproducible, transient, out of scope, or genuinely fixed.
A good scope also includes what the check does not attempt. Public observation is different from authenticated authorization testing. Provider reachability is different from a complete fulfillment path. A page that renders in a browser is not necessarily a page a crawler can index. Stating the limit early protects the reader from overconfidence and tells the operator when to add a deeper review.
Questions the result should answer
- What was tested? Identify the canonical URL, route, provider, account role, release, or customer action rather than describing the scope as “the site.”
- What should have happened? State the expected response, permission, side effect, delivery event, page directive, or recovery signal in plain language.
- What actually happened? Keep the observed status, safe error, response detail, timing context, or missing side effect without pasting credentials or customer data into the record.
- Why does it matter? Connect the observation to a customer, crawler, revenue, security, availability, or release decision so severity is not just a color.
- What happens next? Name the smallest reversible fix, the owner, the rerun, and the condition that will close the issue.
These questions are deliberately boring. Boring evidence is easier to compare, easier to hand off, and easier to defend later. It also gives an answer engine or a future teammate enough context to summarize the result without inventing a claim that the original check never made.
A sequence that holds up under pressure
- Map acquisition, signup, activation, payment, fulfillment, and support.
- Check public security and indexability before connecting private providers.
- Run one representative browser journey.
- Verify payment and webhook side effects in test mode.
- Set a first-day monitoring and incident rule.
The important nuance is this: a checklist only matters when it changes a release decision or creates a follow-up owner. That distinction matters because fast remediation can create a second problem: a broad header change can break a payment script, a credential rotation can break a cron worker, and a restrictive policy can make a valid customer path look like an outage.
Evidence to keep with the fix
| Record | Why it matters |
|---|---|
| Scope | The URL, role, provider, release, and limitation prevent a result from being reused outside the question it actually answered. |
| Before | The original failing observation, environment, and customer impact make the fix auditable. |
| Change | The code, configuration, provider setting, migration, or credential action that should alter the result. |
| After | A rerun against the same scope proves whether the intended behavior recovered. |
| Owner | A named person or team, an expected next action, and a review date keep the result from becoming an orphaned warning. |
| Follow-up | An owner, cadence, or release rule keeps the same class of failure from returning silently. |
Failure modes worth checking twice
- The checklist is a long unordered inventory.
- The owner cannot reproduce a failed item.
- The team optimizes the marketing page while the paid path remains untested.
- The launch is considered done before the first recovery signal exists.
When one of these appears, avoid making several unrelated changes at once. Preserve the failing evidence, isolate the smallest boundary that can explain it, make one reversible correction, and rerun. That rhythm is slower than guessing for the first five minutes and faster than untangling a release that changed three providers at once.
Know when the first layer is not enough
Automation is valuable because it is repeatable, but repeatability is not the same as depth. If the question involves complex authorization, tenant isolation, injection, business logic, a high-value asset, or an adversarial threat model, use the automated result as a map for a deeper review. Give the reviewer the scope, failed observation, relevant release context, and the boundary you want tested. Do not present a public scan as a certification or a substitute for professional security work.
The same rule applies to operations. A successful provider probe may prove that a credential can reach an API, but it may not prove that a webhook creates the correct entitlement. A healthy uptime response may prove reachability, but it may not prove that a signed-in customer can complete the task. Add the assertion or browser journey that matches the real risk, and keep the cheap signal for early warning.
Questions people ask after reading this
What is the fastest useful first step?
Choose one representative scope and write the expected result before running the tool. For this topic, that means whether the release can acquire, convert, serve, and recover customers. A small, explicit baseline is more useful than a large scan whose findings have no owner or decision attached.
What should I do when the result is green?
Keep the scope, timestamp, and limitation, then decide whether the result belongs in a release gate, monitor, report, or follow-up review. Green means the observed contract passed. It does not turn untested behavior into evidence.
What should I do when the result is red?
Read the evidence before changing configuration. Confirm the environment, reproduce the smallest failing behavior, assign the next action, and rerun after the fix. If the issue requires credentials, source access, or adversarial judgment, escalate it rather than hiding the gap behind a retry.
After the fix ships
Run the same check on the canonical production surface, not only on a local or preview environment. If the issue involved a provider, wait for the real callback or scheduled sample. If it involved search, confirm the HTML, canonical, robots, sitemap, and internal links agree. If it involved payments or access, verify the side effect a customer receives rather than stopping at a browser redirect.
PreFlight is designed for this last step: keep the original observation, connect the relevant provider or journey, attach the release context, and let the next run show whether the system stayed healthy. The goal is not a bigger report. It is a shorter path from signal to a verified decision.