What should you monitor first?
If you're a small team, you don't need 50 monitors. You need 3 that protect revenue and sanity.
A simple prioritisation rule
Monitor in this order:
Journeys tied to revenue
Journeys tied to activation
Journeys tied to support load
By the numbers
Organizations that adopt SRE practices tend to see improved service reliability and incident response through practices like SLIs/SLOs and automation.
Google Cloud, DORA research (as summarized in the DORA reports) (2023)The cost of downtime can reach thousands of dollars per minute for many organizations, depending on scale and industry.
Gartner (widely cited estimate on downtime cost per minute) (2014)A large share of outages are caused by changes (deployments, config, dependency updates), reinforcing the need for monitoring the user journeys most affected by releases.
Google Cloud, DORA / Accelerate research (change-related failure patterns discussed across reports) (2023)Payment authentication requirements (e.g., SCA/3DS in Europe) introduce additional checkout failure points that can reduce conversion if not handled well and monitored end-to-end.
Stripe documentation and industry guidance on SCA/3DS impacts and implementation considerations (2020)Real-world examples
Login outage caught before support tickets spike (session store failure)
Scenario: A small SaaS runs a synthetic “email + password login → dashboard loads” check every 2 minutes from US/EU. After a deploy, Redis (session store) hits max memory and starts evicting sessions. Real users see intermittent redirects back to /login.
Outcome: CheckyWorky alerts within 4 minutes with a screenshot loop (login → redirect → login) and the failing network call. Team rolls back and increases Redis memory; incident resolved before a major ticket spike. Measurable impact: time-to-detect reduced from ~30–60 minutes (support-led) to <5 minutes (monitor-led).
Signup activation broken by email provider delay (OTP never arrives)
Scenario: A PLG app monitors “signup → request OTP → enter OTP → create workspace.” Their email provider (SendGrid/Mailgun) experiences delays; OTP emails arrive after expiration. The UI looks fine, but activation fails at the OTP step.
Outcome: Synthetic check fails on “OTP accepted” assertion and captures the exact error message. Team adds longer OTP TTL + fallback to resend + status page messaging. Measurable impact: support tickets for “can’t sign up” drop and activation rate recovers after fix; time-to-detect becomes minutes instead of hours.
Checkout regression after pricing change (wrong Stripe Price ID)
Scenario: Team updates plans and accidentally deploys a stale Stripe Price ID to production. Users can open the upgrade modal, but checkout fails after redirect with a generic error.
Outcome: Billing journey monitor (“open pricing → choose Pro → redirect to Stripe Checkout → return success URL”) fails immediately after deploy and includes the failing Stripe error page screenshot. Measurable impact: prevents a prolonged conversion outage; fix shipped within one deploy cycle.
SSO login breaks after IdP certificate rotation (SAML)
Scenario: Enterprise customers use Okta SAML. Okta rotates signing cert; your app’s SAML metadata isn’t updated. Only SSO users are affected—password logins still work, so basic uptime checks stay green.
Outcome: Dedicated SSO synthetic journey (“start SSO → authenticate test user → assertion → land on dashboard”) fails and provides a trace of the assertion error. Measurable impact: SSO incident detected quickly with clear proof; avoids multi-hour enterprise disruption and escalations.
Key insights
1.
Start with journeys that block revenue and create immediate support load: login, activation, and billing/upgrade. These are the fastest paths to “users can’t use/pay.”
2.
Basic uptime (ping/HTTP 200) often stays green while real users are stuck in redirects, broken forms, or third-party auth loops—journey monitoring catches what status checks miss.
3.
Most high-severity incidents are change-driven (deploys/config/dependency updates), so the best ROI checks are the ones most likely to fail after releases: auth, onboarding gates, pricing/checkout.
4.
Third-party dependencies (IdPs, email/SMS, payment providers, CAPTCHA) fail in ways that look like “your app is down” to customers—monitor the integration boundary end-to-end.
5.
Monitor both “happy path” and one or two high-frequency edge paths (SSO vs password login, 3DS-required card vs normal card) to avoid blind spots.
6.
Alerts without evidence waste time; screenshots, step-level assertions, and network/console context reduce mean time to recovery because engineers can reproduce faster.
7.
Run critical checks from multiple regions to catch DNS/CDN/regional cloud issues that your single-region logs may not reveal.
Pro tips
💡
Create a dedicated “synthetic” tenant and users (password + SSO) and tag them everywhere (analytics, CRM, support). This prevents polluted metrics and makes it safe to run frequent checks.
💡
Add one assertion per step that matches user intent (e.g., “Dashboard heading visible,” “Plan shows Pro,” “Success URL contains /billing/success”)—not just “page loaded.” This makes failures actionable.
💡
After every pricing/auth/onboarding change, temporarily increase check frequency (e.g., 1-minute intervals for 24 hours) and monitor from 2+ regions to catch rollout/regional issues quickly.
How CheckyWorky compares
vs Datadog Synthetics
Strong enterprise monitoring suite and deep integration with Datadog APM/logs, but can be heavier to adopt for small teams. CheckyWorky is positioned to be lightweight and focused on “proof-based” critical journey checks (login/signup/billing) without needing a full observability platform.
vs Checkly
Developer-first and great for code-defined Playwright checks. CheckyWorky emphasizes quick-start, SaaS workflow templates, and business-journey framing (activation/revenue) so small teams can get coverage fast even without building a full monitoring-as-code practice.
vs UptimeRobot
Excellent simple uptime/heartbeat monitoring, but limited for multi-step authenticated flows (SSO, checkout redirects, onboarding). CheckyWorky focuses on real user journeys with step assertions and visual proof when something breaks.