Get alerts where your team already works
Alerts should be actionable, not noisy. CheckyWorky sends proof, not panic.
What every alert includes
Which workflow failed
The journey name and environment
Which step failed
Pinpointed to the exact action
Screenshot
What the check saw at failure time
Quick link
Jump straight to the run details
By the numbers
Organizations with higher observability maturity report faster incident detection and resolution; mature teams are significantly more likely to detect issues before customers report them.
New Relic Observability Forecast (2023)Mean Time to Resolve (MTTR) is strongly influenced by alert quality and routing—teams that reduce noisy alerts and improve context reduce time spent in triage.
Google Cloud, DORA Accelerate State of DevOps Report (2023)A large share of outages are caused by changes (deployments, config, dependency updates), making rapid detection and rollback workflows critical.
Google Cloud, DORA Accelerate State of DevOps Report (2023)Many service incidents stem from third‑party dependencies (CDNs, payment providers, auth, analytics), which synthetic user-journey checks can surface even when your own APIs are healthy.
ThousandEyes Internet Outages Report (2023)Real-world examples
Slack alert with failing step + screenshot cuts triage time
Scenario: A small SaaS team runs a synthetic “Login → Create project → Invite teammate” flow every 5 minutes. After a frontend deploy, the ‘Invite’ modal selector changes and the check fails at Step 6 (button not found). The Slack alert includes the exact failing step name, screenshot of the missing button, and a link to the run details.
Outcome: Engineer identifies the selector regression immediately and ships a hotfix in ~20 minutes instead of spending ~60–90 minutes reproducing the issue across environments.
Webhook deduplication prevents 50+ duplicate pages during a provider outage
Scenario: A dependency (email delivery API) has intermittent 5xx errors across multiple regions. Without dedupe, each failing run would trigger a new incident. The webhook payload uses an incident_key based on (monitor_id + failing_step + provider_domain) and sends status=triggered only once, then updates the same incident until resolved.
Outcome: One incident created and updated over 45 minutes instead of 50–100 duplicate alerts; responders focus on mitigation (fallback provider + status page update) instead of alert cleanup.
Two-stage routing: Slack for visibility, paging only on confirmed failures
Scenario: Checkout failures are high impact, but single-run UI flakes happen. The team routes all failures to #alerts-checkout immediately, but only triggers an on-call page via webhook when 2 of the last 3 runs fail or when failures occur from 2 regions simultaneously.
Outcome: Pages drop by ~70% while still catching real checkout incidents within 10–15 minutes; on-call fatigue decreases and response becomes more consistent.
Email digest for non-critical monitors keeps signal high
Scenario: Non-customer-facing monitors (admin reports, internal dashboards) occasionally fail due to data freshness or long queries. Instead of real-time Slack noise, the team sends a daily email summary with top failing monitors, links to evidence, and suggested owner tags.
Outcome: Alert channel stays focused on customer-impacting flows; internal issues are still tracked and fixed during business hours, improving overall reliability without constant interruptions.
Key insights
1.
Alert payloads that name the exact failing step (not just “monitor failed”) reduce time-to-triage because responders can immediately map the failure to a code path, selector, or dependency.
2.
Deduplication should be designed around an “incident key” (ongoing failure) rather than a “run id” (single execution) to prevent alert storms during partial outages.
3.
Multi-signal confirmation (consecutive failures, multi-region failures) is one of the simplest ways for small teams to reduce false positives without sacrificing detection speed.
4.
Slack is best for collaboration and shared context; webhooks are best for automation (incident creation, ticketing, paging, and lifecycle updates). Many teams need both.
5.
Screenshots (and optionally console/network snippets) are high-leverage evidence for browser checks because they turn a vague alert into an actionable bug report.
6.
Routing based on ownership tags (service/team/repo) prevents “everyone sees everything” overload and ensures the right engineer gets the first look.
7.
Security matters: screenshots and payloads can leak sensitive data unless you mask inputs, avoid secrets in URLs, and restrict retention and channel access.
Pro tips
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Add an “incident key” to every alert (monitor + failing step + error fingerprint) and dedupe for 15–30 minutes; update the same Slack thread/incident instead of sending new alerts every run.
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Use a two-tier policy: send all failures to a Slack channel, but only escalate (webhook/page) when failures are confirmed (e.g., 2 of last 3 runs, or multi-region). This keeps detection fast while cutting noise.
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Standardize alert fields across Slack/email/webhooks: service, env, severity, failing step, run URL, screenshot URL, last-known-good, and runbook link. Consistency is what makes alerts skimmable during an incident.
How CheckyWorky compares
vs Datadog Synthetics
Powerful enterprise platform with deep APM/log integration; can be heavier to configure for small teams. CheckyWorky’s angle is lightweight “pretend customer” workflows with fast-to-read alerts (failing step + screenshot) and simple routing to Slack/email/webhooks.
vs Checkly
Developer-first synthetic monitoring with strong code-based checks and CI/CD workflows. CheckyWorky emphasizes quick setup and operational alert payloads optimized for small teams that want immediate, actionable context in Slack and easy webhook-based incident routing.
vs Uptime Robot
Great for basic uptime/HTTP checks and simple notifications, but less focused on multi-step user journeys. CheckyWorky is designed for workflow monitoring (login/signup/checkout) with step-level failure evidence (screenshots, exact step) and richer payloads for incident response.