Opsis vs Datadog: from metrics and traces to a reproduced, fixed flow
Datadog and Opsis live in different places in your stack. Datadog is a full observability platform: infrastructure, APM, logs, RUM and synthetic monitoring across your whole system. Opsis is the focused QA layer on top that takes the front-end sessions that look broken, reproduces them in a real browser, proves them on video, and writes the fix. They're complements, not substitutes.
At a glance
| Dimension | Opsis | Datadog |
|---|---|---|
| Primary job | Find, prove & fix front-end bugs | Platform observability & APM |
| Session replay | Reads yours (RUM, SDK) | Records its own (RUM) |
| Reproduces the flow in a browser | Yes, via Opsis MCP | – |
| Proof video of the failure | Yes | No (traces, not video) |
| Hands you a copy-paste fix | Yes, per finding | – |
| Pre-deploy QA crawl | Yes, before-ship | Synthetic tests (configurable) |
| Infra / backend / log breadth | No (front-of-app focus) | Yes |
Opsis
Datadog
What Datadog is great at
Platform-wide observability
Infrastructure metrics, APM traces, log management, network monitoring and dashboards in one place. For understanding the health of an entire distributed system, Datadog is genuinely comprehensive.
Real User Monitoring & synthetics
Datadog RUM records front-end sessions and synthetic tests can probe critical journeys. That telemetry is exactly the kind of signal Opsis can read and act on.
Dashboards tell you something is slow or erroring. They don't prove the bug or fix it.
Datadog surfaces the metric and the trace; it doesn't reproduce the exact user-facing failure in a browser, record proof that this specific flow is broken, or hand you the fix. And the costliest front-end bugs (a dead-end checkout, a button that silently does nothing) often show up as a quiet dip in a funnel rather than a clear error, so they're easy to miss in a sea of dashboards. Closing that metric-to-fix gap is what Opsis does.
How they fit together
Point Opsis at the front-end sessions Datadog RUM already records (or use the first-party Opsis SDK). Opsis runs signal detection, reproduces the strongest findings via Opsis MCP, proves each on video, and returns a guard-railed fix. Datadog keeps watching the system; Opsis closes the loop on the user-facing bug.
When to use which
Use Datadog
Reach for Datadog when you need to monitor the whole system: infrastructure, services, traces, logs and uptime. It's the operational nervous system for your platform.
Use Opsis
Reach for Opsis when you need the broken user flow reproduced and proven, with a fix ready to paste, instead of reading traces and rebuilding the failure by hand.
Together
Best together: Datadog watches the platform and records RUM sessions, Opsis turns the bad front-end sessions into proven bugs with fixes.
Questions
Is Opsis a Datadog alternative?
No. Opsis isn't an observability platform and doesn't replace Datadog's metrics, APM or logs. It reads the front-end sessions RUM already captures and adds reproduction, proof and a fix on top.
Can Opsis read Datadog sessions?
Opsis works with the front-end session data you already collect. If RUM (or another source like PostHog, Sentry, or the Opsis SDK) is recording sessions, Opsis can read those and act on them.
What does Opsis catch that Datadog doesn't?
Behavioural front-end failures that never throw or log: a checkout that dead-ends, a form that rejects valid input, a button that does nothing. Opsis detects the signals (rage clicks, abandonment, failed requests), reproduces the flow and writes the fix.