errorgap correlates errors, logs, transactions, uptime checks, and deploys into a single incident, then ranks a likely cause and shows the evidence behind it. This page compares that approach against the categories of tool it replaces or sits beside — by capability, not by brand.
Error trackers stop at the exception. errorgap keeps the exception and correlates it with the logs around it, the transaction that slowed, the check that failed, and the deploy that shipped — then names a likely cause and ranks it.
Suites can correlate too, once you have finished the migration, agreed the seat count, and standardised the collector. errorgap is one JSON envelope and a key. You pay for captured events, not for the people who look at them.
A query language is only useful once you know what to query. errorgap attaches the log window around a failure to the incident itself — duplicates grouped, timestamps stripped — so the relevant lines are already on the page.
Knowing the endpoint is down is the first thirty seconds of the job. When an errorgap check fails, it opens an incident that already carries the errors firing behind it and the release that preceded them.
api.example.com/health returns 503 twice in a row.
Severity critical. No one has to acknowledge a page first.
The 4,100 errors firing behind the check, and release v2.14.0 from 11 minutes earlier.
“Connection pool exhausted after v2.14.0” — with the frames and log lines it was read from.
Typical coverage per category of tool. Individual products vary; where a category commonly ships a partial or add-on version of a capability, it is marked as partial.
| Capability | errorgap | Error tracker | APM suite | Log platform | Uptime monitor |
|---|---|---|---|---|---|
| Correlated incidents across signals | Included | Not offered | partial | Not offered | Not offered |
| Ranked likely cause with evidence | Included | Not offered | Not offered | Not offered | Not offered |
| Error grouping and stack frames | Included | Included | partial | Not offered | Not offered |
| Live log streaming | Included | Not offered | partial | Included | Not offered |
| Uptime checks | Included | Not offered | partial | Not offered | Included |
| Per-transaction timing (APM) | Included | Not offered | Included | Not offered | Not offered |
| Distributed tracing across services | Not offered | Not offered | Included | Not offered | Not offered |
| Session replay | Included | partial | partial | Not offered | Not offered |
| Custom metrics and dashboards | Not offered | Not offered | Included | partial | Not offered |
| MCP access for AI agents | Included | Not offered | Not offered | Not offered | Not offered |
| Pricing model | per event | per event | per host + seat | per GB ingested | per monitor |
| Time to first signal | minutes | minutes | days | hours | minutes |
Three things it is worth knowing before you start a trial.
We run it, you send events. There is no collector to keep alive — which also means the data sits with us, under the terms on our Trust page.
No custom metric ingestion, no PromQL, no long-range business dashboards. errorgap watches failures. Send your revenue graphs somewhere else.
APM is per-transaction timing with DB, view, and external breakdowns. If you need a span graph stitched across a dozen services, an observability suite is the right tool.