Against the field

The homepage table is a summary. Four rows carry the real argument, and each is a decision the incumbents made differently — not a feature they forgot.

Resolution at the moment of failure. Most tools sample every 15 to 60 seconds. When a machine dies, the last data point predates the failure and everything interesting happened between two samples. MonOps keeps a rolling five-minute recording at one frame per second on every machine and flushes it when risk crosses a floor. You browse the crash instead of inferring it from an average.

Confirmation before paging. A failed check is re-run from a second region before anyone is woken. If it recovers, the incident closes itself. The industry default is to page on first failure and let the on-call engineer be the deduplication layer.

Predictions that are graded. Everyone in this category claims prediction. Almost nobody publishes recall or median lead time. The prediction ledger records every call as hit or miss with its lead time and recomputes recall every 60 seconds, on a dashboard you can see. Misses sit next to hits.

Cardinality without the invoice. Tag-based pricing means the useful dimensions are the expensive ones, so teams stop instrumenting precisely where they need visibility. Flat monthly pricing, no per-check metering, no overage invoice after an incident storm.

Pretending otherwise would be the fastest way to lose your trust, so plainly:

Log search, today. If your primary need is querying logs across a large estate right now, the incumbents have spent a decade on that problem and MonOps has not shipped it yet. It is coming as iLog, an in-house Rust logging tier, and until it lands this row belongs to them.

Integration breadth. Hundreds of prebuilt integrations for every SaaS in your stack is a real advantage and a real moat. MonOps reads from native operating-system interfaces instead, which means nothing to instrument but also a shorter list of third-party sources.

Compliance paperwork. Years of accumulated certifications are worth something to a procurement team. If a signed pile of audit reports is a hard requirement today, that is an honest reason to choose someone else.

Dashboards as a product. If your team wants to build arbitrary custom dashboards over arbitrary metrics, a general-purpose observability platform is the better tool. MonOps ships one opinionated console.

Do not take the table on faith. Install the agent on a test machine, then break it deliberately — exhaust memory, saturate a disk, kill the process holding a lock.

Then open the incident and check three things: whether the timeline before the failure is recorded at one-second resolution, whether the responsible process was identified by sustained CPU rather than an instantaneous spike, and whether cluster events from the same minutes are on the same timeline with the same clock.

Run the identical break against whatever you use today and compare what each one hands you. That comparison is worth more than any vendor table, including this one.