Buying AIOps Platform

Decision criteria.

The question

AIOps platforms promise alert reduction, automated triage, and root-cause analysis. The space spans Moogsoft, BigPanda, Splunk ITSI, Datadog Watchdog, and Nova AI Ops.

Default to your existing observability vendor's AIOps add-on first. Switching backbones for AIOps alone rarely pays.

Switch only when alert volume exceeds 10k/day and the current vendor has plateaued.

What to evaluate

Alert clustering: how well does it group related signals? Run on 30 days of historical alerts; measure manual labour saved.

Root-cause hypothesis: does it surface plausible causes? Beware demos with hand-tuned data.

Integration: does it connect to your existing alert sources without rewriting them? Migration is the killer cost.

How to trial

30-day shadow trial. Pipe live alerts; don't act on the AIOps suggestions. Measure precision and recall against your post-incident retros.

Test on a real incident. Trigger a known multi-signal outage in staging; see if the platform clusters correctly.

Talk to 3 reference customers at your scale. Vendor demos cherry-pick; references reveal the real ops burden.

Hidden costs

Data ingestion fees. Most AIOps platforms charge per event; alert storms can blow budgets.

Configuration time. Expect 4 to 8 weeks of an SRE's time to tune the rules and feedback loop.

Vendor lock-in. Custom rules and learned models don't port between vendors.

When to buy

Under 1k alerts/day: skip AIOps. PagerDuty event rules and dedup are enough.

1k to 10k alerts/day: evaluate the add-on from your existing vendor.

Above 10k alerts/day: a dedicated AIOps platform pays for itself in alert reduction within 6 months.