What to think about when evaluating AI for IT solutions
Every vendor’s AI seems the same. What requirements should you be looking for when evaluating AIOps solutions?
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How many metrics should an AIOps platform ingest concurrently?
- At least 100,000 assuming a low- end requirement of about 5,000 nodes and 20 metrics per node monitored at five-minute intervals.
What volume of log data should an AI platform process?
- At least 5GB per core per day with no performance degradation or data loss. Adding server cores should be supported for elastic scaling.
What log compression level should be expected for storage?
- At least 90%+ lossless log compression ratio to reduce storage cost.
Are all AIOps platforms only available on-prem?
- No. Modern AIOps platforms support SaaS and on-prem deployment modes with feature parity across both.
What architecture is required to scale AIOps systems?
- A distributed architecture is required that allows lightweight metric and log worker nodes to be added and data processing jobs to be queued and shared across clustered nodes.
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