Azure ML Online Deployment Idle
An online deployment holds its instances allocated so it can answer immediately, and those instances bill continuously whether or not a request arrives.
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Azure
Found, explained, handed over.
Findings with a dollar figure attached, idle, oversized, orphaned, unscheduled and undiscounted spend.
Detect
ZopNight checks this automatically across Azure, with read-only access to the account.
Explain
Every finding says exactly what to change: Delete the idle ML online deployment. Where the saving can be proven it is priced; where it cannot, the finding says so.
Fix
The finding opens with the fix already written out, step by step, so it is one ticket, not an investigation.
- Applies to
- ML Online Deployments on Azure
- The fix, by hand
- Confirm no application routes inference to this deployment.
- In Azure ML studio (ml.azure.com) → Endpoints → the online endpoint → Deployments.
- Delete the idle deployment, or set its instance count to 0.
- Delete the parent endpoint too if it has no remaining deployments.
These are the steps the finding carries in the product.
- Category
- Idle resources. Resources running but doing no useful work: zero invocations, no connections, no traffic.
- Where it appears
- The Savings tab of Recommendations, with every affected resource listed.
- Rule ID
RC-1397- Full reference
Related checks
See the idle resources in your account.
Connect a read-only role and the first pass runs on your own estate. This check, and the rest of the catalogue, with it.
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- $30M+annualised cloud spend under management
- 550K+resources tracked since launch
- 20-60%off the bill in the first month
- SOC 2Type II report, plus ISO 27001
Figures published on zop.dev.