Cluster Autoscaling Disabled
Without autoscaling the cluster holds its configured worker count for the whole run, so the size chosen for the heaviest stage is paid for during every lighter one.
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AWSAzureGoogle CloudDatabricks
Found, explained, handed over.
Findings with a dollar figure attached, idle, oversized, orphaned, unscheduled and undiscounted spend.
Detect
ZopNight checks this automatically across AWS, Azure and Google Cloud, with read-only access to the account.
Explain
Every finding says exactly what to change: Enable autoscaling on the Databricks cluster. 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
- Databricks Cluster on AWS, Databricks Cluster on Azure, Databricks Cluster on Google Cloud
- The fix, by hand on AWS
- Open the cluster's configuration in the Databricks workspace.
- Enable autoscaling and set sensible min/max worker bounds for the workload.
- Monitor cluster utilisation after the change to confirm the bounds fit demand.
These are the steps the finding carries in the product.
- Category
- Rightsizing. Resources sized for headroom they never use. A smaller size runs the same workload for less.
- Where it appears
- The Savings tab of Recommendations, with every affected resource listed.
- Rule IDs
RC-2208RC-2308RC-2408- Full reference
Related checks
See the oversized 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.