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Source facts

\n

Azure VM and disk bursting operate independently. In the credit-based model, each resource has its own credits, which accumulate when IOPS or bandwidth use is below its performance target. IOPS and bandwidth credits are tracked separately, so one can accumulate while the other is being spent. Microsoft describes credit-based disk bursting as best effort, not guaranteed. Microsoft Learn.

\n

Applicability

\n

Use this check only after confirming that the chosen VM and disk sizes support the relevant bursting model. Separate credit-based behavior from on-demand disk bursting. Record the test’s starting conditions and workload duration instead of comparing results from an idle resource with results from an already busy one.

\n

DSE recommendation

\n

Include both a fresh-credit run and a sustained-demand run in the storage performance acceptance test. Ask the application owner to identify the longest expected busy period and the acceptable behavior after initial headroom is consumed. Evaluate VM-level and disk-level constraints separately. Keep any brief startup improvement distinct from the sustained result used to approve the production workload.

\n

Verification

\n

Capture IOPS, bandwidth, and available bursting observations over the complete trial rather than retaining only the fastest interval. Compare the later workload behavior with the application’s acceptance criteria and the documented baseline targets. If performance changes as credits are consumed, record that transition rather than averaging it away. Repeat the test from a documented starting condition before attributing differences to a configuration change.

\n

Official references

\n

Microsoft Learn: Managed disk bursting. Source reviewed September 9, 2026.

", "content_text": "Source facts\nAzure VM and disk bursting operate independently. In the credit-based model, each resource has its own credits, which accumulate when IOPS or bandwidth use is below its performance target. IOPS and bandwidth credits are tracked separately, so one can accumulate while the other is being spent. Microsoft describes credit-based disk bursting as best effort, not guaranteed. Microsoft Learn.\nApplicability\nUse this check only after confirming that the chosen VM and disk sizes support the relevant bursting model. Separate credit-based behavior from on-demand disk bursting. Record the test’s starting conditions and workload duration instead of comparing results from an idle resource with results from an already busy one.\nDSE recommendation\nInclude both a fresh-credit run and a sustained-demand run in the storage performance acceptance test. Ask the application owner to identify the longest expected busy period and the acceptable behavior after initial headroom is consumed. Evaluate VM-level and disk-level constraints separately. Keep any brief startup improvement distinct from the sustained result used to approve the production workload.\nVerification\nCapture IOPS, bandwidth, and available bursting observations over the complete trial rather than retaining only the fastest interval. Compare the later workload behavior with the application’s acceptance criteria and the documented baseline targets. If performance changes as credits are consumed, record that transition rather than averaging it away. Repeat the test from a documented starting condition before attributing differences to a configuration change.\nOfficial references\nMicrosoft Learn: Managed disk bursting. Source reviewed September 9, 2026.", "content_markdown": "## Source facts\n\nAzure VM and disk bursting operate independently. In the credit-based model, each resource has its own credits, which accumulate when IOPS or bandwidth use is below its performance target. IOPS and bandwidth credits are tracked separately, so one can accumulate while the other is being spent. Microsoft describes credit-based disk bursting as best effort, not guaranteed. [Microsoft Learn](https://learn.microsoft.com/en-us/azure/virtual-machines/disk-bursting).\n\n## Applicability\n\nUse this check only after confirming that the chosen VM and disk sizes support the relevant bursting model. Separate credit-based behavior from on-demand disk bursting. Record the test’s starting conditions and workload duration instead of comparing results from an idle resource with results from an already busy one.\n\n## DSE recommendation\n\nInclude both a fresh-credit run and a sustained-demand run in the storage performance acceptance test. Ask the application owner to identify the longest expected busy period and the acceptable behavior after initial headroom is consumed. Evaluate VM-level and disk-level constraints separately. Keep any brief startup improvement distinct from the sustained result used to approve the production workload.\n\n## Verification\n\nCapture IOPS, bandwidth, and available bursting observations over the complete trial rather than retaining only the fastest interval. Compare the later workload behavior with the application’s acceptance criteria and the documented baseline targets. If performance changes as credits are consumed, record that transition rather than averaging it away. Repeat the test from a documented starting condition before attributing differences to a configuration change.\n\n## Official references\n\n[Microsoft Learn: Managed disk bursting](https://learn.microsoft.com/en-us/azure/virtual-machines/disk-bursting). 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Keep any brief startup improvement distinct from the sustained result used to approve the production workload.\nVerification\nCapture IOPS, bandwidth, and available bursting observations over the complete trial rather than retaining only the fastest interval. Compare the later workload behavior with the application’s acceptance criteria and the documented baseline targets. If performance changes as credits are consumed, record that transition rather than averaging it away. Repeat the test from a documented starting condition before attributing differences to a configuration change.\nOfficial references\nMicrosoft Learn: Managed disk bursting. 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