Azure SLA credits, explained
When Microsoft Azure misses its 99.99% uptime commitment, you’re owed service credits. Here’s exactly how the Azure Virtual Machines (Availability Set) schedule works — and how to claim what you’re due.
- Uptime SLA
- 99.99%
- Downtime budget
- 4 min/mo
- Claim window
- 60 days
- Max credit
- 100%
Azure credit schedule
Service credits are calculated against your monthly bill for the affected service, based on its Monthly Uptime Percentage.
| Monthly uptime | Equivalent downtime | Service credit |
|---|---|---|
| 99.0% – < 99.99% | 4 min/mo – 7.2 hrs/mo | 10% credit |
| 95.0% – < 99.0% | 7.2 hrs/mo – 36 hrs/mo | 25% credit |
| Below 95.0% | 36 hrs/mo – 720 hrs/mo | 100% credit |
Do you qualify for a Azure credit?
Azure credits aren’t automatic, and not every outage counts. Check each condition below before you spend time building a claim.
Your deployment topology meets the SLA tier
Azure VMs hit 99.99% only across an Availability Zone deployment; an Availability Set gets 99.95%, and a single instance needs Premium SSD or Ultra Disk on every disk just to reach 99.9%. Match your topology to the right commitment before you measure.
Monthly Uptime Percentage missed the commitment
Azure measures uptime per resource across the billing month. Connectivity must fail to two or more instances (for multi-instance SLAs) before the minutes count against the Monthly Uptime Percentage.
The downtime is attributable to Azure
Outages caused by your application, configuration, or anything Microsoft classes as a Force Majeure or excluded event do not reduce the Monthly Uptime Percentage.
You hold an eligible subscription
Free, trial, and certain promotional subscriptions are excluded. Credits apply to the paid subscription that incurred the charges for the affected resource.
How to claim your Azure credit
Credits aren’t automatic — you have 60 days to file. Follow these steps.
Identify the breached resource
Determine which Azure resource (VM, App Service, SQL Database) fell below its Monthly Uptime Percentage commitment, using Azure Monitor and Service Health.
Document downtime windows
Export Azure Monitor metrics and Service Health history showing the start/end of each unavailability window during the billing month.
Submit a support request
Open a billing support request in the Azure portal (Help + support → New support request → Billing) within two months of the incident.
Credit applied to your subscription
Approved Service Credits appear on a subsequent monthly invoice for the affected subscription and service.
Eligibility fine print
- Single-instance VMs require Premium SSD/Ultra Disk for all disks to qualify for the 99.9% SLA.
- Credits apply only to the monthly service fees of the affected resource.
- Claims must be filed within two months of the end of the affected billing month.
Estimate your Azure credit
Enter your spend and downtime to see what Azure owes you.
A 10% credit on your $8,000 monthly AWS bill, based on 99.40% uptime.
Estimate only, based on AWS’s flagship compute SLA. Credits are capped at the affected service’s monthly charge. The smallest billable credit here is $800.00. Verify against your provider’s current agreement.
Gather your Azure claim evidence
A complete evidence pack is the single biggest factor in getting a credit approved on the first pass. Tick each item off as you collect it, then export the list for your ticket.
Gather every item below before you file. Complete evidence is the single biggest factor in getting a credit approved on the first pass.
Draft your Azure claim email
Fill in your incident details and we’ll write a claim email in Azure’s own terms, with the credit math already worked out. Copy it, attach your evidence, and send.
Fill in your incident details and we’ll draft a claim email in AWS’s own terms — ready to paste into a AWS Support case (Account and billing → SLA credit).
Subject: SLA Service Credit request — Amazon EC2 / EBS (Region-level) downtime on [incident date] Hello AWS Support, I am writing on behalf of [Your company] to request an SLA Service Credit for downtime that affected Amazon EC2 / EBS (Region-level) on our account ([account / subscription ID]). Incident summary - Affected service: Amazon EC2 / EBS (Region-level) - Date of incident: [incident date] - Total downtime: 4 hours 20 minutes - Resulting Monthly Uptime Percentage: 99.398% Amazon Web Services commits to a 99.99% Monthly Uptime Percentage SLA for this service. Our measured uptime of 99.398% falls below that commitment, which under your published SLA entitles us to a 10% Service Credit against the monthly charges for the affected service. Based on our monthly spend of $8,000 on this service, the 10% Service Credit amounts to approximately $800. Supporting documentation (attached) - Timestamped downtime windows (UTC) - Monitoring metrics / uptime checks for the incident period - The relevant invoice line item for the affected service This claim is submitted within your 60-day claim window. Please confirm receipt and let me know if you require any additional evidence to process the Service Credit. Thank you, [Your name] [Your company]
Review before sending — figures are estimates based on AWS’s flagship compute SLA. Attach your evidence and verify against your current agreement.
Azure SLA credit FAQ
- What is Azure's uptime SLA?
- Microsoft Azure commits to 99.99% Monthly Uptime Percentage for Azure Virtual Machines (Availability Set). Falling below that threshold makes you eligible for service credits on a sliding scale, up to 100% of your monthly bill for the affected service.
- How long do I have to claim a Azure SLA credit?
- You must file your claim within 60 days of the incident (or of becoming eligible). Miss the window and the credit is forfeited — Azure does not issue credits automatically.
- Are Azure SLA credits paid as cash?
- No. Credits are applied against a future monthly invoice for the affected service, not refunded as cash, and they are capped at that service's monthly charge.
- What evidence do I need to claim a credit?
- Provide the dates and times of each downtime window plus supporting monitoring data (error rates, failed requests, uptime checks). Detailed logs make approval far more likely.