Our finance reporting server slowed sharply during month-end close because, according to the team’s account, its burstable cloud instance had exhausted its CPU credits and was operating at its baseline. A report that usually took four minutes took forty, even while the CPU graph showed about 20% utilization. That figure looked like spare capacity; it did not reveal the instance’s remaining credit balance.
How a low annual average hid a month-end bottleneck
Before choosing the instance, the team reviewed a year of monitoring. Processor use averaged about 12% and rarely exceeded 40%, according to Serguey Shinder’s account of the incident. Ordinary weeks went well. Month-end consolidation and finance reporting, however, created a heavier workload that lasted across consecutive days.
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By the middle of the second day, a report that normally took four minutes reportedly took forty minutes, and overnight jobs were still running into the morning. These figures describe the author’s experience; they are not results from an independently audited benchmark or controlled test. The CPU graph showed around 20% utilization, which the team initially read as remaining headroom.
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A burstable instance is designed to run below a CPU baseline much of the time and use accumulated credits to run above that baseline when needed. AWS describes a CPU credit as a unit of vCPU time: an EC2 burstable instance accrues credits below baseline and spends them above it. The incident account does not identify its cloud provider, instance type, or credit mode, so AWS documentation explains the general concept here, not the specific service used in the incident.
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On an EC2 burstable instance in Standard mode, AWS says that when accrued credits are depleted, CPU utilization is gradually brought down to baseline. In Unlimited mode, an instance can use surplus credits after its accrued balance reaches zero, with potential billing implications under AWS’s documented conditions. These modes differ, and the incident account does not establish which, if either, applied. AWS explains CPU credits, baselines, and credit modes.
This distinction helps explain why a utilization graph alone can mislead. A CPU reading shows current utilization; it does not say how many credits remain or whether the instance can sustain a burst. In the account, the roughly 20% reading appeared to indicate unused capacity, but the author’s explanation is that depleted credits had left the server at its baseline.
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What the team changed
For the final working day of the month and the first three working days of the next month, the team moved the reporting server to a fixed-performance instance, then scheduled it back afterward. The account does not name the instance family or provider. This was the team’s response to a recurring peak, not a universal sizing recommendation.
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The team also reported adding alerts for remaining burstable instances when their credit balance fell below 40%. That was its chosen threshold, not an AWS default or a generally established best-practice threshold. It changed its sizing template to ask about the busiest consecutive day, rather than relying only on average use, and found two other servers that were also relying on credits. Shinder’s account describes the incident and the team’s changes.
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How to monitor credit state alongside CPU use
For AWS EC2 burstable instances, CloudWatch includes the CPUCreditBalance metric, which reports accrued credits available for bursting. AWS says CPU credit metrics update every five minutes. Watching the balance alongside CPU utilization can show both current processor use and whether the instance still has credits to sustain above-baseline operation. AWS lists the burstable-instance CloudWatch metrics.
For other providers or services, identify the equivalent service-specific credit or allowance metric rather than assuming the AWS metric name or behavior applies. A useful alert should reflect the workload’s expected peak duration, the instance’s credit behavior, and how much warning the team needs to respond; the incident’s 40% threshold is only one team’s choice.
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Size for the peak pattern, not just the average
The practical lesson is to describe demand in time as well as volume. A workload that briefly exceeds baseline differs from one that stays above baseline over several consecutive days. When reviewing capacity, establish the baseline performance the reporting job requires, how long and how often peak demand lasts, what burst headroom is available, and what happens when credits run out. For AWS EC2, also account for whether the instance is in Standard or Unlimited mode and the latter’s possible billing implications.
- Review the busiest consecutive days, not only a monthly or annual CPU average.
- Check credit balances or equivalent service-specific allowances as well as CPU utilization.
- Make recurring peak schedules visible to the teams that rely on reports and overnight jobs.
- Include other constrained resources in monitoring. The account also mentions a database whose disk-throughput allowance was consumed nightly by backups, but does not identify its provider, storage product, or exact metric.
Shinder’s concise takeaway was: “A cloud resource can run out of things other than money.”
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