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Cloud cost anomalies pop up suddenly, and when they do, speed and context matter. One misconfiguration or deployment mistake can quickly consume budgets. Engineers need to quickly see what changed, why it changed, and exactly what to do next.
We built PointFive’s new Cost Anomaly Detection module with this challenge top of mind. Our Cost Anomaly Detection module embeds a complete contextual view of the anomaly directly into the engineering workflow. Now engineers can investigate quickly and take action without losing momentum.
Every business has unique patterns. A bank’s cloud footprint is completely different from an airline’s. Rigid rules create noise and miss real issues. That’s why we use an AI model called Prophet behind the scenes. It analyzes the full historical dataset for each anomaly scope, and detects seasonality patterns, whether daily, weekly, monthly, or yearly. For example, if your bill consistently spikes at the beginning of each month, Prophet learns that behavior and doesn’t flag it as an anomaly.
Our detection engine gives you the flexibility to define anomaly rules using various dimensions. Dimensions include Account, Service, Region, and others. Whether you want a broad view (e.g. rule to detect anomalies across accounts) or a targeted focus (e.g. rule to detect anomalies per each service and usage type), you can scope rules to quiet noise and surface metrics that matter to your goals and KPIs.
You can also tune thresholds to reduce noise and focus only on cost spikes that meet your definition of abnormal. Thresholds don’t have to be one-size-fits all. You can configure different rules for team-level scopes, specific service and usage types, or a tag-based rule, each customized to its purpose.
Once an anomaly is detected, the goal isn’t just notification. it’s resolution.
That’s why our Cost Anomaly Detection module offers multiple ways to identify the root cause of an anomaly. You can solve the issue at its source and prevent recurrence.
Usage and Rate Breakdowns help you quickly determine whether an anomaly was driven by a change in usage volume or in the effective cost per usage unit. A rate change might mean your price increased because a discount agreement expired or your pricing terms changed. This distinction matters because the root cause determines the right response. Without it, you risk fixing the wrong issue or missing the real source of unexpected costs.
For example, here we can clearly see the anomaly was caused by a change in usage, while the rate remained stable:
And in this example, the cost increase came from a rate change:
Each anomaly includes a recommended set of contributing attributes most likely involved in the spike. This helps engineers quickly narrow down the root cause by highlighting the specific resources, services, tags, or accounts most likely responsible for the spike. At the most granular level, this includes resource IDs and usage types; at higher levels, you may see services or account names.
We re-run the detection algorithm for each contributor independently. If a specific resource shows anomalous behavior on its own, we highlight it. You can then overlay these contributors on the cost trend chart to visually identify which ones drove the anomaly.
Every anomaly includes an Analysis tab that offers flexible ways to explore and understand what’s driving unexpected cost changes. You can break down cost trends over time by dimensions such as charge type and purchase option, helping you identify issues like expired discounts, changes in commitment coverage, or new billing patterns.
In addition to cost analysis, you can investigate changes in operations or usage types that may have contributed to the anomaly. This level of visibility lets you examine anomalies from multiple angles, isolate contributing factors more easily, and reach faster, more confident conclusions.
Once the root cause is identified, you can immediately take action. The anomaly page lets you:
- Open a Jira ticket pre-filled with relevant details
- Assign a team member to follow up
That means the full loop including alerting, investigation, and remediation happens in one place. No more screenshots, Slack threads, or disconnected tools. This ensures nothing gets lost and every anomaly has a clear owner and next step.
From Detection to Resolution. All in One Place
Spotting cloud cost anomalies is hard. Resolving them efficiently is even harder. With PointFive’s Cost Anomaly Detection module, identifying, understanding, and acting on anomalies is faster and clearer than ever. And this is just the beginning. We’re actively expanding the platform to support even more use cases.
Interested in learning more? Book a demo here!
