Leverage anomaly management processes with Microsoft Cost Management

The cloud comes with the promise of significant cost savings compared to on-premises costs. However, realizing those savings requires diligence to proactively plan, govern, and monitor your cloud solutions. Your ability to detect, analyze, and quickly resolve unexpected costs can help minimize the impact on your budget and operations. When you understand your cloud costs you can make more informed decisions on how to allocate and manage those costs. But even with proactive cost management, surprises can still happen. That’s why we developed several tools in Microsoft Cost Management to help you set up thresholds and rules so you can detect problems early and ensure the timely detection of out-of-scope changes in your cloud costs. Let’s take a closer look at some of these tools and how you can use them to discover anomalous costs and usage patterns.

 

 

Identify atypical usage patterns with anomaly detection
Anomaly detection is a powerful tool that can help you minimize unexpected charges by identifying atypical usage patterns like cost spikes or dips based on your cost and usage trends and take corrective actions. For example, you might notice that something has changed, but you’re not sure what. Suppose you have a subscription that consumes around $100 every day. A new service was added into the subscription by mistake, resulting in the daily cost doubling to $200. With anomaly detection, you will be notified about the steep spike in daily cost, which you can then investigate to see if it’s an expected increase or a mistake, leading to early corrective measure.

You can also embed time-series anomaly detection capabilities into your apps to identify problems quickly. AI Anomaly Detector ingests time-series data of all types and selects the best anomaly detection algorithm for your data to ensure high accuracy. Detect spikes, dips, deviations from cyclic patterns, and trend changes through both univariate and multivariate APIs. Customize the service to detect any level of anomaly. Deploy the anomaly detection service where you need it—in the cloud or at the intelligent edge.

 

Use Alerts to get notified when an anomalous usage change is detected
You can subscribe to anomaly alerts to be automatically notified when an anomalous usage change is detected, with a subscription-scope email displaying the underlying resource groups that contributed to the anomalous behavior. Alerts can also be set up for your Azure reserved instances usage to receive email notifications, so you can take remedial action when your reservations have low utilization.

Here’s an example of how to create an anomaly alert rule:

• Select the scope as the subscription which needs monitoring.
• Navigate to the ‘Cost alerts’ page in Cost Management. Select ‘Anomaly’ as the Alert type.
• Specify the recipient email IDs.
• Click on ‘Create alert rule.’

In the event that an anomaly is detected, you will receive alert emails which give you basic information to help you start your investigation.

 

Get deeper insights with smart views
Use smart views in Cost Analysis to view anomaly insights that were automatically detected for each subscription. To drill into the underlying data for something that has changed, select the Insight link. You can also create custom views for anomalous usage detection such as unused costs from Azure reserved instances and savings plans that could point to further optimization for specific workloads.

You can also group related resources in Cost Analysis and smart views. For example, group related resources, like disks under virtual machines or web apps under App Service plans, by adding a “cm-resource-parent” tag to the child resources with a value of the parent resource ID. Or use Charts in Cost Analysis smart views to view your daily or monthly cost over time.

 

Use Copilot for AI-based assistance
For quick identification and analysis of anomalies in your cloud spend, try the AI-powered Copilot in Cost Management––available in preview on the Azure Portal. For example, if a cost doubles you can ask Copilot natural language questions to understand what happened and get the insights you need faster. You don’t need to be an expert in navigating the cost management UI or analyzing the data, you simply let the AI do it for you. For example, you can ask, “why did my cost increase this month?” or “which service led to the increase in cost this month?” Copilot will then provide a breakdown by categories of spend and their percentage impact on your total invoice. From there, you can leverage the generated suggestions to investigate your bill further.

 

Learn more about streamlining anomaly management
Optimizing your cloud spend with Azure becomes much easier when you streamline your anomaly management processes with tools like anomaly detection, alerts, and smart views in Microsoft Cost Management. You can learn even more about using FinOps best practices to manage anomalies in your resource usage at aka.ms/finops/solutions.