With greater adoption of cloud technology, organizations’ expenditures on cloud infrastructure are at all-time highs. Although the cloud offers unparalleled agility, the corresponding financial model often leads to inefficiencies being ignored or infamous cost overruns. For companies using AWS, cost management and optimization is not optional, it is critical.
It aids companies in tracking expenses and pinpointing deviations from typical spending patterns. In essence, it helps companies control budgets and expenditures. In this blog, we have included everything related to AWS Cost Anomaly Detection; its features, stepwise setup instructions, and much more; so you can approach your cloud costs confidently.
What Is AWS Cost Anomaly Detection?
(Image Source: AWS)
AWS Cost Anomaly Detection is a feature within AWS Billing and Cost Management that tracks spending patterns on your account using machine learning. Cost Anomaly Detection monitors unusual spending patterns per your account and notifies you of possible anomalies.
Common scenarios it helps address include:
Unexpected Spikes in EC2 Usage
Anomalies in S3 Storage Costs
Configuration Errors Causing Cost Surges
Unauthorized Usage or Over-Provisioned Resources
Why care about detecting cost anomalies? Proactive detection saves companies from budget overruns, ensures compliance with financial goals, and minimizes resource wastage.
Key Features
Monitors Historical Usage: Billing and usage data are used to set a baseline for normal spending patterns.
Customizable Alerts: Set thresholds for alerts based on cost impact or percentage deviations.
Real-Time Notifications: Alerts are sent via email, SNS, or Slack to ensure timely responses.
How AWS Cost Anomaly Detection Works
Spending on the cloud is not always straightforward to manage, especially with the surprise costs that might appear now and then. AWS Cost Anomaly Detection helps control your spending by detecting any abnormal charge that has the potential to escalate into a bigger problem. Here’s how it works, step by step:
1. Data Collection
Think of it like keeping track of all your household bills. AWS has a collection of services from which data is gathered, such as EC2 and S3. It then compiles the data into a comprehensive understanding of how your cloud spending is structured
2. Historical Data Analysis
Just like how you might notice your electricity bill is higher in the summer because of the AC, AWS looks at your past spending to figure out what’s "normal" for your account. This enables AWS to establish a baseline and a feasible range.
3. Threshold Calculation
AWS has to define specific adaptive boundaries; these are like spending alerts. Such limits are dynamic and change according to detected patterns to avoid detecting something constant such as changes between seasons.
4. Anomaly Detection
Anomaly detection involves noticing when something off-track occurs within a system. This could take the form of a sudden extreme increase in spending under an account. AWS monitors the spending level in comparison to the preset limits to mitigate overdrafts. It’s like spotting an unusually high credit card charge and marking it as off.
5. Alert Generation
The system then sends you an alert right away through your preferred channel, like email or Slack or AWS Chatbot. Just as a bank may text a customer when they detect unusual transactions performing within their account, AWS does the same.
6. Root Cause Analysis
Once you know something’s wrong, AWS supports in provision of detailed information. Perhaps the spending was a result of a user neglecting to turn off an EC2 instance, or some other misconfiguration like an S3 bucket. This phase assists in identifying the exact reason behind the increased spending.
7. Actionable Recommendations
Finally, AWS will offer you some guidance to get you back on track. For example, AWS will recommend scaling down resources such as the EC2 instance, optimizing resource configurations, or even suggesting transitioning to Reserved Instances for more cost-effective pricing.
Benefits and Limitations of AWS Cost Anomaly Detection
Benefits
Proactive Cost Monitoring: Stop issues in their tracks with timely actions before more costly impacts are incurred.
Minimized False Positives: Alerts are further reduced because learning algorithms and non-historic data limit unnecessary activity.
Enhanced Cost Optimization: In-depth examination of the usage makes it easier for entities to resolve unnecessary waste leading to improved and enhanced savings related to infrastructure and resource consumption.
Cross-Organization Monitoring: Best suited for businesses that deal with many accounts or divisions under one AWS account.
Limitations
Limited by Historical Data: Must have rich, ensuring, reliable, unexaggerated data available so that its algorithms are loaded with surmountable historical data.
Setup Complexity: Manual configuration of monitors and thresholds is needed, and missteps could result in gaps in detection.
Latency in Alerts: Due to the latencies in the AWS cost explorer, anomalies could take up to 24 hours to appear in reports and triggers.
Reactive by Design: This is highly useful when it comes to detection but fails when it comes to preemptive action.
How to Set Up AWS Cost Anomaly Detection
Configuring AWS Cost Anomaly Detection requires only a few simple steps within the AWS Management Console:
Step 1. Enable Cost Explorer
Access the Billing and Cost Management section and enable Cost Explorer. This action must be taken prior to enabling anomaly detection.
Step 2. Create a Monitor
Go to the "Cost Anomaly Detection" section.
Choose the "Cost Monitors" tab and Choose "Create Monitor."
Select the desired monitor type:
AWS Services
Linked Accounts
Cost Categories
Cost Allocation Tag
Name the monitor and optionally tag it for better organization.
Step 3. Configure Alert Subscriptions
Create an alert subscription under the "Alert Subscription" section.
Set a Threshold for triggering alerts:
Use absolute thresholds (e.g., anomalies exceeding $500).
Or percentage thresholds (e.g., deviations beyond 20% of expected spend).
Define Recipients by entering email addresses and/or SNS topics.
Choose the notification frequency:
Individual Alerts
Daily Summaries
Weekly Summaries
Step 4. Test Your Setup
Check if alerts are properly configured and modify the thresholds if necessary to reduce unnecessary alerts.
Pro Tip: To receive messages through Slack or Amazon Chime, integrate AWS Chatbot for direct delivery into your preferred workspace.
Best Practices for AWS Cost Anomaly Detection
1. Customize Monitors for Key Spending Areas
Detect spending anomalies for certain services or projects, by creating tailored detection monitors. For example, create a monitor just to watch the expense of EC2 instances for product development to avoid overspending.
2. Regularly Review and Adjust Thresholds
Change set spending mark and patterns during particular cycles such as peak sales seasons. Maintaining a review schedule for thresholds does ensure that they catch unusual activity without resetting false positive alarms.
3. Use AWS Budgets for Better Oversight
AWS Cost Anomaly Detection can be greatly enhanced with the use of AWS Budgets. AWS Budgets helps in setting up an overall limit while the anomaly detection tool ensures that limits are not breached by monitoring costs in real time. This synergetic relation enhances cloud spending visibility.
4. Automate Responses to Save Time and Money
Take action automatically when anomalies are detected. For example, set up alerts so when an anomaly alert is triggered, AWS Lambda stops all idle resources. This allows for the undertaking of spending reduction measures without manual effort.
AWS Cost Anomaly Detection Replacement: PUMP Cost Optimization
Pump is more than just a tool for detecting cost anomalies; it actively reduces your cloud costs. Let’s take an EC2 as an example to see how Pump works compared to AWS Cost Anomaly Detection.
How AWS Cost Anomaly Detection Works:
If your EC2 usage suddenly spikes, AWS Cost Anomaly Detection will flag this as an anomaly and alert you. But that’s where it stops; it identifies the issue but doesn’t help you lower your costs or prevent it from happening again.
How Pump Optimizes EC2 Costs:
Pump doesn’t just detect the spike; it takes action to save you money. For example:
Group Buying: We pool your EC2 usage with other customers, enabling you to access lower rates through volume discounts.
AI-Driven Optimization: We analyze your EC2 instances and suggest rightsizing (e.g., recommending smaller instance types if your current ones are underutilized) or switching to spot instances for better pricing.
Commitment Discounts: We identify consistent EC2 usage patterns and help you secure Reserved Instances or Savings Plans at discounted rates, saving 10-60% without overcommitting.
It's so easy to use, even for non-technical users, with an intuitive interface that streamlines the optimization process. Unlike anomaly detection tools that simply notify you of a cost issue, we solves the problem by directly reducing your EC2 costs; and it does this for AWS, GCP, and Azure. And that too, you can free to use, delivering instant and ongoing savings while keeping your infrastructure scalable.
Conclusion
AWS Cost Anomaly Detection is a must-have for organizations looking to take control of their cloud spending. It provides real-time alerts for anomalous spending along with identifying the underlying causes, enabling companies to actively manage their budgets in AWS.
If you are ready to discover unreliably high spending and surprise bills, begin by enabling AWS Cost Anomaly Detection. For improved optimization, use Pump alongside your detection setup to increase savings throughout your AWS environment.
