Unleash the Power of Tagging with AWS Tag Editor

Tagging is a method of categorizing & organizing resources in a cloud computing environment, such as AWS. Metadata can be added to resources, which can be used to organize, categorize & track costs, identify resources & enforce compliance policies.

Tagging resources can help you make sense of and control your AWS costs. For instance, you can tag resources with the name of the project or team they are part of, so you can see how much each project or team costs. You can also tag resources with the environment they belong to (e.g. production, staging, development) to spot resources that are not being used and shut them down. Plus, you can use tagging to stick to compliance policies, such as tagging resources with the owner's name to make sure that only allowed people access and change them.

AWS Tag Editor is a tool that enables users to manage and organize tags across multiple services and linked accounts, quickly view and edit tags, search for resources based on tags, and create custom reports for cost monitoring.

Keep your spend in check with AWS Cost Explorer

AWS Cost Explorer is a free and interactive tool that allows you to visualize and analyze your AWS costs and usage across multiple services and linked accounts. You can quickly understand how much you are spending on AWS services and identify areas where you can optimize costs.

1. Set up cost allocation tags: Tagging your resources with metadata can help you understand which resources belong to which projects or teams. Cost allocation tags can be used to assign costs to specific projects or teams, so you can see how much each one is costing you.
2. Create custom cost reports: AWS Cost Explorer allows you to create custom reports based on your cost and usage data. You can create reports that show costs by service, by tag, or by account. This can help you identify areas where you can optimize costs, such as by reducing usage of expensive services or by shutting down unused resources.
3. Use the forecast feature: AWS Cost Explorer has a built-in feature that allows you to forecast your costs for the next few months based on your past usage. This can help you budget for future costs and make informed decisions about your resource usage.
4. Compare your costs with other accounts: This is one of the most overlooked feature and we’ve not seen a lot of our customers use this. You can compare your costs with other accounts, even those that are not linked to your AWS Organizations. This can help you identify best practices and cost optimization opportunities that others have already implemented.

You can use the Cost Explorer API in conjunction with the Cost Explorer console to create a more automated and efficient way to monitor your AWS costs. For example, you could use the API to retrieve cost data on a regular basis, then use the console to create custom reports or set budgets and alerts. Or, you could use the API to retrieve cost data and send it to your own data visualization tool for further analysis. Leveraging this API + console combo can help you fasten your workflows.

A closer look at what’s missing in AWS Anomaly Detection

AWS Anomaly Detection is a machine learning-based service that automatically detects anomalies in your time series data. While it’s all good to have a second pair of eyes to monitor your cost, it falls short in certain aspects:

1. Limited customization options: While you can configure some aspects of how the service detects anomalies, such as the frequency of data points and the number of days of data to use, there is currently a limited ability to customize how the service works. For example, you cannot currently specify your own machine learning models or custom detection algorithms.
2. Limited support for data pre-processing: AWS Anomaly Detection does not provide much support for data pre-processing, such as data cleaning or feature extraction. This means that you will need to do this work yourself before using the service.
3. Limited anomaly classification: Currently, AWS Anomaly Detection only classifies anomalies as "positive" or "negative." It does not provide more granular classification, such as "seasonal" or "level shift" anomalies.

Leveraging the combo of CloudWatch Alarms and AWS Cost and Usage Report

You can use CloudWatch Alarms to set alarms that trigger when certain conditions are met, such as when your costs exceed a certain threshold. When an alarm is triggered, you can configure it to perform one or more actions, such as sending an SNS message, stop or terminate an EC2 instance, or even autoscale an ASG.

To monitor cloud costs with CloudWatch Alarms, you can use the Cost and Usage Report (CUR) which is a detailed report of your costs and usage. By creating alarms on specific metrics in the CUR, such as "Estimated charges" or "DataTransfer-Out-Bytes" you can monitor your costs and be notified when they exceed a certain threshold.

For example, you can set an alarm to notify you when your estimated charges for a specific service or linked account exceed a certain budget. This way, you can take action to reduce costs before they become too high. Additionally, you can also use CloudWatch Metrics which can be used to monitor your AWS resource usage and performance.

How to setup Cost and Usage Reports in AWS?

Here are the steps to set up AWS Cost and Usage Reports:

1. Log in to your AWS account and navigate to the Cost Management Console.
2. In the navigation pane, choose "Reports", then choose "Create report"
3. In the "Create report" page, give a name to the report, choose the time range and the frequency of the report.
4. In the "Additional settings" section, you can choose to include resource IDs, tags, and other additional details in the report.
5. In the "Delivery options" section, you can choose to have the report delivered to an S3 bucket, an email address or both.
6. In the "Permissions" section, you can choose who has access to the report.
7. Once you have set up the report, you can view the data in the S3 bucket or email.
8. To schedule the report to run automatically, you can use the AWS Cost Explorer, to set up a recurring report with the same settings.
9. You can also set up alerts based on the cost and usage data from the report, using AWS Budgets.
10. To access the data for programmatic analysis, you can use the AWS Cost and Usage API, which allows you to retrieve the data in JSON or CSV format.

Navigating the limitations of AWS Cost and Usage Reports

AWS Cost and Usage Reports (CUR) provide a detailed view of your AWS costs and usage, which can be helpful for understanding and managing your AWS expenses. Here are a few things to keep in mind when using these reports:

1. Data availability: CUR data is typically available with a delay of 24-48 hours, therefore it's not a real-time monitoring tool. Keep this in mind when using the data in the report.
2. Data granularity: CUR data is available at the hourly granularity level, which can provide a lot of detail, but it can also make it harder to understand the data. To make it easier to understand, you can aggregate the data by service, by account, or by tag.
3. Data accuracy: The CUR data is based on usage and cost data that is provided by the various AWS services. It is possible that this data may be delayed or inaccurate, so keep this in mind when interpreting the data.
4. Data security: CUR data includes sensitive information such as your AWS usage and costs, therefore it's important to keep the data secure. You can use Amazon S3 encryption, SNS notifications, and IAM policies to secure the data.
5. Cost Allocation: CUR data can be useful for cost allocation, but it doesn't provide the full picture. To get a complete picture of your costs, you should also use tags, AWS Cost Explorer, and CloudWatch Alarms.

Setting up QuickSight dashboard with AWS Cost and Usage Reports

When setting up a QuickSight dashboard for monitoring your AWS costs, you will need to take a few additional steps to ensure that you are able to view and analyze your cost data effectively. Here's an overview of how to set up a QuickSight dashboard for cost monitoring:

1. Create a new data set for your cost data: Connect to your AWS Cost and Usage Report (CUR) data source and select the data you want to use for cost monitoring. You can also use other data sources, such as CloudWatch Metrics, to monitor your resource usage and costs.
2. Create visualizations for cost data: Create visualizations, such as line charts, bar charts, and pie charts, that show your costs by service, by account, or by tag. You can also create visualizations that show your costs over time or by usage.
3. Create a dashboard for cost monitoring: Add the visualizations you created in the previous step to a new dashboard. This will allow you to view your costs in one place and compare them to other data.
4. Use filters and calculations: Use QuickSight's filters and calculations to slice and dice your data, and drill down to specific cost data. You can also use calculated fields to create custom metrics that help you understand your costs better.
5. Set up alerts: Use CloudWatch Alarms to set up alerts for when your costs exceed a certain threshold. You can then create visualizations that show when these alerts are triggered, and use them in your dashboard.
6. Schedule Data Refresh: AWS CUR data is not real-time, it's delayed by 24-48 hours. Schedule your data refresh to ensure your dashboard always reflects the latest data.

By following these steps, you can set up a QuickSight dashboard that allows you to view and analyze your AWS costs in an interactive and intuitive way.