The process of shipping AWS Cost and Usage reports into Logz.io begins with enabling them in our AWS account.įirst, we need to create an S3 bucket that will contain the reports. In the next sections we will examine how to ship the reports into Logz.io’s ELK Stack using a Lambda function which also processes the data. Therefore, the biggest challenge is extracting insights from the reports. The result being larger and longer reports. And as your business grows and your application with it, you will begin using more and more AWS services. These reports can be extremely useful for keeping tabs on usage and costs, but their downside is obvious - they are extremely large and difficult to analyze. The screenshot below is an example of how detailed these reports are and what kind of information you can gather about your usage of AWS services. The report contains line items for each unique combination of AWS product, usage type, and operation that your AWS account uses, and the information can be aggregated either by the hour or by day. It’s worth noting that the prices in the report are estimated and are subject to change during the rest of the month as you use more of the services. AWS promises to update the report up to three times a day. Shall we see how? AWS Cost and Usage reportsĪWS cost and usage reports are CSV files that AWS delivers to an S3 bucket which you specify in your account. With the right dashboard, you can analyze and monitor the way you are using different AWS services and actually cut costs. Using these reports, you can track the amount of money you spend on DEV services or see which operation is the most expensive one. One way to make these adjustments and optimize costs is by making use of AWS Cost and Usage reports. This approach gives users amazing flexibility but also makes a lot of room for fine tuning. You pay at the end of the month only for the services you used, and just for that duration. Indeed, most of us will find ourselves walking a delicate tight rope, trying to find a balance between the performance of our applications and the costs their development and maintenance involves.ĪWS pricing is based on a pay-as-you-go approach. If you’re building a production-grade and business critical application on AWS, monitoring the resources it depends on and consumes is critical to gauge your operational and ongoing costs. In part 2 we will show how to analyze and monitor these reports using Kibana queries and visualizations. In part 1, we will describe how to set up a pipeline using a Lambda shipper. This blog series will describe how to ship and analyze AWS cost and usage reports using Lambda and Logz.io’s ELK Stack.
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