Cloud Global

We invite members of the IBM Cloud community to share their insights and experiences in achieving the delicate balance between cost optimization and performance enhancement within AWS cloud environments. Whether you're an AWS architect, a certified with AWS Certification, or a business leader managing AWS resources, your perspectives on best practices, strategies, and real-world examples of achieving cost-efficiency without compromising performance are highly valued. By exchanging ideas and success stories, we aim to collectively enhance our understanding of AWS cloud optimization and help others navigate the complex terrain of cloud cost management.

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Sarfaraz Khan
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Given the wide range of services on AWS, the list of strategies one can deploy is perhaps too long. However, at a high level, I've encountered and used the following categories of strategies over the years:

1- Understanding the nature of the application and resource consumption patterns: These have a huge impact on selecting (or reassessing) the right services to get the job done. It is not rare for developers to jump on hypes without careful consideration of whether it is the right thing for their application. So before starting to use a new programming language, a new service, a new DB, a new AI model, etc., make sure you fully understand what to expect in this transition. An important factor to consider is that workloads change, so do the cost model and performance of various services. So, as you can imagine, this is an iterative process.
2- Rightsizing resources: The need for determining the right configuration is pretty much universal: e.g., picking the right VM type, the right storage class, the right architecture, the right container size, etc. These simple decisions can have an immense impact on the cost and performance optimality of using cloud services (not just limited to AWS). The challenge is that there are so many of these knobs, that prevent spending precious developer-hours (specially, short term). However, as soon as things scale and in the long term, these can make a big difference, often without high overhead on re-architecting the application. It then becomes important to use high quality tools to assist one in this tuning process. (check out this recent paper of ours to see the importance of rightsizing AWS Lambda functions, and the tool we built to co-optimize their cost and performance).