AWS Architecture Blog

Let’s Architect! Cost-optimizing AWS workloads

Every software component built by engineers and architects is designed with a purpose: to offer particular functionalities and, ultimately, contribute to the generation of business value. We should consider fundamental factors, such as the scalability of the software and the ease of evolution during times of business changes. However, performance and cost are important factors as well since they can impact the business profitability.

This edition of Let’s Architect! follows a similar series post from 2022, which discusses optimizing the cost of an architecture. Today, we focus on architectural patterns, services, and best practices to design cost-optimized cloud workloads. We also want to identify solutions, such as the use of Graviton processors, for increased performance at lower price. Cost optimization is a continuous process that requires the identification of the right tools for each job, as well as the adoption of efficient designs for your system.

AWS re:Invent 2022 – Manage and control your AWS costs

Govern cloud usage and avoid cost surprises without slowing down innovation within your organization. In this re:Invent 2022 session, you can learn how to set up guardrails and operationalize cost control within your organizations using services, such as AWS Budgets and AWS Cost Anomaly Detection, and explore the latest enhancements in the AWS cost control space. Additionally, Mercado Libre shares how they automate their cloud cost control through central management and automated algorithms.

Take me to this re:Invent 2022 video!

Work backwards from team needs to define/deploy cloud governance in AWS environments

Work backwards from team needs to define/deploy cloud governance in AWS environments

Compute optimization

When it comes to optimizing compute workloads, there are many tools available, such as AWS Compute Optimizer, Amazon EC2 Spot Instances, Savings Plans, and Graviton instances. Modernizing your applications can also lead to cost savings, but you need to know how to use the right tools and techniques in an effective and efficient way.

For AWS Lambda functions, you can use the AWS Lambda Cost Optimization video to learn how to optimize your costs. The video covers topics, such as understanding and graphing performance versus cost, code optimization techniques, and avoiding idle wait time. If you are using Amazon Elastic Container Service (Amazon ECS) and AWS Fargate, you can watch a Twitch video on cost optimization using Amazon ECS and AWS Fargate to learn how to adjust your costs. The video covers topics like using spot instances, choosing the right instance type, and using Fargate Spot.

Finally, with Amazon Elastic Kubernetes Service (Amazon EKS), you can use Karpenter, an open-source Kubernetes cluster auto scaler to help optimize compute workloads. Karpenter can help you launch right-sized compute resources in response to changing application load, help you adopt spot and Graviton instances. To learn more about Karpenter, read the post How CoStar uses Karpenter to optimize their Amazon EKS Resources on the AWS Containers Blog.

Take me to Cost Optimization using Amazon ECS and AWS Fargate!
Take me to AWS Lambda Cost Optimization!
Take me to How CoStar uses Karpenter to optimize their Amazon EKS Resources!

Karpenter launches and terminates nodes to reduce infrastructure costs

Karpenter launches and terminates nodes to reduce infrastructure costs

AWS Lambda general guidance for cost optimization

AWS Lambda general guidance for cost optimization

AWS Graviton deep dive: The best price performance for AWS workloads

The choice of the hardware is a fundamental driver for performance, cost, as well as resource consumption of the systems we build. Graviton is a family of processors designed by AWS to support cloud-based workloads and give improvements in terms of performance and cost. This re:Invent 2022 presentation introduces Graviton and addresses the problems it can solve, how the underlying CPU architecture is designed, and how to get started with it. Furthermore, you can learn the journey to move different types of workloads to this architecture, such as containers, Java applications, and C applications.

Take me to this re:Invent 2022 video!

AWS Graviton processors are specifically designed by AWS for cloud workloads to deliver the best price performance

AWS Graviton processors are specifically designed by AWS for cloud workloads to deliver the best price performance

AWS Well-Architected Labs: Cost Optimization

The Cost Optimization section of the AWS Well Architected Workshop helps you learn how to optimize your AWS costs by using features, such as AWS Compute Optimizer, Spot Instances, and Savings Plans. The workshop includes hands-on labs that walk you through the process of optimizing costs for different types of workloads and services, such as Amazon Elastic Compute Cloud, Amazon ECS, and Lambda.

Take me to this AWS Well-Architected lab!

Savings Plans is a flexible pricing model that can help reduce expenses compared with on-demand pricing

Savings Plans is a flexible pricing model that can help reduce expenses compared with on-demand pricing

See you next time!

Thanks for joining us to discuss cost optimization! In 2 weeks, we’ll talk about in-memory databases and caching systems.

To find all the blogs from this series, visit the Let’s Architect! list of content on the AWS Architecture Blog.

Luca Mezzalira

Luca Mezzalira

Luca is Principal Solutions Architect based in London. He has authored several books and is an international speaker. He lent his expertise predominantly in the solution architecture field. Luca has gained accolades for revolutionizing the scalability of front-end architectures with micro-frontends, from increasing the efficiency of workflows, to delivering quality in products.

Federica Ciuffo

Federica Ciuffo

Federica is a Solutions Architect at Amazon Web Services. She is specialized in container services and is passionate about building infrastructure with code. Outside of the office, she enjoys reading, drawing, and spending time with her friends, preferably in restaurants trying out new dishes from different cuisines.

Vittorio Denti

Vittorio Denti

Vittorio Denti is a Machine Learning Engineer at Amazon based in London. After completing his M.Sc. in Computer Science and Engineering at Politecnico di Milano (Milan) and the KTH Royal Institute of Technology (Stockholm), he joined AWS. Vittorio has a background in distributed systems and machine learning. He's especially passionate about software engineering and the latest innovations in machine learning science.

Zamira Jaupaj

Zamira Jaupaj

Zamira is an Enterprise Solutions Architect based in the Netherlands. She is highly passionate IT professional with over 10 years of multi-national experience in designing and implementing critical and complex solutions with containers, serverless, and data analytics for small and enterprise companies.