This course covers cost optimization techniques and strategies for various commonly used AWS services and workloads. It focuses on helping learners identify opportunities to reduce cloud spend through tactics like rightsizing, leveraging reserved capacity, and taking advantage of serverless offerings.
It provides an overview of techniques for managing and optimizing data transfer costs across AWS services and regions, followed by the best practice guidance for monitoring and optimizing cost of commonly used core networking services and features. The course also explores best practices for optimizing costs in container-based architectures using Amazon ECS and EKS, as well as strategies for optimizing costs in analytics workloads powered by Amazon Athena, Amazon EMR, and Amazon Redshift. Additionally, this course covers how to leverage artificial intelligence, machine learning, and generative AI capabilities in a cost-effective manner using services like Amazon SageMaker, Amazon Bedrock, and Amazon Q
- Course level: Intermediate
- Duration: 60 minutes
Activities
On-demand, self service training, videos, and knowledge checks.
Course objectives
In this course, you'll learn:
- The fundamentals and importance of defining a cost-aware culture.
- Gain insights into why cost visibility is crucial and strategies to achieve it.
- Gain knowledge in how to systematically optimize AWS cost across your business.
- The course also emphasizes the importance of cost forecasting and how it supports in your consumption-based pricing journey.
Target audience
This course is aimed at: Developer, Architect, FinOps Practitioner/Manager, DevOps Engineer, IT Manager
Requisites
Fundamental knowledge of core AWS networking, analytics, containers, and AI/ML services.
It's also recommended to have foundational knowledge of AWS Cloud Financial Management solutions and implementation strategies. Alternatively, we recommend completing Part 1 and Part 2 of the AWS Cloud Financial Management Foundations course.
Course outline
Course Information - Introduction
Cost Optimization Techniques for Commonly Used Services:
- Data Transfer
- Networking
- Analytics
- Containers
- AI/ML and Generative AI
Additional Resources & Getting Help
