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Starts 5 June 2025 00:40

Ends 5 June 2025

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Managing Costs for Amazon Bedrock

Discover how to optimize Amazon Bedrock costs through token management, workload configuration, and strategic techniques like prompt engineering and response caching for cost-efficient AI solutions.
via Pluralsight

659 Courses


33 minutes

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Overview

In today’s technology landscape, AI is here to stay, and organizations that fail to embrace it risk losing competitiveness. Amazon Bedrock provides powerful tools to help achieve these goals.

But the real challenge is riding the wave without breaking the budget along the way. In this course, Managing Costs for Amazon Bedrock, you’ll learn how to identify cost components and optimize workloads by implementing cost effective strategies without sacrificing performance.

First, you’ll explore Amazon Bedrock’s key cost drivers, breaking down how token-based charges, model invocations, and request frequency impact costs. Next, you’ll discover how different workload configurations impact costs and identify key areas for optimization, such as data transfer, API calls, and AWS integrations.

Finally, you’ll learn how to implement cost-saving strategies, including prompt engineering, response caching, and efficient resource allocation. When you’re finished with this course, you’ll have the skills and knowledge to manage costs for Amazon Bedrock to ensure high-performance AI solutions while maintaining cost efficiency.

Syllabus

  • Introduction to Amazon Bedrock
  • Overview of Amazon Bedrock and its capabilities
    Importance of managing costs in AI implementations
  • Understanding Cost Components
  • Token-based charges
    Model invocations
    Request frequency and its impact on costs
  • Identifying Key Cost Drivers
  • Analyzing workload configurations
    Evaluating data transfer costs
    Assessing API calls and AWS integrations
  • Cost Optimization Techniques
  • Strategies for reducing data transfer costs
    Optimizing API usage and invocations
  • Implementing Cost-Saving Strategies
  • Introduction to prompt engineering
    Techniques for response caching
    Efficient resource allocation practices
  • Practical Applications and Case Studies
  • Real-world examples of cost management in Amazon Bedrock
    Analysis of successful cost optimization case studies
  • Monitoring and Managing Costs
  • Tools and services for cost tracking within AWS
    Setting up alerts and budgets to prevent overspending
  • Course Wrap-Up
  • Key takeaways and final thoughts
    Additional resources for continued learning
  • Assessment and Certification
  • Course quiz to test understanding
    Certification process and prerequisites

Taught by

Chris Espinoza


Subjects

Programming