Innovate with AWS Cloud

Learning Objectives

After completing this unit, you’ll be able to:

Summarize innovation with the AWS Cloud.
Explain the benefit of serverless computing.
Describe the purpose of AWS Artificial Intelligence (AI) services.
Identify the use of Amazon SageMaker for machine learning (ML).

Much of this module focuses on the best practices and strategies to help you migrate effectively into the AWS Cloud. What happens after you’ve migrated?

As your organization evolves, you identify new ways to refine your processes, new products to offer your customers, and new ideas that can help you stand out from the competition. AWS provides the technology to support you with agile development, rapid deployment, and unlimited scale to achieve your goals.

What Does It Mean to Innovate in the Cloud?

Arrow flying upward through a square

Innovation drives business growth. The following roadmap guides you to even more efficiency, agility, and quicker time-to-achievement as you seek opportunities for innovating in the cloud.

Migrate to the cloud to free up IT resources. Move to the cloud to lower infrastructure costs, reduce downtime, boost IT staff productivity, and deliver more features for your customers.
Modernize development for rapid innovation. Replace your overly complex applications with microservices that deploy and scale independently.
Analyze your data faster for deeper insights. Use machine learning and analytics tools to help you make data-driven decisions, deepen your customer relationships, and reduce business risk.
Reinforce security, compliance, and resiliency. Elevate the security posture of your business to ensure your data stays private, resilient, and available.
Empower teams to boost speed and agility. Build small, decentralized teams to own and operate what they build, and improve the pace of innovation with faster decision-making.
Upskill your workforce to bridge the talent gap. Train and equip your teams to operate successfully in the cloud.

Innovate with AWS Services

Plant growing

When reviewing how to use AWS services, it’s important to focus on the desired outcomes. You are equipped to drive innovation in the cloud if you can clearly articulate:

The current state
Where you want to end up
The problems you are trying to solve

Take a moment to consider some of the paths to explore in the future as you continue on your cloud journey.

Go Serverless

With AWS, serverless refers to applications that don’t require you to provision, maintain, or administer servers. You don’t need to worry about fault tolerance and availability. AWS handles those capabilities for you.

AWS Lambda is an example of a service that you can use to develop serverless applications. You learn more about it in Core AWS Services. If you design your architecture to trigger Lambda functions to run your code, then you can bypass the need to manage a fleet of servers.

Building your architecture with serverless applications allows your developers to focus on their core product instead of managing and operating servers.

Use Artificial Intelligence

AWS offers a variety of services powered by artificial intelligence (AI). You can convert speech to text with Amazon Transcribe, discover patterns in text with Amazon Comprehend, and identify potentially fraudulent online activities with Amazon Fraud Detector.

Additionally, AWS has introduced several new AI services to expand its offerings.

Amazon Q is an AI-powered assistant. It offers a suite of different products that can help with tasks such as summarizing documents, answering questions, generating code, creating detailed and customizable data stories, and more. Amazon Q can be integrated into existing workflows and applications, making it easier for users to access information and complete tasks. For more information, see Amazon Q.

Amazon Bedrock provides access to high-performance foundation models (FMs) from leading AI companies through a single API.

With Amazon Bedrock’s comprehensive capabilities, you can experiment with a variety of top FMs, privately customize them with your data using techniques such as fine-tuning and retrieval augmented generation (RAG), and create managed agents that execute complex business tasks——all without writing any code. For more information, see Amazon Bedrock.

PartyRock is an educational tool for building and playing with generative AI applications. With PartyRock, you can learn about the techniques and capabilities needed to make the most of generative AI, including understanding different models’ strengths, experimenting with different text-based prompts, and chaining prompts together. For more information, see PartyRock.

Benefit from Machine Learning

Traditional machine learning (ML) development can be complex, expensive, time-consuming, and error-prone. AWS offers Amazon SageMaker to remove the heavy lifting from the process and empower you to build, train, and deploy ML models quickly.

You can use ML to analyze data, solve complex problems, and predict outcomes before they happen.

Innovation Wrap-Up

In this module, you explore approaches you can take to prepare your organization for a successful cloud adoption journey, strategies for migrating from an on-premises environment to the AWS Cloud, and how you can optimize for innovation.

As you continue to invent on behalf of your customers, the AWS Cloud platform will continue to expand every day to provide you the tools you need to achieve your goals.

Move on to the next module in this trail to learn about the AWS Certified Cloud Practitioner Exam and get tips on how to prepare.

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