
Discover how AWS Kiro's IDE enables cloud-based, agent-based AI development with tools like Cloud9 and Qiro, featuring wipe coding and inline code assistants for faster coding.
Monitor live application performance to detect bottlenecks and maintain reliability, using latency, throughput, memory profiling, cpu usage, error rates, and real-time dashboards to proactively optimize scalable systems.
Understand how MCPs connect AI agents with external services via a standardized tool interface, using GitHub and file system MCP servers to perform read and write operations securely.
Install a power in AWS Kiro to give the AI agent domain-specific expertise on demand, packaging tools, workflows, MCP integrations, and validation logic.
Master IAM controls and permission management in AWS Kiro, focusing on roles, policies, and least-privilege access. Use profiles, external identities, and access analyzer to enforce minimum access.
Learn to monitor cloud environments with AWS CloudTrail, tracking API calls, IAM activity, and security events to support compliance, incident response, and audit readiness.
Enable only required extensions per project and per task, scope the context, and use performance-aware extensions to reduce latency and keep AWS Kiro's development workflow fast.
Disclosure: This course contains the use of artificial intelligence.
Cloud computing and AI are transforming how modern applications are built, and combining both gives you a powerful advantage. In this course, you will learn how to build intelligent, scalable applications using Amazon Web Services (AWS) Kiro and modern cloud development practices.
This course is designed to help you understand how AI-powered applications can be developed, automated, and deployed using AWS services. You will explore how to design cloud workflows, integrate APIs, and create scalable architectures using serverless technologies.
We start from the fundamentals and gradually move into building real-world projects. You will learn how to connect services, automate tasks, manage data, and deploy applications in a cloud environment. The focus is on practical learning, so you will build complete solutions instead of just learning theory.
By the end of this course, you will be able to confidently design and deploy AI-driven cloud applications using AWS. You will also gain a strong understanding of how modern cloud systems work and how automation can improve productivity and efficiency.
Whether you are a beginner exploring cloud computing or a developer looking to expand into AI-powered applications, this course will provide you with the skills needed to build real-world solutions using AWS Kiro.