Advanced Developing on AWS Course Overview

Advanced Developing on AWS Course Overview

The Advanced Developing on AWS course is designed for individuals who are familiar with software development and AWS services, aiming to enhance their skills in building and deploying scalable, reliable applications on the AWS platform. Throughout the course, learners will delve into a range of advanced topics, starting with a recap of core AWS fundamentals like global infrastructure and SDK usage, moving through Architectural styles, and exploring Migration strategies with a focus on Monolithic applications.

The course emphasizes gaining agility through DevOps practices, transitioning from monolithic architectures to microservices, and implementing Polyglot persistence. Learners will also gain insights into designing Resilient systems, handling Distributed complexity, and ensuring Security and observability within their applications. By integrating services such as AWS Elastic Beanstalk, AWS Lambda, API Gateway, and Amazon Cognito, participants will learn how to handle real-world challenges of modern application development. The Advanced Developing on AWS course is a comprehensive program that empowers developers with the knowledge and tools to optimize their AWS-based applications for scalability, resilience, and maintainability.

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Successfully delivered 8 sessions for over 54 professionals

Training Advantage
Number of Learners
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Successfully delivered 8 sessions for over 54 professionals

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  • Live Training (Duration : 24 Hours)
  • Per Participant
  • Classroom Training price is on request
  • Including Official Coursebook

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

To ensure that participants are adequately prepared for the Advanced Developing on AWS course and can fully benefit from its content, the following minimum prerequisites are recommended:


  • Basic understanding of core AWS services and AWS architecture, including experience with compute, networking, storage, and database AWS services.
  • Familiarity with AWS CloudFormation and the AWS Command Line Interface (CLI).
  • Proficiency in at least one high-level programming language, such as Java, Python, or Node.js.
  • Foundational knowledge of the software development lifecycle and modern application development processes including DevOps practices.
  • Practical experience with version control systems, such as Git.
  • An understanding of the concepts and terminology related to cloud computing and AWS, including regions, Availability Zones, and security groups.
  • Basic knowledge of web development and common internet protocols (HTTP, DNS).

These prerequisites are aimed to provide the foundational knowledge required to comprehend the advanced topics covered in the course. However, a willingness to learn and the ability to adapt to new technologies are equally important for success in this training program.


Target Audience for Advanced Developing on AWS

  1. The Advanced Developing on AWS course is designed for experienced developers seeking to deepen their cloud expertise and master AWS services.


  • Experienced AWS Developers
  • Cloud Solutions Architects
  • DevOps Engineers
  • Software Engineers transitioning to the cloud
  • IT Professionals with a background in software development
  • Systems Engineers with cloud experience
  • Technical Leads managing cloud-based projects
  • Application Developers looking to leverage AWS for scalability and reliability
  • Cloud Technical Consultants
  • System Integrators working with AWS services
  • Enterprise Architects planning cloud adoption or migration


Learning Objectives - What you will Learn in this Advanced Developing on AWS?

Introduction to Advanced Developing on AWS Course Learning Outcomes

Gain advanced skills in AWS development for building, deploying, and managing applications with agility, resilience, and security through hands-on experience and best practices.

Learning Objectives and Outcomes

  • Understand the AWS Global Infrastructure and apply best practices in authentication and SDK usage to ensure robust cloud application development.
  • Design and migrate monolithic applications to AWS using architectural patterns and Elastic Beanstalk, ensuring scalability and maintainability.
  • Implement DevOps culture with AWS developer tools like CodeCommit, CodeBuild, CodeDeploy, CodePipeline, and CodeStar to automate build, release, and deployment processes.
  • Transform monolithic architectures into microservices using domain-driven design, Lambda, API Gateway, and CloudFormation, while ensuring system decoupling and a serverless mindset.
  • Master polyglot persistence and manage distributed system complexity, ensuring data integrity and performance with services like DynamoDB, CAP Theorem, and AWS Step Functions.
  • Enhance application resilience and scalability with patterns like CQRS, event sourcing, and circuit breakers, utilizing AWS services such as Kinesis, SQS, and SNS.
  • Implement security best practices with Amazon Cognito for authentication and manage API access control, while using AWS X-Ray for debugging and traceability.
  • Adopt asynchronous and synchronous decoupling strategies to handle communication between services and components in a distributed system.
  • Design for failure using serverless event buses and caching strategies, ensuring high availability and performance.
  • Gain practical experience and expertise in developing microservices on AWS with a focus on hands-on labs and real-world examples.

Technical Topic Explanation

SDK usage

An SDK, or Software Development Kit, is a collection of software tools and programs used by developers to create applications for specific platforms. SDKs simplify the development process by providing critical building blocks needed to develop applications more efficiently. These typically include compile libraries, debuggers, and hardware or software guidelines. By utilizing an SDK, developers can ensure their software is compatible and optimized for a particular operating system or platform, reducing the need for from-scratch programming and accelerating the development cycle. This is particularly useful for advanced developing on platforms like AWS, where SDKs can leverage cloud functionalities effectively.

Architectural styles

Architectural styles in software engineering are distinct methods used to plan and construct software systems. Each style, such as Layered, Microservices, or Event-driven, provides guidelines on organizing system components and managing data flow and control. These styles influence functionality, scalability, and maintenance, and adopt a specific way to handle requests and distribute responsibilities among components. Choosing the right architectural style depends on the specific needs and constraints of the project, impacting system performance and future adaptability.

Migration strategies

Migration strategies refer to the plans and methods used by organizations to move their data, applications, and IT processes from one environment to another, typically from on-premises to the cloud. This process includes assessing the current environment, choosing the right cloud provider, and determining the most efficient way to transfer data and applications without causing significant downtime or data loss. Effective migration strategies ensure compatibility between old and new systems, address security concerns, and optimize performance post-migration to harness the full benefits of the cloud environment.

Monolithic applications

Monolithic applications are single-tiered software where the user interface, data access logic, and data storage are all combined into a single program from a single platform. This structure makes it simple to develop, deploy, and scale in environments where applications remain relatively small and straightforward. However, as an application grows, updates and scaling can become complex due to the intertwined components. This often leads to challenges in continuous integration and deployment, potentially affecting productivity and agility in dynamic computing environments like advanced development on AWS.

DevOps

DevOps is a combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity. This approach emphasizes collaboration between software developers and other IT professionals while automating the process of software delivery and infrastructure changes. DevOps aims to shorten the development life cycle, enabling continuous delivery with high software quality. It involves frequent, incremental changes to code versions, which allows for quick detection and correction of problems. This methodology fosters a culture where building, testing, and releasing software can happen rapidly, reliably, and more frequently.

Microservices

Microservices are a software development technique where an application is divided into small, independent parts called services. Each service performs a specific function and communicates with other services through well-defined interfaces. This approach makes it easier to develop, test, and maintain each part of the application individually. The architecture promotes scalability and resilience, allowing updates and improvements to be made to one service without impacting others. Microservices are especially popular for deploying applications in cloud environments like AWS, enhancing continuous delivery and facilitating advanced development practices.

Polyglot persistence

Polyglot persistence refers to the practice of using different types of database storage technologies to handle varied data storage needs within a single application. This approach allows developers to choose the most effective storage solution for specific types of data, enhancing performance, scalability, and manageability. By tailoring database choices to the unique challenges of each data type—whether it's text, numbers, or multimedia—teams can optimize data operations and drive efficiency in response to diverse application demands.

Distributed complexity

Distributed complexity refers to the study and measurement of the computational complexity and resources required when solving computational problems across multiple interconnected computers or systems, instead of a single processor. This field evaluates how the distribution of data and tasks affects the time and communication needed to solve problems. Key concerns include how efficiently problems can be decomposed into smaller tasks, how these tasks are distributed across systems, and the coordination and communication overhead involved. Understanding distributed complexity helps in designing more efficient algorithms and systems for large-scale, distributed computing environments.

Security and observability

Security in computing involves implementing measures and technologies that protect data, systems, and networks from unauthorized access or attacks. Observability, meanwhile, is the capability to monitor systems and applications in real-time, analyzing data from various sources to understand their performance and health deeply. It helps promptly identify and resolve issues, ensuring systems are efficient and operational. Understanding both is crucial for maintaining robust, reliable digital services and infrastructure.

Resilient systems

Resilient systems are designed to handle disruptions and failures without significant impact on their performance or functionality. They continue to operate even when parts of the system fail. By having backups, redundant components, and effective failover processes, these systems can quickly recover and maintain service continuity. This resilience is crucial in environments where constant availability and reliability are key, such as in critical infrastructure, financial services, and healthcare systems. Implementing resilient systems ensures that services can withstand various challenges, including technical malfunctions, cyber-attacks, and natural disasters, thereby minimizing downtime and maintaining user trust and business continuity.

AWS Elastic Beanstalk

AWS Elastic Beanstalk is a service provided by Amazon Web Services that helps you deploy and manage applications in the cloud without worrying about the infrastructure that runs them. You simply upload your code, and Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, and auto-scaling to application health monitoring. This service is ideal for developers who want to focus on writing code rather than managing the infrastructure. Elastic Beanstalk supports several programming languages and development stacks, so you can use it for a wide range of applications, making it a versatile tool for advanced developing on AWS.

AWS Lambda

AWS Lambda is a service provided by Amazon Web Services that allows you to run code without provisioning or managing servers. You simply upload your code, and Lambda takes care of everything required to run and scale it with high availability. You pay only for the compute time you consume, making it a cost-effective way to run applications that handle varying levels of traffic. Lambda supports multiple programming languages and integrates well with other AWS services, making it a powerful tool for building and deploying applications quickly and efficiently. It is ideal for event-driven or periodic tasks.

API Gateway

An API Gateway is a management tool that sits between clients and backend services, acting as a reverse proxy to aggregate various service APIs. It provides a central point to control API traffic, enforces policies, enables security measures, authenticates traffic, and handles load balancing and analytics. This gateway helps enterprises to efficiently manage API ecosystems, ensuring smooth data transfer, and service interaction, simplifying development operations and providing a better user experience by optimizing request routing and protocol translation.

Amazon Cognito

Amazon Cognito is a service provided by AWS that helps you manage user authentication and access for your apps, without worrying about backend code for handling secure sign-in and sign-up processes. It supports both social identity providers like Google or Facebook, and enterprise identities through SAML 2.0. With Cognito, you can keep your application’s user data safe with options for multi-factor authentication and encryption, making it easier to scale securely as your number of users grows. This service integrates seamlessly with other AWS services, allowing for streamlined development and deployment processes.

Target Audience for Advanced Developing on AWS

  1. The Advanced Developing on AWS course is designed for experienced developers seeking to deepen their cloud expertise and master AWS services.


  • Experienced AWS Developers
  • Cloud Solutions Architects
  • DevOps Engineers
  • Software Engineers transitioning to the cloud
  • IT Professionals with a background in software development
  • Systems Engineers with cloud experience
  • Technical Leads managing cloud-based projects
  • Application Developers looking to leverage AWS for scalability and reliability
  • Cloud Technical Consultants
  • System Integrators working with AWS services
  • Enterprise Architects planning cloud adoption or migration


Learning Objectives - What you will Learn in this Advanced Developing on AWS?

Introduction to Advanced Developing on AWS Course Learning Outcomes

Gain advanced skills in AWS development for building, deploying, and managing applications with agility, resilience, and security through hands-on experience and best practices.

Learning Objectives and Outcomes

  • Understand the AWS Global Infrastructure and apply best practices in authentication and SDK usage to ensure robust cloud application development.
  • Design and migrate monolithic applications to AWS using architectural patterns and Elastic Beanstalk, ensuring scalability and maintainability.
  • Implement DevOps culture with AWS developer tools like CodeCommit, CodeBuild, CodeDeploy, CodePipeline, and CodeStar to automate build, release, and deployment processes.
  • Transform monolithic architectures into microservices using domain-driven design, Lambda, API Gateway, and CloudFormation, while ensuring system decoupling and a serverless mindset.
  • Master polyglot persistence and manage distributed system complexity, ensuring data integrity and performance with services like DynamoDB, CAP Theorem, and AWS Step Functions.
  • Enhance application resilience and scalability with patterns like CQRS, event sourcing, and circuit breakers, utilizing AWS services such as Kinesis, SQS, and SNS.
  • Implement security best practices with Amazon Cognito for authentication and manage API access control, while using AWS X-Ray for debugging and traceability.
  • Adopt asynchronous and synchronous decoupling strategies to handle communication between services and components in a distributed system.
  • Design for failure using serverless event buses and caching strategies, ensuring high availability and performance.
  • Gain practical experience and expertise in developing microservices on AWS with a focus on hands-on labs and real-world examples.