About the course

Description:

A "Live Cloud AWS Project Experience" refers to hands-on experience working with Amazon Web Services (AWS) to design, implement, and manage cloud-based applications or infrastructure in a live, production environment. These projects often involve various AWS services to build scalable, secure, and cost-efficient systems that meet business needs. Below is an outline of what this experience typically involves:

1. Cloud Infrastructure Setup & Management:

• Virtual Machines (EC2): Setting up, configuring, and managing Amazon EC2 instances to run applications or services in the cloud. This includes choosing the right instance types, configuring security groups, managing key pairs, and setting up auto-scaling groups.
• Elastic Load Balancing (ELB): Distributing incoming traffic across multiple EC2 instances to ensure high availability and reliability. This involves configuring Application Load Balancer (ALB) or Network Load Balancer (NLB), depending on the use case.
• Virtual Private Cloud (VPC): Designing secure networks in AWS by configuring VPCs, subnets, route tables, security groups, and network ACLs. This setup allows users to isolate and secure applications while enabling private or public access as needed.

2. Storage and Database Solutions:

• Amazon S3 (Simple Storage Service): Setting up scalable object storage with S3 for static files, backups, and media storage. This includes configuring lifecycle policies, versioning, and secure access.
• Amazon RDS (Relational Database Service): Setting up and managing relational databases using RDS for MySQL, PostgreSQL, SQL Server, or Oracle. This involves database backup strategies, automatic scaling, performance tuning, and replication.
• Amazon DynamoDB: Implementing NoSQL databases using DynamoDB to support fast, scalable, and high-availability key-value store use cases.
• Amazon EFS (Elastic File System): Setting up a scalable file storage solution for EC2 instances with EFS, allowing shared access between multiple instances in a VPC.

3. Compute & Serverless Architecture:

• AWS Lambda (Serverless): Designing serverless applications using AWS Lambda, which automatically scales the compute power based on the number of incoming requests. This includes integrating Lambda with other AWS services like API Gateway, DynamoDB, and S3.
• AWS Elastic Beanstalk: Deploying and managing applications in Elastic Beanstalk, which abstracts away infrastructure management and handles scaling and deployment automatically.

4. Automation & Infrastructure as Code (IaC):

• AWS CloudFormation: Writing CloudFormation templates to automate the provisioning of infrastructure resources such as EC2, RDS, and VPCs in a repeatable and version-controlled manner.
• AWS CDK (Cloud Development Kit): Using AWS CDK to define cloud resources programmatically with higher-level languages (Python, TypeScript, Java), reducing boilerplate code and improving developer productivity.

5. Security & Access Control:

• IAM (Identity and Access Management): Configuring IAM roles, policies, and users to securely manage access to AWS resources. This includes setting up role-based access control (RBAC) for applications and limiting access to sensitive resources using least-privilege principles.
• AWS KMS (Key Management Service): Managing encryption keys for secure data storage and transmission by integrating KMS with services like S3, RDS, and EC2.
• AWS WAF (Web Application Firewall): Protecting applications from common web exploits and malicious traffic using AWS WAF.

6. Networking & Content Delivery:

• AWS CloudFront (CDN): Implementing CloudFront to distribute content globally with low latency by caching static files and dynamically generating content from origin servers.
• Route 53 (DNS): Configuring Route 53 to manage DNS records for high availability and fault tolerance, including routing traffic to healthy resources based on geo-location or failover conditions.
• VPN & Direct Connect: Setting up VPN connections and AWS Direct Connect to establish private, secure communication between on-premises data centers and AWS cloud resources.

7. Monitoring, Logging & Performance Optimization:

• Amazon CloudWatch: Setting up CloudWatch for monitoring AWS resources (like EC2, RDS, Lambda) and custom metrics. This includes creating dashboards, setting alarms, and automating responses to performance issues.
• AWS X-Ray: Using X-Ray to analyze and debug distributed applications, enabling end-to-end tracing of requests, which helps optimize performance and troubleshoot issues.
• AWS Trusted Advisor: Utilizing Trusted Advisor to monitor the AWS environment for best practices, cost optimization, and security, and receiving recommendations for improving infrastructure performance.

8. Deployment & Continuous Integration/Continuous Deployment (CI/CD):

• AWS CodePipeline: Automating the CI/CD pipeline using AWS CodePipeline to build, test, and deploy applications across different environments. This involves integrating other services like CodeBuild for building applications and CodeDeploy for automated deployment to EC2 instances or Lambda functions.
• Elastic Container Service (ECS) & EKS (Kubernetes): Using ECS or EKS to deploy and manage containerized applications with Docker, scaling applications across multiple containers with managed orchestration.

9. Cost Management & Optimization:

• AWS Cost Explorer: Using Cost Explorer to track, analyze, and optimize AWS resource usage and spending. Implementing cost-saving measures such as reserved instances, spot instances, and auto-scaling to avoid over-provisioning.
• AWS Budgets: Setting up budgets to monitor spending thresholds and receiving alerts when costs exceed a defined budget.

Example of a Live AWS Project:

"In a recent project, I led the migration of a legacy web application to AWS. We leveraged EC2 instances for compute resources, and RDS for the database layer to ensure scalability and reliability. The application was containerized using Docker, and we orchestrated containers with Amazon ECS. We set up an auto-scaling group to handle varying loads and used Elastic Load Balancer (ELB) to distribute traffic. For storage, we utilized S3 for static content and CloudFront for content delivery. We automated deployments with CodePipeline, integrating it with CodeBuild for automated builds and CodeDeploy for rolling deployments. Additionally, we set up CloudWatch monitoring for performance tracking and alerts, ensuring the application remained healthy in production. Security was enforced with IAM policies and AWS KMS for encryption. The project resulted in improved scalability, lower operational costs, and better application performance."

Key Skills & Tools:

• Compute: EC2, Lambda, Elastic Beanstalk, ECS, EKS.
• Storage & Databases: S3, RDS, DynamoDB, EFS, Glacier.
• Networking: VPC, CloudFront, Route 53, VPN, Direct Connect.
• Security: IAM, KMS, WAF.
• Automation & IaC: CloudFormation, CDK, Terraform.
• Monitoring & Logging: CloudWatch, X-Ray, CloudTrail.
• CI/CD: CodePipeline, CodeBuild, CodeDeploy.
• Cost Management: Cost Explorer, Trusted Advisor, Budgets.

This type of experience showcases your ability to design, implement, and manage cloud-native applications on AWS, ensuring they are scalable, cost-efficient, and secure while following best practices for monitoring and optimization.

Key Highlights:

• Build a live project on AWS
• Hands-on experience with AWS services
• Design, deploy, and manage a real-world project
• Practical application of cloud computing skills

What you will learn:

• Hands-on Project Development
  Gain practical experience in building a live project from scratch on AWS.
• AWS Service Integration
  Learn to integrate various AWS services to create a comprehensive cloud solution.
• Real-world Project Management
  Develop skills in managing and maintaining a live project on the AWS platform.