Chapter 1: Introduction to AWS and Developer Tools
- Overview of AWS Cloud Computing
- Introduction to AWS Global Infrastructure
- Developer Tools in AWS
- AWS SDKs
- AWS CLI
- AWS Elastic Beanstalk
- AWS Free Tier and Billing Concepts
Chapter 2: AWS Identity and Access Management (IAM)
- IAM Basics: Users, Groups, Roles, and Policies
- IAM Roles for Services: Configuring IAM roles for EC2, Lambda, and ECS
- Fine-Grained Permissions: Least-privilege access
- Best Practices: Multi-Factor Authentication (MFA) and IAM Policy Simulator
- Error Handling in IAM: Permission denied issues and logging security events
Chapter 3: AWS SDK and API Interactions
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Setting Up AWS SDKs:
- Go, Python (Boto3), Java, and Node.js
- Configuring SDK credentials and environment variables
- Basic API Interactions: S3, EC2, Lambda, DynamoDB
- Asynchronous API Calls: Managing async calls and handling responses
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Error Handling with SDK:
- Understanding and handling common SDK errors
- Structured error messages
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Retries:
- AWS SDK retry mechanisms
- Custom retry logic and exponential backoff
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Logging in AWS SDK:
- Configuring logging for SDK calls
- Log levels (debug, info, error)
- Integrating with CloudWatch for centralized logging
Chapter 4: AWS Storage Services (S3, EBS, and Glacier)
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Amazon S3:
- Bucket creation, object storage, and versioning
- Uploading and downloading objects using the SDK
- Error handling for S3 API
- Retries for network issues and S3 limits
- Logging S3 requests and access patterns
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Amazon EBS:
- EBS volumes and EC2 integration
- Creating snapshots and backups
- Error handling with EBS
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Amazon Glacier:
- Archival and retrieval processes
- Logging Glacier jobs and performance considerations
Chapter 5: Compute Services (EC2, Lambda, and ECS)
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Amazon EC2:
- Launching EC2 instances programmatically
- Handling EC2 failures (capacity limits, instance startup issues)
- Retries for instance creation and termination
- SDK Logging for EC2 operations
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AWS Lambda:
- Creating and invoking Lambda functions using the SDK
- Error handling: timeouts, memory limits, retries
- Configuring and logging Lambda retries with Dead Letter Queues (DLQ)
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Amazon ECS and Fargate:
- Launching containers programmatically using SDK
- Error handling for ECS tasks
- SDK logging for container tasks
Chapter 6: Databases (RDS, DynamoDB, and Aurora)
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Amazon RDS:
- Programmatically creating, updating, and deleting RDS instances
- Retries for RDS creation and backups
- Handling common RDS errors (storage limits, connection failures)
- Monitoring and logging RDS operations
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Amazon DynamoDB:
- Using the SDK to interact with DynamoDB: put, get, query
- Error handling: throttling, limits, retries
- Custom retry strategies for DynamoDB operations
- Logging DynamoDB activities with CloudWatch
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Amazon Aurora:
- Programmatically managing Aurora clusters
- Handling connection issues, failovers, and retries
- Error handling for database access
- Logging Aurora queries and performance
Chapter 7: Serverless Applications (Lambda, API Gateway, and Step Functions)
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AWS Lambda:
- Advanced Lambda features: triggers, concurrency, and scaling
- Error handling with Lambda and retries for function failures
- Lambda logging and CloudWatch integration
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Amazon API Gateway:
- Setting up REST APIs programmatically
- Error handling in API Gateway (authorization failures, 5xx errors)
- Retry strategies for API Gateway calls
- Logging requests and responses in API Gateway
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AWS Step Functions:
- Managing workflows with Step Functions
- Handling failures and retries for workflow states
- Logging Step Functions’ executions
Chapter 8: CI/CD with AWS (CodePipeline, CodeBuild, and CodeDeploy)
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AWS CodePipeline:
- Automating application deployments
- Error handling for pipeline stages
- Retries for failed pipeline actions
- Monitoring and logging pipeline executions
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AWS CodeBuild:
- Building code programmatically
- Handling build failures and retries
- Logging build processes in CloudWatch
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AWS CodeDeploy:
- Managing deployments to EC2 and Lambda
- Error handling in CodeDeploy: rollback strategies
- Logging deployment progress and failures
Chapter 9: Monitoring and Troubleshooting (CloudWatch and X-Ray)
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Amazon CloudWatch:
- Creating custom metrics and alarms
- Logging SDK calls and API requests
- Setting up CloudWatch Logs for Lambda, ECS, and API Gateway
- Handling and analyzing CloudWatch metrics
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AWS X-Ray:
- Tracing API calls and analyzing performance bottlenecks
- Logging error traces with X-Ray
- Implementing X-Ray with AWS SDKs
Chapter 10: Messaging and Event-Driven Architectures (SQS, SNS, and EventBridge)
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Amazon SQS:
- Working with queues programmatically
- Error handling and retries for SQS messages
- Logging message processing and failures
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Amazon SNS:
- Creating and managing topics programmatically
- Error handling for SNS failures
- Logging SNS notifications
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Amazon EventBridge:
- Setting up rules and events programmatically
- Error handling in EventBridge
- Logging event delivery and failures
Chapter 11: Security and Encryption in AWS
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IAM:
- Managing programmatic access with the AWS SDK
- Error handling for authentication and permission issues
- Logging security-related events
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AWS Key Management Service (KMS):
- Programmatically encrypting and decrypting data
- Error handling in KMS interactions
- Logging cryptographic operations
Chapter 12: Cost Management and Optimization
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AWS Cost Explorer:
- Programmatically retrieving cost and usage reports
- Error handling for Cost Explorer API
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Billing and Budgets:
- Setting up budgets programmatically
- Logging billing alerts and budget performance
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