🔧 AWS: Developer Associate

🕛 Zeit seit Veröffentlichung: 51 Tage, 19 Stunden 30 Minuten
📆 Veröffentlicht am: 14.10.2024 um 19:24 Uhr
Nachrichtenbereich: 🔧 Programmierung
🔗 Quelle: dev.to

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

• 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
• Error Handling with SDK:
  • Understanding and handling common SDK errors
  • Structured error messages
• Retries:
  • AWS SDK retry mechanisms
  • Custom retry logic and exponential backoff
• 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)

• 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
• Amazon EBS:
  • EBS volumes and EC2 integration
  • Creating snapshots and backups
  • Error handling with EBS
• Amazon Glacier:
  • Archival and retrieval processes
  • Logging Glacier jobs and performance considerations

Chapter 5: Compute Services (EC2, Lambda, and ECS)

• 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
• 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)
• 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)

• 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
• 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
• 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)

• AWS Lambda:
  • Advanced Lambda features: triggers, concurrency, and scaling
  • Error handling with Lambda and retries for function failures
  • Lambda logging and CloudWatch integration
• 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
• 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)

• AWS CodePipeline:
  • Automating application deployments
  • Error handling for pipeline stages
  • Retries for failed pipeline actions
  • Monitoring and logging pipeline executions
• AWS CodeBuild:
  • Building code programmatically
  • Handling build failures and retries
  • Logging build processes in CloudWatch
• 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)

• 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
• 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)

• Amazon SQS:
  • Working with queues programmatically
  • Error handling and retries for SQS messages
  • Logging message processing and failures
• Amazon SNS:
  • Creating and managing topics programmatically
  • Error handling for SNS failures
  • Logging SNS notifications
• Amazon EventBridge:
  • Setting up rules and events programmatically
  • Error handling in EventBridge
  • Logging event delivery and failures

Chapter 11: Security and Encryption in AWS

• IAM:
  • Managing programmatic access with the AWS SDK
  • Error handling for authentication and permission issues
  • Logging security-related events
• AWS Key Management Service (KMS):
  • Programmatically encrypting and decrypting data
  • Error handling in KMS interactions
  • Logging cryptographic operations

Chapter 12: Cost Management and Optimization

• AWS Cost Explorer:
  • Programmatically retrieving cost and usage reports
  • Error handling for Cost Explorer API
• Billing and Budgets:
  • Setting up budgets programmatically
  • Logging billing alerts and budget performance

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