AWS Basic Core Training

Embarking on a journey to master Amazon Web Services (AWS) involves understanding its core services and functionalities. Here's a structured guide to essential AWS training modules:

1. Introduction to Cloud Computing and AWS

• Overview of Cloud Computing: Understand the fundamentals of cloud computing, its models (IaaS, PaaS, SaaS), and deployment strategies.
• Introduction to AWS: Explore AWS's global infrastructure, core services, and the shared responsibility model.

2. Compute Services

• Amazon EC2 (Elastic Compute Cloud): Learn to launch, configure, and manage virtual servers.
• AWS Lambda: Understand serverless computing and how to run code without provisioning servers.
• Amazon Elastic Beanstalk: Deploy and manage applications in various programming languages.

3. Storage Services

• Amazon S3 (Simple Storage Service): Manage scalable object storage for data backup, archiving, and analytics.
• Amazon EBS (Elastic Block Store): Provision block-level storage volumes for use with EC2 instances.
• Amazon Glacier: Archive data with low-cost, long-term storage.

4. Networking

• Amazon VPC (Virtual Private Cloud): Create isolated networks within AWS to control resources.
• Amazon Route 53: Manage domain name system (DNS) services.
• AWS Direct Connect: Establish dedicated network connections from on-premises to AWS.

5. Databases

• Amazon RDS (Relational Database Service): Set up, operate, and scale relational databases.
• Amazon DynamoDB: Utilize a managed NoSQL database service.
• Amazon Redshift: Implement data warehousing solutions for analytics.

6. Security and Identity

• AWS IAM (Identity and Access Management): Manage user access and permissions securely.
• AWS KMS (Key Management Service): Create and control encryption keys for data security.
• AWS Shield and WAF: Protect applications from DDoS attacks and web exploits.

7. Monitoring and Management

• Amazon CloudWatch: Monitor AWS resources and applications in real-time.
• AWS CloudTrail: Track user activity and API usage for compliance.
• AWS Config: Assess, audit, and evaluate configurations of AWS resources.

8. DevOps and Automation

• AWS CloudFormation: Automate the deployment of AWS resources using templates.
• AWS CodePipeline: Implement continuous integration and delivery pipelines.
• AWS OpsWorks: Manage configurations and deployments using Chef and Puppet.

9. Machine Learning and AI

• Amazon SageMaker: Build, train, and deploy machine learning models at scale.
• AWS Rekognition: Analyze images and videos for facial recognition and object detection.
• AWS Lex and Polly: Develop conversational interfaces with chatbots and text-to-speech services.

10. Analytics

• Amazon EMR (Elastic MapReduce): Process vast amounts of data using Hadoop and Spark.
• Amazon Kinesis: Collect, process, and analyze real-time streaming data.
• AWS Data Pipeline: Orchestrate data movement and transformation.