AWS Cloud Technology and Services Concepts
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Learn how AWS compute, database, networking, storage, AI and analytics services work and how to choose among them, with self-paced interactive exercises.
Building on Amazon Web Services means choosing among many services that overlap, such as several ways to run code or keep data. You compare the main options businesses rely on: where to run application code, when to use a managed database instead of one on an EC2 server, how to set up a private network and its routing, and how to organize stored data. The last part shows where pre-trained AI, machine learning and analytics services fit into an AWS setup.
What You Will Achieve
- Select an EC2 instance type, launch a web server on it and scale it as traffic changes
- Decide when RDS, DynamoDB or a database on EC2 suits an application, and pick a migration route to AWS
- Build a basic VPC and optimize S3 storage for changing data access patterns
- Match a business task to a suitable AWS AI, machine learning or analytics service
Program Overview
Compute, Containers and Serverless on AWS
Starts with the AWS interface and Amazon EC2, then shows how traffic and capacity are handled and when container or serverless options replace servers.
- The AWS user interface and EC2 instance types
- Launch templates, load balancers and auto-scaling groups
- Container services with ECS, EKS and Fargate
- Event-driven code with AWS Lambda
Databases, Migration, Networking and Storage
Compares AWS database services, walks through moving existing databases into AWS, and adds the network and storage services applications depend on.
- RDS, DynamoDB and MemoryDB
- Database Migration Service, the Snow Family and migration steps
- Virtual private clouds and routing policy choices
- Optimizing S3 for changing access patterns
AI, Machine Learning, Analytics and Secondary Services
Sorts pre-trained AI services and machine learning tools, introduces analytics, BI and data warehousing, and ends with AWS’s secondary service categories.
- The machine learning process and a first model in AWS
- Classifying AI and ML services
- Analytics projects, BI and data warehousing
- Secondary categories for code development, chatbots and messaging
Certificate Awarded (Paid)
Complete the course to earn it.
Job Outlook
Knowing how AWS compute, database, networking and storage services fit together is useful in cloud support, operations and development work, and in teams that run applications or data projects on Amazon Web Services.
Good for: Learners who want a structured map of the main AWS service families, with short exercises that ask them to set up resources and choose between similar services.
Keep in mind: The lessons line up with some AWS Cloud Practitioner (CLF-C02) topics, but that certification is a separate AWS exam; the course awards its own certificate of completion.
Bottom line: A survey of AWS built around choosing between similar services, such as RDS or EC2 for databases and ECS or EKS for containers.
Frequently Asked Questions
Which ways of running code on AWS are compared?
The first chapter works with EC2 instances, including picking an instance type and launching a web server, then adds load balancing and auto-scaling. It closes with container services on ECS, EKS and Fargate and with AWS Lambda for event-driven code.
Does the course show how to move an existing database to AWS?
Yes. The second chapter looks at Database Migration Service and the AWS Snow Family, asks you to identify the correct migration service for a situation, and walks through the steps of a migration before moving on to networking and storage.
What do the AI and analytics lessons include?
They describe the machine learning process and building a first model in AWS, then ask you to classify AI and ML services. Analytics and BI services, starting an analytics project and data warehousing follow, before a tour of secondary service categories.
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