Learn Cloud Computing with AWS in a Weekend

Discover cloud fundamentals and why enterprises move away from data centers and servers to the cloud, with a step-by-step visual approach and real enterprise scenarios.

Explore why enterprises need thousands of servers, from web to database servers, and how scaling and data centers address single points of failure.

Explore why data centers with thousands of servers require specialized infrastructure—power, cooling, networking, and security—and how high upfront costs, capacity guessing, and latency challenges emerge.

Learn how cloud computing rents infrastructure like electricity, offering on-demand access, elasticity, and pay-as-you-go from providers such as AWS, Azure, and Google Cloud.

Explore the cloud's pay-for-use model, economies of scale, and elastic capacity that reduce upfront risk. Learn how cloud enables faster innovation, global deployment, and avoids undifferentiated heavy lifting.

Master cloud terminology by understanding elasticity, agility, global reach, and latency, and learn how availability and cost concepts like CapEx, OpEx, and pay-as-you-go shape deployment.

Explore elasticity and agility in cloud use, with pay as you go opex, high availability, geo distribution, low latency, economies of scale, and avoiding undifferentiated heavy lifting.

Explore how Amazon Web Services evolved from an internal on-demand platform to the cloud computing pioneer. See how S3, EC2, and SQS enable global, scalable compute and storage infrastructure.

Discover a structured, step-by-step path to learning cloud skills across AWS, Azure, and Google Cloud, using a cloud account as a gateway to practice with free credits.

Create your AWS account through the free tier, verify your email and phone, enter billing and contact details, and access the management console to start exploring cloud resources.

Create an IAM group called developers with administrator access, add the in 28 minutes_dev user, and use the IAM login URL instead of the root account.

Explore regions and zones, including availability zones, and learn how distributing data centers across multiple regions delivers low latency and high availability for cloud apps.

Understand how to choose the right AWS region by considering compliance, data localization, latency, service availability, and pricing to optimize performance and cost.

Deploy your applications across multiple regions to reduce latency, expand globally, and meet data residency requirements. Enhance availability and speed disaster recovery by deploying across multiple regions.

Explore how zones, or availability zones, provide high availability within a single region by deploying across multiple isolated data centers in the London region.

Learn how regions and availability zones enable disaster recovery, data residency, and low-latency access, while practicing multi-region and multi-zone designs to ensure high availability.

AWS infrastructure spans regions and availability zones worldwide, with examples like US East one, EU West two, and AP South one, to enable highly available, low-latency apps.

Learn how to create and manage EC2 virtual machines in AWS, attach EBS storage, and implement load balancing for scalable applications.

Launch and configure Amazon EC2 in the Mumbai region using Amazon Linux 2, micro instance type, and a key pair; connect, secure, monitor, tag, and terminate.

Launch an EC2 instance, install Apache web server with yum, and open port 80 via a security group. Access the site using the instance’s public IP to verify the setup.

Review essential EC2 concepts, including EMI/AMI, instance families and sizes, elastic block store, security groups, and key pairs, to configure and secure EC2 instances.

Explore cloud computing beyond infrastructure by understanding IaaS, PaaS, and SaaS, and get started with managed services using cloud native approaches to run applications.

Compare IaaS and PaaS with app and database examples. Provision virtual machines and manage OS and runtimes in IaaS; deploy code and scale with automated backups and maintenance in PaaS.

Explore iaas vs paas, detailing cloud provider versus customer responsibilities for hardware, operating system, runtime, and scaling, and discover how managed services let you focus on application code and data.

Explore software as a service (SaaS) and its subscription model, with examples like Gmail, Google Docs, and Office 365, highlighting provider responsibilities versus user data and configuration.

Explore infrastructure as a service, platform as a service, and software as a service through practical scenarios, including virtual machines, managed databases, and legacy and rapid development considerations.

Explore public, private, hybrid, and multi-cloud models, comparing opex versus capex, scalability, and shared responsibility, while noting connectivity and security considerations and scenarios for each approach.

Explore cloud deployment models, including public, private, hybrid, and multi-cloud, for zero upfront cost launches, on-premise data, and failover with burst load to handle extra load.

Discover Elastic Beanstalk, a platform as a service that deploys and scales web applications with automatic load balancing and auto scaling. Supports many languages and Docker containers with automated updates.

Deploy and scale web applications with AWS Elastic Beanstalk, using a sample Python app, configuring load-balanced, multi-instance environments with auto scaling.

Learn how to quickly deploy a Python 3.8 web app on AWS Elastic Beanstalk, with auto scaling, load balancing, and environment management.

Understand why containers and docker images standardize deployment across languages and clouds, enabling microservices architecture with lightweight isolation and consistent monitoring and deployment across environments.

Explore container orchestration for deploying microservice containers, enabling auto scaling, service discovery, load balancing, self-healing, and zero-downtime deployments with Kubernetes, Amazon Elastic Container Service, and serverless options.

Explore a hands-on demo of AWS elastic container service with Fargate, using a serverless approach to run containers and deploy a scalable service behind an application load balancer.

Deploy a sample app on Amazon Elastic Container Service, create a default cluster, run a two-task service with a load balancer, and monitor tasks to maintain steady state.

Discover serverless computing with AWS Lambda, focusing on code while the cloud handles scaling, availability, and pay-for-use pricing based on requests, duration, and memory.

Learn how to create your first AWS lambda function with Node.js, test with a sample event, view logs, deploy changes, and understand serverless auto scaling for millions of requests.

Explore lambda monitoring with CloudWatch metrics and logs, and enable X-Ray tracing for visibility. Configure memory, timeouts, environment variables, and concurrency options including provisioned concurrency.

Explore AWS compute options from traditional shell-server setups with elastic load balancing to managed services like Elastic Beanstalk, container options with EKS and ECS, plus serverless with Fargate and Lambda.

Explore AWS compute options from serverless lambda and Elastic Beanstalk to container orchestration with ECS and EKS, and compare PaaS, IaaS, and Kubernetes for custom OS needs.

Learn five best practices for managing cloud costs with AWS: monitor the billing dashboard daily, set budget alerts, stop unused resources, and understand the free tier and pricing basics.

Understand the data journey, from raw facts to structured, semi-structured, and unstructured forms, and learn how descriptive, diagnostic, predictive, and prescriptive analytics—along with AI—turn data into actionable intelligence.

Explore reliable cloud data systems by mastering the four pillars—availability, durability, scalability, and consistency—and understanding their trade-offs for robust data stores.

Explore the difference between availability and durability in cloud databases, learn how uptime targets like 99.99% and 99.999% are achieved through redundancy, geo distribution, failover, and versioning.

Explore scalability by comparing vertical and horizontal scaling, showing how increasing a single server's power differs from adding multiple servers to handle more data, users, and queries.

Explore horizontal scaling with two options: read replicas offloading reads from the primary database, and distributed data stores splitting data across servers for scalability and high availability.

Explore how strong consistency and eventual consistency trade off availability, durability, and latency across replicated databases, with updates and coordination in banking, inventory, social media, and personalization.

Evaluate data reliability by examining availability, durability, scalability, and consistency, including 99.99% availability and 11 nines durability. Compare strong and eventual consistency to select the right model for your application.

Explore structured data in relational databases with predefined schemas, keys, and relationships, and compare OLTP and OLAP use cases, including row storage for transactions and columnar storage for analytics.

Explore Amazon RDS, a managed relational database service for oltp workloads, with Aurora compatibility, multi-AZ deployments, read replicas, auto scaling, automated backups, and serverless options.

Create and configure a managed relational database in AWS RDS, selecting MySQL, choosing standard or free tier, and enabling storage auto scaling with a multi-AZ standby.

Explore creating and connecting to an Amazon RDS MySQL database, configure security groups and public access, and practice creating tables, inserting data, and querying in a Cloud Shell environment.

Explore semi-structured data with JSON examples and the flexible, evolving schemas of NoSQL databases, which scale horizontally to handle petabytes of data, including document, key-value, graph, and column family types.

Explore semi-structured data through document databases that store JSON documents with nested objects and arrays under unique IDs, using flexible, application-defined schemas.

Explore semi-structured data types: key value, graph, and column family. Learn how these models map to simple lookups, complex relationships, and flexible schemas, with AWS, Azure, and Google Cloud services like DynamoDB, Neptune, Cassandra, and Bigtable.

Explore Amazon DynamoDB, a fast, scalable no sql key-value and document store, with schema-less tables, primary keys, and support for transactions and global tables for high-volume workloads.

Explore how Amazon DynamoDB, a fast, schema-less NoSQL database, creates tables with a primary key, inserts items with attributes, and uses query and scan operations with provisioned capacity.

Explore unstructured data and learn how to store it using block, file, and object storage, with AWS, Azure, and Google Cloud examples like S3, blob storage, and Google Cloud Storage.

Explore block storage in AWS, comparing instance store and elastic block store, with instance store as temporary, host-attached storage and EBS as durable, detachable network storage.

Explore elastic block store by launching an EC2 instance, examining root and attached volumes, and managing snapshots, encryption, and delete on termination.

Explore aws efs file storage for petabyte-scale, auto-scaling shared storage across multiple virtual servers. See encryption at rest and in transit, and compare fsx for lustre and windows file servers.

Explore Amazon s3 object storage, unlimited storage with high availability and durability, using buckets and keys via a rest api, plus glacier for low-cost archives.

Explore Amazon S3 storage by creating globally unique buckets and uploading objects. Learn about versioning, encryption, logging, and object lock to manage data securely.

Enable static website hosting on your S3 bucket, disable block public access, and configure a bucket policy to allow public read of all objects, then view the site via index.html.

Explore hybrid storage with AWS storage gateway, offering file, tape, and volume gateways that bridge on-premise storage to cloud services S3, Glacier, and EBS, with cached or stored volumes.

Review storage options for unstructured data in aws, including object storage with Amazon S3, block storage with EBS, and file storage with EFS, plus Glacier archiving and hybrid gateway.

explores data-store scenarios in AWS, mapping use cases to DynamoDB, DocumentDB, RDS, Neptune, Redshift, Amazon FS, and S3 for schema-less documents, transactions, graphs, analytics, and file or image storage.