AWS Zero to Hero: Day 1

Task 1 : Learn about the different pricing models offered by AWS and write a post in own words.

AWS offers various pricing models, including on-demand, reserved instances, spot instances, and pay-as-you-go, to cater to diverse workloads and budgets, with tools like the Pricing Calculator and Cost Explorer aiding in cost management and optimization.

Here's a breakdown of common AWS pricing models:

1. On-Demand Instances:

• Description: You pay for the resources you use, with no long-term commitments or upfront costs.

• Use Cases: Ideal for workloads with unpredictable usage patterns or when you need flexibility.

• Example: Amazon EC2 On-Demand Instances.

2. Reserved Instances:

• Description: You commit to using specific resources for a set period (1 or 3 years) at a discounted rate.

• Use Cases: Best for workloads with predictable usage and long-term needs.

• Example: Amazon EC2 Reserved Instances.

3. Spot Instances:

• Description: You bid on unused AWS capacity, paying a lower price than on-demand instances.

• Use Cases: Suitable for fault-tolerant applications or workloads that can be interrupted.

• Example: Amazon EC2 Spot Instances.

4. Pay-As-You-Go:

• Description: You pay only for the resources you consume, with no minimum fees or upfront costs.

• Use Cases: Common for services like S3, Lambda, and RDS.

• Example: Amazon S3, AWS Lambda, Amazon RDS.

5. Dedicated Hosts:

• Description: You rent a physical server (host) that is dedicated to your use, allowing you to use your

• own licenses.

• Use Cases: Ideal for workloads with regulatory or compliance requirements that require complete isolation.

• Example: Amazon EC2 Dedicated Hosts.

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Task 2: Differentiate between on-premises, on-cloud, and hybrid cloud computing models, and explain when each might be most appropriate.

1. On-premise model:

   • Previously, the development team used the servers in their office to deploy the application on that

   • In this model, an organization hosts its cloud infrastructure and data within its own physical facilities, providing complete control and customization but requiring significant investment and in-house expertise.

   • Can be used when organisations want to establish a Private cloud.

   • Use Case: Suitable for industries with strict regulatory requirements or the need to establish a private cloud.

2. On-cloud model:

   • This model refers to using cloud computing services, where data, applications, and resources are hosted and accessed remotely via the internet, rather than being stored and managed on-premises.

   • This model offers flexibility, scalability, and cost-effectiveness compared to traditional on-premises infrastructure.

   • Can be used in both cases, depends on organisation whether they want to establish a Public or Private Cloud.

   • Use Case: Ideal for businesses looking for agility, rapid deployment, and cost-effectiveness.

3. Hybrid model:

   • In this model, the organization used both on-cloud and on-prem models according to their use case and load.

   • It combines on-premises infrastructure (a private cloud) with a public cloud, allowing organizations to leverage the strengths of both environments for data and application management while maintaining flexibility and control.

   • Use Case: Recommended for organizations with fluctuating workloads or those in transition to the cloud.

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Task 3: Explore IAAS, PAAS, and SAAS with examples.

IaaS (Infrastructure as a Service) provides virtualized computing resources, PaaS (Platform as a Service) offers a platform for developing and deploying applications, and SaaS (Software as a Service) delivers ready-to-use software over the internet.

Here's a breakdown with examples:

1. IaaS (Infrastructure as a Service)

• Definition:

  IaaS provides on-demand access to virtualized computing resources like servers, storage, and networking, allowing users to manage the operating system, applications, and data.

• Examples:

  • Amazon Web Services (AWS)

  • Microsoft Azure

  • Google Cloud Platform (GCP)

  • DigitalOcean

  • Rackspace

  • Linode

2. PaaS (Platform as a Service)

• Definition:

  PaaS provides a platform for developers to build, deploy, and manage applications without worrying about the underlying infrastructure.

• Examples:

  • Heroku

  • Google App Engine

  • Microsoft Azure App Service

  • AWS Elastic Beanstalk

  • Force.com

  • Red Hat OpenShift

3. SaaS (Software as a Service)

• Definition:

  SaaS delivers software applications over the internet, typically accessed through a web browser, with the provider managing everything from infrastructure to maintenance.

• Examples:

  • Salesforce

  • Google Workspace (Gmail, Google Docs, etc.)

  • Microsoft 365

  • Dropbox

  • Shopify

  • Netflix

  • Slack

  • Zoom

  • HubSpot

  • MailChimp

  • Cisco Webex

  • GoToMeeting

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Task 4: Learn about the history of AWS and key milestones and developments in its evolution

The Evolution of AWS

Amazon Web Services (AWS) launched publicly in 2006, revolutionizing cloud computing by offering services like Amazon S3, EC2, and SQS under the Infrastructure as a Service (IaaS) model.

Key Milestones:

• 2008: AWS Management Console released.

• 2011: Launch of AWS GovCloud (US) for secure government workloads.

• 2014: Introduction of AWS Lambda, enabling serverless computing.

• 2018: AWS Outposts brought hybrid cloud capabilities.

• 2020: Launch of AWS Graviton ARM-based processors.

• 2023: Amazon Bedrock introduced for generative AI apps.

• 2024: AWS Q, an AI assistant for cloud builders, announced.

AWS has grown into a global leader with 30+ regions, 100+ availability zones, and customers ranging from startups to enterprises like Netflix, NASA, and McDonald’s.

It remains at the forefront of cloud innovation, with strong emphasis on compute, AI/ML, edge computing, and sustainability.

For an in-depth article on AWS history, you can read my blog here: The History and Evolution of AWS

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Conclusion

Understanding the fundamentals of AWS pricing models, deployment types, service models, and its evolution is essential for anyone beginning their cloud or DevOps journey. These core concepts lay the foundation for designing cost-effective, scalable, and reliable cloud architectures.

From choosing the right pricing model to determining the appropriate deployment strategy and service type (IaaS, PaaS, or SaaS), every decision impacts performance, cost, and security. Additionally, having a historical perspective on AWS’s growth helps appreciate how it has become a market leader and how it continues to innovate with offerings like serverless computing and generative AI.

Whether you’re a student, a beginner in tech, or preparing for AWS certifications, mastering these basics will strengthen your understanding and give you confidence to explore more advanced topics in cloud computing and DevOps.