marc:studie:aws:01_aws_certified_cloud_practitioner
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| marc:studie:aws:01_aws_certified_cloud_practitioner [2026/05/12 09:59] – marcv | marc:studie:aws:01_aws_certified_cloud_practitioner [2026/05/14 09:38] (current) – [Pillars Of The Well-Architected Framework] marcv | ||
|---|---|---|---|
| Line 1: | Line 1: | ||
| ====== AWS Certified Cloud Practitioner (CLF-C02) ====== | ====== AWS Certified Cloud Practitioner (CLF-C02) ====== | ||
| + | |||
| + | ====== Amazon AWS Cloud Computing ====== | ||
| + | |||
| + | ===== Benefits of Cloud Computing ===== | ||
| + | |||
| + | * Cloud computing offers cost-efficiency, | ||
| + | * The four main cloud service models' | ||
| + | * Essential cloud computing features include on-demand self-service, | ||
| + | * Businesses benefit from cloud computing' | ||
| ===== Types of Cloud Computing: ===== | ===== Types of Cloud Computing: ===== | ||
| Line 8: | Line 17: | ||
| - | ==== Infrastructure as a Service (IaaS): ==== | + | ==== 1) Infrastructure as a Service (IaaS): ==== |
| **Infrastructure as a Service (Iaas)** is a cloud computing model that provides **virtualized computing resources** over the internet. It provides scalable and on-demand access to essential IT components such as **Virtual Machines (VMs) Storage, and networking resources** without the need to invest in hardware. | **Infrastructure as a Service (Iaas)** is a cloud computing model that provides **virtualized computing resources** over the internet. It provides scalable and on-demand access to essential IT components such as **Virtual Machines (VMs) Storage, and networking resources** without the need to invest in hardware. | ||
| Line 22: | Line 31: | ||
| * VPN connections | * VPN connections | ||
| - | ==== Platform as a Service (PaaS): ==== | + | ==== 2) Platform as a Service (PaaS): ==== |
| **Platform as a Service (PaaS)** provides a platform allowing customers to develop, run, and manage applications without encountering the complexity of building and maintaining the underlying infrastructure. | **Platform as a Service (PaaS)** provides a platform allowing customers to develop, run, and manage applications without encountering the complexity of building and maintaining the underlying infrastructure. | ||
| | | ||
| Line 32: | Line 41: | ||
| * **Elastic Beanstalk: | * **Elastic Beanstalk: | ||
| - | ==== Software as a Service (SaaS): ==== | + | ==== 3) Software as a Service (SaaS): ==== |
| **Software as a Service (SaaS)** delivers software applications over the internet on a subscription basis. In the SaaS model, the software is hosted and maintained by a third-party provider, which eliminates the need for users to install, manage, or update the software locally on their devices. Instead, users can access the software through a web browser or application interface, typically paying a monthly or annual fee for usage. | **Software as a Service (SaaS)** delivers software applications over the internet on a subscription basis. In the SaaS model, the software is hosted and maintained by a third-party provider, which eliminates the need for users to install, manage, or update the software locally on their devices. Instead, users can access the software through a web browser or application interface, typically paying a monthly or annual fee for usage. | ||
| Line 39: | Line 48: | ||
| {{: | {{: | ||
| - | ===== Functions as a Service (FaaS): | + | ==== 4) Functions as a Service (FaaS): ==== |
| Functions as a Service (FaaS): commonly known as **serverless computing**, | Functions as a Service (FaaS): commonly known as **serverless computing**, | ||
| Line 48: | Line 57: | ||
| AWS's FaaS Solutiun is called **AWS Lambda**. | AWS's FaaS Solutiun is called **AWS Lambda**. | ||
| + | |||
| + | ===== Core AWS Services: ===== | ||
| + | * Compute Services (e.g. Amazon EC2) | ||
| + | * Storage Services (e.g. Amazon S3) | ||
| + | * Database Services (e.g. Amazon RDS) | ||
| + | * Analytics Services (e.g. Amazon Redshift) | ||
| + | * Networking Services (e.g. Amazon VPC) | ||
| + | * Developer Tools (e.g. AWS CodeDeploy) | ||
| + | * Management Tools (e.g. AWS CloudWatch) | ||
| + | |||
| + | ===== AWS Global Infrastructure: | ||
| + | |||
| + | The key components of the AWS Global Infrastructure include: | ||
| + | - Regions | ||
| + | - Availability Zones | ||
| + | - Edge Locations | ||
| + | |||
| + | ==== Regions: ==== | ||
| + | |||
| + | Currently, **AWS operates 38 geographic regions globally**, spanning across various continents such as North America, Europe, Asia Pacific, and South America. AWS is still expanding to include new regions. | ||
| + | |||
| + | :!: It is important to note that **resources and pricing can vary between AWS Regions**. Factors such as local infrastructure costs, taxes, and regulations can influence the cost of operating in different regions, which leads to differences in pricing for AWS services. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | ==== Availability Zones: ==== | ||
| + | |||
| + | AWS availability zones are **distinct data centers within a single AWS region**. Each region has its own infrastructure and services which is designed to provide fault tolerance and high availability. These zones are interconnected through low-latency links, while enabling redundancy and resilience for applications and data hosted in the cloud. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | Each AWS region is composed of **a minimum of three availability zones** that are isolated and physically separate zones within a geographic area to provide customers with options for deploying highly available and fault-tolerant applications. Furthermore, | ||
| + | |||
| + | ==== Edge Locations: ==== | ||
| + | |||
| + | AWS edge locations are endpoints for AWS services that are specifically optimized for content delivery to users at a global scale. They serve as entry points for accessing AWS services and are strategically positioned to reduce latency, and improve performance for end users. | ||
| + | |||
| + | In addition to edge locations, AWS operates 11 **regional edge caches**, which are larger cache clusters located in major metropolitan areas around the world. | ||
| + | |||
| + | By leveraging edge locations and regional edge caches, AWS customers can deliver content and applications with low latency and high throughput, while providing a seamless user experience and ensuring optimal performance for their web applications, | ||
| + | |||
| + | :!: Always refer to the AWS global infrastructure site for updated region, availability zone and edge locations prior to the exam. | ||
| + | |||
| + | ==== Local Zones: ==== | ||
| + | |||
| + | AWS local zones bring the power of AWS infrastructure closer to end users in metropolitan areas, enabling low-latency access to compute, storage, and other AWS services. With local zones, customers can address use cases such as real-time gaming, media and entertainment content delivery, ML inference at the edge, and interactive streaming services. | ||
| + | |||
| + | ==== Direct Connect: ==== | ||
| + | |||
| + | AWS Direct Connect is a **dedicated network connection service** that provides **private connectivity** between an **organization' | ||
| + | |||
| + | ==== Outposts: ==== | ||
| + | |||
| + | AWS Outposts extend the AWS infrastructure and services directly into a customer’s on-premises data center or co-location facility. They bring the same hardware, services, APIs, and management tools that run in AWS Regions, but are delivered and operated locally by AWS. With Outposts, organizations can run services such as Amazon EC2, EBS, RDS, ECS, EKS, and even S3 right within their own facilities, while still connecting seamlessly to the nearest AWS Region for broader service integration. | ||
| + | | ||
| + | This capability is especially valuable for workloads that require **ultra-low latency, local data processing, or strict data residency compliance**. | ||
| + | |||
| + | ==== Naming Conventions for AWS Regions and Availability Zones: ==== | ||
| + | |||
| + | * **Regions: | ||
| + | * **Availability Zones (AZs):** Within each AWS region, there are multiple availability zones, each identified by a distinct letter. For instance, in the US West (Oregon) region, availability zones may be labeled as " | ||
| + | AWS continues to follow the same naming convention for **instances** (__family + generation + size__), but newer families now include suffixes like **‘g’** for __Graviton__ processors, **‘a’** for __AMD-based__ instances, or **‘i’** for __Intel__. | ||
| + | | ||
| + | This helps customers easily identify the underlying processor or special capabilities of the instance. | ||
| + | |||
| + | :!: Points to remember: | ||
| + | |||
| + | * AWS, the world' | ||
| + | * With **38 regions globally**, AWS provides high availability and low-latency services to users worldwide. | ||
| + | * Each region consists of minimum **3 availability zones** (**120 AZ’s** in total), ensuring fault tolerance and redundancy. | ||
| + | * AWS Edge Locations, comprising **700+ Points of Presence** and **11 Regional Edge Caches**, optimize content delivery and enhance user experiences. | ||
| + | * Direct Connect offers secure, low-latency connections to AWS services from **115 locations worldwide**. | ||
| + | * Local Zones (**43 in number**) extend AWS infrastructure to metropolitan areas, facilitating proximity to end-users and low-latency applications. | ||
| + | * Understanding the naming nomenclature of AWS regions and availability zones aids in navigating the global infrastructure efficiently. | ||
| + | |||
| + | ====== AWS Well Architected Framework and Shared Responsibility Model ====== | ||
| + | |||
| + | ===== The Well-Architected Framework ===== | ||
| + | |||
| + | This framework serves as a guiding principle for designing and evaluating cloud architectures, | ||
| + | * configuring robust Identity and Access Management (IAM) policies | ||
| + | * encrypting data at rest and in transit | ||
| + | * implementing network security measures such as firewalls and intrusion detection systems | ||
| + | * etc | ||
| + | |||
| + | Practitioners are encouraged to optimize their infrastructure for speed and efficiency, while leveraging scalable compute resources, caching mechanisms, and strengthening Content Delivery Networks (CDNs) to minimize latency and improve responsiveness. | ||
| + | |||
| + | The framework focuses on building resilient infrastructure that can withstand failures and disruptions. | ||
| + | | ||
| + | Practitioners are advised to design for fault tolerance by deploying redundant components, implementing automated failover mechanisms, and regularly testing their disaster recovery procedures. | ||
| + | |||
| + | Finally, the Well-Architected Framework helps practitioners optimize their infrastructure for cost-effectiveness. | ||
| + | | ||
| + | | ||
| + | By analyzing their resource utilization, | ||
| + | |||
| + | ===== Pillars Of The Well-Architected Framework ===== | ||
| + | |||
| + | {{: | ||
| + | |||
| + | ^ Key Pillar ^ Description ^ | ||
| + | | **Operational Excellence** | This pillar focuses on supporting the effective development and operation of workloads, gaining insights into operations, and continuously improving processes and procedures to deliver business value efficiently. | | ||
| + | | **Security** | The security pillar guides organizations in leveraging cloud technologies to protect data, systems, and assets, thereby enhancing their overall security posture. | | ||
| + | | **Reliability** | This pillar encompasses the ability of a workload to perform its intended function correctly and consistently, | ||
| + | | **Performance Efficiency** | The performance efficiency pillar emphasizes using computing resources efficiently to meet system requirements, | ||
| + | | **Cost Optimization** | Cost optimization involves running systems to deliver business value at the lowest price point possible, while optimizing resource utilization, | ||
| + | | **Sustainability** | The sustainability pillar focuses on continually improving sustainability impacts by reducing energy consumption, | ||
| + | |||
| + | Terms used to describe the components and structure of cloud solutions: | ||
| + | * **Component: | ||
| + | * **Workload: | ||
| + | * **Architecture: | ||
| + | * **Milestones: | ||
| + | * **Technology Portfolio: | ||
| + | * **Level of Effort:** This categorizes the time, effort, and complexity required for task implementation. It is crucial to consider team size, expertise, and workload complexity for context. These levels are as follows: | ||
| + | * **High:** Tasks may span **weeks** or **months**, often requiring multiple stories, releases, and tasks. | ||
| + | * **Medium:** Tasks are typically completed within **days** or **weeks**, possibly across multiple releases. | ||
| + | * **Low:** Tasks are generally finished in **hours** or **days**, possibly involving multiple smaller tasks. | ||
| + | |||
| + | :!: When architecting workloads, there are several trade-offs between pillars based on business context. These decisions influence engineering priorities, such as optimizing sustainability and cost over reliability in development environments or prioritizing reliability at higher costs for mission-critical solutions. In ecommerce, performance directly impacts revenue and customer engagement. However, **security** and **operational excellence** are pillars that are generally **non-negotiable** and should not be compromised for the sake of others! | ||
| + | |||
| + | ===== General Design Principles ===== | ||
| + | |||
| + | Key design Principles: | ||
| + | * **Capacity Planning:** Avoid guesswork by leveraging the flexibility of cloud computing. With on-demand scalability, | ||
| + | * **Production-Scale Testing:** Cloud environments enable the creation of realistic test environments on demand. By simulating production conditions, you can conduct thorough testing without incurring the high costs associated with maintaining dedicated testing infrastructure. | ||
| + | * **Automation: | ||
| + | * **Evolutionary Architectures: | ||
| + | * **Data-Driven Design:** Leverage data to inform architectural decisions and optimize workload performance. By collecting and analyzing data on workload behavior, you can identify areas for improvement and make informed decisions to enhance overall efficiency and effectiveness. | ||
| + | |||
marc/studie/aws/01_aws_certified_cloud_practitioner.1778572766.txt.gz · Last modified: by marcv
