AWS - CLOUD PRACTIONER NOTES - CHAPTER 2 . EC2 N COMPUTE

 

Amazon elastic compute cloud (Amazon EC2) provides secure, resizable compute capacity in the cloud as Amazon EC2 instances.  

 with an Amazon EC2 instance you can use a virtual server to run applications in the AWS Cloud.

• You can provision and launch an Amazon EC2 instance within minutes.
• You can stop using it when you have finished running a workload.
• You pay only for the compute time you use when an instance is running, not when it is stopped or terminated.
• You can save costs by paying only for server capacity that you need or want.

Amazon EC2 instance types

Amazon EC2 instance types are optimized for different tasks. When selecting an instance type, consider the specific needs of your workloads and applications. This might include requirements for compute, memory, or storage capabilities.

1.General purpose instances

General purpose instances provide a balance of compute, memory and networking resources, and can be used for a variety of diverse workloads. These instances are ideal for applications that use these resources in equal proportions such as web servers and code repositories. 

• application servers
• gaming servers
• backend servers for enterprise applications
• small and medium databases

2.Compute optimized instances

Compute Optimized instances are ideal for compute bound applications that benefit from high performance processors. Instances belonging to this family are well suited for batch processing workloads, media transcoding, high performance web servers, high performance computing (HPC), scientific modeling, dedicated gaming servers and ad server engines, machine learning inference and other compute intensive applications.

High performance computing (HPC), batch processing, ad serving, video encoding, gaming, scientific modelling, distributed analytics, and CPU-based machine learning inference.

3.Memory optimized instances

Memory optimized instances are designed to deliver fast performance for workloads that process large data sets in memory. Memory optimized instances enable you to run workloads with high memory needs and receive great performance 

Memory-intensive applications such as open-source databases, in-memory caches, and real time big data analytics

4.Accelerated computing instances

Accelerated computing instances use hardware accelerators, or co-processors, to perform functions, such as floating point number calculations, graphics processing, or data pattern matching, more efficiently than is possible in software running on CPUs.

Machine learning, high performance computing, computational fluid dynamics, computational finance, seismic analysis, speech recognition, autonomous vehicles, and drug discovery.

5.Storage optimized instances

Storage optimized instances are designed for workloads that require high, sequential read and write access to very large data sets on local storage. They are optimized to deliver tens of thousands of low-latency, random I/O operations per second (IOPS) to applications.

These instances maximize the number of transactions processed per second (TPS) for I/O intensive and business-critical workloads which have medium size data sets and can benefit from high compute performance and high network throughput such as relational databases (MySQL, MariaDB, and PostgreSQL), and NoSQL databases (KeyDB, ScyllaDB, and Cassandra). They are also an ideal fit for workloads that require very fast access to medium size data sets on local storage such as search engines and data analytics workloads.

Amazon EC2 pricing

With Amazon EC2, you pay only for the compute time that you use. 

1.On-Demand

With on-demand instance, you pay for the compute capacity by second  with no long term commitment. You have complete control over instance life cycle when to start  stop or terminate

- no upfront fee

- charged by hour or sec

-  no commitment,

- ideal for short term needs or 

- unpredicatable workloads

2. Reserved Instances

- full upfront, partial upfront, no upfront

- one-three year commitment

-  once expired automatically on demand price

Reserved instances are not physical instances rather billing discount applied to on demand instance.. on-Demand instances must match critieria to which determines price/billing discount. 

Reserved instance billing criteria:

-Instance type - ex m4.large - m4(instance family,  large-instance size

-region  - which region instance is purchased

-tenancy - shared or single tenant hardware.

-platform - windows or linux

Types of reserved instance:

Standard - This provides significant discount. Cannot be exchanged but can be modified.

Convertible - Provides lower discount, but can be exchanged for reserved instance with different attribute. can also be modified.

3. Savings plan

- no upfront , partial upfront or all upfront

-  reduce cost by commiting 1-3 year

- saves 66% over on demand

Types of savings plan

Compute savings plan :

provides more flexibility and 66% of demand rates. These plans automatically apply to your ec2 instance regardless of instance size, instance family, region , operating system, or tenancy. Also applies to Fargate n lambda usage. 

EC2 instance savings plan:

Provides savings upto 72% in exchange for commitment to Specific instance family in a chosen region, regardless of size, tenancy, OS

AWS Cost Explorer : a tool that enables you to visualize, understand, and manage your AWS costs and usage over time. 

If you are considering your options for Savings Plans, AWS Cost Explorer can analyze your Amazon EC2 usage over the past 7, 30, or 60 days.

 AWS Cost Explorer also provides customized recommendations for Savings Plans. These recommendations estimate how much you could save on your monthly Amazon EC2 costs, based on previous Amazon EC2 usage and the hourly commitment amount in a 1-year or 3-year plan.

4. Spot Instances

Spot instance uses spare ec2 capacity which is available for less than on demand price. spot instance enable you to request unused EC2 instance at huge discount. Charged by hour. This is suitable for workloads that can be interrupted.

5. Dedicated hosts

An amazon ec2 host is a physical server with ec2 instance capacity fully dedicated to your use. Dedicated hosts allow you to use your exisiting per-socket, per-core, per vm software licenses.

6. Dedicated  instances

Dedicated Instances are Amazon EC2 instances that run in a virtual private cloud (VPC) on hardware that's dedicated to a single customer. 

“An important difference between a Dedicated Host and a Dedicated Instance is that a Dedicated Host gives you additional visibility and control over how instances are placed on a physical server, and you can consistently deploy your instances to the same physical server over time.”

 Scalability

Scalability involves beginning with only the resources you need and designing your architecture to automatically respond to changing demand by scaling out or in. As a result, you pay for only the resources you use. You don’t have to worry about a lack of computing capacity to meet your customers’ needs.

 Amazon EC2 Auto Scaling

-minimum size

-maximum size

-desired capacity

Amazon EC2 Auto Scaling helps you ensure that you have the correct number of Amazon EC2 instances available to handle the load for your application. You create collections of EC2 instances, called Auto Scaling groups. 

You can specify the minimum number of instances in each Auto Scaling group, and Amazon EC2 Auto Scaling ensures that your group never goes below this size.

 You can specify the maximum number of instances in each Auto Scaling group, and Amazon EC2 Auto Scaling ensures that your group never goes above this size. 

If you specify the desired capacity, either when you create the group or at any time thereafter, Amazon EC2 Auto Scaling ensures that your group has this many instances.

 If you specify scaling policies, then Amazon EC2 Auto Scaling can launch or terminate instances as demand on your application increases or decreases.                                  

Within Amazon EC2 Auto Scaling, you can use two approaches: dynamic scaling and predictive scaling.

Dynamic scaling: responds to changing demand. 

Predictive scaling: automatically schedules the right number of Amazon EC2 instances based on predicted demand.

To scale faster, you can use dynamic scaling and predictive scaling together.

Adding Amazon EC2 Auto Scaling to your application architecture is one way to maximize the benefits of the AWS Cloud. When you use Amazon EC2 Auto Scaling, your applications gain the following benefits:

• Better fault tolerance. Amazon EC2 Auto Scaling can detect when an instance is unhealthy, terminate it, and launch an instance to replace it. You can also configure Amazon EC2 Auto Scaling to use multiple Availability Zones. If one Availability Zone becomes unavailable, Amazon EC2 Auto Scaling can launch instances in another one to compensate.

• Better availability. Amazon EC2 Auto Scaling helps ensure that your application always has the right amount of capacity to handle the current traffic demand.

• Better cost management. Amazon EC2 Auto Scaling can dynamically increase and decrease capacity as needed. Because you pay for the EC2 instances you use, you save money by launching instances when they are needed and terminating them when they aren't.                                           

Elastic Load Balancing

Elastic Load Balancing automatically distributes your incoming traffic across multiple targets, such as EC2 instances, containers, and IP addresses, in one or more Availability Zones. It monitors the health of its registered targets, and routes traffic only to the healthy targets. Elastic Load Balancing scales your load balancer as your incoming traffic changes over time. It can automatically scale to the vast majority of workloads.

Load balancer benefits

A load balancer distributes workloads across multiple compute resources, such as virtual servers. Using a load balancer increases the availability and fault tolerance of your applications.

You can add and remove compute resources from your load balancer as your needs change, without disrupting the overall flow of requests to your applications.

You can configure health checks, which monitor the health of the compute resources, so that the load balancer sends requests only to the healthy ones. You can also offload the work of encryption and decryption to your load balancer so that your compute resources can focus on their main work.

Elastic Load Balancing supports the following load balancers: Application Load Balancers, Network Load Balancers, Gateway Load Balancers, and Classic Load Balancers.                                   

                                  

Monolithic applications and microservices

In a microservices approach, application components are loosely coupled. In this case, if a single component fails, the other components continue to work because they are communicating with each other. The loose coupling prevents the entire application from failing. 

When designing applications on AWS, you can take a microservices approach with services and components that fulfill different functions. Two services facilitate application integration: Amazon Simple Notification Service (Amazon SNS) and Amazon Simple Queue Service (Amazon SQS)

Amazon Simple Notification Service (Amazon SNS) 

Amazon Simple Notification Service (Amazon SNS) is a publish/subscribe service. Using Amazon SNS topics, a publisher publishes messages to subscribers. This is similar to the coffee shop; the cashier provides coffee orders to the barista who makes the drinks. 

In Amazon SNS, subscribers can be web servers, email addresses, AWS Lambda functions, or several other options. 

Amazon Simple Queue Service (Amazon SQS)

Amazon Simple Queue Service (Amazon SQS) is a message queuing service. 

Using Amazon SQS, you can send, store, and receive messages between software components, without losing messages or requiring other services to be available. In Amazon SQS, an application sends messages into a queue. A user or service retrieves a message from the queue, processes it, and then deletes it from the queue.

Serverless computing

Earlier in this module, you learned about Amazon EC2, a service that lets you run virtual servers in the cloud. If you have applications that you want to run in Amazon EC2, you must do the following:

Provision instances (virtual servers).

Upload your code.

Continue to manage the instances while your application is running. 

The term “serverless” means that your code runs on servers, but you do not need to provision or manage these servers. With serverless computing, you can focus more on innovating new products and features instead of maintaining servers.

Another benefit of serverless computing is the flexibility to scale serverless applications automatically. Serverless computing can adjust the applications' capacity by modifying the units of consumptions, such as throughput and memory. 

An AWS service for serverless computing is AWS Lambda.

AWS Lambda 

AWS Lambda is a service that lets you run code without needing to provision or manage servers. 

While using AWS Lambda, you pay only for the compute time that you consume. Charges apply only when your code is running. You can also run code for virtually any type of application or backend service, all with zero administration. 

For example, a simple Lambda function might involve automatically resizing uploaded images to the AWS Cloud. In this case, the function triggers when uploading a new image

You upload your code to Lambda. 

You set your code to trigger from an event source, such as AWS services, mobile applications, or HTTP endpoints.

Lambda runs your code only when triggered.

You pay only for the compute time that you use. In the previous example of resizing images, you would pay only for the compute time that you use when uploading new images. Uploading the images triggers Lambda to run code for the image resizing function.

In AWS, you can also build and run containerized applications 

Containers 

Containers provide you with a standard way to package your application's code and dependencies into a single object. You can also use containers for processes and workflows in which there are essential requirements for security, reliability, and scalability.

Amazon Elastic Container Service (Amazon ECS) 

* highly scalable  

* high-performance container management system that enables you to run and scale the  containerized applications on AWS.  

* Amazon ECS supports Docker containers. 

*With Amazon ECS, you can use API calls tolaunch n stop Docker-enabledapplications

 Docker is a software platform that enables you to build, test, and deploy applications quickly. 

AWS supports the use of open-source Docker Community Edition and subscription-based Docker Enterprise Edition. 

Amazon Elastic Kubernetes Service (Amazon EKS)

Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed service that you can use to run Kubernetes on AWS. kubernetes is open-source software that enables you to deploy and manage containerized applications at scale. A large community of volunteers maintains Kubernetes, and AWS actively works together with the Kubernetes community. As new features and functionalities release for Kubernetes applications, you can easily apply these updates to your applications managed by Amazon EKS.

AWS Fargate

AWS Fargate is a serverless compute engine for containers. It works with both Amazon ECS and Amazon EKS. 

When using AWS Fargate, you do not need to provision or manage servers. AWS Fargate manages your server infrastructure for you. You can focus more on innovating and developing your applications, and you pay only for the resources that are required to run your containers.