EC2 Instances Flashcards
EC2 instance
A compute instance in the Amazon EC2 service.
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.
EC2 Auto Scaling
Amazon EC2 Auto Scaling enables you to automatically add or remove Amazon EC2 instances in response to changing application demand. By automatically scaling your instances in and out as needed, you can maintain a greater sense of application availability.
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.
Amazon Single Queue Service (SKS)
Elastic Load Balancing
Elastic Load Balancing is the AWS service that automatically distributes incoming application traffic across multiple resources, such as Amazon EC2 instances.
A load balancer acts as a single point of contact for all incoming web traffic to your Auto Scaling group. This means that as you add or remove Amazon EC2 instances in response to the amount of incoming traffic, these requests route to the load balancer first. Then, the requests spread across multiple resources that will handle them.
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.
Serverless computing
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.
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)
Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high-performance container management system that enables you to run and scale containerized applications on AWS.
Amazon ECS supports Docker containers. Docker(opens in a new tab) 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. With Amazon ECS, you can use API calls to launch and stop Docker-enabled applications.
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.
Amazon EC2
Amazon Elastic Compute Cloud is a web service for launching and managing Linux/UNIX and Windows server instances in Amazon data centers.
Kubernetes
Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications.
It groups containers that make up an application into logical units for easy management and discovery.
Amazon EC2 instance types
- General Purpose Instances
- Compute Optimised Instances
- Memory Optimised Instances
- Accelerated Computing Instances
- Storage Optimised Instances
General Purpose Instances
General purpose instances provide a balance of compute, memory, and networking resources. You can use them for a variety of workloads, such as:
- application servers
- gaming servers
- backend servers for enterprise
- applications
- small and medium databases
Compute Optimised Instances
Compute optimized instances are ideal for compute-bound applications that benefit from high-performance processors. Like general purpose instances, you can use compute optimized instances for workloads such as web, application, and gaming servers.
However, the difference is compute optimized applications are ideal for high-performance web servers, compute-intensive applications servers, and dedicated gaming servers. You can also use compute optimized instances for batch processing workloads that require processing many transactions in a single group.
Memory Optimised Instances
Memory optimized instances are designed to deliver fast performance for workloads that process large datasets in memory. In computing, memory is a temporary storage area. It holds all the data and instructions that a central processing unit (CPU) needs to be able to complete actions. Before a computer program or application is able to run, it is loaded from storage into memory. This preloading process gives the CPU direct access to the computer program.
Suppose that you have a workload that requires large amounts of data to be preloaded before running an application. This scenario might be a high-performance database or a workload that involves performing real-time processing of a large amount of unstructured data. In these types of use cases, consider using a memory optimized instance. Memory optimized instances enable you to run workloads with high memory needs and receive great performance.
Accelerated Computing Instances
Accelerated computing instances use hardware accelerators, or coprocessors, to perform some functions more efficiently than is possible in software running on CPUs. Examples of these functions include floating-point number calculations, graphics processing, and data pattern matching.
In computing, a hardware accelerator is a component that can expedite data processing. Accelerated computing instances are ideal for workloads such as graphics applications, game streaming, and application streaming.
Storage Optimised Instances
