Compute in the Cloud Flashcards
What is Amazon EC2?
Amazon Elastic Compute Cloud (Amazon EC2) provides scalable computing capacity in the Amazon Web Services (AWS) Cloud.
What are the main features of Amazon EC2?
Amazon Elastic Compute Cloud (Amazon EC2)
- Virtual computing environments (VMs), known as instances
- Various configurations of CPU, memory, storage, and networking capacity for your instances, known as instance types
- Temporary and Persistent storage volumes called instance store volumes and Amazon EBS volumes respectively.
- A firewall that enables you to specify the protocols, ports, and source IP ranges that can reach your instances using security groups
- Virtual networks you can create that are logically isolated from the rest of the AWS Cloud, and that you can optionally connect to your own network, known as virtual private clouds (VPCs)
What are the types of Amazon EC2 instances?
Amazon EC2 instance types are optimized for different tasks.
- General purpose instances
- Compute optimised instances
- Memory optimised instances
- Accelerated compute instances
- Storage optimised instances
What are EC2 General purpose instances used for?
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
Suppose that you have an application in which the resource needs for compute, memory, and networking are roughly equivalent. You might consider running it on a general purpose instance because the application does not require optimization in any single resource area.
What are EC2 Compute optimized instances used for?
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 areideal 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.
What are EC2 Memory optimized instances used for?
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.
What are EC2 Accelerated computing instances used for?
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.
What are EC2 Storage optimized instances used for?
Storage optimized instances are designed for workloads that require high, sequential read and write access to large datasets on local storage. Examples of workloads suitable for storage optimized instances include distributed file systems, data warehousing applications, and high-frequency online transaction processing (OLTP) systems.
In computing, the term input/output operations per second (IOPS) is a metric that measures the performance of a storage device. It indicates how many different input or output operations a device can perform in one second. Storage optimized instances are designed to deliver tens of thousands of low-latency, random IOPS to applications.
You can think of input operations as data put into a system, such as records entered into a database. An output operation is data generated by a server. An example of output might be the analytics performed on the records in a database. If you have an application that has a high IOPS requirement, a storage optimized instance can provide better performance over other instance types not optimized for this kind of use case.
Match each description to an Amazon EC2 instance type.
See screenshot
Answers
What are the Amazon EC2 pricing options?
- On-Demand
- Amazon EC2 Savings Plans
- Reserved Instances
- Spot Instances
- Dedicated Hosts
What is the Amazon EC2 On-Demand pricing option ideal for?
On-Demand Instances are ideal for short-term, irregular workloads that cannot be interrupted. No upfront costs or minimum contracts apply. The instances run continuously until you stop them, and you pay for only the compute time you use.
Sample use cases for On-Demand Instances include developing and testing applications and running applications that have unpredictable usage patterns. On-Demand Instances are not recommended for workloads that last a year or longer because these workloads can experience greater cost savings using Reserved Instances.
What is the Amazon EC2 Savings Plans pricing option ideal for?
AWS offers Savings Plans for several compute services, including Amazon EC2. Amazon EC2 Savings Plans enable you to reduce your compute costs by committing to a consistent amount of compute usage for a 1-year or 3-year term. This term commitment results in savings of up to 72% over On-Demand costs.
Any usage up to the commitment is charged at the discounted Savings Plan rate (for example, $10 an hour). Any usage beyond the commitment is charged at regular On-Demand rates.
Later in this course, you will review 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 Savings Plan.
What is the Amazon EC2 Reserved Instances pricing option ideal for?
Reserved Instances are a billing discount applied to the use of On-Demand Instances in your account. You can purchase Standard Reserved and Convertible Reserved Instances for a 1-year or 3-year term, and Scheduled Reserved Instances for a 1-year term. You realize greater cost savings with the 3-year option.
At the end of a Reserved Instance term, you can continue using the Amazon EC2 instance without interruption. However, you are charged On-Demand rates until you do one of the following:
- Terminate the instance.
- Purchase a new Reserved Instance that matches the instance attributes (instance type, Region, tenancy, and platform).
What is the Amazon EC2 Spot Instances pricing option ideal for?
Spot Instances are ideal for workloads with flexible start and end times, or that can withstand interruptions. Spot Instances use unused Amazon EC2 computing capacity and offer you cost savings at up to 90% off of On-Demand prices.
Suppose that you have a background processing job that can start and stop as needed (such as the data processing job for a customer survey). You want to start and stop the processing job without affecting the overall operations of your business. If you make a Spot request and Amazon EC2 capacity is available, your Spot Instance launches. However, if you make a Spot request and Amazon EC2 capacity is unavailable, the request is not successful until capacity becomes available. The unavailable capacity might delay the launch of your background processing job.
After you have launched a Spot Instance, if capacity is no longer available or demand for Spot Instances increases, your instance may be interrupted. This might not pose any issues for your background processing job. However, in the earlier example of developing and testing applications, you would most likely want to avoid unexpected interruptions. Therefore, choose a different EC2 instance type that is ideal for those tasks.
What is the Amazon EC2 Dedicated Hosts pricing option ideal for?
Dedicated Hosts are physical servers with Amazon EC2 instance capacity that is fully dedicated to your use.
You can use your existing per-socket, per-core, or per-VM software licenses to help maintain license compliance. You can purchase On-Demand Dedicated Hosts and Dedicated Hosts Reservations. Of all the Amazon EC2 options that were covered, Dedicated Hosts are the most expensive.
What is Amazon 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 are able to 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.
How does AWS Lambda work?
- 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.
