Showing posts with label compute optimizer. Show all posts
Showing posts with label compute optimizer. Show all posts

November 24, 2022

Top 20 AWS Compute Optimizer Interview Questions and Answers

 

AWS Compute Optimizer uses machine learning to examine historical utilisation metrics to help you determine the best AWS resource configurations for Amazon Elastic Compute Cloud (EC2) instance types, Amazon Elastic Block Store (EBS) volume configurations, and AWS Lambda function memory sizes. By suggesting the best AWS resources for your AWS workloads, AWS Compute Optimizer offers a collection of APIs and a console interface to help you lower costs and boost workload performance.

 

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Ques. 1): What information is used by AWS Compute Optimizer to make its recommendations?

Answer:

You give AWS Compute Optimizer permission to use CloudWatch metrics and resource configuration information when you choose to use the service. AWS Compute Optimizer uses this information to identify the resources to evaluate and to make suggestions because it needs a long enough metrics history.

 

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Ques. 2): How can I pinpoint my biggest room for performance and cost improvement?

Answer:

Through two new sets of dashboard-level metrics, savings opportunity and performance improvement opportunity, you can easily find and prioritise top optimization opportunities.

By implementing Compute Optimizer suggestions, you can save money each month on Amazon EC2, Amazon EBS, and AWS Lambda at the account level, resource type level, or resource level. Savings opportunity metrics quantify these savings. These indicators can be used to assess and rank cost-saving opportunities as well as track your progress over time. The percentage and number of underprovisioned resources at the account level and resource type level are quantified using performance improvement opportunity metrics. These indicators can be used to rank performance improvement initiatives that address the risks of resource bottlenecks.

 

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Ques. 3): What factors does AWS Compute Optimizer consider when selecting recommended EC2 instance options?

Answer:

Performance risk is a measure of how likely it is that the instance type won't provide enough resources for your task. For the recommended instance's CPU, RAM, EBS throughput, EBS IOPS, disc throughput, network throughput, and network PPS, Compute Optimizer determines a unique performance risk score. The percentage of time over the historical lookback period where capacity may be limited in the given resource dimension is used to calculate the performance risk score for each resource dimension. The maximum performance risk score across the examined resource specifications is used to compute the performance risk of the suggested instance.


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Ques. 4): What recommendations for Auto Scaling groups does AWS Compute Optimizer support?

Answer:

For EC2 Auto Scaling groups with a fixed group size, where desired, minimum, and maximum are all set to the same value and no scaling policy is applied, AWS Compute Optimizer recommends EC2 instance type and size. Additionally, all instances that make up an Auto Scaling group must fall into the M, C, R, T, X, I, D, H, and z instance families. Currently, Auto Scaling groups configured with a mixed instances policy are not supported by Compute Optimizer.


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Ques. 5): What information is used by AWS Compute Optimizer to recommend my EBS volume?

Answer:

Before making suggestions for EBS volumes, AWS Compute Optimizer requires at least 30 hours of metrics over a sustained period of time. IOPS and throughput measurements from CloudWatch are analysed by AWS Compute Optimizer for EBS volumes.


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Ques. 6): What types of Lambda functions can be used with Compute Optimizer?

Answer:

You may optimise two types of Lambda functions with the aid of Compute Optimizer. Lambda functions in the first category might have excessive amounts of memory. To cut costs, you can think about reducing these functions' memory requirements. Compute-intensive Lambda functions that might benefit from more CPU power fall under the second category. To make an equivalent increase in the CPU resources available to these routines and shorten runtime, you can think about increasing their memory sizes. Compute Optimizer does not provide recommendations for any functions that do not fit into one of these categories.


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Ques. 7): Does Compute Optimizer take into account pricing details for Lambda functions when making recommendations?

Answer:

Yes. When Compute Optimizer determines the best memory sizes for your Lambda functions, it also takes into account the predicted function runtime, public Lambda pricing, and the number of function invocations over the previous 14 days to arrive at a "would-be" cost figure. You can use this figure to calculate your Lambda cost if the memory size of your Lambda function had been set to the suggested value.


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Ques. 8): What is AWS Compute Optimizer capable of?

Answer:

With the aid of AWS Compute Optimizer, you can quickly select the best AWS resources for your workloads without the need for specialised knowledge or a significant time and financial commitment. To help you find the most effective optimization opportunities, the AWS Compute Optimizer console gives you a comprehensive, cross-account view of all the resources that AWS Compute Optimizer has assessed.


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Ques. 9): When should I utilise the EC2 instance type recommendations from AWS Compute Optimizer and when should I use the EC2 resource rightsizing suggestions from AWS Cost Explorer?

Answer:

The recommendation engine used by Compute Optimizer and Cost Explorer Resource Rightsizing Recommendations is the same. Customers can use Compute Optimizer's recommendations to find the best EC2 instance types for their workloads. In order to help cost-management owners quickly identify infrastructure rightsizing savings opportunities, the Cost Explorer console and API surfaces a subset of these recommendations that may result in cost savings and supplements them with customer-specific cost and savings information (such as billing information, available credits, RI and Savings Plans). All recommendations are sent through the Compute Optimizer console and its API, regardless of their financial impact. Engineering teams can use Compute Optimizer to evaluate price-performance trade-off for their workloads, receive recommendations that incorporate additional data (such as memory metrics), and evaluate projected resource utilization and performance risk.

 

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Ques. 10): How can I better comprehend the suggested EC2 instance settings using AWS Compute Optimizer?

Answer:

To help you understand how your workload would have performed under the recommended parameters, AWS Compute Optimizer predicts the CPU and memory utilisation of your EC2 instance if you had chosen the recommended option. In order to help you understand the adjustments you would need to make in order to move your workloads from the current instance to the recommended instance type, AWS Compute Optimizer additionally provides the configuration differences between the current instance and the suggested instance type.


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Ques. 11): What information is used by AWS Compute Optimizer to recommend my Auto Scaling group?

Answer:

Before making recommendations for Auto Scaling groups, AWS Compute Optimizer requires measurements for at least 30 hours. AWS Compute Optimizer examines both the settings of the Auto Scaling group, such as the scaling policy and related launch template, and the default CloudWatch metrics of each member EC2 instance, such as CPU utilisation and network I/O metrics.


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Ques. 12): Is there a connection between AWS Organizations and AWS Compute Optimizer?

Answer:

Yes, there is an integration between AWS Compute Optimizer and AWS Organizations that enables you to view all of your recommendations within your organisation. You must sign in using the principal account for your organisation and your organization's "all features" must be enabled in order to access this function.

 

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Ques. 13): How can I get AWS Compute Optimizer started?

Answer:

Visit the AWS Compute Optimizer console and select "opt in" to register for AWS Compute Optimizer. To use this service, you need an AWS account. AWS Compute Optimizer analyses your AWS resources as soon as you opt in and starts making recommendations. It could take up to 12 hours for AWS Compute Optimizer to thoroughly examine the AWS resources in your account when you first turn it on.


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Ques. 14): Enhance infrastructure metrics: what are they?

Answer:

Enhancing recommendation accuracy and relevance for workloads with monthly or quarterly utilisation patterns is a premium Compute Optimizer option for EC2 instances. When the functionality is activated, Compute Optimizer automatically ingests and examines up to six times more usage metrics history than the Compute Optimizer option that is used by default (up to three months of history compared to 14 days). With the Compute Optimizer console or API, you may enable the capability for all existing and newly generated EC2 instances and Auto Scaling groups at the organisation, account, or resource level.

 

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Ques. 15): Does AWS Compute Optimizer take into account the cost of EC2 instances when making recommendations?

Answer:

Following the creation of a list of the best AWS resources for your workload, AWS Compute Optimizer uses predicted performance risk and a number of pricing factors, such as on-demand pricing, to rank its suggestions. Spot pricing and other transient pricing considerations are not taken into account by AWS Compute Optimizer.

 

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Ques. 16): How does the recommended EBS volume alternatives' performance risk get determined by AWS Compute Optimizer?

Answer:

Performance risk is a measure of how likely it is that the suggested solution won't be able to handle your workload's performance demands. You may need to put in more work to confirm that the recommended EBS volume configuration satisfies your workload's performance needs the higher the performance risk.

 

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Ques. 17): Do all AWS resources receive suggestions from AWS Compute Optimizer?

Answer:

For particular classes of EC2 instances, EC2 Auto Scaling groups, EBS volumes, and Lambda functions, AWS Compute Optimizer provides suggestions.

 

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Ques. 18): What information is used by AWS Compute Optimizer to suggest EC2 instances for me?

Answer:

When recommending an EC2 instance type, AWS Compute Optimizer looks at standard CloudWatch parameters including CPU utilisation, network packets per second, local storage throughput, and local storage IOPS.

 

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Ques. 19): What categories of EBS volumes does AWS Compute Optimizer recommend?

Answer:

IOPS recommendations for Provisioned IOPS (io1 and io2) volumes as well as throughput recommendations for General Purpose (SSD) (gp3) volumes are supported by AWS Compute Optimizer.

 

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Ques. 20): When making suggestions, does AWS Compute Optimizer take into account EBS volume price data?

Answer:

After determining a list of the best EBS volume configurations for your workload, AWS Compute Optimizer uses estimated performance risk and public EBS price to rank the suggestions.

 

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