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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November 21, 2022

Top 20 AWS CodeArtifact Interview Questions and Answers

With the help of AWS CodeArtifact, businesses of any size can quickly and easily save, publish, and distribute the software packages they use in their software development process. This service is fully managed. The popular package managers and build tools Maven and Gradle (for Java), npm and yarn (for JavaScript), pip and twine (for Python), and NuGet are all compatible with CodeArtifact (.NET).

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Ques. 1): How can I begin using CodeArtifact?

Answer:

By setting up a fresh domain and repository through the AWS Management Console, SDKs, or CLI, you can start utilising CodeArtifact. Then, you can publish packages to your repository using well-known package managers and build tools like the npm or yarn CLI (for JavaScript), maven or gradle (for Java), pip (for Python), or NuGet (for.NET). Additionally, you may use your CodeArtifact repository, which keeps any packages used in this manner, to consume open-source packages from widely accessible repositories like npm registry, Maven Central, Python Package Index (PyPI), or NuGet.org.

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Ques. 2): What is a CodeArtifact repository?

Answer:

Each set of package versions in a CodeArtifact repository corresponds to a different group of assets. A single repository may contain packages of any supported kind since repositories are polyglot. Each repository provides APIs that may be used with programmes like the npm CLI, the Maven CLI (mvn), pip, and NuGet to fetch and publish packages. See Quotas in AWS CodeArtifact for information on resource limitations.

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Ques. 3): How can I use the AWS CLI to log into a CodeArtifact repository?

Answer:

Install the AWS CLI first, then setup the AWS login information for an IAM user or role that has the necessary access rights to CodeArtifact. To utilise the CodeArtifact GetAuthorizationToken API, use the CLI. This API sells authentication tokens, which may be requested by package managers and development tools and supplied in the HTTP Authorization header. The login command from the CLI makes use of GetAuthorizationToken and sets up a package manager to utilise this token for all requests. Developers who have used the docker CLI to communicate with Amazon ECR will be familiar with this approach because it is comparable to the get-login command offered by Amazon ECR.

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Ques. 4): Can I combine AWS CodeBuild with AWS CodeArtifact?

Answer:

Yes. In your CodeBuild project setup, you may define which CodeArtifact repositories to utilise for downloading and publishing packages. Client tools for all the package types supported by CodeArtifact are included in the available CodeBuild images. With the help of the build's IAM role, CodeBuild configures the build tool or package manager to utilise the given repository and obtain a CodeArtifact auth token at build time. Additionally, you may select which build artefacts should be added to your CodeArtifact repository when the build is finished. When the contents of a CodeArtifact repository change, CloudWatch Events are released, which may be used to start a CodeBuild build.

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Ques. 5): Permissions may be enabled at the package level, right?

Answer:

Yes. CodeArtifact supports write permissions at the package level. These may be set up by adding clauses that identify a package ARN as the resource in a repository resource policy document. CodeArtifact only supports read permissions at the repository level, meaning an IAM principal may either read every package in a repository or none of them.

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Ques. 6): What is a domain in CodeArtifact?

Answer:

A domain is a feature unique to CodeArtifact that enables the management of several CodeArtifact repositories owned by the same company across various AWS accounts. For instance, a company may establish a central repository for team package sharing and project-level repositories to house package usage-specific storage.

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Ques. 7): What is the price of CodeArtifact?

Answer:

There are no up-front costs or commitments with CodeArtifact. You only pay for the amount of data transported out of an AWS Region, the volume of requests performed, and the software packages stored. A monthly free tier for storage and requests is offered by CodeArtifact.

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Ques. 8): How can I get a CodeArtifact artefact back?

Answer:

Use tools that are inherent to the language to fetch artefacts. Run the CodeArtifact CLI "login" command, followed by npm install webpack, to install, for instance, the npm package webpack and all of its dependencies. npm retrieves webpack from CodeArtifact and resolves dependencies using data from webpack's package. json file, after which it pulls all necessary dependencies recursively from CodeArtifact.

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Ques. 9): My packets are encrypted using CodeArtifact.

Answer:

Yes. All of the packages that CodeArtifact stores are secured at rest and in transit using TLS and AES-256 symmetric key encryption, respectively. Both the AWS Key Management Service (KMS) client controlled CMKs and the AWS managed CMKs are supported by CodeArtifact.

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Ques. 10): In CodeArtifact, how do I build repositories?

Answer:

Using the console wizard, the AWS SDKs or CLI, or programmatically, you may build repositories.

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Ques. 11): How can I set up a CodeArtifact repository to fetch packages from outside package archives like the npm registry?

Answer:

Create a repository with an external connection on the CodeArtifact console to fetch packages from a public repository like the npm registry. The AssociateExternalConnection API may also be used to link a public repository with a CodeArtifact repository. If the desired packages are not already available, CodeArtifact fetches and caches them from outside repositories whenever a package request is made.

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Ques. 12): How do I publish artifacts to CodeArtifact?

Answer:

Using language-specific tools like npm or yarn (for JavaScript), maven or gradle (for Java), twine (for Python), or NuGet, you may publish artefacts (.NET). For instance, using npm, releasing a new package version necessitates running two commands: To upload the package to the repository, first use the "login" command in the CodeArtifact CLI, and then run npm publish. As part of a continuous integration (CI) workflow, AWS CodeBuild may publish new package versions by executing the same instructions.

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Ques. 13): AWS CodeArtifact and AWS CodePipeline are compatible, right?

Answer:

Yes. When a package kept in a CodeArtifact repository changes, as when a new version of the package is released, you can use Amazon EventBridge to start a CodePipeline build.

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Ques. 14): Can I make my repositories accessible across accounts?

Answer:

Yes. Resource policies are supported by CodeArtifact repositories to allow cross-account access. By using the console or AWS CLI, you may add a resource policy.

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Top 20 AWS EC2 Auto Scaling Interview Questions and Answers

To assist you make sure you have the appropriate number of Amazon EC2 instances available to handle the load for your application, Amazon EC2 Auto Scaling is a fully managed solution designed to deploy or terminate Amazon EC2 instances automatically. Through fleet management for EC2 instances, which recognises and replaces unhealthy instances, and by automatically scaling your Amazon EC2 capacity up or down in accordance with conditions you establish, Amazon EC2 Auto Scaling aids you in maintaining application availability. To preserve performance and lower costs, you may utilise Amazon EC2 Auto Scaling to automatically increase the number of Amazon EC2 instances during surges in demand.

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Ques. 1): What is target tracking?

Answer:

You may quickly configure dynamic scaling for your application using target tracking, a new kind of scaling strategy. Goal tracking allows you to choose a load measure for your application, such as request count or CPU usage, define a target value, and Amazon EC2 Auto Scaling will change the number of EC2 instances in your ASG as necessary to meet that target. It works like a thermostat for your house, automatically altering the system to maintain the appropriate temperature. For instance, you may set goal tracking so that 50% of your fleet of web servers' CPUs are always in use. Then, to maintain an average CPU usage of 50%, Amazon EC2 Auto Scaling starts or terminates EC2 instances as necessary.

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Ques. 2): How does capacity balance work in Amazon EC2 Auto Scaling?

Answer:

A best practise for well-architected applications is to balance resources across Availability Zones, since this considerably improves aggregate system availability. When you specify several zones in your EC2 Auto Scaling group settings, Amazon EC2 Auto Scaling automatically distributes EC2 instances across the configured zones. New instances are always started by Amazon EC2 Auto Scaling so that the fleet as a whole is balanced between zones as evenly as feasible. Additionally, Amazon EC2 Auto Scaling only starts up in Availability Zones with capacity for the requested instance type.

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Ques. 3): What is meant by the phrase "stateful instances"?

Answer:

A stateful instance is one that contains data on it that is unique to that instance when the term is used. A stateful instance's data (or state information) is often lost when the instance is terminated. You might want to think about enabling instance protection to stop Amazon EC2 Auto Scaling from terminating a stateful instance or utilising lifecycle hooks to transfer the data off of it before it is terminated.

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Ques. 4): When should I choose AWS Auto Scaling over Amazon EC2 Auto Scaling?

Answer:

To handle scaling for numerous resources across different services, you should utilise AWS Auto Scaling. Using specified scaling methods, AWS Auto Scaling enables you to define dynamic scaling policies for several EC2 Auto Scaling groups or other resources. It takes less time to manage scaling policies for all of the scalable resources in your application using AWS Auto Scaling than it does using individual service consoles for each resource. Additionally, it is simpler since AWS Auto Scaling comes with predefined scaling methods that make it simpler to set up scaling policies.

If you simply need to scale Amazon EC2 Auto Scaling groups or if you only care about keeping the health of your EC2 fleet, you should utilise EC2 Auto Scaling. If you need to set up scheduled or step scaling policies, or if you need to build or configure Amazon EC2 Auto Scaling groups, you should also utilise EC2 Auto Scaling (as AWS Auto Scaling supports only target tracking scaling policies).

The EC2 interface, the Auto Scaling API, or CloudFormation may all be used to establish and configure EC2 Auto Scaling groups outside of AWS Auto Scaling. You may define dynamic scaling policies for your current EC2 Auto Scaling groups with the aid of AWS Auto Scaling.

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Ques. 5): A launch configuration is what?

Answer:

An EC2 Auto Scaling group will utilise a launch configuration as a template for launching EC2 instances. A key pair, one or more security groups, a block device mapping, the ID of the Amazon Machine Image (AMI), the instance type, and other details are all specified when creating a launch configuration for an instance. You provided the identical details to launch the instance if you've launched an EC2 instance before. An EC2 Auto Scaling group's launch settings must be specified when the group is created. You can use several EC2 Auto Scaling groups to describe your launch settings. One launch configuration may only be specified for one EC2 Auto Scaling group at a time, and once a launch configuration has been defined, it cannot be changed. Therefore, you must first construct a launch configuration before updating your EC2 Auto Scaling group with the new launch setting if you wish to alter the launch configuration for your EC2 Auto Scaling group. New instances are launched using the new configuration settings when the launch configuration for your EC2 Auto Scaling group is changed, but existing instances are unaffected.

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Ques. 6): Is there a method to create a volume just using Amazon EC2 Auto Scaling without installing an instance?

Answer:

Each time a new instance is introduced, a volume is associated with it. When a volume is nearly full, Amazon EC2 Auto Scaling doesn't instantly add another. A volume can be added to an existing instance using the EC2 API.

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Ques. 7): What distinguishes Predictive Scaling Policy from AWS Auto Scaling Plan's Predictive Scaling?

Answer:

In EC2 Auto Scaling, Predictive Scaling Policy introduces the same prediction mechanism that is available through AWS Auto Scaling plan as a native scaling policy. As with other scaling policies like Simple Scaling or Target Tracking, you may utilise predictive scaling directly using the AWS Command Line Interface (CLI), EC2 Auto Scaling Management Console, and AWS SDKs. Predictive scaling does not need the creation of an AWS Auto Scaling plan.

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Ques. 8): An EC2 Auto Scaling group (ASG) is what, exactly?

Answer:

For the purposes of fleet management and dynamic scaling, an Amazon EC2 Auto Scaling group (ASG) is a collection of EC2 instances that have similar features and are considered as a logical grouping. If a single application runs on many instances, for instance, you could wish to raise the number of instances in that group to improve the performance of the application or decrease the number of instances to save expenses during periods of low demand. Even if an instance falls unwell or depending on criteria you provide, Amazon EC2 Auto Scaling will automatically alter the number of instances in the group to keep a fixed number of instances.

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Ques. 9): How do lifecycle hooks work?

Answer:

With the use of lifecycle hooks, you may intervene before an instance starts running or before it is destroyed. If you are not building your software environment into an Amazon Machine Image, this can be extremely helpful (AMI). For instance, launch hooks can configure an instance's software to make sure it is ready to handle traffic before Amazon EC2 Auto Scaling connects it to your load balancer. Connecting the launch hook to an AWS Lambda function that calls RunCommand on the instance is one method to do this. Terminate hooks may be helpful for gathering crucial information from an instance before it disappears. For example, you could use a terminate hook to preserve your fleet’s log files by copying them to an Amazon S3 bucket when instances go out of service.

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Ques. 10): How can I manage who has access to the resources in Amazon EC2 Auto Scaling?

Answer:

You may perform the following things thanks to the integration between Amazon EC2 Auto Scaling and AWS Identity and Access Management (IAM), a service:

Create users and groups under the AWS account for your company.
Provide each user with their own security credentials under your AWS account.
Manage the rights each user has to access AWS resources for tasks.
Share your AWS resources with users of other AWS accounts.
Define the users or services that can take responsibilities in your AWS account.
Use your company's current IDs to provide rights to carry out actions utilising AWS resources.
Create an IAM policy, for instance, allowing the Managers group to utilise only the DescribeAutoScalingGroups.

For example, you could create an IAM policy that grants the Managers group permission to use only the DescribeAutoScalingGroups, DescribeLaunchConfigurations, DescribeScalingActivities, and DescribePolicies API operations. Users in the Managers group could then use those operations with any Amazon EC2 Auto Scaling groups and launch configurations. With Amazon EC2 Auto Scaling resource-level permissions, you can restrict access to a particular EC2 Auto Scaling group or launch configuration.

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Ques. 11): What if an Availability Zone does not offer the instance types I prefer?

Answer:

The launches will be retargeted to other Availability Zones included in the Auto Scaling group if none of the specified instance types are available in one. If all instance types are not accessible in an Availability Zone, Auto Scaling will retarget and always prefer to maintain your computing distributed across Availability Zones.

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Ques. 12): What distinguishes fleet management from dynamic scaling?

Answer:

You have a "fleet" if your application uses Amazon EC2 instances, as the term implies. The capability that automatically replaces unhealthy instances and keeps your fleet operating at the desired capacity is referred to as fleet management. The fleet management of Amazon EC2 Auto Scaling makes sure that both the instances themselves are operating properly and that your application can handle traffic. When Auto Scaling notices a failed health check, it can automatically switch out the instance.

The capability of Amazon EC2 Auto Scaling that automatically raises or reduces capacity based on demand or other variables is referred to as its dynamic scaling capabilities. For example, if your CPU spikes above 80% (and you have an alarm setup) Amazon EC2 Auto Scaling can add a new instance dynamically.

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Ques. 13): What constitutes an instance that is "unhealthy"?

Answer:

An unhealthy instance is one that fails a user-configured ELB health check or where the hardware has degraded for whatever reason (bad disc, etc.). Each individual EC2 instance is periodically given a health check by Amazon EC2 Auto Scaling. If the instance is linked to an Elastic Load Balancing load balancer, it may additionally execute ELB health checks.

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Ques. 14): How may a damaged instance be replaced by Amazon EC2 Auto Scaling?

Answer:

Amazon EC2 Auto Scaling immediately kills an unhealthy instance and substitutes a new one when it fails a health check. Amazon EC2 Auto Scaling gently detaches the compromised instance from the load balancer if you're using one before generating a new one and connects it to the load balancer. When an instance has to be replaced, nothing needs to be done manually because everything is handled automatically.

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Ques. 15): Is it possible to scale instances across several purchasing choices with a single ASG?

Answer:

Yes. In a single Auto Scaling Group, you can provide and automatically scale EC2 capacity across several EC2 instance types, Availability Zones, and On-Demand, RIs, and Spot purchasing options. You may choose which instance types are best for your application, set the appropriate split between On-Demand and Spot capacity, and indicate your preferences for how EC2 Auto Scaling should allocate the ASG capacity within each purchase model.

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Ques. 16): Can I scale out my ASG on Spot instances after establishing a basic capacity using On-Demand instances and RIs?

Answer:

Yes. You may set the group's basic capacity to be met by On-Demand instances when creating an ASG to mix buying models. EC2 Auto Scaling makes ensuring that the basic capacity is filled with On-Demand instances when the ASG scales in or out, and that anything beyond that is filled with either entirely Spot instances or a specific % mix of On-Demand or Spot instances.

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Ques. 17): How long does it take Amazon EC2 Auto Scaling to launch a new instance in the inService state after identifying a malfunctioning server?

Answer:

Within minutes, everything is ready. The bulk of replacements take place in within five minutes, and on average it takes considerably less time. It depends on a number of variables, including how long it takes for your instance's AMI to boot up.

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Ques. 18): Can I alter an ASG's setup to reflect new characteristics for merging buying models and defining multiple instance types?

Answer:

Yes. Customers can update an existing ASG to change one or all parameters related to combining purchasing models and specifying multiple instance types, including instance types, priority order for On-Demand instances, percentage split between On-Demand and Spot instances, and allocation strategy. This is similar to how other ASG parameters can be changed.

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Ques. 19): What advantages does utilising Amazon EC2 Auto Scaling offer?

Answer:

Your Amazon EC2 instance availability is maintained with the aid of Amazon EC2 Auto Scaling. Using Amazon EC2 Auto Scaling, you can automatically replace any Amazon EC2 instances that become faulty, whether you are operating one or hundreds of them. This makes sure that your application has the expected amount of computing power. To reduce the need to manually provision Amazon EC2 capacity in advance, you may utilise Amazon EC2 Auto Scaling to automatically expand your Amazon EC2 fleet by following the demand curve for your applications. For instance, when the average usage of your Amazon EC2 fleet is high, you may establish a condition to add new instances in increments to the ASG. Likewise, when CPU utilisation is low, you can set a condition to remove instances in increments. Additionally, you may utilise Elastic Load Balancing (ELB) to distribute traffic to your instances inside the ASG and Amazon CloudWatch to transmit alarms that will start scaling actions. Predictive Scaling strategy may be used to proactively expand capacity in advance of impending demand if you have predicted load variations. You can run your Amazon EC2 fleet at maximum utilisation thanks to Amazon EC2 Auto Scaling.

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Ques. 20): How would users be routed to the other servers in a group in the event of a breakdown without elastic load balancing (ELB)?

Answer:

You can connect to Route53 (which Amazon EC2 Auto Scaling does not currently support out of the box, but many customers use). You may also use your own reverse proxy or service discovery tools for internal microservices.

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