Top 20 AWS Auto Scaling Interview Questions and Answers

While your applications are monitored by AWS Auto Scaling, capacity is automatically adjusted to provide constant, predictable performance at the lowest feasible cost. It's simple to build up application scaling for numerous resources across many services in a matter of minutes using Amazon Auto Scaling. You may create scaling plans for resources like Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas using the service's straightforward but effective user interface. With recommendations that let you balance performance, prices, or both, Amazon Auto Scaling simplifies scaling. You may now combine Amazon EC2 Auto Scaling and AWS Auto Scaling to scale extra resources for other AWS services if you already use Amazon EC2 Auto Scaling to dynamically scale your Amazon EC2 instances. With AWS Auto Scaling, your applications always have the right resources at the right time.

Ques. 1): What advantages does AWS Auto Scaling offer?

Answer:

The performance and expenses of your apps may be optimised quickly and easily using AWS Auto Scaling.

Scaling can be set up rapidly thanks to Amazon Auto Scaling, which offers a consistent scaling experience across all the scalable resources that support your application. With a single, user-friendly interface, you can rapidly specify target utilisation levels for each group of similar resources and view the average utilisation for all of your scalable resources.

Make informed scaling choices by automating the way groups of various resources react to changes in demand with AWS Auto Scaling. You can choose to optimise availability, costs, or a balance of the two using simple scaling strategies. According to your preferences, Amazon Auto Scaling automatically generates all scaling policies and establishes objectives for you.

Automatically maintain performance: Amazon Auto Scaling continuously checks that the resources supporting your application are performing at the levels you've set. In order to maintain a high level of service when demand spikes, Amazon Auto Scaling automatically raises the capacity of limited resources.

AWS Auto Scaling can assist you in maximising your utilisation and cost efficiencies while utilising AWS services so that you only pay for the resources you actually require. In order to save you money, Amazon Auto Scaling will automatically eliminate any extra resource capacity when demand declines.

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Ques. 2): How can I scale AWS resources in multiple ways?

Answer:

Customers of AWS have a variety of choices for resource scaling. You can make sure that you have the appropriate number of Amazon EC2 instances available to handle the load for your application by using Amazon EC2 Auto Scaling. Moreover, EC2 Auto Scaling has the ability to recognise when an instance is unhealthy, terminate it, and start a new instance in its place. Your applications benefit from improved fault tolerance, availability, and cost control when you use EC2 Auto Scaling.

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Ques. 3): When compared to auto scaling for individual services, when should I use Amazon auto scaling?

Answer:

To manage scaling for numerous resources across multiple services, you should use Amazon Auto Scaling. Unified scaling for numerous resources is possible with Amazon Auto Scaling, and provided instructions assist make configuring scaling simpler and quicker. To scale certain AWS services, you can also utilise the individual service consoles, the Auto Scaling API, or the Application Auto Scaling API. If you wish to build up step scaling rules or scheduled scaling, you should also use the separate consoles or API, as Amazon Auto Scaling only generates target tracking scaling policies.

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Ques. 4): How can I combine target tracking with predictive scaling?

Answer:

Target tracking and predictive scaling together increase the responsiveness of your EC2 capacity changes to incoming application traffic. Target tracking modifies the real capacity based on the current traffic, whereas predictive scaling sets the minimum capacity for your application based on anticipated traffic. Target tracking attempts to monitor the desired capacity utilisation levels under a variety of traffic scenarios and takes into account unforeseen traffic spikes and other changes. A user configures predictive scaling and target tracking jointly to produce a scaling plan.

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Ques. 5): With AWS Auto Scaling, what can I scale?

Answer:

Via a single, unified interface, you can utilise AWS Auto Scaling to configure scaling for the following resources in your application:

groups for Amazon EC2 auto scaling:

Services offered by Amazon Elastic Container Service (currently ECS services cannot be discovered using resource tags)

EC2 Spot Fleets from Amazon:

replicas for Amazon Aurora with a capacity for Amazon DynamoDB throughput

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Ques. 6): What is the price of AWS Auto Scaling?

Answer:

AWS Auto Scaling is free to utilise, just like Auto Scaling on specific AWS resources. Amazon CloudWatch enables AWS Auto Scaling, so service fees for CloudWatch and your application resources apply (such as Amazon EC2 instances, Elastic Load Balancing load balancers, etc.).

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Ques. 7): How does AWS Auto Scaling recommend scalability?

Answer:

The most prominent scaling metrics and thresholds utilised for Auto Scaling serve as the foundation for AWS Auto Scaling's scaling recommendations. By offering recommendations for the minimum and maximum sizes of the resources, it also suggests secure scaling guardrails. By doing this, you can start out rapidly and gradually fine-tune your scaling plan.

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Ques. 8): What is a scaling plan?

Answer:

A scaling plan is a set of instructions for scaling various Amazon resources. You set up a scaling strategy by first choosing every EC2 resource that supports your application in AWS Auto Scaling. Then you choose the resource utilisation measure you want to monitor, like CPU utilisation, and set the value to monitor, like 50%. Finally, if you haven't done, you may need to set up the CloudWatch statistic that represents your input traffic flow.

The primary inputs for the scaling strategy are the metrics for resource utilisation and incoming traffic. Predictive Scaling creates traffic projections using the incoming traffic metric.Based on these forecasts; Predictive Scaling then schedules future scaling actions to configure minimum capacity. Dynamic Scaling uses the resource utilization metric and its target value to dynamically change the EC2 capacity for your application over time as traffic varies.

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Ques. 9): How can I begin using Amazon Auto Scaling?

Answer:

You can choose your applications using Amazon Auto Scaling based on resource tags or AWS CloudFormation stacks. You may quickly and easily construct a scaling strategy for your application that specifies how each of its resources should be scaled. According to the scaling method you've chosen, Amazon Auto Scaling builds a target tracking scaling policy for each resource using the most common measure for that type of resource. You can select from three predefined scaling recommendations that optimise availability, optimise costs, or balance the two in order to set target values for your resource metrics. You can also specify your own goal values if you'd like. AWS Auto Scaling also automatically sets the min/max values for the resources.

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Ques. 10): When ought I to employ AWS Auto Scaling?

Answer:

If your application employs one or more scalable resources and has fluctuating load, you should use Amazon Auto Scaling. A web application for online shopping that experiences fluctuating traffic throughout the day would be a suitable example. Elastic Load Balancing is used to distribute incoming traffic, Amazon EC2 handles the compute layer, and DynamoDB handles the data layer in accordance with conventional three-tier architecture. In this scenario, EC2 Auto Scaling groups and DynamoDB tables that are supporting the application will be scaled by AWS Auto Scaling in response to the demand curve.

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Ques. 11): What is Predictive Scaling?

Answer:

Amazon Auto Scaling's Predictive Scaling feature analyses past traffic patterns and projects them into the future to plan future adjustments to the number of EC2 instances at the proper periods. Machine learning models are used in predictive scaling to predict daily and weekly patterns.

Predictive scaling combined with auto scaling results in capacity provisioning that is quicker, easier, and more precise, which makes applications more responsive and less expensive. Predictive Scaling makes Auto Scaling faster and more precise by provisioning EC2 instances in ahead of changing traffic.

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Ques. 12): AWS Auto Scaling versus Amazon EC2 Auto Scaling: When Should I Use Each?

Answer:

To manage scaling for numerous resources across multiple services, you should use Amazon Auto Scaling. Using specified scaling methods, AWS Auto Scaling enables you to define dynamic scaling policies for numerous 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 because AWS Auto Scaling comes with predefined scaling strategies that make it simpler to set up scaling policies. If you wish to generate predictive scaling for EC2 resources, you need also use Amazon Auto Scaling.

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 use EC2 Auto Scaling. If you need to set up scheduled or step scaling policies, or if you need to create or configure Amazon EC2 Auto Scaling groups, you should also use EC2 Auto Scaling (as AWS Auto Scaling supports only target tracking scaling policies).

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

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Ques. 13): Can Predictive Scaling be set up to provision instances before a traffic increase actually occurs?

Answer:

Yes, you can opportunistically set a buffer time to supply instances ahead of an expected change in traffic. Applications whose EC2 instances require some "warm-up" time before they are prepared to serve application traffic can benefit from this.

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Ques. 14): What resources are scalable according to AWS Auto Scaling?

Answer:

In order to find the supported Amazon resource types that can be scaled, AWS Auto Scaling will examine your chosen AWS CloudFormation stack or resources with the provided tags. Please be aware that tags cannot presently be used to find ECS services.

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Ques. 15): What resources are scalable according to AWS Auto Scaling?

Answer:

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Ques. 16): How do I choose a stack of applications in AWS Auto Scaling?

Answer:

Choose resources based on a shared resource tag or an AWS CloudFormation stack (s). Please be aware that tags cannot presently be used to find ECS services.

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Ques. 17): What volume of historical data is required by Predictive Scaling to produce the scaling plan?

Answer:

Although it can create a prediction scaling schedule with as little as a day's worth of data, predictive scaling requires up to two weeks of historical data.

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Ques. 18): Predictive Scaling predicts traffic for how far into the future?

Answer:

Predictive Scaling predicts traffic 48 hours in advance and plans capacity changes for those 48 hours once every 24 hours.

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Top 20 AWS Cloud Control API Interview Questions and Answers

Ques. 1): What is AWS Cloud Control API?

Answer:

AWS Cloud Control API is a brand-new AWS feature that offers a standard set of CRUDL (Create, Read, Update, Delete, and List) APIs to make it simple and consistent for developers to manage their cloud infrastructure. Developers can uniformly manage the lifecycle of AWS and third-party services thanks to Cloud Control API's common APIs.

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Ques. 2): What type of resource type operations are provided by Cloud Control API?

Answer:

All control plane (CRUDL) operations are supported by the Cloud Control API. A cloud-based resource can be created, read, updated, deleted, or listed using these procedures. You can use these operations, for instance, to control an AWS Lambda Function's lifecycle. You cannot, however, operate on the underlying objects kept in the AWS Lambda Function using control plane operations. They are data plane operations and are not supported by Cloud Control API.

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Ques. 3): How can I benefit by using Cloud Control API?

Answer:

As a developer, you may prefer to simplify the way you manage the lifecycle of all your resources. To configure your cloud resources in a consistent manner, you can use the pre-defined format of the Cloud Control APIs' uniform resource configuration model. Additionally, while managing your resources, you will profit from consistent API behaviour (response components and errors). For example, you will find it simple to debug errors during CRUDL operations through uniform error codes surfaced by Cloud Control API that are independent of the resources you operate on. You will find it straightforward to set up cross-resource dependencies by using the Cloud Control API. You will also no longer require to author and maintain custom code across multiple vendor tools and APIs to use AWS and third-party resources together.

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Ques. 4): Can I publish third-party resource types that the Cloud Control API can make available?

Answer:

Yes. If you intend to use third-party resources in your cloud infrastructure or applications that aren't supported by the Cloud Control API, you can model and publish that type of resource by creating the provisioning logic for it and making sure it satisfies the contract test bar set by the CloudFormation Registry. You can then use the Cloud Control API to access your resource type once it has been published on the CloudFormation Registry.

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Ques. 5): How do I get started as a developer using the Cloud Control API?

Answer:

The first step in getting started after completing the prerequisite is to configure your resources in accordance with the Cloud Control API universal resource model. You can accomplish so by defining the resource attributes (properties or tags) (properties or tags). After that, you can construct, configure, and manage your cloud infrastructure by passing those values to the Cloud Control API Build, Update, Delete APIs using the Amazon CLI. For instance, you may use the Create API with the following API parameters to create an AWS CloudWatch Log resource using the CLI:

aws cloudcontrol create-resource --type-name AWS::Logs::LogGroup --desired-state "{\"LogGroupName\": \"CloudControlExample\",\"RetentionInDays\":90}"

To find the resources that make up your infrastructure and evaluate its configuration, you may also utilise the Cloud Control API List and Describe APIs. For instance, you can get the properties of the CloudWatch Log resource you established using the Cloud API GetResource API.

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Ques. 6): Can I publish my own resources for developers to use?

Answer:

Yes. Once your resource types pass a series of contract tests that outline the required behaviour of your resource type, you may publish them to the CloudFormation Public Registry.

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Ques. 7): Which partner tools can be integrated with the Cloud Control API?

Answer:

Cloud Control API can be integrated with any partner tool that communicates with AWS service-specific control plane APIs for integration. For instance, Cloud Control API can be integrated with infrastructure as code (IaC) solutions that let developers control their applications automatically. The Cloud Control API partners for IaC tools are HashiCorp Terraform and Pulumi. In a similar vein, Cloud Control API can be integrated with configuration management tools or cloud security posture management tools that enable developers to track configuration changes on their application to spot compliance and security gaps.

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Ques. 8): How would developers who use partner tools integrated into Cloud Control API find the experience of using it?

Answer:

As soon as new Amazon resources become available on the CloudFormation Registry, you will have access to support for all current and future AWS resources. On the day of launch, new AWS resources are normally accessible on the CloudFormation Registry.

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Ques. 9): What connection exists between Amazon CloudFormation Registry and Cloud Control API?

Answer:

As soon as they become accessible on the CloudFormation Registry, AWS Cloud Control API will handle every AWS resource type (whether it be fully mutable or immutable) as well as third-party resource types. By visiting the CloudFormation Registry, you can learn the schema and handler rights for resources supported by the Cloud Control API.

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Ques. 10): The AWS Cloud Control API: Why should I use it?

Answer:

If you want to control your cloud infrastructure quickly, consistently, and simply utilising a collection of standard APIs, you should utilise the Cloud Control API. There are fewer APIs to learn as developers add services to their infrastructure since they can manage supported services consistently using the Cloud Control API. For instance, developers can use the Cloud Control API's CreateResource API to build any supported cloud resource, including IAM roles, Lambda functions, and third-party resources like Datadog monitors and MongoDB Atlas clusters that are listed in the CloudFormation Registry. By removing the need to write, maintain, and configure bespoke code across many service-specific APIs, developers can work more quickly. Also, while managing your resources, you will profit from consistent API behaviour (response components and errors). For example, you will find it straightforward to debug failures during CRUDL operations using uniform error codes displayed by Cloud Control API that are standardised across the resource types you operate on.

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Ques. 11): Which AWS resource types can I use? How quickly will new AWS resource types be supported by the Cloud Control API?

Answer:

Cloud Control API supports hundreds of AWS resources. Refer to our documentation, for a full list of supported resources. Cloud API will provide support for future AWS resource types as soon as they are published on the CloudFormation Registry.

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Ques. 12): How can I benefit by onboarding with Cloud Control API?

Answer:

In order for our shared clients to quickly take advantage of the most recent Amazon advancements, you may wish to consider supporting all AWS resources in your tool offerings as a partner. You can avoid the ongoing development work that can take weeks to build support for each new AWS resource released by onboarding with Cloud Control API only once. Once partners have integrated their own solutions with Cloud Control API, new AWS services and features can be automatically accessed without further integration work because Cloud Control API is always up to date with the most recent AWS resources as soon as they become available on the CloudFormation Registry.

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Ques. 13): What do resource types mean?

Answer:

A resource type allows you to manage the lifecycle of resources such as an AWS Lambda Function. A resource type includes handlers that manage API interactions with the underlying AWS or third-party services as well as schema (resource properties and handler permissions). These API interactions include create, read, update, delete, or list depending upon the service.

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Ques. 14): How do I raise any issues faced while using Cloud Control API?

Answer:

If you face run-time issues, for example CRUDL operation failure, then contact AWS Support. If you face issues pertaining to gaps in AWS resource support or need for feature enhancements for supported AWS resources, then create an issue on the AWS CloudFormation Open Coverage Roadmap.

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Ques. 15): Why should I use the Cloud Control API if I already have interfaces with existing Amazon resources?

Answer:

Using one-time onboarding with Cloud Control API, you may save recurring work to model integrations with new AWS resources.

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Ques. 16): Can I manage my cloud infrastructure using both the Cloud Control API and service-specific APIs?

Answer:

Yes. To control your cloud infrastructure, you can use either the currently available service-specific APIs or the standard APIs provided by Cloud Control API.

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Ques. 17): What third-party resources does Cloud Control API support?

Answer:

Cloud API supports all third-party public or private resource types published in the CloudFormation Registry.

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Ques. 18): How do I get started on Cloud Control API?

Answer:

By creating a one-time integration with Cloud Control API's CRUDL APIs and resource configuration paradigm, partners can sign up for the service (schema).

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Ques. 19): Are there any prerequisites for setting up Cloud Control API?

Answer:

Yes. An AWS account set up with the proper Amazon Identity and Access Management (IAM) user is required.

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