March 27, 2023

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.

 

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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:

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. 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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