Showing posts with label dynamodb. Show all posts
Showing posts with label dynamodb. Show all posts

March 26, 2023

Top AWS Fault Injection Simulator (FIS) Interview Questions and Answers

    

    An application's performance, observability, and resilience can all be increased by using the AWS Fault Injection Simulator (FIS), a fully managed service. To help teams gain confidence in the behavior of their applications, FIS streamlines the process of setting up and performing controlled fault injection experiments across a variety of AWS services.


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Ques. 1): AWS Fault Injection Simulator (FIS) – what is it?

Answer:

It is simpler to increase an application's performance, observability, and resiliency by using the AWS Fault Injection Simulator, a fully managed service for fault injection experiments on AWS. Chaos engineering, which is the practise of straining an application in testing or production environments by generating disruptive events, such as a rapid spike in CPU or memory consumption, watching how the system reacts, and making modifications as necessary, uses fault injection experiments.


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Ques. 2): How closely do the defects that AWS FIS injects match up to actual world circumstances?

Answer:

The conditions produced by FIS fault inject actions are quite similar to those that exist in reality. As an illustration, increasing CPU usage actually uses CPU resources. The experience is the same as with any other throttling because the operation to throttle API calls throttles those requests at the control plane level. In contrast to the actual world, FIS gives you the power to halt an experiment at any time and, when practical, to specify rollback actions that go into effect when an action period is up.


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Ques. 3): What fundamental ideas underlie fault injection actions?

Answer:

A fault injection activity in FIS can result in a heavy CPU burden being placed on an EC2 instance. A distinct set of attributes are accepted by every FIS action. The property for this example of CPU load on an EC2 instance would be the% value of the load. There are many FIS actions with various property values. You may also manage the experiment's timeline and duration with the aid of FIS activities. You can select the StartTime and length of the experiment for each action. For instance, you may plan your experiment so that it includes a CPULoad action that raises the CPU load to 75%, starts at StartTime of 0, and runs for 60 seconds.


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Ques. 4): How do I keep track of an AWS FIS experiment's effects?

Answer:

You may check on an experiment's progress and see the results of each completed step using the FIS console. You may also utilise CloudWatch dashboards and monitoring to keep an eye on the condition of your Amazon resources. Throughout an experiment, FIS creates CloudTrail logs for every action it makes on your AWS resources, giving you complete visibility and auditing over all account activity.


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Ques. 5): How can I begin utilising AWS FIS?

Answer:

To define, manage, and control the experiment, utilise either the FIS console or the Amazon CLI. To begin, design an experiment that contains any actions you want to take against any number of targets. The experiment template allows you to define every aspect of the experiment, including the targets, actions, alarm, and stop circumstances. The experiment can then be started. A distinct execution-id is returned by each start-experiment. The execution-id argument can be used to monitor the progress of a particular run.


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Ques. 6): How does Chaos Engineering work?

Answer:

Chaos engineering is the technique of stressing an application in testing or production environments by inflicting disruptive events—like server failures or API throttling—and then watching the system's reaction and making adjustments as necessary. Teams can better understand hidden problems, monitoring blind spots, and performance bottlenecks in distributed systems by using chaos engineering to simulate real-world settings. Starting with steady-state behaviour analysis, creating an experiment hypothesis (for example, terminating x instances will result in x% more retries), running the experiment by injecting fault actions, watching for rollback conditions, and fixing the flaws are the first steps.


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Ques. 7): What are the core concepts of the target resources?

Answer:

The Amazon resources selected as the experiment's targets for fault injection. Examples include tags, instance-id, cluster-id, VPC, etc. Targets could be random or specified Amazon resources (s).


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Ques. 8): How can I find out the progress of the AWS FIS experiment?

Answer:

To monitor the experiment's status, utilise the management console or AWS CLI. You can list all experiment executions with the list-experiment-executions command. You can obtain information about a specific execution with get-experiment-execution. You can obtain the precise actions taken and their corresponding outcomes by requesting information about a specific run. You can record and continually track the actions that are taken using CloudTrail.


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Ques. 9): Is an agent required for AWS FIS?

Answer:

The installation of any agents in your resources is not necessary for many action kinds. The SSM agent is necessary for instance level problems, such as increased CPU and memory usage.


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Ques. 10): Why need I to utilise AWS FIS?

Answer:

To enhance performance, observability, and resiliency, utilise FIS to scale up the discovery of an application's flaws. You no longer need to handle complicated tooling since FIS provides practical fault injection experience from a centralised UI. Using FIS's adaptable experiment template, you can create unique experiments to model complicated outage scenarios and combine several failure kinds within a single experiment. Stop conditions are built-in safety procedures offered by FIS that halt an experiment before it spirals out of control.


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Ques. 11): What defect types can I introduce using AWS FIS?

Answer:

You can run pre-defined fault injection experiments using FIS on several platforms, including computation, databases, networks, and more.


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Ques. 12): What fundamental ideas underpin the conduct of an experiment?

Answer:

One or more sets of Target, Fault Injection Actions, Post Action, and Stop Condition are included in a FIS experiment. With fault injection action(s) and an AWS target, you begin the FIS experiment (s). You broaden the scope of the experiment to incorporate more Amazon resources and fault injection actions as your application's resilience increases. Once the experiment is specified, you may set up a schedule for it to run at particular times.


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Ques. 13): How do I put a halt to the test?

Answer:

You can use the CLI command stop-experiment or the FIS console to execute stop-experiment. You can also halt an experiment by using CloudWatch enable-alarm-actions.


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Ques. 14): Do I need to do anything before using AWS FIS?

Answer:

Before adopting FIS, there are a number of factors to consider. You must first decide on the experiment's intended deployment. If this is your first trial, you might want to think about starting in a test or pre-production setting. You can introduce fault injection as your fault injection experiment develops to continuously evaluate resilience in the production environment. The steady-state behaviour must be defined, and significant technical and business parameters (such as latency and CPU load) must be identified (e.g., failed logins per minute, number of retries, page load speed). The next step is to formulate a hypothesis for the outcome of the experiment. If done, the impact of any commercial or technical indicator should not be greater than, is how your hypothesis is characterised. For an authentication service, for instance, your hypothesis might be "if network latency increases by 10%, there will be fewer than 1% increase in login failures." After the experiment, you assess whether the application's resilience meets your technical and business expectations.


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Ques. 15): Can I incorporate AWS FIS into my CD pipeline?

Answer:

Sure, you may incorporate FIS into your pipeline for continuous delivery. You will be able to do this as part of your software delivery process to repeatedly test how fault actions affect the outcome.


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Top 20 AWS CodePipeline Interview Questions and Answers


        Model, visualise, and automate the steps necessary to deploy your product with AWS CodePipeline, a continuous delivery service. You can model the entire release process for creating your code, deploying it to test environments, testing your application, and releasing it to production with AWS CodePipeline. Every time there is a code change, AWS CodePipeline then builds, tests, and deploys your application in accordance with the specified workflow. An end-to-end continuous delivery solution can be created by integrating partner technologies and your own unique tools into any stage of the release process.


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Ques. 1): What makes AWS CodePipeline a good choice?

Answer:

You can speed up and improve the quality of your software updates by automating your build, test, and release processes with AWS CodePipeline. This is done by subjecting all fresh changes to a standardised set of quality tests.


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Ques. 2): Describe an artefact.

Answer:

A file or set of files are affected when an action is executed. These documents are known as artefacts. Further steps in the pipeline can work on these items. For instance, a build action will read in a source artefact that contains the most recent version of the code that was output by a source action. The build action will upload the build output after compilation so that it can be read by the later deployment activities.


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Ques. 3): How would I begin a pipeline?

Answer:

When you build a pipeline, it will immediately start a run to publish the most recent version of your source code. After then, a fresh run is started each time your source location is modified. Moreover, you can use the Release Change button in the pipeline console to re-run the most recent revision through the pipeline.


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Ques. 4): How can I use AWS Lambda functions and serverless applications to practise continuous delivery?

Answer:

By integrating the AWS Serverless Application Model template and its accompanying files in your source code repository, you can publish modifications to your serverless application. To package your code for distribution, you can utilise AWS CodeBuild in your pipeline. Afterwards, you may develop a change set and launch your serverless application using AWS CloudFormation activities. You have the choice to add more phases to your workflow, such as automated tests or manual approvals.


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Ques. 5): What products can be integrated with AWS CodePipeline?

Answer:

AWS Elastic Beanstalk, AWS CloudFormation, AWS OpsWorks, Amazon ECS, and AWS Lambda are just a few of the AWS services that AWS CodePipeline connects with. AWS CodePipeline also incorporates with a variety of partner products. Finally, CodePipeline allows you to integrate any existing tool and create your own unique actions.


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Ques. 6): Can I allow an IAM user in a different Amazon account to access the pipeline in a different AWS account?

Answer:

Yes. To grant access to the pipeline and any associated resources to an IAM user in another account, you can create an IAM role in the AWS account that owns the pipeline. See Walkthrough: Delegating Access Across AWS Accounts For Accounts You Own Using IAM Roles and Setup Cross-Account Access to a Pipeline for instructions on how to enable such cross account access.


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Ques. 7): What is continuous delivery?

Answer:

A software development method known as "continuous delivery" involves automatically building, testing, and getting code updates ready for production release. You can use AWS CodePipeline as a service to carry out continuous delivery.


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Ques. 8): An transition is what?

Answer:

In the AWS CodePipeline console, the arrows that connect the stages of a pipeline are transitions. The transition arrow represents the automatic sending of revisions to the following stage once they have successfully completed the actions in a stage. Between phases, transitions may be blocked or enabled.


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Ques. 9): Is it possible to duplicate an existing pipeline?

Answer:

Yes. To obtain the JSON structure of your current pipeline, use the Amazon CLI command get-pipeline. Then, you can create a new pipeline with the exact same structure as the previous one using that JSON and the create-pipeline Amazon CLI command.


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Ques. 10): How do I use a release workflow process to provision and manage my AWS resources?

Answer:

You can use continuous delivery to automatically build and test modifications to your AWS CloudFormation stacks before promoting them to production stacks using AWS CodePipeline and AWS CloudFormation. You may quickly and dependably make changes to your Amazon infrastructure using this release method. You can add more actions to your workflow, such as manual approvals, test actions, or the execution of Amazon Lambda functions.


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Ques. 11): How can I set up and administer my AWS resources using a release workflow procedure?

Answer:

Continuous delivery enables you to automatically generate and test modifications to your AWS CloudFormation stacks prior to promoting them to production stacks using AWS CodePipeline and AWS CloudFormation. You may make changes to your AWS infrastructure quickly and reliably using this release method. You can add more steps to your workflow, such as test activities, human approvals, or calls to Amazon Lambda functions.


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Ques. 12): How can I get notified or alerted when something happens in AWS CodePipeline?

Answer:

For events that have an effect on your pipelines, you can generate notifications. Amazon SNS notifications will be used for notifications. Each notification will have a link to the resources whose event caused it, along with a status message. There is no additional price for notifications, but you can be charged for other AWS services that notifications uses, including Amazon SNS. Customers can also set up notifications to go to their Slack channels or Amazon Chime chat rooms when utilising the AWS Chatbot.


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Ques. 13): Describe a pipeline.

Answer:

A pipeline is a workflow concept that explains the release procedure for software modifications. The workflow is described using a list of phases and activities.


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Ques. 14): How can a pipeline be stopped?

Answer:

You can disable a transition from one step to another to halt a pipeline. Your pipeline will keep running revisions through the steps after it has been disabled, but revisions will not be promoted via the disabled transition to subsequent stages.


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Ques. 15): Is it possible to obtain a call log for the AWS CodePipeline API?

Answer:

Yes. Simply enable Amazon CloudTrail in the AWS Management Console to acquire a history of all AWS CodePipeline API calls made on your account for security analysis and operational troubleshooting.


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Ques. 16): How do revisions work?

Answer:

A revision is a modification made to the pipeline's specified source location. It may contain data, build output, configuration, or source code. Several revisions may be going through a pipeline at once.


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Ques. 17): Can I modify an already-built pipeline?

Answer:

Yes. You can add or delete pipeline stages as well as add, amend, or remove stage actions using the Amazon CodePipeline console or AWS CLI.


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Ques. 18): What is an action?

Answer:

An action is a procedure carried out on a revision. According on the stage design, pipeline events happen in a predetermined sequence, either serially or concurrently.


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Ques. 19): Can actions run in parallel?

Answer:

Yes. For any stage, you can set up one or more actions to run concurrently.


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