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.

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 AWS DMS Interview Questions and Answers

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AWS DMS supports both homogenous migrations, such as Oracle to Oracle, and heterogeneous migrations between multiple database engines, such as Microsoft SQL Server to Amazon Aurora, and helps databases move to AWS rapidly, securely, and with the least amount of downtime possible.

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Ques. 1): What is AWS Database Migration Service, and how do I use it?

Answer:

With Amazon Database Migration Service, getting started is quick and easy. It takes less than ten minutes to set up the majority of data replication activities. Enter the Start Migration wizard by going to the Amazon Database Migration Service section of the AWS Management Console. Choose an existing replication instance or start a new one, choose your source and target endpoints, accept the built-in schema mapping rules, or define your own modifications. As soon as you finish the wizard, data replication will begin.

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Ques. 2): Does the Amazon Database Migration Service support any specific sources or targets?

Answer:

Many homogeneous and heterogeneous data replications are supported by AWS Database Migration Service (DMS).

Both the source and the target databases (or just one of them) must be located on EC2 or RDS. On-premises to on-premises database replication is not supported.

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Ques. 3): Do these steps differ while replicating data continuously?

Answer:

The production environment switchover, which does not occur in continuous data replication, is the only distinction. Until you modify it or stop it, your data replication task will continue to function.

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Ques. 4): Can I replicate data from sources that are encrypted?

Answer:

Amazon Database Migration Service can read from and write to encrypted databases, hence the answer is yes. Your database endpoints are connected to by AWS Database Migration Service via the SQL interface layer. AWS Database Migration Service may retrieve encrypted data from these sources and copy it to the target if you use the Transparent Data Encryption features of Oracle or SQL Server. Storage-level encryption is the same. Amazon Database Migration Service will be able to connect to the database source and propagate data (in unencrypted form) to the target as long as it has the proper login credentials. To keep your information confidential, we advise employing encryption-at-rest on the target. If you use application-level encryption, the data will be transmitted through AWS Database Migration Service as is, in encrypted format, and then inserted into the target database.

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Ques. 5): When should I choose Amazon Application Discovery Service and Migration Evaluator over AWS DMS Fleet Advisor?

Answer:

Those wishing to move a sizable number of database and analytics servers to Amazon should use AWS DMS Fleet Advisor. Use Amazon DMS Fleet Advisor to find and assess your online transaction processing (OLTP) and online analytical processing (OLAP) database workloads so that you can move them to target services in AWS when you're ready. By figuring out how difficult it will be to migrate your source databases to the target services on AWS, Fleet Advisor enables you to create a tailored migration plan.

Broad-based computing and associated block storage discovery is the focus of the Amazon Application Discovery Service (ADS) and Migration Evaluator. Customers beginning their migration process who are searching for a data-driven business case for AWS use the Migration Evaluator. ADS is used to feed the Amazon Migration Hub to view server to server dependencies, establish application groups, and track migration progress.

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Ques. 6): Will the AWS Database Migration Service assist me in converting my Oracle PL/SQL and SQL Server T-SQL code to stored procedures in Amazon Aurora, MySQL, or PostgreSQL?

Answer:

Yes, the free AWS Schema Conversion Tool (SCT), which automates the conversion of Oracle PL/SQL and SQL Server T-SQL code to equivalent code in the Amazon Aurora / MySQL dialect of SQL or the equivalent PL/pgSQL language in PostgreSQL, is a component of the AWS Database Migration Service. When a piece of code can't be translated automatically into the intended language, SCT will make sure to note every place that needs the application developer to enter manual input.

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Ques. 7): Why should I choose the Amazon Database Migration Service over my own independently managed replication system?

Answer:

Using Amazon Database Migration Service couldn't be simpler. Unlike self-managed replication systems that need to be installed and configured, replication jobs can be set up in minutes as opposed to hours or days. AWS Database Migration Service keeps an eye out for replication jobs, network outages, and host failures and automatically sets up a new server in the event that a failure cannot be fixed. Customers of AWS Database Migration Service don't have to overprovision capacity and invest in expensive hardware and replication software, as they generally have to do with self-managed solutions. Users of the Amazon Database Migration Service can scale their replication infrastructure up or down depending on the load and benefit from on-demand pricing. Amazon Database Migration Service data replication interacts directly with the AWS Schema Conversion Tool, facilitating heterogeneous database migration tasks.

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Ques. 8): Can I keep track of a database migration task's progress?

Answer:

Yes. Many metrics for Amazon Database Migration Service are visible in the AWS Management Console. It gives an end-to-end view of the data replication process, including diagnostic and performance statistics for each stage in the replication pipeline. Other Amazon services like CloudTrail and CloudWatch Logs are integrated with the AWS Database Migration Service as well. Clients can combine their existing tools or create specialised monitoring tools to meet their unique needs by utilising the Amazon Database Migration Service API and AWS Command Line Interface (AWS CLI).

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Ques. 9): When should I use Amazon DMS Fleet Advisor in conjunction with AWS Application Discovery Service and Migration Evaluator?

Answer:

You can get an early understanding of the inventory portfolio of your whole on-premises data centre with the aid of Migration Evaluator and AWS Application Discovery Service. Use Amazon DMS Fleet Advisor to design a database migration plan to AWS when you're prepared to conduct a more thorough study of your database and analytics workloads to identify the migration routes in AWS.

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Ques. 10): Can I use AWS Database Migration Service for ongoing data replication in addition to one-time data migration?

Answer:

Yes, you may utilise the AWS Database Migration Service for ongoing data replication as well as one-time data migration into RDS and EC2-based databases. Changes made to the source database will be captured by the AWS Database Migration Service and applied to the destination database in a transactionally consistent manner. Continuous replication is possible from your data centre to the AWS databases as well as in the opposite direction, replicating from a database in AWS to a database in your datacenter. Both homogeneous and heterogeneous databases may perform continuous ongoing replication. Using Multi-AZ for high availability would be better for continuous replication.

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Ques. 11): Can you give me a summary of the Amazon Database Migration Service's database migration procedures?

Answer:

Creating a target database, migrating the database schema, setting up the data replication process, starting the full load and a subsequent change data capture and apply, and concluding with a switchover of your production environment to the new database once the target database has caught up with the source database are all steps in a typical simple database migration.

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Ques. 12): Will the database schema be moved for me using Amazon Database Migration Service?

Answer:

You can rely on the Basic Schema Copy capability of AWS Database Migration Service to easily migrate a database schema to your target instance. If the target instance does not already have tables with the identical names, Basic Schema Copy will automatically generate tables and primary keys. When performing a test migration or a heterogeneous database migration, Basic Schema Copy is excellent (e.g., Oracle to MySQL or SQL Server to Oracle). Foreign keys, stored procedures, and secondary indexes cannot be migrated using Basic Schema Copy. You can use the AWS Schema Conversion Tool for both homogeneous and heterogeneous migrations when you need a more customizable schema migration process (for example, when you are moving your production database and need to move your stored procedures and secondary database objects), or use the native schema export tools of the source engine if you are doing homogeneous migrations, such as (1) SQL Server Management Studio's Import and Export Wizard, (2) Oracle's SQL Developer.

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Ques. 13): How are AWS Schema Conversion Tool (SCT) and AWS Database Migration Service (DMS) related?

Answer:

Together, DMS and SCT provide continuing replication for various purposes, including filling datamarts and synchronising systems, as well as database migration. Database schemas for homogeneous migrations can be copied and converted for heterogeneous migrations using SCT. The schemas may differ between data warehouses, such as Netezza and Amazon Redshift, or different databases, such as Oracle and PostgreSQL.

Depending on the amount of data and/or supported engines, either DMS or SCT are used to transport the data after a schema has been established on an empty target. While SCT is typically used to convert big data warehouse workloads, DMS is typically utilised to transfer smaller relational workloads (10 TB) and MongoDB. DMS supports ongoing replication to keep the target in sync with the source; SCT does not.

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Ques. 14): What additional applications can I combine with AWS Database Migration Service?

Answer:

AWS Database Migration Service offers a provisioning API that enables you to script the generation of replication tasks at predetermined periods throughout the day or to create them straight from your development environment. Developers and database administrators can automate replication task creation, restart, administration, and termination using the service API and CLI.

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Ques. 15): What sources and targets can be converted using the Amazon Schema Conversion Tool?

Answer:

These database and data warehouse conversions are supported by the Amazon Schema Conversion Tool (SCT), which is listed here. Be aware that SCT can be applied to:

Transfer a database schema from one place to another
a database or data warehouse schema conversion
Evaluate a database to ascertain the difficulty of the conversion
Examine a database to find out if there are any limitations to using Amazon RDS.
Determine whether a licence downgrade is achievable by analysing a database.
a program's embedded SQL code converted
Transfer data from a data warehouse to Amazon Redshift

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