Top 20 AWS QuickSight Interview Questions and Answers

 

                        Amazon QuickSight, a very quick, simple-to-use, cloud-powered business analytics service. All employees within an organisation can easily create visualisations, carry out ad-hoc analysis, and quickly gain business insights from their data with the help of AWS QuickSight. This can be done anytime, anywhere, and on any device. Access on-premises databases like SQL Server, MySQL, and PostgreSQL, upload CSV and Excel files, connect to SaaS programmes like Salesforce, and easily find your AWS data sources like Amazon Redshift, Amazon RDS, Amazon Aurora, Amazon Athena, and Amazon S3. With the help of a powerful in-memory engine, QuickSight allows businesses to grow their business analytics capabilities to hundreds of thousands of users while providing quick and responsive query performance (SPICE).

 

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Ques: 1).  Can you describe SPICE?

Answer:

The "SPICE" super-fast, parallel, in-memory calculation engine is used in the construction of Amazon QuickSight. Built specifically for the cloud, SPICE runs interactive queries on massive datasets and provides quick results by combining columnar storage, in-memory technologies made possible by the newest hardware advancements, and machine code generation. With the support of SPICE, you can do complex calculations to get the most out of your study without having to worry about provisioning or managing infrastructure. Until a user manually deletes data, it is persistent in SPICE. SPICE also enables QuickSight to grow to hundreds of thousands of users who can all concurrently undertake quick interactive analysis across a wide range of AWS data sources, and it replicates data automatically for high availability.

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Ques: 2). With Amazon QuickSight, how can I make an analysis?

Answer:

Making an analysis is straightforward. Within your AWS account, Amazon QuickSight automatically finds data in well-known AWS data repositories. Simply target one of the found data sources at Amazon QuickSight. You can specify the connection information of the source to connect to another AWS data source that is not in your AWS account or in a different zone. After that, pick a table and begin examining your data. Additionally, you may upload CSV and spreadsheet files, and Amazon QuickSight can be used to examine your data. Start by choosing the data fields you wish to examine, dragging the fields into the visual canvas, or performing a combination of these two activities. Amazon QuickSight will automatically select the appropriate visualization to display based on the data you’ve selected.

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Ques: 3). If QuickSight is running in the background of a browser, will a Reader be charged?

Answer:

No, there won't be any use fees if Amazon QuickSight is active in a background tab. Only when there is explicit Reader action on the QuickSight web application does a session start. No further sessions (beyond those started when the Reader was active on the window or tab) will be charged if the QuickSight page is minimised or moved to the background until the Reader interacts with QuickSight once again.

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Ques: 4). Is Amazon QuickSight compatible with my mobile device?

Answer:

For quick access to your data and insights so that you can make choices while you're out and about, use the QuickSight mobile applications (available on iOS and Android). Utilize your dashboards to browse, search, and take action. Dashboards can be added to Favorites for fast access. Using dig downs, filters, and other methods, explore your data. Any mobile device with a web browser may be used to access Amazon QuickSight.

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Ques: 5). How can I get access to my AWS data sources data?

Answer:

Your AWS data sources that are accessible in your account and have your approval are effortlessly discovered by Amazon QuickSight. You may start viewing the data and creating visualisations right now. By supplying connection information for such sources, you may also explicitly connect to additional AWS data sources that are not in your account or in a different region.

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Ques: 6). Can I use JDBC or ODBC to connect to hosted or local databases and specify the AWS region?

Answer:

Yes. Customers are urged to utilise the area where your data is housed for better performance and user interaction. Only the AWS region of the Amazon QuickSight endpoint to which you are connected is used by the auto discovery function of Amazon QuickSight to identify data sources.

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Ques: 7). Row-level security: what is it?

Answer:

With row-level security (RLS), QuickSight dataset owners may restrict access to data at the row level based on the user's rights while interacting with the data. Users of Amazon QuickSight need to maintain one set of data and apply the proper row-level dataset rules to it with RLS. These guidelines will be enforced by all connected dashboards and analytics, making it easier to manage datasets and eliminating the need to keep separate datasets for users with various levels of data access privileges.

 

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Ques: 8). Who are QuickSight's "Authors" and "Readers"?

Answer:

A person who can connect to data sources (inside or outside of AWS), produce graphics, and evaluate data is known as a QuickSight Author. Authors may publish dashboards with other account users and construct interactive dashboards utilising sophisticated QuickSight features like parameters and computed fields.

A user that consumes interactive dashboards is known as a QuickSight Reader. Using a web browser or mobile app, readers may log in using the desired authentication method for their company (QuickSight username/password, SAML portal, or AD auth), view shared dashboards, filter data, dig down to details, or export data as a CSV file. Readers are not allotted any SPICE capacity.

It is possible to grant certain end users access to QuickSight as Readers. Reader price is only valid for manual session interactions. If, in its discretion, it would discovers that you are using reader sessions for other purposes, it has the right to charge the reader at the higher monthly author fee (e.g., programmatic or automated queries).

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Ques: 9). Who is a QuickSight “Admin”? Can I make an Author or Reader an Admin?

Answer:

A person who has the ability to manage QuickSight users, account-level preferences, and buy SPICE capacity and yearly subscriptions for the account is known as a QuickSight Admin. Administrators have access to all QuickSight writing features. If necessary, administrators can also upgrade accounts from Standard Edition to Enterprise Edition.

Authors and Readers of Amazon QuickSight can at any moment become Admins.

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Ques: 10). Can more users be invited by Qucksight "Authors" or "Readers"?

Answer:

No, QuickSight Authors and Readers are the only user categories that are unable to modify account permissions or extend an invitation to other users. One may acquire SPICE capacity and yearly subscriptions for the account as well as manage QuickSight users and account-level options using the Admin user that QuickSight gives. Administrators have access to all QuickSight writing features. If necessary, administrators can also upgrade accounts from Standard Edition to Enterprise Edition.

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Ques: 11). My data's source is not in a tidy format. How should the data be formatted and transformed before visualisation?

Answer:

You can prepare data that isn't ready for visualisation using Amazon QuickSight. The connection dialog's "Edit/Preview Data" button should be selected. To format and alter your data, Amazon QuickSight includes a number of features. You can alter data types and alias data fields. You can use drag and drop to conduct database join operations and built-in filters to subset your data. Using mathematical operations and built-in functions like conditional statements, text, numerical, and date functions, you can also build calculated fields.

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Ques: 12). Can QuickSight dashboards be displayed and refreshed scriptedly on monitors or other big displays using my QuickSight Reader account?

Answer:

The reader price for Amazon QuickSight is applicable to interactive data consumption by end users inside an enterprise. It is advisable that using an Author account to adhere to the QuickSight Reader's fair use standards for automated refresh and programmatic access.

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Ques: 13). A recommended visualisation is what? How are suggestions generated by Amazon QuickSight?

Answer:

A built-in recommendation engine in Amazon QuickSight offers you potential representations depending on the characteristics of the underlying datasets. Suggestions act as potential first or next steps in an analysis, eliminating the time-consuming job of querying and comprehending your data's structure. The recommendations will change as you work with more precise data to reflect the subsequent actions that are appropriate for your current research.

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Ques: 14). How does SageMaker's interaction with QuickSight work?

Answer:

Connecting the data source from which you wish to pull data is the first step. Once you've established a connection to a data source, choose "Augment using SageMaker." The next step is to choose the model you wish to use from a list of SageMaker models in your AWS account and supply the schema file, which is a JSON-formatted file containing the input, output, and run-time parameters. Compare the columns in your data collection with the input schema mapping. When you're finished, you may run this task and begin the inference.

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Ques: 15). What types of visualizations are supported in Amazon QuickSight?

Answer:

Amazon QuickSight supports assorted visualizations that facilitate different analytical approaches:

• Comparison and distribution
• Bar charts (several assorted variants)
• Changes over time
• Line graphs
• Area line charts
• Correlation
• Scatter plots
• Heat maps
• Aggregation
• Pie graphs
• Tree maps
• Tabular
• Pivot tables

 

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Ques: 16). How do stories work?

Answer:

Stories act as walking tours of certain analyses. In order to facilitate cooperation, they are used to communicate significant ideas, a thinking process, or the development of an analysis. They may be built in Amazon QuickSight by recording and annotating particular analysis states. Readers of the tale are directed to the analysis when they click on a story image, where they can further investigate on their own.

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Ques: 17). Which data sources can I use with Amazon QuickSight?

Answer:

AWS data sources including Amazon RDS, Amazon Aurora, Amazon Redshift, Amazon Athena, and Amazon S3 are all accessible through connections. Additionally, you may connect to on-premises databases like SQL Server, MySQL, and PostgreSQL, upload Excel spreadsheets or flat files (CSV, TSV, CLF, and ELF), and import data from SaaS programmes like Salesforce.

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Ques: 18). How can I control who may access Amazon QuickSight?

Answer:

By default, you are given administrator rights when you establish a new Amazon QuickSight account. Whoever invites you assigns you either an ADMIN or a USER role if they want you to utilise Amazon QuickSight. If you have the ADMIN position, you may also buy yearly subscriptions, SPICE capacity, and create and remove user accounts in addition to utilising the service.

Sending an email invitation to the user using an in-app interface allows you to establish a user account. The user then completes the account creation process by choosing a password and logging in.

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Ques: 19). In what ways can I establish a dashboard?

Answer:

Dashboards are groups of visual displays that are grouped and made visible at once, such as tables and visualisations. By selecting the sizes and layouts of the visualisations in an analysis, you may create a dashboard using Amazon QuickSight, which you can then share with a group of people inside your company.

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Ques: 20). What does "private VPC access" entail in regard to Amazon QuickSight?

Answer:

This functionality is for you if you have data in AWS (perhaps in Amazon Redshift, Amazon Relational Database Service (RDS), or on EC2) or locally on Teradata or SQL Server servers on servers without public connection. Elastic Network Interface (ENI) is used by Private VPC (Virtual Private Cloud) Access for QuickSight for secure, private connection with data sources in a VPC. You may also utilise AWS Direct Connect to establish a private, secure connection with your on-premises resources.

 

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Top 20 AWS EventBridge Interview Questions and Answers

                    Without having to write any code, Amazon EventBridge offers real-time access to data changes in AWS services, your own applications, and software as a service (SaaS) applications. AWS Lambda, Amazon Simple Notification Service (SNS), and Amazon Kinesis Data Firehose are just a few of the AWS services you can choose from as targets once you've chosen an event source on the Amazon EventBridge panel. The events will be automatically delivered via Amazon EventBridge in close to real-time. 

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Ques. 1): What are the steps for using Amazon EventBridge?

Answer:

Choose an event source from a list of partner SaaS applications and AWS services by logging into your AWS account, going to the Amazon EventBridge dashboard, and selecting that source. Make sure your SaaS account is set up to emit events if you're using a partner application, then accept the source in the provided event sources section of the Amazon EventBridge console. Your event bus will be immediately created by Amazon EventBridge and used to route events. As an alternative, you can instrument your application with the AWS SDK to begin broadcasting events to your event bus. Add a target for your events and optionally configure a filtering rule; the target may be a Lambda function, for instance. The events will be automatically ingested, filtered, and sent to the specified target in a secure and highly available manner by Amazon EventBridge.

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Ques. 2): EventBridge API Destinations: What are they?

Answer:

Developers may regulate throughput and authentication while sending events back to any on-premises or SaaS apps using API Destinations. EventBridge will handle security and delivery while customers set rules with input transformations that transfer the event format to the format of the receiving service. When a rule is activated, Amazon EventBridge transforms the event in accordance with the parameters supplied and sends it to the defined web service along with the authentication data specified when the rule was created. Developers no longer have to create authentication components for the service they wish to utilise because security is already built in.

 

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Ques. 3): How are CloudWatch Events related to Amazon EventBridge?

Answer:

CloudWatch Events are improved and expanded upon by Amazon EventBridge. It makes use of the same service API, endpoint, and underpinning infrastructure. Nothing has changed for current CloudWatch Events users; you can continue to utilise the same API, CloudFormation templates, and console. Customers told us that CloudWatch Events is the best service for creating event-driven architectures, so we created new features to let customers link data from their own SaaS apps and those of other companies. We have launched this feature under the moniker Amazon EventBridge rather than under the CloudWatch service to reflect its extension outside the monitoring use case for which it was designed.

 

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Ques. 4): Which AWS services are included with Amazon EventBridge as event sources?

Answer:

Over 90 AWS services, including AWS Lambda, Amazon Kinesis, AWS Fargate, and Amazon Simple Storage Service, are available as event sources for EventBridge (S3).

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Ques. 5): How do I filter which events are delivered to a target?

Answer:

You can filter events with rules. A rule matches incoming events for a given event bus and routes them to targets for processing. A single rule can route to multiple targets, all of which are processed in parallel. Rules allow different application components to look for and process the events that are of interest to them. A rule can customize an event before it is sent to the target, by passing only certain parts or by overwriting it with a constant.  

 

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Ques. 6): What does the feature of schema discovery do?

Answer:

The procedures for locating schemas and adding them to your registry are automated by schema discovery. Each event's schema is automatically uploaded to the registry when schema discovery is enabled for an EventBridge event bus. Schema discovery will instantly update the schema in the registry if the schema of an event changes. Once a schema has been uploaded to the registry, you can create a code binding for it either in the EventBridge console or directly in your IDE. This enables you to represent the event in your code as a strongly-typed object and utilise IDE features like validation and auto-complete.

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Ques. 7): The Serverless Application Model (AWS SAM) allows for the use of schema.

Answer:

Yes, you may build new serverless apps on EventBridge for any schema as an event type using the interactive mode of the most recent AWS SAM CLI. Simply select the "EventBridge Starter App" template and the event's schema, and AWS SAM will create an application with a Lambda function that is called by EventBridge and handling code for the event. This implies that you may utilise IDE tools like validation and auto-complete and treat an event trigger like a regular object in your code.

AWS Toolkit for Visual Studio Code and the AWS Toolkit for Jetbrains (Intellij, PyCharm, Webstorm, Rider) plugins both offer the ability to create serverless apps from this template with a schema acting as a trigger right inside of these IDEs.

 

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Ques. 8): How can writing less code using the schema registry benefit me?

Answer:

In order to avoid having to manage your event schema manually, you can first utilise schema discovery to automatically identify schema for any events transmitted to your EventBridge event bus and save them in the registry. Second, you can develop and download code bindings for this schema when creating apps that process events on your bus so that you can use strongly-typed objects right away. Deserialization, validation, and guesswork for your event handler are all avoided as a result.

 

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Ques. 9): How can I protect my use of Amazon EventBridge?

Answer:

You can define the actions that a user within your AWS account is permitted to take by integrating Amazon EventBridge with AWS Identity and Access Management (IAM). You could, for instance, set an IAM policy that allows only specific users in your company to add event targets or create event buses.

 

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Ques. 10): What justifies my use of global endpoints?

Answer:

By reducing the quantity of data at risk during service interruptions, global endpoints assist you in giving your end users a better experience. By being able to failover your event ingestion to a backup region automatically and without the need for manual intervention, you can increase the stability and resilience of your event-driven applications. To decide whether to failover and when to transport events back to the primary region, you can freely set failover criteria using CloudWatch Alarms (through Route53 health checks).

 

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Ques. 11): What are the Recovery Point Objective (RPO) and Expected Recovery Time Objective (RTO)?

Answer:

The Recovery Time Objective (RTO) is the period of time following a failure when the backup Region or target will begin to receive new events. The amount of data that will remain unprocessed in the event of a failure is measured by the Recovery Point Objective (RPO). The RTO and RPO for global endpoints will be 360 seconds provided you adhere to our prescriptive recommendations for alarm setting (with a maximum of 420). When calculating RTO, the time is taken into account for setting off CloudWatch Alarms and updating Route53 health check statuses. Events that are not copied to the secondary region and remain in the primary region until the service or region recovers are included in the RPO time.

 

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Ques. 12): EventBridge Archive and Replay Events: What Is It?

Answer:

Customers can reprocess previous events back to an event bus or a specific EventBridge rule using the new feature Event Replay for Amazon EventBridge. Developers can use this functionality to quickly debug their apps, extend them by hydrating targets with historical events, and fix mistakes. Developers may rest easy knowing that they will always have access to any event submitted to EventBridge thanks to Event Replay.

 

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Ques. 13): Why would I use Amazon EventBridge into my SaaS application?

Answer:

SaaS vendors can easily integrate their services with the event-driven architectures created by their clients and hosted on AWS thanks to Amazon EventBridge. Millions of AWS developers may now directly access your product thanks to Amazon EventBridge, opening up new applications. It provides an entirely safe, scalable, and auditable solution to convey events without requiring the SaaS vendor to handle any eventing infrastructure.

 

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Ques. 14): Does Amazon EventBridge allow me to publish my own events?

Answer:

Yes. Through the use of the service's APIs, you can create unique application-level events and publish them to Amazon EventBridge. Additionally, you can create scheduled events that are generated on a regular basis and process these events in any of the available targets for Amazon EventBridge.

 

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Ques. 15): What is the price of the schema registry?

Answer:

The schema registry is free to use, however when you enable schema discovery, there is a fee per ingested event. The majority of development consumption should be covered by the free tier of 5M ingested events offered by schema discovery each month. For usage above the free tier, there is an extra charge of $0.10 per million ingested events.

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 Ques. 16): When should I make use of Amazon SNS and when of Amazon EventBridge?

Answer:

Your choice will depend on your particular requirements, but you may create event-driven apps using both Amazon EventBridge and Amazon SNS. When creating an application that responds to events from SaaS applications and/or AWS services, Amazon EventBridge is advised. The only event-based service that interacts directly with external SaaS providers is Amazon EventBridge. Without needing developers to create any resources in their account, Amazon EventBridge also automatically ingests events from over 90 AWS services. Over 15 AWS services, including Amazon Lambda, Amazon SQS, Amazon SNS, Amazon Kinesis Streams, and Kinesis Data Firehose, are presently supported as targets by Amazon EventBridge. With a limited throughput at launch that can be expanded upon request and an average latency of about half a second, Amazon EventBridge is currently in beta.

 

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Ques. 17): How should I failover my global endpoint? What metrics should I use?

Answer:

In order to make it simple for you to identify whether there are any difficulties with EventBridge that would necessitate you failovering your event ingestion to the secondary region, we have added a new measure that shows the end-to-end latency of Amazon EventBridge. By offering a pre-populated CloudFormation stack (that you may alter if you so desire) for setting a CloudWatch Alarm and Route53 Health Checks in the console, AWS has made it simple for you to get started.

 

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Ques. 18): Do I need to enable replication?

Answer:

Yes. To reduce the amount of data that is vulnerable during a service failure, replication should be enabled. You can update your applications to publish your events to the global endpoint after setting up your custom buses in both regions and making the global endpoint. By doing this, after the problem is resolved, your incoming events will be copied back to the primary area. To ensure that none of your events are lost in the event of a disruption, you can archive your events in the secondary region. You can replicate your design in the secondary zone to carry on processing events while you swiftly recover from disturbances. In order to assure automatic recovery once the problem has been resolved, you must additionally enable replication.

 

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Ques. 19): Should I failover my global endpoint using metrics from my subscriber?

Answer:

We don't advise integrating subscriber metrics in your health check because doing so can force your publisher to switch to the backup area if one subscriber has a problem even though all the others are fine in the primary region. You should enable replication if one of your subscribers in the primary region isn't processing events properly in order to make sure that your subscriber in the secondary region can.

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Ques. 20): How does a global endpoint increase my applications' availability?

Answer:

Events are routed to the event bus in your main area after they are published to the global endpoint. Your healthcheck is flagged as unhealthy and incoming events are directed to the secondary area if faults are found in the primary region. Using CloudWatch Alarms (through Route53 health checks) that you set, errors can be quickly found. As soon as the problem is resolved, AWS routes fresh events back to the original Region and get on with event processing.

 

Top 20 AWS MSK Interview Questions and Answers

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Ques: 1). What is streaming data in AWS MSK?  

Answer:

The answer is that streaming data is a constant stream of brief recordings or events—typically only a few kilobytes in size—produced by tens of thousands of equipment, gadgets, websites, and software programmes. A wide range of data, including log files produced by users of your mobile or web applications, e-commerce purchases, in-game player activity, information from social networks, trading information from financial trading floors, geospatial services, security logs, metrics, and telemetry from connected devices or instrumentation in data centres are all examples of streaming data. Continuously gathering, processing, and delivering streaming data is made simple for you by streaming data services like Amazon MSK and Amazon Kinesis Data Streams.

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Ques: 2). What does Amazon MSK really do as open-source service?

Answer:

Apache Kafka open-source versions may be easily installed and deployed on AWS with excellent availability and security thanks to Amazon MSK. Additionally, Amazon MSK provides AWS service integrations without the operational burden of maintaining an Apache Kafka cluster. While the service supports the setup, provisioning, AWS integrations, and ongoing maintenance of Apache Kafka clusters, Amazon MSK enables you to use open-source versions of Apache Kafka.

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Ques: 3). What are Apache Kafka's fundamental ideas?

Answer:

Topics are how Apache Kafka stores records. Consumers read records from subjects, and data producers write records to topics. In Apache Kafka, each record is made up of a key, a value, a timestamp, and occasionally header metadata. Apache Kafka divides topics into replicas that are replicated over several brokers, or nodes. A highly available cluster of brokers running Apache Kafka may be created by placing brokers in different AWS availability zones. When it comes to managing state for services communicating with an Apache Kafka cluster, Apache Kafka depends on Apache ZooKeeper.

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Ques: 4). How can I get access to the Apache Kafka broker logs?

Answer:

For provisioned clusters, broker log delivery is an option. Broker logs may be sent to Amazon Kinesis Data Firehose, Amazon Simple Storage Service (S3), and Amazon CloudWatch Logs. Among other places, Kinesis Data Firehose supports Amazon OpenSearch Service.

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Ques: 5). How can I keep track of consumer lag?

Answer:

The standard collection of metrics that Amazon MSK delivers to Amazon CloudWatch for all clusters includes topic-level consumer latency indicators. For these metrics to be obtained, no further setup is needed. You may also obtain consumer latency data at the partition level for provisioned clusters (partition dimension). On your cluster, turn on enhanced monitoring (PER PARTITION PER TOPIC). As an alternative, you may use a Prometheus server to activate Open Monitoring on your cluster and collect partition-level metrics from the cluster's brokers. Consumer latency measurements, like other Kafka metrics, are accessible through port 11001.

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Ques: 6). How does Amazon MSK handle data replication?

Answer:

To replicate data between brokers, Amazon MSK leverages the leader-follower replication feature of Apache Kafka. Clusters with multi-AZ replication may be easily deployed using Amazon MSK, and you have the option to apply a specific replication technique for each topic. Every replication option by default deploys and isolates leader and follower brokers according to the replication technique chosen. A cluster of three brokers will be created by Amazon MSK (one broker in three AZs in a region), for instance, if you choose a three AZ broker replication strategy with one broker per AZ cluster. By default (unless you choose to override the topic replication factor), the topic replication factor will also be three.

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Ques: 7). MSK Serverless: What is it?

Answer:

You may operate Apache Kafka clusters using MSK Serverless, a cluster type for Amazon MSK, without having to worry about managing computation and storage capacity. You just pay for the data volume that you stream and keep when using MSK Serverless, which allows you to execute your apps without needing to setup, configure, or optimise clusters.

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Ques: 8). What security features are available with MSK Serverless?

Answer:

Using service-managed keys obtained from the AWS Key Management Service, MSK Serverless encrypts all data in transit and at rest (KMS). AWS PrivateLink is used by clients to establish private connections to MSK Serverless, shielding your traffic from the public internet. IAM Access Control, another feature of MSK Serverless, allows you to control client authorization and client authentication for Apache Kafka resources like topics.

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Ques: 9). What do I require to provision a cluster of Amazon MSK?

Answer:

With each cluster you build for provided clusters, you must provision broker instances and broker storage. Storage throughput for storage volumes is an optional provision that may be used to expand I/O without the need for additional brokers. Nodes for Apache ZooKeeper are already included with each cluster you establish, so you don't need to supply them. You just construct a cluster as a resource for serverless clusters.

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Ques: 10). How does Amazon MSK handle authorization?

Answer:

If you are using IAM Access Control, Amazon MSK authorises actions based on the policies you create and its own authorizer. Apache Kafka employs access control lists (ACLs) for authorisation if you are utilising SASL/SCRAM or TLS certificate authentication. You must enable client authentication using SASL/SCRAM or TLS certificates in order to activate ACLs.

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Ques: 11). What is the maximum data throughput capacity supported by MSK Serverless?

Answer:

Up to 200 MBps of write throughput and 400 MBps of read capacity per cluster are offered by MSK Serverless. Additionally, MSK Serverless allots up to 5 MBps of immediate write capacity and 10 MBps of instant read capacity per partition to guarantee enough throughput availability for every partition in a cluster.

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Ques: 12). What high availability measures does MSK Serverless take?

Answer:

When a partition is created, MSK Serverless makes two copies of it and stores them in various availability zones. To provide high availability, MSK serverless automatically finds and restores malfunctioning backend resources.
 

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Ques: 13). How can I set up my first MSK cluster on Amazon?

Answer:

Using the AWS administration console or the AWS SDKs, you can quickly establish your first cluster. To construct an Amazon MSK cluster, first choose an AWS region in the Amazon MSK dashboard. Give your cluster a name, decide the Virtual Private Cloud (VPC) you want to use to run it, and select the subnets for each AZ. You may select a broker instance type, the number of brokers per AZ, and the amount of storage per broker when constructing a provisioned cluster.

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Ques: 14). Does Amazon MSK run in an Amazon VPC?

Answer:

Yes, Amazon MSK always operating inside an Amazon VPC that is overseen by the Amazon MSK service. When the cluster is configured, the Amazon MSK resources will be accessible to your own Amazon VPC, subnet, and security group. Elastic network interfaces (ENIs), which connect IP addresses from your VPC to your Amazon MSK resources, ensure that all network traffic stays within the AWS network and is not by default available to the internet.

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Ques: 15). Between my Apache Kafka clients and the Amazon MSK service, is data secured in transit?

Answer:

Yes, only clusters established using the CLI or AWS Management Console have in-transit encryption configured by default to TLS. For clients to communicate with clusters utilising TLS encryption, further setup is needed. By choosing the TLS/plaintext or plaintext options, you may modify the default encryption configuration for supplied clusters. Study up on MSK Encryption.

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Ques: 16). How much do the various CloudWatch monitoring levels cost?

Answer:

The size of your Apache Kafka cluster and the monitoring level you choose will determine how much it costs to monitor your cluster using Amazon CloudWatch. Amazon CloudWatch has a free tier and charges monthly based on metrics.

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Ques: 17). Which monitoring tools are compatible with Prometheus' Open Monitoring?

Answer:

Open Monitoring is compatible with tools like Datadog, Lenses, New Relic, Sumo Logic, or a Prometheus server that are made to read from Prometheus exporters.

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Ques: 18). Are my clients' connections to an Amazon MSK cluster secure?

Answer:

By default, a private connection between your clients in your VPC and the Amazon MSK cluster is the only way data may be generated or consumed from an Amazon MSK cluster. But if you enable public access for your Amazon MSK cluster and use the public bootstrap-brokers string to connect to it, the connection—while authenticated, permitted, and encrypted—will no longer be regarded as private. If you enable public access, it is advised that you setup the cluster's security groups to include inbound TCP rules that permit public access from your trusted IP address and to make these rules as stringent as feasible.

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Ques: 19). Is it possible to move data from my current Apache Kafka cluster to Amazon MSK?

Answer:

Yes, you may duplicate data from clusters onto an Amazon MSK cluster using third-party tools or open-source tools like MirrorMaker, supported by Apache Kafka. To assist you with completing a migration, Amazon provides an Amazon MSK migration lab.

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Ques: 20). How do I handle data processing for my MSK Serverless cluster?

Answer:

You can process data in your MSK Serverless cluster topics using any technologies that are Apache Kafka compliant. MSK Serverless interacts with AWS Lambda for event processing and Amazon Kinesis Data Analytics for stateful stream processing using Apache Flink. Kafka Connect sink connectors may be used to transmit data to any desired location.