SQS, SNS, Kinesis Flashcards
You have an e-commerce website and you are preparing for Black Friday which is the biggest sale of the year. You expect that your traffic will increase by 100x. Your website already using an SQS Standard Queue. What should you do to prepare your SQS Queue?
A. Contact AWS Support to pre-warm your SQS Standard Queue
B. Enable Auto Scaling in your SQS queue
C. Increase the capacity of the SQS queue
D. Do nothing, SQS scales automatically
D. Do nothing, SQS scales automatically
How would you configure your SQS messages to be processed by consumers only after 5 minutes of being published to your SQS Queue?
A. Increase the DelaySeconds parameter
B. Change the Visibility Timeout
C. Enable Long Polling
D. Use Amazon SQS Extended Client
A. Increase the DelaySeconds parameter
SQS Delay Queues is a period of time during which Amazon SQS keeps new SQS messages invisible to consumers. In SQS Delay Queues, a message is hidden when it is first added to the queue. (default: 0 mins, max.: 15 mins)
You have an SQS Queue where each consumer polls 10 messages at a time and finishes processing them in 1 minute. After a while, you noticed that the same SQS messages are received by different consumers resulting in your messages being processed more than once. What should you do to resolve this issue?
A. Enable Long Polling
B. Add DelaySeconds parameter to the messages when being produced
C. Increase Visibility Timeout
D. Decrease Visibility Timeout
C. Increase Visibility Timeout
SQS Visibility Timeout is a period of time during which Amazon SQS prevents other consumers from receiving and processing the message again. In Visibility Timeout, a message is hidden only after it is consumed from the queue. Increasing the Visibility Timeout gives more time to the consumer to process the message and prevent duplicate reading of the message. (default: 30 sec., min.: 0 sec., max.: 12 hours)
You have a fleet of EC2 instances (consumers) managed by an Auto Scaling Group that used to process messages in an SQS Standard Queue. Lately, you have found a lot of messages processed twice and after further investigation, you found that these messages can not be processed successfully. How would you troubleshoot (debug) why these messages fail?
A. SQS Standard Queue
B. SQS Dead Letter Queue
C. SQS Delay Queue
D. SQS FIFO Queue
B. SQS Dead Letter Queue
SQS Dead Letter Queue is where other SQS queues (source queues) can send messages that can’t be processed (consumed) successfully. It’s useful for debugging as it allows you to isolate problematic messages so you can debug why their processing doesn’t succeed.
Which SQS Queue type allows your messages to be processed exactly once and in order?
A. SQS Standard Queue
B. SQS Dead Letter Queue
C. SQS Delay Queue
D. SQS FIFO Queue
D. SQS FIFO Queue
SQS FIFO (First-In-First-Out) Queues have all the capabilities of the SQS Standard Queue, plus the following two features. First, The order in which messages are sent and received are strictly preserved and a message is delivered once and remains available until a consumer process and deletes it. Second, duplicated messages are not introduced into the queue.
You have 3 different applications that you’d like to send them the same message. All 3 applications are using SQS. What is the best approach would you choose?
A. Use SQS Replication Feature
B. Use SNS + SQS Fan Out Pattern
C. Send messages individually to 3 SQS queues
B. Use SNS + SQS Fan Out Pattern
This is a common pattern where only one message is sent to the SNS topic and then “fan-out” to multiple SQS queues. This approach has the following features: it’s fully decoupled, no data loss, and you have the ability to add more SQS queues (more applications) over time.
You have a Kinesis data stream with 6 shards provisioned. This data stream usually receiving 5 MB/s of data and sending out 8 MB/s. Occasionally, your traffic spikes up to 2x and you get a ProvisionedThroughputExceededException exception. What should you do to resolve the issue?
A. Enable Kinesis Replication
B. Add more Shards
C. Use SQS as a buffer to Kinesis
B. Add more Shards
The capacity limits of a Kinesis data stream are defined by the number of shards within the data stream. The limits can be exceeded by either data throughput or the number of reading data calls. Each shard allows for 1 MB/s incoming data and 2 MB/s outgoing data. You should increase the number of shards within your data stream to provide enough capacity.
You have a website where you want to analyze clickstream data such as the sequence of clicks a user makes, the amount of time a user spends, and where the navigation begins, and how it ends. You decided to use Amazon Kinesis, so you have configured the website to send these clickstream data all the way to a Kinesis data stream. While you checking the data sent to your Kinesis data stream, you found that the users’ data is not ordered and the data for one individual user is spread across many shards. How would you fix this problem?
A. There are too many shards, you should only use one shard
B. You shouldn’t use multiple consumers, only one and it should re-order data
C. For each record sent to Kinesis add a partition key that represents the identity of the user
C. For each record sent to Kinesis add a partition key that represents the identity of the user
Kinesis Data Stream uses the partition key associated with each data record to determine which shard a given data record belongs to. When you use the identity of each user as the partition key, this ensures the data for each user is ordered hence sent to the same shard.
Which AWS service is most appropriate when you want to perform real-time analytics on streams of data?
A. SQS
B. SNS
C. Kinesis Data Analytics
D. Kinesis Data Firehose
C. Kinesis Data Analytics
Use Kinesis Data Analytics with Kinesis Data Streams as the underlying source of data.
You are running an application that produces a large amount of real-time data that you want to load into S3 and Redshift. Also, these data need to be transformed before being delivered to their destination. What is the best architecture would you choose?
A. SQS + AWS Lambda
B. SNS + HTTP Endpoint
C. Kinesis Data Streams + Kinesis Data Firehose
C. Kinesis Data Streams + Kinesis Data Firehose
This is a perfect combo of technology for loading data near real-time data into S3 and Redshift. Kinesis Data Firehose supports custom data transformations using AWS Lambda.
Which of the following is NOT a supported subscriber for AWS SNS?
A. Kinesis Data Streams
B. SQS
C. Lambda
D. HTTP(S) Endpoint
A. Kinesis Data Streams
Note: Kinesis Data Firehose is now supported, but not Kinesis Data Streams.
Which AWS service helps you when you want to send email notifications to your users?
A. SQS with Lambda
B. SNS
C. Kinesis
B. SNS
You have an SNS topic with 1000s of subscribers and you want to send some messages to certain subscribers and not others. What SNS feature allows you to do so?
A. SNS Message Filtering
B. SNS Access Policy
C. SNS FIFO Topic
A. SNS Message Filtering
SNS Message Filtering allows you to filter messages sent to SNS topic’s subscriptions.
You have an e-commerce website and you are preparing for Black Friday which is the biggest sale of the year. You expect that your traffic will increase by 100x. Your website already using an SQS Standard queue. Due to the spike in traffic, consumers may fail multiple times while processing messages within the Visibility Timeout, due to some constrains to the application database. What else should you do to handle failed messages?
A. Add an SQS filter to verify the message format
B. Implement a Dead Letter Queue (DLQ) with a redrive policy
C. Increase the Visibility Timeout
B. Implement a Dead Letter Queue (DLQ) with a redrive policy
Your SQS costs are extremely high. Upon closer look, you notice that your consumers are polling your SQS queues too often and getting empty data as a result. What should you do?
A. Decrease the number of consumers
B. Enable Long Polling
C. Increase the Visibility Timeout
B. Enable Long Polling
