Storing Millions of IoT Messages | Ideal Implementation Steps | AWS Certified Big Data Specialty Exam

Ideal Implementation Steps

Question

A company wants to store millions of messages being sent from their IoT devices.

They need to have a durable and highly available data store in AWS to store the incoming messages.

It needs to be ensured that the Infrastructure for the data store can scale without much intervention.

Which of the following would be the ideal implementation steps? Choose 2 answers from the options given below.

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Answer - B and C.

You can use DynamoDB for storing the messages as this is a high scalable service.

Here you don't need to manage the underlying infrastructure for scalability.

Then you can use IoT rules to transfer the messages to DynamoDB as shown below.

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To create a DynamoDB rule.

In the AWS IoT console, in the left navigation pane, choose Act.

Option A is incorrect since this is used to maintain the state of the device.

Option D is incorrect since AWS DynamoDB would be a better store based on the scalability requirements.

For more information on creating a rule for IoT and DynamoDB, please visit the url.

https://docs.aws.amazon.com/iot/latest/developerguide/iot-ddb-rule.html

For storing millions of messages from IoT devices, it is important to choose a durable and highly available data store that can scale seamlessly. AWS provides various services for storing and processing big data, including Amazon DynamoDB, AWS IoT, and Amazon Redshift. Let's discuss the ideal implementation steps for storing messages from IoT devices in AWS:

Step 1: Create AWS IoT Core Rule The first step is to create an AWS IoT Core Rule that will allow transferring the data from IoT devices to the storage service. The rule can be created using AWS IoT Core console, AWS CLI, or AWS SDK. The rule will define the conditions under which the incoming messages will be routed to the storage service. For example, you can define a rule to route all messages with a specific topic to the storage service.

Step 2: Use DynamoDB for Data Storage The second step is to choose the appropriate data storage service for storing the messages. In this case, Amazon DynamoDB is the best fit for storing the messages due to its high availability, durability, and scalability. It provides seamless scaling without any downtime or performance impact. DynamoDB can be created using the AWS Management Console, AWS CLI, or AWS SDK.

Step 3: Configure IoT Rules to Transfer Data to DynamoDB The third step is to configure the AWS IoT Core rule created in step 1 to transfer the data to the DynamoDB table. This can be achieved by specifying the name of the DynamoDB table in the rule action. AWS IoT Core will then automatically transfer the incoming messages to the DynamoDB table based on the specified rule.

Step 4: Monitor and Manage the Data Store Once the data is being transferred to DynamoDB, it is important to monitor and manage the data store to ensure optimal performance and availability. This can be achieved by using AWS CloudWatch, which provides real-time monitoring and alerts for DynamoDB performance metrics.

Step 5: Optional Step: Use Redshift for Data Warehousing If the data needs to be analyzed and queried for business intelligence purposes, AWS Redshift can be used as a data warehouse. In this case, the IoT device shadows can be persisted to Redshift for further analysis. However, it is important to note that Redshift is not recommended for storing real-time data, as it is optimized for querying large datasets.

In summary, the ideal implementation steps for storing millions of messages from IoT devices in AWS are to create an AWS IoT Core rule, use Amazon DynamoDB for data storage, configure IoT rules to transfer data to DynamoDB, monitor and manage the data store using AWS CloudWatch, and optionally persist the IoT device shadows to AWS Redshift for further analysis.