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Answer: An IoT gateway connected to Cloud Pub/Sub, with Cloud Dataflow to read and process the messages from Cloud Pub/Sub.
The recommended cloud-native architecture for handling spikes in message ingestion from IoT devices is to use an IoT gateway connected to Cloud Pub/Sub, with Cloud Dataflow to read and process the messages from Cloud Pub/Sub. Pub/Sub can act as a buffer and rate leveller for incoming data streams, which is essential for handling the bursty traffic caused by intermittent internet connectivity. Furthermore, Pub/Sub can scale to handle data spikes, ensuring that the system remains robust and cost-effective. Option A (Edge TPUs) is not relevant as it is used for deploying machine learning models. Option B (Cloud Dataflow connected to Kafka) does not address the global ingestion and buffering issues. Option D (Kafka cluster on Compute Engine) would still face similar manageability and scalability problems.
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You are managing a single on-premises Kafka cluster located in a data center in the us-east region. This cluster handles the ingestion of messages from IoT devices worldwide. Due to poor internet connectivity in many parts of the world, messages often accumulate at the edge and are then sent in large batches, causing spikes in load on your Kafka cluster. This situation is becoming challenging to manage and increasingly costly. What is the Google-recommended cloud-native architecture for addressing this scenario?
A
Edge TPUs as sensor devices for storing and transmitting the messages.
B
Cloud Dataflow connected to the Kafka cluster to scale the processing of incoming messages.
C
An IoT gateway connected to Cloud Pub/Sub, with Cloud Dataflow to read and process the messages from Cloud Pub/Sub.
D
A Kafka cluster virtualized on Compute Engine in us-east with Cloud Load Balancing to connect to the devices around the world.
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