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Answer: 1 Run the air quality devices' backends in a managed instance group. 2. Create an external Application Load Balancer, and connect it to the managed instance group. 3. Configure a connection between the air quality devices and the Application Load Balancer.
The goal is to minimize latency (TTFB) for thousands of devices sending data every minute via HTTP. - **Options A & B** use DNS-based load balancing (round robin), which is static and doesn't account for backend instance health or load. DNS caching can lead to suboptimal routing, increasing latency. - **Option C** uses a Network Load Balancer (Layer 4), which forwards TCP traffic directly to backend VMs. While this reduces proxy overhead, it lacks HTTP-aware load balancing, potentially routing traffic to overloaded instances, increasing TTFB. - **Option D** uses an Application Load Balancer (Layer 7), which terminates HTTP connections and intelligently routes requests based on backend health, load, or other metrics. This ensures traffic is distributed to the least busy instances, minimizing TTFB despite slight proxy overhead. Since the backend is RESTful (HTTP), the Application Load Balancer is the optimal choice for dynamic load balancing in this scenario.
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How should you design a service to connect thousands of air quality monitoring devices to a RESTful backend in a single cloud region, using Premium Tier networking, such that the devices can send and receive data payloads via curl commands every minute while minimizing daily average latency (measured by Time to First Byte)?
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1 Run the air quality devices' backends in a managed instance group. 2. Create an external Application Load Balancer, and connect it to the managed instance group. 3. Configure a connection between the air quality devices and the Application Load Balancer.