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Answer: Create a Service Directory namespace. Use API calls to register the services during deployment, and query during runtime.
The problem requires dynamic service discovery in a scalable way. Option B (Service Directory) is the correct choice because it provides a managed solution for service registration and discovery. By creating a Service Directory namespace and registering services during deployment, interservice communication can dynamically query the directory at runtime. This eliminates manual ENV variable maintenance. - **Option A** involves querying Cloud Run/Cloud Functions APIs directly, which introduces latency, permission complexities, and lacks scalability. - **Option C** relies on naming conventions, which are fragile and error-prone. - **Option D** proposes Hashicorp Consul on a single VM, which is not scalable (single point of failure) and adds operational overhead. Service Directory (B) is the most scalable, managed, and integrated solution for Google Cloud environments.
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You are developing an application deployed on Cloud Run that utilizes Cloud Functions. With each new feature addition, new Cloud Functions and Cloud Run services are deployed. Environment variables are currently used to track services and enable interservice communication, but maintaining these variables has become cumbersome. How can you implement a scalable dynamic discovery mechanism to address this issue?
A
Configure your microservices to use the Cloud Run Admin and Cloud Functions APIs to query for deployed Cloud Run services and Cloud Functions in the Google Cloud project.
B
Create a Service Directory namespace. Use API calls to register the services during deployment, and query during runtime.
C
Rename the Cloud Functions and Cloud Run services endpoint is using a well-documented naming convention.
D
Deploy Hashicorp Consul on a single Compute Engine instance. Register the services with Consul during deployment, and query during runtime.
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