Exam Associate Cloud Engineer topic 1 question 278 discussion

Here's why A is the most effective solution to mitigate API quota errors during traffic spikes: Cold Starts and API Calls: Cloud Run services scale to zero when not in use. When a new request arrives, a new instance is spun up, leading to a cold start. During this cold start, multiple API calls might be made to initialize the application and connect to the Cloud SQL database. If there's a sudden spike in traffic, a large number of cold starts can occur simultaneously, exceeding the Cloud SQL API quota. Minimum Instances: By setting a minimum number of Cloud Run instances, you can ensure that a few instances are always running, even during periods of low traffic. This eliminates cold starts during traffic spikes and reduces the number of concurrent API calls made to Cloud SQL, helping you stay within the quota limits.

There has been a previous question relating to this issue which is caused by Cold Starts (RuchiMishra explains this). Solving the issue would be by configuring a minimum number of instances always running

Cloud Run allows you to configure a concurrency setting (using the --concurrency flag when deploying the service). In this context, “set a minimum concurrent requests environment variable” refers to configuring your service so that each instance handles a higher number of concurrent requests. Therefore, don't reach the API quota errors due too many cloud run instances created and doing requests at the same time.

A minimum number of running instances helps reduce cold start delays, but it does not prevent new instances from scaling up rapidly during a traffic spike. The API quota issue occurs when too many Cloud Run instances spawn too quickly, each establishing new connections to Cloud SQL.

A Make sense

As explained by RuchiMishra, we need to keep a minimum number of instances always running.