Google Professional Cloud Architect

Choose your answer

• A

  Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones

• B

  Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce "chaos" to the system by terminating random resources on both zones

• C

  Expose the new system to a larger group of users, and increase group size each day until autoscale logic is triggered on all layers. At the same time, terminate random resources on both zones

• D

  Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing user’s usage of the app, and deploy enough resources to handle 200% of expected load

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Choose your answer

• A

  Remove Python after running pip

• B

  Remove dependencies from requirements.txt

• C

  Use a slimmed-down base image like Alpine Linux

• D

  Use larger machine types for your Google Container Engine node pools

• E

  Copy the source after he package dependencies (Python and pip) are installed

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Choose your answer

• A

  Deploy fewer changes to production

• B

  Deploy smaller changes to production

• C

  Increase the load on your test and staging environments

• D

  Deploy changes to a small subset of users before rolling out to production

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Choose your answer

• A

  Set timeouts on your application so that you can fail requests faster

• B

  Send custom metrics for each of your requests to Stackdriver Monitoring

• C

  Use Stackdriver Monitoring to look for insights that show when your API latencies are high

• D

  Instrument your application with Stackdriver Trace in order to break down the request latencies at each microservice

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Choose your answer

• A

  Use a different database

• B

  Choose larger instances for your database

• C

  Create snapshots of your database more regularly

• D

  Implement routinely scheduled failovers of your databases

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