[2024-Feb-New]Braindump2go Professional-Cloud-Developer PDF Dumps(102-268)

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A. Download, install, and start the Snapshot Debugger agent in your VM. Take debug snapshots of
the functions that take the longest time. Review the call stack frame, and identify the local
variables at that level in the stack.
B. Import the Cloud Profiler package into your application, and initialize the Profiler agent. Review
the generated flame graph in the Google Cloud console to identify time-intensive functions.
C. Import OpenTelemetry and Trace export packages into your application, and create the trace
provider.
Review the latency data for your application on the Trace overview page, and identify where
bottlenecks are occurring.
D. Create a Cloud Logging query that gathers the web application's logs. Write a Python script that
calculates the difference between the timestamps from the beginning and the end of the
application's longest functions to identity time-intensive functions.
One Time!
Answer: B
Explanation:
https://cloud.google.com/profiler/docs/about-profiler
Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation
information from your production applications. It attributes that information to the source code that generated it, helping
you identify the parts of your application that are consuming the most resources, and otherwise illuminating your
applications performance characteristics.
QUESTION 239
You have a container deployed on Google Kubernetes Engine. The container can sometimes be slow to launch, so you
have implemented a liveness probe. You notice that the liveness probe occasionally fails on launch. What should you
do?
A. Add a startup probe.
B. Increase the initial delay for the liveness probe.
C. Increase the CPU limit for the container.
D. Add a readiness probe.
Answer: A
Explanation:
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#define-startupprobes
The kubelet uses startup probes to know when a container application has started. If such a probe is configured, it
disables liveness and readiness checks until it succeeds, making sure those probes don't interfere with the application
startup. This can be used to adopt liveness checks on slow starting containers, avoiding them getting killed by the
kubelet before they are up and running.
QUESTION 240
You work for an organization that manages an ecommerce site. Your application is deployed behind a global HTTP(S)
load balancer. You need to test a new product recommendation algorithm. You plan to use A/B testing to determine the
new algorithm's effect on sales in a randomized way. How should you test this feature?
A. Split traffic between versions using weights.
B. Enable the new recommendation feature flag on a single instance.
C. Mirror traffic to the new version of your application.
D. Use HTTP header-based routing.
Answer: A
Explanation:
https://cloud.google.com/traffic-director/docs/advanced-traffic-management#weightbased_traffic_splitting_for_safer_deployments
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