Free Associate-Cloud-Engineer Exam Dumps

Question 16

You want to run a single caching HTTP reverse proxy on GCP for a latency-sensitive website. This specific reverse proxy consumes almost no CPU. You want to have a 30-GB in-memory cache, and need an additional 2 GB of memory for the rest of the processes. You want to minimize cost. How should you run this reverse proxy?

A. Create a Cloud Memorystore for Redis instance with 32-GB capacity.
B. Run it on Compute Engine, and choose a custom instance type with 6 vCPUs and 32 GB of memory.
C. Package it in a container image, and run it on Kubernetes Engine, using n1-standard-32 instances as nodes.
D. Run it on Compute Engine, choose the instance type n1-standard-1, and add an SSD persistent disk of 32 GB.

Correct Answer:A
What is Google Cloud Memorystore?
Overview. Cloud Memorystore for Redis is a fully managed Redis service for Google Cloud Platform. Applications running on Google Cloud Platform can achieve extreme performance by leveraging the highly scalable, highly available, and secure Redis service without the burden of managing complex Redis deployments.

Question 17

A company wants to build an application that stores images in a Cloud Storage bucket and wants to generate thumbnails as well as resize the images. They want to use a google managed service that can scale up and scale down to zero automatically with minimal effort. You have been asked to recommend a service. Which GCP service would you suggest?

A. Google Compute Engine
B. Google App Engine
C. Cloud Functions
D. Google Kubernetes Engine

Correct Answer:C
Text Description automatically generated with low confidence
Associate-Cloud-Engineer dumps exhibit
Cloud Functions is Google Cloud’s event-driven serverless compute platform. It automatically scales based on the load and requires no additional configuration. You pay only for the resources used.
Ref: https://cloud.google.com/functions
While all other options i.e. Google Compute Engine, Google Kubernetes Engine, Google App Engine support autoscaling, it needs to be configured explicitly based on the load and is not as trivial as the scale up or scale down offered by Google’s cloud functions.

Question 18

You are deploying an application to App Engine. You want the number of instances to scale based on request rate. You need at least 3 unoccupied instances at all times. Which scaling type should you use?

A. Manual Scaling with 3 instances.
B. Basic Scaling with min_instances set to 3.
C. Basic Scaling with max_instances set to 3.
D. Automatic Scaling with min_idle_instances set to 3.

Correct Answer:D

Question 19

You have a Compute Engine instance hosting a production application. You want to receive an email if the instance consumes more than 90% of its CPU resources for more than 15 minutes. You want to use Google services. What should you do?

A. * 1. Create a consumer Gmail account.* 2. Write a script that monitors the CPU usage.* 3. When the CPU usage exceeds the threshold, have that script send an email using the Gmail account and smtp.gmail.com on port 25 as SMTP server.
B. * 1. Create a Stackdriver Workspace, and associate your Google Cloud Platform (GCP) project with it.* 2.Create an Alerting Policy in Stackdriver that uses the threshold as a trigger conditio
C. 3.Configure your email address in the notification channel.
D. * 1. Create a Stackdriver Workspace, and associate your GCP project with it.* 2.Write a script that monitors the CPU usage and sends it as a custom metric to Stackdrive
E. 3.Create an uptime check for the instance in Stackdriver.
F. * 1. In Stackdriver Logging, create a logs-based metric to extract the CPU usage by using this regular expression: CPU Usage: ([0-9] {1,3})%* 2.In Stackdriver Monitoring, create an Alerting Policy based on this metri
G. 3.Configure your email address in the notification channel.

Correct Answer:B
Specifying conditions for alerting policies This page describes how to specify conditions for alerting policies. The conditions for an alerting policy define what is monitored and when to trigger an alert. For example, suppose you want to define an alerting policy that emails you if the CPU utilization of a Compute Engine VM instance is above 80% for more than 3 minutes. You use the conditions dialog to specify that you want to monitor the CPU utilization of a Compute Engine VM instance, and that you want an alerting policy to trigger when that utilization is above 80% for 3 minutes. https://cloud.google.com/monitoring/alerts/ui-conditions-ga
https://cloud.google.com/monitoring/alerts/using-alerting-ui https://cloud.google.com/monitoring/support/notification-options

Question 20

You are creating a Google Kubernetes Engine (GKE) cluster with a cluster autoscaler feature enabled. You need to make sure that each node of the cluster will run a monitoring pod that sends container metrics to a third-party monitoring solution. What should you do?

A. Deploy the monitoring pod in a StatefulSet object.
B. Deploy the monitoring pod in a DaemonSet object.
C. Reference the monitoring pod in a Deployment object.
D. Reference the monitoring pod in a cluster initializer at the GKE cluster creation time.

Correct Answer:B
https://cloud.google.com/kubernetes-engine/docs/concepts/daemonset https://cloud.google.com/kubernetes-engine/docs/concepts/daemonset#usage_patterns
DaemonSets attempt to adhere to a one-Pod-per-node model, either across the entire cluster or a subset of nodes. As you add nodes to a node pool, DaemonSets automatically add Pods to the new nodes as needed.
In GKE, DaemonSets manage groups of replicated Pods and adhere to a one-Pod-per-node model, either across the entire cluster or a subset of nodes. As you add nodes to a node pool, DaemonSets automatically add Pods to the new nodes as needed. So, this is a perfect fit for our monitoring pod.
Ref: https://cloud.google.com/kubernetes-engine/docs/concepts/daemonset
DaemonSets are useful for deploying ongoing background tasks that you need to run on all or certain nodes, and which do not require user intervention. Examples of such tasks include storage daemons like ceph, log collection daemons like fluentd, and node monitoring daemons like collectd. For example, you could have DaemonSets for each type of daemon run on all of your nodes. Alternatively, you could run multiple DaemonSets for a single type of daemon, but have them use different configurations for different hardware types and resource needs.