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Google Cloud Monitoring

  • Cloud Monitoring collects metrics, events, and metadata, hosted uptime probes, and application instrumentation to gain visibility into the performance, availability, and health of your applications and infrastructure.

Features

  • Collect metrics from multicloud and hybrid infrastructure in real time.
  • Metrics, events, and metadata are displayed with rich query language that helps identify issues and uncover significant patterns.
  • Reduces time spent navigating between systems with one integrated service for metrics, uptime monitoring, dashboards, and alerts.
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Workspaces

  • Cloud Monitoring utilizes workspaces to organize and manage its information.
  • A Workspace can manage the monitoring data for a single Google Cloud project, or it can manage the data for multiple Google Cloud projects and AWS accounts.
  • But, a Google Cloud project or an AWS account can only be associated with one Workspace at a time.
  • You must have at least one of the following IAM role name for the Google Cloud project to create a Workspace:
    • Monitoring Editor
    • Monitoring Admin
    • Project Owner

Cloud Monitoring Agent

  • The Cloud Monitoring agent is a collectd-based daemon that collects application and system metrics from virtual machine (VM) instances.
  • The Monitoring agent collects disk, network, CPU, and process metrics by default.
  • You can configure the Monitoring agent to monitor third-party applications.

Pricing

  • Monitoring charges only for the volume of ingested metric data and Cloud Monitoring API read calls that exceed the free monthly allotment.
  • Non-chargeable metrics and Cloud Monitoring API write calls don’t count towards the allotment limit.

Validate Your Knowledge

Question 1

You are managing your company’s cloud resources that are residing in multiple GCP projects. You are tasked to set up centralized monitoring of all the CPU, memory, and disk metrics of your resources. You want to follow Google’s recommended best practices.

What should you do?

  1. Create an export sink on each project. Export the logs on a single BigQuery dataset.
  2. Configure Metrics Scope in Cloud Monitoring. Create a new scoping project and include all GCP Projects for monitoring.
  3. Enable Cloud Monitoring on all projects to monitor all resources. Create a custom application that processes metrics from Cloud Monitoring.
  4. Deploy a Cloud Monitoring agent on all projects to collect metrics. Create an application that consumes and presents these metrics.

Correct Answer: 2

Cloud Monitoring collects measurements of your service and of the Google Cloud resources that you use.

Monitoring lets you view and manage metrics in the following ways:

– For a single project

– For multiple projects within a single organization

– For multiple projects across multiple organizations

– For multiple Google Cloud projects and AWS accounts

By default, a Google Cloud project has visibility only to the metrics it stores. However, you can expand the set of metrics that a project can access by adding other Google Cloud projects to the project’s metrics scope. The metrics scope defines the set of Google Cloud projects whose metrics the current Google Cloud project can access.

A scoping project hosts a metrics scope. Because every Google Cloud project hosts a metrics scope, every project is also a scoping project. The scoping project stores information about its metrics scope. It also stores the alerts, uptime checks, dashboards, and monitoring groups that you configure for the metrics scope. You can identify the scoping project for a metrics scope as the project selected by the Cloud Console project picker.

Google recommends the use of a new Cloud project or one without resources as the scoping project when you want to view metrics for multiple Cloud projects or AWS accounts.

Hence, the correct answer is: Configure Metrics Scope in Cloud Monitoring. Create a new scoping project and include all GCP Projects for monitoring.

The option that says: Create an export sink on each project. Export the logs on a single BigQuery dataset is incorrect because you can’t use BigQuery for monitoring cloud resources. BigQuery is primarily used for storing and analyzing large data like logs using SQL queries.

The option that says: Enable Cloud Monitoring on all projects to monitor all resources. Create a custom application that processes metrics from Cloud Monitoring is incorrect as this is not a Google-recommended practice. Doing so will consume significant costs. It also takes time to set up and maintain.

The option that says: Deploy a Cloud Monitoring agent on all projects to collect metrics. Create an application that consumes and presents these metrics is incorrect because Cloud Monitoring agents are only used to collect metrics from VMs. These metrics are then forwarded to Cloud Monitoring. A better solution is to configure metrics scope instead.

References:

https://cloud.google.com/monitoring/settings
https://cloud.google.com/monitoring/settings/multiple-projects

Note: This question was extracted from our Google Certified Associate Cloud Engineer Practice Exams.

For more Google Cloud practice exam questions with detailed explanations, check out the Tutorials Dojo Portal:

Google Certified Associate Cloud Engineer Practice Exams

References:
https://cloud.google.com/monitoring
https://cloud.google.com/monitoring/workspaces/create
https://cloud.google.com/monitoring/agent

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