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How to become a Google Associate Cloud Engineer?

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Google Associate Cloud Engineer

This evolution of the Information Technology world is showing marks of growth, whether it’s connected to the cloud or any other area. Individuals who want to start a career in IT are becoming increasingly interested in being certified as a result of this development. That is to say, most people are considering a career in cloud computing as it opens up a whole new universe of possibilities by providing the most in-demand employment role of Google Cloud Engineer Associate.

A Google Cloud Engineer possessses the skills to build platforms that enable enterprises to store and operate data and programs online. However, in order to better understand this role, we will cover all elements and pathways for preparing for and achieving it here in this blog.

What does it take to become a Google Cloud Engineer?

It is necessary to fulfil some recommended key prerequisites in order to work as a cloud engineer. Let’s find out more about them.

  • You must have a bachelor’s degree in computer science or a related subject.
  • Secondly, it is suggested that you have at least three years of cloud computing expertise. Advanced expertise and comprehension of CI/CD and SysOps platforms are also required. 
  • Thirdly, you should have troubleshooting and analytical skills, as well as communication, teamwork, and customer management skills.
  • Lastly, earning a Google Cloud Engineer certification is the greatest approach to improving a cloud engineer’s knowledge and abilities.

Google Associate Cloud Engineer Certification Preparation Guide

The first and only method to get into this position is to obtain certification by studying for and passing the Associate Cloud Engineer exam.

Google Associate Cloud Engineer Certification

Step 1: Understanding the Associate Cloud Engineer Exam

Associate Cloud Engineers who can install apps, monitor operations, and manage corporate solutions should take this exam. They use the Google Cloud Console and the command-line interface for doing typical platform-based operations in order for maintaining one or more deployed solutions on Google Cloud that use Google-managed or self-managed services. However, the Associate Cloud Engineer exam measures your ability to do the following:

  • Creating a cloud-based solution environment.
  • Secondly, create a cloud solution and configure it.
  • Then, installing and configuring a cloud solution.
  • Ensuring that a cloud solution runs smoothly.
  • Lastly, configuring security and access.

About Exam Format:

Google Associate Cloud Engineer Exam will have around 50 questions with a limit of 2 hours. The question format type will be multiple choice and multiple select. Further, the exam can be given in English, Spanish, and Japanese language with a registration fee of $125 (plus tax where applicable). Taking about the exam delivery method, you can:

  • Firstly, go for the online-proctored exam from a remote location
  • Secondly, the onsite-proctored exam at a testing center

Step 2: Getting real-world experience

Before attempting the exam, it’s recommended that you have 6+ months of hands-on experience with Google Cloud products and solutions. However, get yourself familiar with Google products. Some of them are:

  • Compute Engine
    • Scalable, high-performance virtual machines.
  • Cloud Storage
    • Class performance, reliability, and pricing for all storage requirements.
  • BigQuery
    • Fully managed, petabyte-scale, analytics data warehouse.
  • Google Kubernetes Engine
    • Container orchestration via Kubernetes clusters, handled by Google.
  • App Engine
    • A platform for creating scalable web applications and mobile back ends.
  • Cloud Run
    • A completely managed environment for running stateless containers.
  • Cloud Build
    • Fast, consistent, reliable builds on Google Cloud.
  • Operations (formerly Stackdriver)
    • Monitoring, logging, and diagnostics for applications on Google Cloud.

Step 3: Exploring the Exam Guide

The ACE exam guide contains a full list of topics that could appear on the exam. The Google Associate Cloud Engineer exam, on the other hand, will verify your abilities in installing and securing apps and infrastructure, monitoring multiple projects’ operations, and managing corporate solutions to achieve performance targets. Experience with public clouds and on-premises solutions is required. You’ll also be able to utilize Google Cloud Console and the command-line interface to manage and scale one or more deployed solutions by performing common platform-based operations. Also, check the exam guide to identify your skills to have a better understanding of these topics.

1. Setting up a cloud solution environment (17.5%)

1.1 Setting up cloud projects and accounts. Activities include:

  • Creating a resource hierarchy
  • Applying organizational policies to the resource hierarchy
  • Granting members IAM roles within a project
  • Managing users in Cloud Identity (manually and automated) (GCP Documentation: Cloud Identity)
  • Enabling APIs within projects (GCP Documentation: Enabling an API in your Google Cloud project)
  • Provisioning and setting up products in Google Cloud’s operations suite

1.2 Managing billing configuration. Activities include:

1.3 Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project).

2. Planning and configuring a cloud solution (17.5%)

2.1 Planning and estimating Google Cloud product use using the Pricing Calculator

2.2 Planning and configuring compute resources. Considerations include:

2.3 Planning and configuring data storage options. Considerations include:

  • Product choice (e.g., Cloud SQL, BigQuery, Firestore, Spanner, Bigtable) (GCP Documentation: Google Cloud products)
  • Choosing storage options (e.g., Zonal persistent disk, Regional balanced persistent disk, Standard, Nearline, Coldline, Archive)

2.4 Planning and configuring network resources. Tasks include:

3. Deploying and implementing a cloud solution (25%)

3.1 Deploying and implementing Compute Engine resources. Tasks include:

  • Launching a compute instance using the Google Cloud console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)
  • Creating an autoscaled managed instance group using an instance template (GCP Documentation: Creating managed instance groups)
  • Generating/uploading a custom SSH key for instances (GCP Documentation: Managing SSH keys in metadata)
  • Installing and configuring the Cloud Monitoring and Logging Agent
  • Assessing compute quotas and requesting increases (GCP Documentation: Requesting an increase in quota)

3.2 Deploying and implementing Google Kubernetes Engine resources. Tasks include:

  • Installing and configuring the command line interface (CLI) for Kubernetes (kubectl)
  • Deploying a Google Kubernetes Engine cluster with different configurations including AutoPilot, regional clusters, private clusters, etc.
  • Deploying a containerized application to Google Kubernetes Engine (GCP Documentation: Deploying a containerized web application)
  • Configuring Google Kubernetes Engine application monitoring and logging (GCP Documentation: Overview of Google Cloud’s operations suite for GKE)

3.3 Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable:

  • Deploying an application and updating scaling configuration, versions, and traffic splitting (GCP Documentation: Splitting Traffic)
  • Deploying an application that receives Google Cloud events (e.g., Pub/Sub events, Cloud Storage object change notification events)

3.4 Deploying and implementing data solutions. Tasks include:

  • Initializing data systems with products (e.g., Cloud SQL, Firestore, BigQuery, Spanner, Pub/Sub, Bigtable, Dataproc, Dataflow, Cloud Storage) (GCP Documentation: Initialization actions)
  • Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub) (GCP Documentation: Introduction to loading data)

3.5 Deploying and implementing networking resources. Tasks include:

  • Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC) (GCP Documentation: Using VPC networks)
  • Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags) (GCP Documentation: Creating instances with multiple network interfaces)
  • Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, network tags, service accounts) (GCP Documentation: VPC firewall rules overview)
  • Creating a VPN between a Google VPC and an external network using Cloud VPN (GCP Documentation: Cloud VPN overview)
  • Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer) (GCP Documentation: External TCP/UDP Network Load Balancing overview)

3.6 Deploying a solution using Cloud Marketplace. Tasks include:

3.7 Implementing resources via infrastructure as code. Tasks include:

  • Building infrastructure via Cloud Foundation Toolkit templates and implementing best practices
  • Installing and configuring Config Connector in Google Kubernetes Engine to create, update, delete, and secure resources

4. Ensuring successful operation of a cloud solution (20%)

4.1 Managing Compute Engine resources. Tasks include:

  • Managing a single VM instance (e.g., start, stop, edit configuration, or delete an instance) (GCP Documentation: Virtual machine instances)
  • Remotely connecting to the instance
  • Attaching a GPU to a new instance and installing CUDA libraries (GCP Documentation: Adding or removing GPUs)
  • Viewing current running VM inventory (instance IDs, details) (GCP Documentation: Instance life cycle)
  • Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot) (GCP Documentation: Creating persistent disk snapshots)
  • Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image) (GCP Documentation: Images)
  • Working with instance groups (e.g., set autoscaling parameters, assign instance template, create an instance template, remove instance group) (GCP Documentation: Instance groups)
  • Working with management interfaces (e.g., Google Cloud console, Cloud Shell, Cloud SDK) (GCP Documentation: Cloud management tools)

4.2 Managing Google Kubernetes Engine resources. Tasks include:

  • Viewing current running cluster inventory (nodes, pods, services) (GCP Documentation: GKE Dashboards)
  • Browsing the container image repository and viewing container image details (GCP Documentation: gcloud container images list)
  • Working with node pools (e.g., add, edit, or remove a node pool) (GCP Documentation: Node pools)
  • Working with pods (e.g., add, edit, or remove pods) (GCP Documentation: Pod)
  • Working with services (e.g., add, edit, or remove a service) (GCP Documentation: About Google Cloud services)
  • Working with stateful applications (e.g. persistent volumes, stateful sets) (GCP Documentation: Deploying a stateful application)
  • Managing Horizontal and Vertical autoscaling configurations
  • Working with management interfaces (e.g., Google Cloud Console, Cloud Shell, Cloud SDK, kubectl) (GCP Documentation: Cloud management tools)

4.3 Managing Cloud Run resources. Tasks include:

  • Adjusting application traffic splitting parameters (GCP Documentation: Splitting Traffic)
  • Setting scaling parameters for autoscaling instances (GCP Documentation: Autoscaling groups of instances)
  • Determining whether to run Cloud Run (fully managed) or Cloud Run for Anthos

4.4 Managing storage and database solutions. Tasks include:

4.5 Managing networking resources. Tasks include:

4.6 Monitoring and logging. Tasks include:

  • Creating Cloud Monitoring alerts based on resource metrics
  • Creating and ingesting Cloud Monitoring custom metrics (e.g., from applications or logs)
  • Configuring log sinks to export logs to external systems (e.g., on-premises or BigQuery) (GCP Documentation: Exporting with the Logs Viewer)
  • Configuring log routers
  • Viewing and filtering logs in Stackdriver (GCP Documentation: Advanced logs queries)
  • Viewing specific log message details in Stackdriver (GCP Documentation: Viewing logs (Classic))
  • Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time) (GCP Documentation: Error Reporting)
  • Viewing Google Cloud status (GCP Documentation: Google Cloud Status Dashboard)

5. Configuring access and security (20%)

5.1 Managing identity and access management (IAM). Tasks include:

  • Viewing IAM policies
  • Creating IAM policies
  • Managing the various role types and defining custom IAM roles (e.g., primitive, predefined and custom) (GCP Documentation: Basic concepts)

5.2 Managing service accounts. Tasks include:

  • Creating service accounts
  • Using service accounts in IAM policies with minimum permissions (GCP Documentation: Service accounts)
  • Assigning service accounts to resources (GCP Documentation: Creating and enabling service accounts for instances)
  • Managing IAM of a service account
  • Managing service account impersonation
  • Creating and managing short-lived service account credentials

5.3 Viewing audit logs

Cloud Engineer Cheat Sheet online tutorials

Step 4: Gain skills using the Cloud Engineer learning path

The learning path takes you through a series of courses to help you prepare for the Cloud Engineer Associate exam.

➼ Google Cloud Fundamentals: Core Infrastructure

Reference: https://www.cloudskillsboost.google/course_templates/77?utm_source=gcp_training&utm_medium=website&utm_campaign=cgc&skip_cache=true

  • Understand the process of Google Cloud’s computing and storage services available, including Compute Engine, Google Kubernetes Engine, App Engine, Cloud Storage, Cloud SQL, and BigQuery. Moreover, the course provides an overview of resource and policy management tools such as the Resource Manager hierarchy and Cloud Identity and Access Management.
➼ Architecting with Google Compute Engine

Reference: https://cloud.google.com/training/course/architecting-with-google-compute-engine?skip_cache=true

  • Use Compute Engine for exploring and installing infrastructure components such as networks, systems, and application services. Further, this course covers how to implement practical solutions, such as securely linking networks, using customer-supplied encryption keys, security and access control, quotas and pricing, and resource monitoring.
➼ Begin with Google Kubernetes Engine

Reference: https://cloud.google.com/training/course/getting-started-with-google-kubernetes-engine?skip_cache=true

  • Learn how to use Google Kubernetes Engine to implement solutions (GKE). Moreover, you’ll learn how to create, plan, practice load balancing, and monitor workloads in this course. And, learning the process of handling role-based access control and security, as well as how to provide your cloud apps persistent storage.
➼ Creating and Managing Cloud Resources

Reference: https://cloud.google.com/training/course/getting-started-create-and-manage-cloud-resources?skip_cache=true

  • Understand the Google Cloud’s important tools and services. Further, learn how to use Cloud Shell to perform commands and launch your first virtual machine, as well as how to use Google Kubernetes Engine and load balancing to run apps.
➼ Executing Foundational Infrastructure Tasks in Google Cloud

Reference: https://cloudskillsboost.google/quests/118?utm_source=gcp_training&utm_medium=website&utm_campaign=cgc-infmod&skip_cache=true

  • Developing important skills for using Google Cloud effort by diving into Cloud Storage and other major application services like,
    • Stackdriver
    • Cloud Functions. 
➼ Setting up a Cloud Environment in Google Cloud

Reference: https://cloudskillsboost.google/quests/119?utm_source=gcp_training&utm_medium=website&utm_campaign=cgc-infmod&skip_cache=true

  • Get familiar with the services that will be covered in the Google Cloud Associate Cloud Engineer test. Further, you’ll also learn about IAM, networking, and deploying Google Kubernetes Engine.
➼ Using Terraform for Automating Infrastructure on Google Cloud

Reference: https://cloudskillsboost.google/quests/159?utm_source=gcp_training&utm_medium=website&utm_campaign=cgc-infmod&skip_cache=true

  • Learn how to use Terraform, an open-source infrastructure deployment solution, to automate your infrastructure on Google Cloud.

Step 5: Use the Google exam readiness course

To familiarise yourself with the exam materials, take the “Preparing for the Associate Cloud Engineer Examination” course.

Preparing for the Associate Cloud Engineer Exam

This on-demand course helps you in organizing study for the Associate Cloud Engineer exam. The structure and format of the test, as well as its link to other Google Cloud certifications, will be covered in this session. You will familiarise yourselves with the areas covered by the test through lectures, demos, and hands-on laboratories. 

Further, this course will not prepare you for the Associate Cloud Engineer certification test on its own. It will, however, assist you in better understanding the test’s topics and navigating the recommended resources supplied by Google and Qwiklabs for preparation for the exam, allowing you to develop your own customized study strategy.

Step 6: Using Additional Training Resources

The more study materials you have for the Cloud Engineer Associate certification Exam, the better. To put it another way, if you want a good revision, you should focus on improving your foundational understanding. There are, nevertheless, some resources worth investigating:

  • Taking a webinar
    • Use this to connect with Googlers and recognized professionals can help you prepare for the exam. Further, learn useful test tips and tactics for the Associate Cloud Engineer exam, as well as hear from professionals in the field.

Step 7: Get yourself enrolled in Online Course

To pass the Cloud Engineer Associate Exam, you’ll need a solid understanding of how to use Google Cloud, the most secure cloud environment available. You’ll need to gain the relevant abilities for the Google Cloud Engineer Associate job and certification exams. And you may do so by enrolling in the Google Cloud Training online course. It will also help you prepare for the Google exam. There will also be expert-level help available to assist you in addressing any difficulties or queries you may have. 

Here are a few online course providers that may assist you in becoming well-versed and equipped with in-depth knowledge in order to pass the test.

  • Udemy
  • Coursera
  • Testprep Training
  • Simplilearn

Step 8: Evaluate yourself with Practice Tests

Practice exams for Google Certified Cloud Engineer Associate will assist you in identifying your weak areas so that you can develop. You will also be able to evaluate your strong and weak areas by assessing yourself using these assessments. You’ll also be able to improve your replying skills, which will help you save time. The greatest time to begin holding practice examinations, though, is after you’ve completed one full topic.

Step 9: Scheduling the Exam

  • To get started, go to Google Cloud and register for the exam you wish to take.
    • However, Google Cloud certifications are available in a variety of languages. A list of available languages may be seen on the exam page.
  • Secondly, create a new user account in Google Cloud’s instance of that language in Webassessor if you’re a first-time test taker or want to take the certification exam in a localized language.
  • Then select an exam and a delivery option for it from the catalog (remote or from a testing center).
  • After that, select your exam day, time, and testing center location  (if applicable). Then, confirm your payment.
  • Lastly, after your registration is complete, Kryterion provides you with a unique Test Taker Authorization Code through email. Further, to begin your exam at the testing center, you’ll need this code.

After passing the exam:

Step 10: Start working on projects and applying for jobs

After certification, you should engage in various professional projects to expand your knowledge and abilities. This will prepare you for productive performance. On the other side, Google certification can lead to a range of high-paying jobs. You may advance your career by earning more money and working in a more exciting position if you have some work experience and certification. However, an Associate Cloud Engineer’s salaries in India range from 2.0 lakhs to 12.8 lakhs, with an average yearly pay of 4.0 lakhs, according to market data.

Further, some of the top companies hiring for this role include:

  • TCS
  • Cognizant
  • Larsen & Toubro Infotech
  • Oracle

Final Words

Gaining the ability to establish remote networks for organizations to exchange and transmit data, do big data analysis, store backup data, and even test and develop apps will help you get the position of Google Cloud engineer. To put it another way, all you need is a thorough comprehension of the topic, a good qualifying score on the Google Cloud Engineer Associate exam, and some job experience. Cloud engineers are needed by almost every firm, big or small. So don’t it on hold for any longer and begin preparing to become a Google Cloud Engineer right away.

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Pulkit Dheer
With a background in Engineering and a great enthusiasm for writing, Pulkit focuses on intensive research to create targeted content. He brings his years of learning and experience to his current role. With a zeal towards technological research and powerful use of words dedicated to inspire and help professionals onset their career.
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