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Is the Google Associate Cloud Engineer Certification worth it?

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Is the Google Associate Cloud Engineer Certification worth it?

Cloud computing has become an increasingly important aspect of the technology industry, and many companies are adopting cloud-based solutions to increase efficiency and reduce costs. As a result, there is a growing demand for professionals who have the knowledge and skills to manage cloud infrastructure and applications. The Google Associate Cloud Engineer Certification is designed to meet this demand by providing individuals with the necessary skills to manage GCP resources, create and deploy applications, and monitor and manage GCP services.

Obtaining this certification can be a significant asset for professionals in the cloud computing industry. It demonstrates to employers that you have the knowledge and skills necessary to work with GCP and can add value to their organization. Additionally, it can increase your earning potential and open up new career opportunities.

However, pursuing the Google Associate Cloud Engineer Certification requires a significant amount of time and effort. It involves studying the GCP documentation, attending training sessions, and passing an exam. Therefore, it is important to carefully consider if this certification aligns with your career goals and if the benefits outweigh the costs.

In this blog post, we will discuss the topics covered in the certification exam, the benefits of obtaining the certification, and how it can impact your career in cloud computing. We will also provide tips on how to prepare for the exam and share insights from individuals who have already obtained the certification. By the end of this post, you will have a better understanding of whether the Google Associate Cloud Engineer Certification is worth pursuing for your career goals in cloud computing.

About Google Associate Cloud Engineer Certification

Google Associate Cloud Engineers deploy applications, monitor the operations of multiple projects, and maintain enterprise solutions to ensure that performance metrics are met. This person has worked with both public clouds and on-premises solutions. They can use Google Cloud Console and the command-line interface to perform common platform-based tasks to maintain one or more deployed solutions on Google Cloud that use Google-managed or self-managed services.

The Associate Cloud Engineer exam assesses your ability to:

  • Set up a cloud solution environment
  • Plan and configure a cloud solution
  • Deploy and implement a cloud solution
  • Ensure successful operation of a cloud solution
  • Configure access and security

Glossary for Google Associate Cloud Engineer Terminology

  1. Cloud Computing – Cloud computing refers to the delivery of computing services over the internet. It involves the provision of computing resources such as servers, storage, databases, software, and other resources over the internet.
  2. Cloud Service Provider (CSP) – A cloud service provider (CSP) is a company that offers cloud computing services to businesses and individuals. Examples of CSPs include Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
  3. Virtual Machine (VM) – A virtual machine (VM) is a software emulation of a physical computer. It allows multiple operating systems to run on a single physical machine.
  4. Infrastructure as a Service (IaaS) – Infrastructure as a service (IaaS) is a cloud computing model in which a third-party provider hosts computing infrastructure such as servers, storage, and networking hardware. Customers rent this infrastructure and use it to host their applications and data.
  5. Platform as a Service (PaaS) – Platform as a service (PaaS) is a cloud computing model in which a third-party provider offers a platform for customers to develop, run, and manage applications. PaaS providers typically offer a preconfigured environment with programming languages, libraries, and tools for application development.
  6. Software as a Service (SaaS) – Software as a service (SaaS) is a cloud computing model in which a third-party provider hosts software applications and makes them available to customers over the internet.
  7. Load Balancing – Load balancing is the process of distributing incoming network traffic across multiple servers to ensure that no single server is overwhelmed with traffic. This helps to improve the performance and availability of applications.
  8. Auto Scaling – Auto scaling is a feature that allows a cloud service to automatically adjust its computing resources based on changes in demand. This helps to ensure that there is always enough capacity to handle incoming traffic.
  9. Cloud Storage – Cloud storage refers to the storage of data on remote servers that can be accessed over the internet. Cloud storage providers offer scalable and flexible storage options that can be accessed from anywhere.
  10. Virtual Private Cloud (VPC) – A virtual private cloud (VPC) is a virtual network that is isolated from other networks and is used by a single organization. It provides a secure environment for running applications and storing data.
  11. Cloud Security – Cloud security refers to the measures taken to protect cloud computing environments from cyber threats such as hacking, malware, and data breaches. It involves a combination of physical security, network security, and data security measures.

Exam preparation resources for Google Associate Cloud Engineer Exam

There are several resources available for preparing for the Google Associate Cloud Engineer exam. Here are some of the most popular ones:

  • Google Cloud Certification Exam Guide: This guide provides an overview of the certification exam, including the topics covered, the format of the exam, and tips for preparing for the exam. You can access the guide here: https://cloud.google.com/certification/guides/cloud-engineer
  • Google Cloud’s Online Training: Google Cloud offers several online training courses that cover the topics included in the Associate Cloud Engineer certification exam. These courses are self-paced and include interactive demos and quizzes. You can access the training here: https://cloud.google.com/training/cloud-infrastructure
  • Practice Exams: Practice exams are an excellent way to prepare for the certification exam. Google Cloud offers a practice exam for the Associate Cloud Engineer certification that simulates the actual exam experience. You can access the practice exam here: https://cloud.google.com/certification/practice-exam/cloud-engineer
  • Official Study Guide: Google Cloud offers an official study guide that covers all the topics included in the Associate Cloud Engineer certification exam. The study guide includes detailed explanations and examples, as well as practice questions and quizzes. You can access the study guide here: https://services.google.com/fh/files/misc/cloud-engineer-study-guide.pdf
  • Google Cloud Community: The Google Cloud Community is an online forum where you can connect with other professionals who are preparing for the certification exam. The community is an excellent resource for asking questions, sharing study tips, and learning from others’ experiences. You can access the community here: https://cloud.google.com/community

Let us now look at the course outline to get a better picture of the exam –

Course Outline

Google Associate Cloud Engineer Course Covers the following 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

Let us now come to the main point of the article –

Is it worth taking Google Associate Cloud Engineer Certification?

Students who want to take the prestigious Google Certified Associate Cloud Engineer and Architect exam should take this course. This exam combines three courses: Introduction to Google Cloud Platform, Google Certified Cloud Data Engineer, and Nigel Poulton’s Kubernetes deep dive. All of these courses are essential for Google Cloud Platform certifications. Hence, the certification is worthy of both time and effort.

The questions on the Google Cloud Platform Certification exams are notoriously difficult, so prior preparation and training are required. Surprisingly, Google does not assign grades to its exams. Instead, it assigns a “Pass” or “Fail” rating to the score. This makes it difficult for students to know what and where to focus to avoid receiving a “fail.”

Let us now delve into the resources that will help you crack the exam –

Online training

Numerous websites offer online preparation for this exam. The best way to prepare for the exam while developing a strong understanding of the concepts is through online training. The online classes also provide you with good reading material, such as notes, or recommend books that you might find useful. Google has recommended some training that may assist you in scoring well and that is officially prepared by Google itself via Coursera and other sites.

Complete the recommended curriculum in Google Associate Cloud Engineer Training:

Broaden your knowledge with additional self-paced labs and quests:

Practice Tests

Your practice is what will determine your future. You should try to take as many Google Associate Cloud Engineer Practice Tests as possible because they will never let you down. Practicing will help you determine where you are lacking in your performance and will also help you gain confidence on the day of the exam by eliminating your silly mistakes. You can take a free Google Associate Cloud Engineer practice test right now.

Google documentation

Google documentation is the most reliable resource for preparation, and it is also free. You can find the documentation for this exam on Google’s official site. Google has divided its documentation into the four major sections listed below:

You can look through these documents to find reliable and high-quality content for your preparation.

Conclusion

The ACE is all about being able to use the Google Cloud Platform—both via the web interface and the command line. This certification focuses on the most important GCP foundation. It includes all of the critical system building blocks, such as data processing, memory, and data movement. So, hurry up and get certified now!

Anandita Doda
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