The Google Associate Cloud Engineer (ACE) certification is one of the most popular entry-level cloud certifications offered by Google Cloud. It’s designed for individuals who want to demonstrate their ability to deploy, manage, and monitor cloud applications on the Google Cloud Platform (GCP).
Whether you are starting your cloud career or transitioning from another IT role, the Google Associate Cloud Engineer certification provides a solid foundation. It covers key skills like setting up cloud environments, configuring virtual machines, managing Kubernetes clusters, securing resources, and using Google’s powerful command-line tools and console.
In today’s job market, where cloud computing skills are in high demand, becoming a Google Associate Cloud Engineer can open doors to roles such as Cloud Engineer, DevOps Associate, or Site Reliability Engineer—especially in organizations that use or plan to adopt Google Cloud.
What is the Google Associate Cloud Engineer Certification?
The Google Associate Cloud Engineer (ACE) certification is an entry-level credential that demonstrates your ability to work with Google Cloud Platform (GCP) services in real-world environments. It validates your skills in deploying, managing, and operating cloud applications and infrastructure on GCP.
Overview of the Certification
The ACE certification is ideal for those who are new to cloud computing or new to Google Cloud. It focuses on practical, hands-on skills that a cloud engineer would use daily—like managing virtual machines, configuring access, setting up cloud storage, and using both the Google Cloud Console and the command-line interface (gcloud).
It is often considered the first step in Google Cloud’s certification path, serving as a foundational certification before moving on to advanced roles such as Professional Cloud Architect or DevOps Engineer.
Skills Required
The ACE exam assesses your ability to:
- Set up and configure cloud environments (projects, billing, networking)
- Deploy and manage compute engines and Kubernetes applications
- Monitor and log GCP services
- Implement IAM policies and secure cloud resources
- Use Google Cloud tools like Cloud Shell, Cloud Console, and the
gcloudCLI
These tasks represent the day-to-day responsibilities of a junior cloud engineer, making this certification highly relevant for early-career professionals.
How it Fits in the Google Cloud Certification Path
The Associate Cloud Engineer certification is positioned at the foundation level, preparing candidates for more specialized professional certifications such as:
- Professional Cloud Architect
- Professional Cloud Developer
- Professional Cloud Security Engineer
- Professional Data Engineer
It’s a great way to demonstrate your readiness for cloud-based roles and gain familiarity with GCP’s ecosystem before diving deeper.
Exam Format
| Feature | Details |
|---|---|
| Exam Name | Associate Cloud Engineer |
| Level | Associate |
| Duration | 2 hours |
| Format | Multiple choice and multiple select |
| Delivery Method | Online (proctored) or in-person at a test center |
| Languages Available | English, Japanese |
| Cost | $125 USD |
| Result | Immediate pass/fail notification after submission |
| Retake Policy | 14-day waiting period between attempts |
Visit the official certification page:
https://cloud.google.com/certification/cloud-engineer
Who should take the exam?
The Google Associate Cloud Engineer (ACE) certification is designed for individuals who are starting their journey in cloud computing, especially within the Google Cloud ecosystem. It’s ideal for anyone who wants to build, deploy, and manage applications and services on Google Cloud using both the web console and command-line tools.
Ideal Candidate Profile
This certification is a great fit for:
- Students and recent graduates who want to break into cloud roles
- Entry-level cloud engineers looking to validate their foundational skills
- IT professionals transitioning from on-premise to cloud environments
- Developers or sysadmins who want to understand GCP infrastructure
You don’t need to be an expert to take this exam—just someone eager to learn and apply cloud concepts practically.
Recommended Experience Level
Google recommends around 6+ months of hands-on experience working with Google Cloud. This includes familiarity with:
- Deploying basic cloud infrastructure (VMs, storage, networking)
- Managing IAM and permissions
- Using GCP services via the Cloud Console and gcloud CLI
Even if you don’t have direct work experience, completing guided labs and projects through platforms like Google Cloud Skills Boost or Qwiklabs can prepare you well.
Career Roles It Helps With
This certification can open doors to several cloud-related roles, including:
- Associate Cloud Engineer
- Cloud Support Engineer
- DevOps Associate
- Junior Site Reliability Engineer (SRE)
- Technical Support Specialist
- Cloud Infrastructure Analyst
It’s widely recognized by employers looking for GCP talent and provides a solid credential on your resume if you’re aiming to work in startups, tech companies, or enterprise IT teams adopting Google Cloud.
Google Associate Cloud Engineer Course Outline
The Google Associate Cloud Engineer (ACE) certification tests your ability to manage cloud infrastructure effectively on the Google Cloud Platform. The exam is divided into five key domains that reflect the real-world tasks of a cloud engineer. Here’s a breakdown of each domain:
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:
- Creating one or more billing accounts (GCP Documentation: Create, modify, or close your Cloud Billing account)
- Linking projects to a billing account (GCP Documentation: Modify a project’s billing settings)
- Establishing billing budgets and alerts (GCP Documentation: Set budgets and budget alerts)
- Setting up billing exports
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:
- Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, Cloud Run, Cloud Functions) (GCP Documentation: Choosing the right compute option in GCP: a decision tree)
- Using preemptible VMs and custom machine types as appropriate (GCP Documentation: Custom Machine Types)
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:
- Differentiating load balancing options (GCP Documentation: Cloud Load Balancing overview)
- Identifying resource locations in a network for availability (GCP Documentation: Geography and regions)
- Configuring Cloud DNS (GCP Documentation: Cloud DNS )
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:
- Browsing Cloud Marketplace catalogue and viewing solution details (GCP Documentation: GOOGLE CLOUD MARKETPLACE)
- Deploying a Cloud Marketplace solution (GCP Documentation: Creating Deployments with Google Cloud Platform Marketplace)
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:
- Managing and securing objects in and between Cloud Storage buckets (GCP Documentation: Moving and renaming buckets)
- Setting object life cycle management policies for Cloud Storage buckets (GCP Documentation: Object Lifecycle Management)
- Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable) (GCP Documentation: Querying Cloud Storage data)
- Estimating costs of a BigQuery query (GCP Documentation: Estimating storage and query costs)
- Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore) (GCP Documentation: Restoring an instance)
- Reviewing job status in Cloud Dataproc, Cloud Dataflow, or BigQuery (GCP Documentation: Life of a Dataproc Job)
4.5 Managing networking resources. Tasks include:
- Adding a subnet to an existing VPC (GCP Documentation: Using VPC networks)
- Expanding a subnet to have more IP addresses (GCP Documentation: gcloud compute networks subnets expand-ip-range)
- Reserving static external or internal IP addresses (GCP Documentation: Reserving a new static external IP address)
- Working with CloudDNS, CloudNAT, Load Balancers and firewall rules
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 look at the preparatory resources.
Google Associate Cloud Engineer Preparation Guide
Passing the Google Associate Cloud Engineer (ACE) exam requires a combination of structured learning, hands-on practice, and smart revision. Below is a practical study plan divided into five key steps to guide your preparation.
a. Understand the Exam Guide
Before starting your preparation, download and read the official exam guide from Google Cloud. It outlines the domains, weightage, and expected skills for the exam. Understanding this structure helps you organize your study time and identify high-priority topics.
Link to the official exam guide:
https://cloud.google.com/certification/guides/cloud-engineer
Focus on each domain individually and make sure you can perform the tasks mentioned — not just recall facts.
b. Learning Resources
Here are some reliable resources to build your theoretical foundation:
- Google Cloud Skills Boost: The official platform with curated learning paths, skill badges, and labs designed by Google.
- Skilr: Offers exam-focused training and practice questions tailored to the ACE certification.
- YouTube Playlists: Channels like Simplilearn, Tech with Nana, and Google Cloud Platform have high-quality tutorials and walkthroughs.
- GCP Documentation & Labs: Read Google’s product documentation and use code samples to explore how services work.
These resources help you understand both “how” and “why” GCP services are used in real-world environments.
c. Hands-on Practice
Nothing beats actual experience. Set up your own sandbox to experiment:
- Create a GCP Free Tier account to access core services like Compute Engine, Cloud Storage, and Cloud Functions.
- Use Qwiklabs to complete real-world tasks, such as configuring IAM roles, deploying Kubernetes clusters, or monitoring VM instances.
- Work on small end-to-end projects like hosting a static website or deploying an app with Cloud Run to build confidence.
Focus on services you’ll likely see in the exam, especially IAM, Compute Engine, Cloud Monitoring, and Cloud Console basics.
d. Mock Exams and Practice Questions
Testing yourself regularly helps reinforce learning and identify weak areas:
- Use mock exams from Skilr.
- Google Cloud Skills Boost also offers challenge labs and skill badges that simulate exam-like scenarios.
- After each practice test, review both correct and incorrect answers. Focus more on your reasoning than memorization.
Track your progress and aim for 80% or higher consistently before scheduling the real exam.
e. Community and Forums
Join peer communities to stay motivated and informed:
- Reddit: Subreddits like r/googlecloud or r/AWSCertifications often share study tips, review notes, and success stories.
- LinkedIn Study Groups: Many certification aspirants form open groups to share learning materials and exam updates.
- Discord or Telegram: Interactive communities with active discussions, doubt-clearing sessions, and live quizzes.
Engaging with others can expose you to real questions, clarify tricky concepts, and keep you accountable.
Tips to Crack the Google Associate Cloud Engineer Exam
The Google Associate Cloud Engineer exam is designed to test practical, scenario-based knowledge—so it’s important to go beyond just reading and really build your problem-solving skills. Here are some essential tips to help you clear the exam confidently:
Focus on Hands-On Experience
The exam isn’t just theoretical. You’ll be tested on tasks you would perform in real projects. Spend time using the Google Cloud Console and the gcloud command-line tool. The more you practice deploying VMs, configuring IAM, or managing networks, the more confident you’ll feel during the test.
Understand Real-World GCP Use Cases
GCP services often have overlapping functionalities. Understanding when and why a particular service is used in real-world scenarios helps you make the right choices on the exam. For example, knowing when to use Cloud Run vs App Engine, or how billing differs between storage classes, can help eliminate wrong options.
Learn to Troubleshoot Using Cloud Console and gcloud CLI
Troubleshooting is a critical skill for any cloud engineer. The exam includes questions where you’ll have to figure out what went wrong and how to fix it—such as broken permissions, failed deployments, or missing logs. Practice navigating the Cloud Console and using commands like gcloud compute instances list or gcloud projects describe to identify issues quickly.
Manage Your Time During the Exam
You’ll have 2 hours to complete around 50–60 questions. Don’t get stuck on difficult ones. If you’re unsure, mark the question and move on. Come back later if time permits. Keeping a steady pace is key to finishing the exam without stress.
Revisit IAM, Billing, Storage Classes, and Deployment Tools
Certain topics tend to appear frequently in the exam. Make sure you’re very familiar with:
- IAM roles and permissions
- Billing account structure and budget alerts
- Cloud Storage classes and lifecycle rules
- Deployment tools like Cloud Shell, gcloud CLI, and Deployment Manager
Understanding these well gives you a major advantage, as they form the backbone of many GCP tasks.
After the Exam: What’s Next?
Passing the Google Associate Cloud Engineer (ACE) exam is a major milestone in your cloud journey. Once you’ve completed the exam, here’s what to expect and how to make the most of your achievement.
When to Expect Results and Certificate
You’ll receive your pass/fail result immediately after submitting the exam. The official certificate and detailed score report are typically available within 7–10 business days in your Google Cloud Certification account.
You’ll also receive a confirmation email once your digital credentials are ready to be claimed.
Digital Badge via Credly
After passing the exam, Google Cloud will issue you a verified digital badge through Credly, a platform used to display and validate professional certifications.
This badge can be added to:
- LinkedIn profile (under “Licenses & Certifications”)
- Email signatures
- Digital resumes or portfolios
It includes your name, the date you earned the certification, and a link that employers can verify.
Where to Showcase Your Certification
Don’t let your certification go unnoticed. Highlight it where it matters:
- LinkedIn: Share a post about your accomplishment and tag Google Cloud or relevant communities
- Resume: Add it under “Certifications” and emphasize it under technical skills
- GitHub/Portfolio: If you’ve completed hands-on projects while preparing, showcase them and mention your certification in the README
This increases visibility and makes you stand out to recruiters and hiring managers.
What’s the Next Level?
Once you’ve earned your Associate certification, consider pursuing advanced certifications that align with your career goals:
- Professional Cloud Architect
For those who want to design scalable, secure, and reliable GCP solutions at an enterprise level. - Professional Cloud DevOps Engineer
Ideal if you’re focused on automation, CI/CD pipelines, and reliability engineering. - Professional Data Engineer
If you’re leaning toward big data, machine learning, and analytics on GCP.
Each of these certifications builds on the foundational knowledge of ACE and deepens your expertise in specialized areas of cloud computing.
Final Thoughts
The Google Associate Cloud Engineer certification is a solid starting point for anyone looking to build a career in cloud computing with GCP. It proves that you can deploy, manage, and troubleshoot cloud-based solutions using real tools and industry-standard practices.
But more importantly, this certification helps you build confidence. It gives you hands-on skills that are valuable across job roles, industries, and cloud projects. Whether you’re just starting out, switching careers, or upskilling, the ACE certification acts as a launchpad toward higher-level roles and certifications in the Google Cloud ecosystem.
