The Google GCP-ACE exam preparation guide is designed to provide candidates with necessary information about the Associate Cloud Engineer exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the Google Cloud Platform - Associate Cloud Engineer (GCP-ACE) exam.
It is recommended for all the candidates to refer the GCP-ACE objectives and sample questions provided in this preparation guide. The Google Associate Cloud Engineer certification is mainly targeted to the candidates who want to build their career in Associate domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual Google Associate Cloud Engineer exam.
Google GCP-ACE Exam Summary:
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Exam Name
|
Google Associate Cloud Engineer |
| Exam Code | GCP-ACE |
| Exam Price | $125 USD |
| Duration | 120 minutes |
| Number of Questions | 50-60 multiple choice and multiple select questions |
| Passing Score | Pass / Fail (Approx 70%) |
| Recommended Training / Books | Google Cloud training |
| Schedule Exam | Google CertMetrics |
| Sample Questions | Google GCP-ACE Sample Questions |
| Recommended Practice | Google Cloud Platform - Associate Cloud Engineer (GCP-ACE) Practice Test |
Google Cloud Engineer Syllabus:
| Section | Objectives |
|---|---|
Setting up a cloud solution environment (23% of the exam) |
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| Setting up cloud projects and accounts. Considerations include: |
- Creating a resource hierarchy
- Applying organizational policies to the resource hierarchy - Granting members Identity and Access Management (IAM) roles within a project - Managing users and groups in Cloud Identity (manually and automated) - Enabling APIs within projects - Provisioning and seing up products in Google Cloud Observability - Assessing quotas and requesting increases - Setting up standalone organizations - Setting up cloud networking - Conrming availability of products in geographical locations (e.g., regional, global) - Conguring Cloud Asset Inventory and using Gemini Cloud Assist to analyze resources |
| Managing billing configuration. Considerations include: |
- Creating one or more billing accounts - Linking projects to a billing account - Establishing billing budgets and alerts - Setting up billing exports |
Planning and implementing a cloud solution (~30% of the exam) |
|
| Planning and implementing compute resources. Considerations include: |
- Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine [GKE], Cloud Run, Cloud Run functions, Knative serving)
- Launching a compute instance (e.g., availability policy, SSH keys) - Choosing the appropriate storage for Compute Engine (e.g., zonal Persistent Disk, regional Persistent Disk, Google Cloud Hyperdisk) - Creating an autoscaled managed instance group by using an instance template - Conguring OS Login - Conguring VM Manager - Using Spot VM instances and custom machine types - Installing and conguring the command-line interface (CLI) for Kubernetes (kubectl) - Deploying a GKE cluster with dierent congurations (e.g., GKE Autopilot, regional clusters, private clusters) - Deploying a containerized application to GKE - Deploying an application to serverless compute plaorms, including for the processing of Google Cloud events (e.g., Pub/Sub events, Cloud Storage object change notication events, Eventarc) |
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Planning and implementing storage and data solutions. Considerations include:
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- Choosing and deploying data products (e.g., Cloud SQL, BigQuery, Firestore, Spanner, Bigtable, AlloyDB, Dataow, Pub/Sub, Google Cloud Managed Service for Apache Kaa, Memorystore)
- Choosing and deploying storage products (e.g., Cloud Storage, Filestore, Google Cloud NetApp Volumes) and Cloud Storage options (e.g., Standard, Nearline, Coldline, Archive) - Loading data (e.g., command-line upload, load data from Cloud Storage, Storage Transfer Service) - Maintaining multi-region redundancy across data solutions |
| Planning and implementing networking resources. Considerations include: |
- Creating a VPC with subnets (e.g., custom mode VPC, Shared VPC)
- Creating and applying Cloud Next Generation Firewall (Cloud NGFW) policies with ingress and egress rules and aributes (e.g., action, source, destination, targets, protocols, ports) - Using Tags (e.g., secure Tags) and service accounts in Cloud NGFW policy rules - Establishing network connectivity (e.g., Cloud VPN, VPC Network Peering, Cloud Interconnect) Choosing and deploying load balancers - Dierentiating Network Service Tiers |
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Planning and implementing resources through infrastructure as code. Considerations include:
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- Infrastructure as code tooling (e.g., Fabric FAST, Cong Connector, Terraform, Helm)
- Planning and executing infrastructure as code deployments, including versioning, state management, and updates |
Ensuring successful operation of a cloud solution (~27% of the exam) |
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| Managing compute resources. Considerations include: |
- Remotely connecting to a Compute Engine instance
- Viewing current running Compute Engine instances - Working with snapshots and images (e.g., create, view, and delete images or snapshots; schedule a snapshot) - Viewing current running GKE cluster inventory (e.g., nodes, Pods, Services) - Conguring GKE to access Artifact Registry - Working with GKE node pools (e.g., add, edit, or remove a node pool; autoscaling node pool) - Working with Kubernetes resources (e.g., Pods, Services, StatefulSets) - Managing horizontal and vertical Pod autoscaling congurations - Managing GKE Autopilot Pod resource requests - Deploying new versions of a Cloud Run application - Adjusting application trac spliing parameters (e.g., Cloud Run, Cloud Run functions, GKE) - Conguring autoscaling for a Cloud Run application |
| Managing storage and data solutions. Considerations include: |
- Managing and securing objects in Cloud Storage buckets
- Setting object lifecycle management policies for Cloud Storage buckets - Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Bigtable, Spanner, Firestore, AlloyDB) - Estimating costs of data storage resources - Backing up and restoring database instances (e.g., Cloud SQL, Firestore, Spanner, AlloyDB, Bigtable) - Reviewing job status (e.g., Dataow, BigQuery) - Using Database Center to manage the Google Cloud database fleet |
| Managing networking resources. Considerations include: |
- Adding a subnet to an existing VPC
- Expanding a subnet to have more IP addresses - Reserving static external or internal IP addresses - Adding custom static routes in a VPC - Working with Cloud DNS and Cloud NAT |
| Monitoring and logging. Considerations include: |
- Creating Cloud Monitoring alerts based on resource metrics
- Creating and ingesting Cloud Monitoring custom metrics (e.g., from applications or logs) - Exporting logs to external systems (e.g., on-premises, BigQuery) - Conguring log buckets, log analytics, and log routers - Viewing and ltering logs in Cloud Logging - Viewing specic log message details in Cloud Logging - Using cloud diagnostics to research an application issue (e.g., Cloud Trace, Cloud Proler, Query Insights, index advisor) - Viewing the Personalized Service Health dashboard - Conguring and deploying Ops Agent
- Deploying Google Cloud Managed Service for Prometheus
- Conguring audit logs - Using Gemini Cloud Assist for Cloud Monitoring - Using Active Assist to optimize resource utilization |
Configuring access and security (17.5% of the exam) |
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| Managing Identity and Access Management (IAM). Considerations include: |
- Viewing and creating IAM policies - Managing the various role types and defining custom IAM roles (e.g., basic, predefined, custom) |
| Managing service accounts. Considerations include: |
- Creating service accounts - Using service accounts in IAM policies with minimum permissions - Assigning service accounts to resources - Managing IAM of a service account - Managing service account impersonation - Creating and managing short-lived service account credentials - Using a Google Cloud service account with a GKE application |