GCP-GC-REP Practice Test Overview: Conquer Your Exam
This practice test will help you ace the Google Cloud Certified - Professional Cloud Architect exam. It’s designed to mimic the real thing, so you’ll feel confident going in.
Total Questions: 100 (This number may vary slightly depending on the version of the practice test)
Target Job Roles: This test is ideal for aspiring and current:
- Cloud Architects: Designing, building, and managing cloud infrastructure.
- Cloud Engineers: Implementing and maintaining cloud-based solutions.
- DevOps Engineers: Bridging the gap between development and operations.
- System Administrators: Managing and monitoring cloud systems. Think of it as a serious challenge – and a useful one!
Language: English
Key Test Coverage Areas:
This practice test covers the core competencies assessed in the GCP-GC-REP exam. We've broken it down for easier preparation:
I. Core Infrastructure & Networking:
- Compute Engine: Instance types, networking, scaling, and cost optimization. Think about choosing the right instance size for your needs – it's like picking the right car for your journey!
- Example question: What are the key differences between a
n1-standard-1 and a c2-standard-2 VM instance?
- Virtual Private Cloud (VPC) Networking: Subnets, firewalls, routing, VPN, and peering. Imagine your VPC as your own private network within Google Cloud – secure and controlled.
- Example question: How would you configure a firewall rule to allow only SSH traffic to your web servers?
- Cloud Load Balancing: Different types of load balancers and their use cases. Think of it as distributing traffic evenly, like a skilled air traffic controller guiding planes to land.
- Example question: When would you use a regional vs. a global HTTP(S) load balancer?
- Cloud DNS: Managing DNS zones and records. This is the foundational layer for directing network traffic; like the address book for your cloud infrastructure.
II. Data Storage & Databases:
- Cloud Storage: Object storage, lifecycle management, and access control. Think of it as your cloud-based file cabinet, but much more powerful and scalable.
- Example question: What are the different storage classes available in Cloud Storage and their cost implications?
- Cloud SQL: Relational database management, instance configurations, and backups. This is where you store structured data, similar to a traditional database server, but in the cloud.
- Example question: How do you perform a failover on a Cloud SQL instance?
- Cloud Spanner: Globally distributed, scalable database. Imagine a database that's always available, no matter where your users are located.
- Bigtable: NoSQL database for large-scale analytical workloads. Perfect for storing and querying massive datasets, like everything you'd find on a website like YouTube.
III. Data Processing & Analytics:
- Dataflow: Building and managing data pipelines. Think of it as an assembly line for processing data, enabling seamless and automated movement of information.
- Example question: What are the different Dataflow runners and their characteristics?
- Dataproc: Running Spark and Hadoop clusters on GCP. This is your platform for massive data processing using industry-standard tools.
- BigQuery: Data warehousing and analytics. Think of it as your powerful data analysis tool – querying terabytes of data in seconds.
IV. Security & Operations:
- Identity and Access Management (IAM): Roles, permissions, and security best practices. This is crucial for controlling who has access to your resources – think of it as the key to your cloud kingdom!
- Cloud Key Management Service (KMS): Encrypting and managing cryptographic keys. This layer ensures data confidentiality and protects sensitive information.
- Monitoring & Logging: Using Cloud Monitoring and Cloud Logging to track and troubleshoot issues. Monitoring is like having your watchful eyes on your systems ensuring everything runs smoothly.
- I remember once misconfiguring a firewall, and losing access to a server. Cloud monitoring alerted me to this instantly, saving me tons of troubleshooting time.
V. Deployment & Management:
- Kubernetes Engine (GKE): Container orchestration. This is like a conductor leading an orchestra of containers, making sure everything works in harmony.
- Cloud Functions: Serverless computing. Think of it as executing code without worrying about managing servers.
- Deployment Manager: Infrastructure as code. This enables you to automate deployment and management of your infrastructure.
This practice test provides a comprehensive review of these key areas. Good luck with your preparation! Remember, consistent study and practice are key to success.
