Are you getting started with Google Cloud Platform or gearing up for a GCP certification in 2025? Whether you’re a developer, architect, data engineer, or cloud enthusiast, navigating GCP’s vast services can feel overwhelming. That’s exactly why we created this updated and simplified GCP Cheat Sheet for 2025, to help you grasp key concepts, memorize services faster, and stay exam-ready. No fluff. Just clean, crisp, and practical knowledge you can use in real-world projects or on your certification path.
From Compute Engine vs. App Engine, IAM roles, Cloud Storage tiers, to BigQuery, Pub/Sub, and Cloud Functions — this cheat sheet covers all the essentials you need to understand Google Cloud, fast. Whether you are preparing for the Associate Cloud Engineer, Professional Data Engineer, or simply trying to compare GCP with AWS or Azure, this guide will save you time and boost your confidence.
Google Cloud Platform Glossary
Here are some terms and definitions related to Google Cloud Platform (GCP):
- Virtual machine (VM): A virtual computer you can use on a real computer to run different things at the same time.
- Platform-as-a-Service (PaaS): When you use a cloud computer, they let you use their platform to build and put out apps without worrying about the computer stuff underneath.
- Infrastructure-as-a-Service (IaaS): When you use a cloud computer, they give you virtual computers, storage, and networks that you can use and control.
- Kubernetes: An open-source tool that helps make sure apps in boxes work well by handling how they start, grow, and are taken care of.
- Object storage: A data storage architecture that manages data as objects, rather than as blocks or files, and provides scalable, distributed storage for unstructured data.
- Database-as-a-Service (DBaaS): When you use a cloud computer, they give you a managed database so you don’t need to worry about the computer part.
- Data warehouse: A big computer place to store lots of information from many places, to use it for understanding and reporting.
- Serverless computing: When you use a cloud computer, they take care of the computer resources and give you what you need, when you need it.
- Cloud computing: Getting computer resources like storage and programs on the internet from anywhere.
- Cloud storage: Saving your stuff on other computers far away, so you can get it from anywhere with the internet.
- Big data: Really huge amounts of information that need special things to work with them.
- Machine learning: A kind of computer AI that lets them learn and get better by themselves, without someone telling them exactly what to do.
Google Cloud Platform Exam Guide
Here are some official Google Cloud Platform (GCP) exam resources:
- Google Cloud certification program: https://cloud.google.com/certification/
- Learn Google Cloud training: https://cloud.google.com/training/
- Google Cloud documentation: https://cloud.google.com/docs/
- Learn Google Cloud tutorials: https://cloud.google.com/docs/tutorials/
- Google Cloud Qwiklabs: https://www.qwiklabs.com/catalog?locale=en
- Google Cloud community: https://cloud.google.com/community/
- Learn Google Cloud blog: https://cloud.google.com/blog/
- Google Cloud YouTube channel: https://www.youtube.com/user/googlecloudplatform
- Learn Google Cloud podcasts: https://www.gcppodcast.com/
- Google Cloud case studies: https://cloud.google.com/customers/case-studies/
Google Cloud Platform Exam Tips and Tricks
Here are some tips and tricks to help you prepare for a Google Cloud Platform (GCP) certification exam:
- Review the exam guide: The exam guide provides a detailed overview of the exam structure, content, and objectives. It will help you understand what topics you need to focus on, what skills you need to demonstrate, and what level of understanding is expected.
- Take advantage of the official study resources: Google provides a range of official study resources, including training courses, documentation, tutorials, and hands-on labs. Use these resources to familiarize yourself with GCP services, concepts, and best practices.
- Practice with Qwiklabs: Qwiklabs provides access to interactive, hands-on labs that simulate real-world scenarios using GCP services. Practicing with Qwiklabs will help you gain practical experience with GCP and prepare you for the types of tasks and challenges you may encounter on the exam.
- Join the GCP community: Joining the GCP community will give you access to a network of experts and peers who can help you with questions, challenges, and study tips. Participate in forums, attend events, and connect with other learners to build your knowledge and confidence.
- Take practice exams: Google gives you practice tests that look and feel like the real test. These tests can help you check how ready you are, find out what you don’t know yet, and understand how the test works.
- Manage your time: The GCP certification exams are timed, so it’s important to manage your time effectively. Plan your exam strategy, allocate time for each question, and avoid spending too much time on difficult questions.
- Read the questions carefully: Exam questions can be tricky and require close attention to detail. Read the questions carefully, and make sure you understand what is being asked before answering.
Key Advantages of Google Cloud Platform:
Google Cloud Platform (GCP) meets these requirements. So, let’s take a brief reflection on the benefits of GCP can help you form the basis of reasons to adopt the Google Cloud Platform.
- Higher Productivity owing to Quick Access to Innovation: Firstly, Google’s systems are capable of delivering updates efficiently and on a weekly basis.
- Less Disruption When Users Adopt New Functionality: Secondly, it involves fewer batches of change, and delivers manageable improvements in a continuous stream.
- Employees Can Work from Anywhere: Subsequently, GCP offers massive advantages in the laps of its employees.
- Google Cloud Allows Quick Collaboration: Then, Google users can easily get to their projects and data at once, because everything is kept in the cloud, not on their own computers.
- Google’s Investments in Security Protect Customers: In addition, Google hires leading security experts, thereby providing customers benefits including process-based and physical security investments.
- Fewer Data stored on Vulnerable Devices: Plus, only a little bit of data is kept on computers, and that’s good because those computers could be unsafe once a person is done using internet apps on the cloud.
- Control and Flexibility Available to Users: Further, users have control over technology and have ownership over their data in Google apps.
Google Cloud Platform: Products and Services
Here are some of the key products and services offered by GCP:
Compute
- GCP provides several compute options, including virtual machines (VMs), containers, and serverless computing. The key compute products are:
- Compute Engine: Provides virtual machines (VMs) that can be customized with different operating systems and configurations.
- Kubernetes Engine: A managed service for running containerized applications on Kubernetes.
- App Engine: A fully-managed platform for building and deploying web and mobile applications.
- Cloud Functions: A serverless computing platform for running event-driven functions.
Storage
- GCP provides several options for storing data, including:
- Cloud Storage: A scalable and durable object storage service for unstructured data.
- Understanding Cloud SQL: A fully-managed relational database service for MySQL and PostgreSQL.
- Cloud Bigtable: A NoSQL database service for handling large amounts of structured data.
- Cloud Spanner: A big database that’s all around the world, used for keeping track of lots of transactions.
Networking
- GCP provides several networking options to connect your cloud resources to the internet and other GCP resources. Some of the key networking products include:
- Virtual Private Cloud (VPC): A network of your own virtual machines (VMs) in the cloud.
- Cloud Load Balancing: A managed service for distributing traffic across multiple instances and regions.
- Understanding Cloud CDN: A content delivery network for delivering content to users around the world.
- Cloud Interconnect: A service for connecting your on-premises data center to GCP.
Big Data and Analytics
- GCP offers several big data and analytics products that can be use to process and analyze large datasets, including:
- BigQuery: A serverless, fully-managed data warehouse service for analyzing large datasets.
- Cloud Dataflow: A fully-managed service for processing data in real-time or batch mode.
- Understanding Cloud Dataproc: A fully-managed service for running Apache Hadoop and Spark clusters.
- Cloud Pub/Sub: A messaging service for exchanging data between applications.
AI and Machine Learning
- GCP provides several AI and machine learning products that can be use to build intelligent applications, including:
- Cloud AI Platform: A fully-managed platform for building, deploying, and managing machine learning models.
- Cloud AutoML: A set of tools that let people create special computer models to learn things, and they don’t need to write any code.
- Understanding Cloud Vision API: A service for analyzing images and detecting objects and text.
- Cloud Natural Language API: A service for analyzing text and extracting insights.
These are just some of the key products and services offered by GCP. GCP also provides many other products and services for security, identity and access management, developer tools, and more.
That’s exactly why we’ve created this updated and simplified GCP Cheat Sheet for 2025—to help you:
✔ Grasp key concepts quickly
✔ Memorize essential services
✔ Stay exam-ready (for Associate Cloud Engineer, Professional Data Engineer, etc.)
✔ Compare GCP with AWS & Azure
No fluff—just clean, crisp, and practical knowledge for real-world projects and certifications.
Core GCP Services Overview (2025)
1. Compute Services
| Service | Best For | Key Feature |
|---|---|---|
| Compute Engine | VMs (IaaS) | Customizable, scalable virtual machines |
| App Engine | PaaS (Web Apps) | Fully managed, auto-scaling |
| Kubernetes Engine (GKE) | Containers | Managed Kubernetes clusters |
| Cloud Run | Serverless Containers | Auto-scaling, pay-per-use |
| Cloud Functions | Event-driven serverless | Small functions, event triggers |
When to Use?
- Compute Engine → Full control over VMs
- App Engine → No infrastructure management
- GKE → Microservices & container orchestration
- Cloud Run/Functions → Event-driven, serverless workloads
2. Storage & Database Services
Cloud Storage (Object Storage)
| Storage Class | Use Case |
|---|---|
| Standard | Frequently accessed data (hot storage) |
| Nearline | Accessed once a month (cool storage) |
| Coldline | Accessed once a quarter (cold storage) |
| Archive | Rarely accessed (lowest cost) |
Databases
| Service | Type | Best For |
|---|---|---|
| Cloud SQL | Managed SQL | MySQL, PostgreSQL, SQL Server |
| Cloud Spanner | Globally distributed SQL | High scalability, ACID transactions |
| Firestore | NoSQL (Document DB) | Real-time apps, mobile backends |
| Bigtable | NoSQL (Wide-column) | High-throughput analytics (e.g., IoT, Ads) |
| Memorystore | In-memory DB | Redis & Memcached caching |
When to Use?
- Cloud SQL → Traditional relational workloads
- Spanner → Global-scale SQL with strong consistency
- Firestore → Real-time, document-based apps
- Bigtable → High-speed analytics (like Hadoop/HBase)
3. Networking
| Service | Purpose |
|---|---|
| VPC (Virtual Private Cloud) | Isolated cloud network |
| Cloud Load Balancing | Distribute traffic across instances |
| Cloud CDN | Content delivery network (fast caching) |
| Cloud Interconnect | Dedicated connection to GCP |
| Cloud NAT | Outbound Internet for private VMs |
✅ Key Concepts:
- Subnets → Regional (unlike AWS’s AZ-specific)
- Firewall Rules → Stateful (allow/deny traffic)
4. Big Data & AI/ML
Big Data Services
| Service | Use Case |
|---|---|
| BigQuery | Serverless data warehouse (SQL analytics) |
| Pub/Sub | Real-time messaging (event streaming) |
| Dataflow | Stream & batch processing (Apache Beam) |
| Dataproc | Managed Hadoop/Spark |
| Looker (BI) | Business intelligence & dashboards |
AI/ML Services
| Service | Purpose |
|---|---|
| Vertex AI | Unified ML platform (AutoML, custom models) |
| Vision AI | Image & video analysis |
| Natural Language API | Text sentiment/entity analysis |
| Speech-to-Text | Convert audio to text |
| Recommendations AI | Personalized product recommendations |
When to Use?
- BigQuery → Fast SQL analytics on petabytes
- Pub/Sub → Event-driven architectures (like Kafka)
- Vertex AI → Build, train, and deploy ML models
5. Security & Identity (IAM)
IAM (Identity & Access Management)
- Roles:
- Viewer → Read-only
- Editor → Edit resources (but not manage access)
- Owner → Full control + manage roles
- Custom Roles → Fine-grained permissions
- Principals: Users, Service Accounts, Google Groups
Security Tools
| Service | Purpose |
|---|---|
| Cloud KMS | Key management (encryption) |
| Secret Manager | Store API keys, passwords securely |
| Security Command Center | Threat detection & compliance |
Best Practices:
- Least privilege principle → Grant minimal necessary access
- Service accounts → For apps (not human users)
GCP vs. AWS vs. Azure (Quick Comparison)
| Service | GCP | AWS | Azure |
|---|---|---|---|
| Compute | Compute Engine | EC2 | Virtual Machines |
| Serverless | Cloud Functions | Lambda | Azure Functions |
| Kubernetes | GKE | EKS | AKS |
| Object Storage | Cloud Storage | S3 | Blob Storage |
| Data Warehouse | BigQuery | Redshift | Synapse Analytics |
🔹 GCP Certification Path (2025)
- Associate Cloud Engineer → Entry-level, hands-on GCP skills
- Professional Cloud Architect → Design scalable GCP solutions
- Professional Data Engineer → Big data & ML on GCP
- Professional DevOps Engineer → CI/CD, automation
Focus on hands-on practice (Qwiklabs, Google Cloud Skills Boost).
Final Thoughts
To conclude, the above-mentioned list is a comprehensive rundown when it comes to Google Cloud Platform services. It not only lists every Google Cloud product but pulls off the amazing feat of describing each of them in four words or less! If you’re pretty well verse in GCP, it’s an invaluable resource, and if you’re just finding your way around, it makes for a great look down the rabbit hole.
Stand out from the crowd with advanced learning skills and expert tutorials on Google Cloud Platform. Prepare and become a Certified Google Cloud Professional Now!
