With the increasing adoption of cloud computing, cloud certifications have become a valuable asset for IT professionals seeking to advance their careers. The Google Professional Cloud Developer Exam is one such certification that validates an individual’s expertise in developing and managing cloud applications using Google Cloud Platform services. However, many individuals may wonder about the difficulty level of the exam and whether it is worth pursuing.
In this blog post, we will discuss the difficulty level of the Google Professional Cloud Developer Exam, including the factors that affect exam difficulty, a comparison with other certification exams, and testimonials from previous test-takers. We will also provide tips and strategies for preparing for the exam and achieving success. By the end of this post, you should have a good understanding of the difficulty level of the Google Professional Cloud Developer Exam and whether it is the right certification for you.
About Google Professional Cloud Developer
Google Professional Cloud Developer Exam is a certification exam offered by Google Cloud that validates the skills of individuals in designing, developing, and managing cloud solutions using Google Cloud technologies. The exam measures an individual’s ability to develop highly scalable and reliable applications using Google Cloud services, APIs, and best practices. The certification is ideal for developers who are looking to advance their career in cloud computing and demonstrate their expertise in building and managing cloud applications on the Google Cloud Platform.
Knowing how difficult the Google Professional Cloud Developer Exam is can help individuals prepare better for the exam. It gives them an idea of what to expect in terms of the level of complexity of the questions, the depth of knowledge required, and the time required to complete the exam. Understanding the difficulty level of the exam can also help individuals plan their study schedule and allocate sufficient time to prepare adequately. Additionally, knowing the difficulty level of the exam can help individuals manage their expectations and reduce anxiety and stress associated with taking the exam.
Glossary for Google Professional Cloud Developer (GCP) Terminology
Here’s a glossary of some key terms and concepts related to the Google Cloud Platform (GCP) and specifically, the Google Professional Cloud Developer certification:
- Google Cloud Platform (GCP): A suite of cloud computing services provided by Google.
- Compute Engine: A service in GCP that lets users create and run virtual machines (VMs) on Google’s infrastructure.
- App Engine: A Platform as a Service (PaaS) offering in GCP that lets users build and deploy scalable web applications.
- Kubernetes Engine: A managed service in GCP for deploying, managing, and scaling containerized applications.
- Cloud Storage: A service in GCP that provides scalable and durable object storage.
- BigQuery: A fully-managed, serverless data warehouse in GCP that lets users analyze large datasets using SQL-like queries.
- Cloud Pub/Sub: A messaging service in GCP that lets users exchange messages between applications and services.
- Cloud Datastore: A NoSQL document database in GCP that provides automatic scaling and high availability.
- Cloud SQL: A fully-managed relational database service in GCP that supports MySQL, PostgreSQL, and SQL Server.
- Cloud Spanner: A fully-managed relational database service in GCP that provides horizontal scalability and strong consistency.
- Cloud Functions: A serverless compute service in GCP that lets users run code in response to events.
- Cloud Build: A continuous integration/continuous deployment (CI/CD) service in GCP that automates the building and testing of code.
- Identity and Access Management (IAM): A service in GCP that lets users manage access to resources and services.
- Service accounts: Identity and access management entities that represent applications or services, rather than users.
- Google Cloud SDK: A set of command-line tools for interacting with GCP services and resources.
Exam preparation resources for Google Professional Cloud Developer Exam
To prepare for the Google Professional Cloud Developer Exam, it is essential to have a thorough understanding of Google Cloud Platform and its various services. Google offers a variety of study resources that can help candidates prepare for the exam, including:
- Exam Guide: The Google Professional Cloud Developer Exam Guide provides an overview of the exam format, topics covered, and the skills tested. It is a must-read for anyone preparing for the exam. You can find it here: https://cloud.google.com/certification/cloud-developer
- Sample Questions: Google provides sample questions to give you an idea of the type of questions you can expect on the exam. You can find them here: https://cloud.google.com/certification/sample-questions/cloud-developer
- Training Courses: Google offers several training courses to help you prepare for the exam. You can choose from instructor-led courses or self-paced online courses. Here are some links:
- Google Cloud Fundamentals: Core Infrastructure: https://cloud.google.com/training/course/google-cloud-fundamentals-core-infrastructure
- Developing Applications with Google Cloud: https://cloud.google.com/training/course/developing-apps-gcp-self-paced
- Google Cloud Certification – Professional Cloud Developer Exam Prep: https://cloud.google.com/training/certification/professional-cloud-developer
- Practice Exam: Google provides a practice exam that simulates the actual exam environment. This is a great way to gauge your readiness for the exam. You can find it here: https://cloud.google.com/certification/practice-exam/cloud-developer
- Google Cloud Documentation: Google Cloud documentation is an essential resource for any cloud developer. It provides detailed information on Google Cloud products, services, and APIs. You can access it here: https://cloud.google.com/docs
How difficult is Google Professional Cloud Developer Exam?
The difficulty level of the Google Professional Cloud Developer Exam can vary based on several factors, including:
- Candidate’s experience: The candidate’s level of experience with Google Cloud Platform and developing cloud applications can impact the difficulty level of the exam.
- Covered topics: The exam covers a broad range of topics, and some topics may be more challenging than others.
- Exam format: The exam format, which includes multiple-choice and scenario-based questions, can impact the difficulty level of the exam.
- Time pressure: The exam duration is two hours, and candidates must complete 50 questions in that time. Time pressure can increase the difficulty level of the exam.
The difficulty level of the Google Professional Cloud Developer Exam is comparable to other cloud certification exams, such as AWS Certified Developer Associate and Microsoft Certified: Azure Developer Associate. However, the level of difficulty can vary based on the candidate’s experience and knowledge of Google Cloud Platform and its various services.
According to testimonials from previous test-takers, the Google Professional Cloud Developer Exam is challenging but achievable with proper preparation. Many test-takers recommend gaining hands-on experience with Google Cloud Platform services, using practice exams, and studying the official exam guide and Google Cloud documentation. Some test-takers also suggest allocating sufficient time for studying and taking regular breaks during the exam to manage time pressure.
Who should take the GCP Cloud Developer exam?
The Google Professional Cloud Developer Exam is designed for individuals who have experience in developing and managing cloud applications using Google Cloud technologies. It is suitable for developers, software engineers, and architects who have a good understanding of software development, cloud computing concepts, and experience with the Google Cloud Platform.
More specifically, the exam is intended for individuals who:
- Have experience developing applications using Google Cloud Platform services, such as App Engine, Compute Engine, Kubernetes Engine, and Cloud Functions.
- Are proficient in one or more programming languages, such as Python, Java, or Node.js.
- Have experience integrating Google Cloud services with other third-party services and tools.
- Are familiar with developing applications using cloud-native architectures, such as microservices and serverless computing.
- Have experience implementing security and compliance best practices in cloud-based environments.
Course Outline
The Google Professional Cloud Developer exam outline covers the following topics:
Topic 1: Designing highly scalable, available, and reliable cloud-native applications (33%)
1.1 Designing high-performing applications and APIs. Considerations include:
- Microservices (Google Documentation: Microservices Architecture on Google App Engine, Migrating a monolithic application to microservices on Google Kubernetes Engine)
- Choosing the appropriate platform based on the use case and requirements (e.g., IaaS [infrastructure as a service], CaaS [container as a service], PaaS [platform as a service], FaaS [function as a service])
- Application modernization (e.g., containerization)
- Understanding how Google Cloud services are geographically distributed (e.g., latency, regional services, zonal services) (Google Documentation: Geography and regions, Regions and Zones)
- User session management (Google Documentation: Handling sessions with Firestore, Managing sessions with external identities
- Caching solutions (Google Documentation: Memorystore)
- HTTP REST versus gRPC (Google Remote Procedure Call) (Google Documentation: gRPC vs REST)
- Incorporating Service Control capabilities offered by API services (e.g. Apigee) (Google Documentation: What is Apigee?)
- Loosely coupled asynchronous applications (e.g., Apache Kafka, Pub/Sub, Eventarc) (Google Documentation: Connect Pub/Sub to Apache Kafka, Eventarc)
- Instrumenting code to produce metrics, logs, and traces (Google Documentation: Instrument for Cloud Trace)
- Cost optimization and resource optimization
- Graceful handling of errors, disasters, and scaling events (Google Documentation: Data deletion on Google Cloud)
1.2 Designing secure applications. Considerations include:
- Implementing data lifecycle and residency requirements for applicable regulations
- Security mechanisms that protect services and resources (Google Documentation: Google Infrastructure Security Design Overview)
- Security mechanisms that identify vulnerabilities and protect services and resources (e.g., Identity Aware Proxy [IAP], Web Security Scanner) (Google Documentation: Setting up custom scans using Web Security Scanner)
- Security mechanisms that secure/scan application binaries, dependencies, and manifests (e.g., Container Analysis) (Google Documentation: Container scanning overview)
- Storing, accessing, and rotating application secrets and encryption keys (e.g., Secret Manager, Cloud Key Management Service) (Google Documentation: Enable customer-managed encryption keys for Secret Manager)
- Authenticating to Google Cloud services (e.g., application default credentials, JSON Web Token [JWT], OAuth 2.0) (Google Documentation: Authentication methods at Google)
- End-user account management and authentication using Identity Platform
- Identity and Access Management (IAM) roles for users, groups, and service accounts (Google Documentation: IAM Overview)
- Securing service-to-service communications (e.g., service mesh, Kubernetes Network Policies, and Kubernetes namespaces) (Google Documentation: Kubernetes best practices: Organizing with Namespaces)
- Running services with keyless and least privileged access (e.g., Workload Identity, Workload identity federation) (Google Documentation: Workload Identity)
- Certificate-based authentication (e.g., SSL, mTLS) (Google Documentation: SSL certificates overview, Mutual TLS authentication)
- Supply-chain Levels for Software Artifacts (SLSA)
1.3 Choosing storage options for application data. Considerations include:
- Time-limited access to objects (Google Documentation: Overview of access control)
- Data retention requirements (Google Documentation: Retention policies and retention policy locks)
- Structured versus unstructured data (e.g., SQL versus NoSQL)
- Strong versus eventual consistency (Google Documentation: Balancing Strong and Eventual Consistency with Datastore)
- Data volume (Google Documentation: Storage options)
- Data access patterns
- Online transaction processing (OLTP) versus data warehousing
Topic 2: Building and testing applications (26%)
2.1 Setting up your local development environment. Considerations include:
- Emulating Google Cloud services for local application development (Google Documentation: Using the Local Development Server)
- Using the Google Cloud console, Google Cloud SDK, Cloud Shell, and Cloud Workstations
- Using developer tooling (e.g., common IDEs, Cloud Code, Skaffold) (Google Documentation: Kubernetes development, simplified—Skaffold is now GA)
- Authenticating to Google Cloud services (e.g., Cloud SQL Auth proxy, AlloyDB Auth proxy)
2.2 Building. Considerations include:
- Source control management (Google Documentation: Cloud Source Repositories
- Creating secure container images from code (Google Documentation: Building Containers, Quickstart for Container Registry)
- Developing a continuous integration pipeline using services (e.g., Cloud Build, Artifact Registry) that construct deployment artifacts (Google Documentation: CI/CD on Google Cloud, Quickstart for Container Registry, Cloud Build)
- Code and test build optimization
2.3 Testing. Considerations include:
- Unit testing (Google Documentation: Local Unit Testing for Python 2, Testing Overview)
- Integration testing including the use of emulators
- Performance testing (Google Documentation: Testing Overview, Distributed load testing using Google Kubernetes Engine)
- Load testing (Google Documentation: Distributed load testing using Google Kubernetes Engine)
- Failure testing/chaos engineering
Topic 3: Deploying applications (19%)
3.1 Adopting appropriate feature rollout strategies. Considerations include:
- A/B testing (Google Documentation: Monitor and analyze A/B experiments)
- Feature flags
- Backward compatibility (Google Documentation: Compatibility)
- Versioning APIs (e.g., Apigee) (Google Documentation: What is Apigee API hub?)
3.2 Deploying applications to a serverless computing environment. Considerations include:
- Deploying applications from source code (Google Documentation: Deploy from source code)
- Using triggers to invoke functions (Google Documentation: Cloud Functions triggers)
- Configuring event receivers (e.g., Eventarc, Pub/Sub) (Google Documentation: Receive events using Pub/Sub messages (gcloud CLI))
- Exposing and securing application APIs (e.g., Apigee) (Google Documentation: Overview of Advanced API Security)
3.3 Deploying applications and services to Google Kubernetes Engine (GKE). Considerations include:
- Deploying a containerized application to GKE (Google Documentation: Deploying a containerized web application)
- Integrating Kubernetes role-based access control (RBAC) with IAM
- Defining workload specifications (e.g., resource requirements) (Google Documentation: Workload Identity)
- Building a container image using Cloud Build (Google Documentation: Building container images)
Topic 4: Integrating an application with Google Cloud services (22%)
4.1 Integrating an application with data and storage services. Considerations include:
- Managing connections to data stores (e.g., Cloud SQL, Cloud Spanner, Firestore, Bigtable, Cloud Storage)
- Reading/writing data to or from various datastores
- Writing an application that publishes/consumes data asynchronously (e.g., from Pub/Sub or streaming data sources) (Google Documentation: Writing and Responding to Pub/Sub Messages, Pub/Sub)
- Orchestrate application services with Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler
4.2 Integrating an application with Google Cloud APIs. Considerations include:
- Enabling Google Cloud services
- Making API calls using supported options (e.g., Cloud Client Library, REST API or gRPC, APIs Explorer) taking into consideration:
- Batching requests (Google Documentation: Batching requests)
- Restricting return data (Google Documentation: Working with Quotas, Usage limits)
- Paginating results (Google Documentation: Paging through table data, Paginating data with query cursors)
- Caching results (Google Documentation: Using cached query results)
- Error handling (e.g., exponential backoff) (Google Documentation: Truncated exponential backoff)
- Using service accounts to make Cloud API calls (Google Documentation: Service accounts)
- Integrating with Google Cloud’s operations suite
You can get more information about Google Professional Cloud Developer Examination tutorial!
Download the Exam Guide
Google Official Exam Guide comprises of all the domains and topics of the examination. So, make sure to download the exam guide. In this exam guide, you’ll be able to understand each and every topic in detail. This will help you prepare each domain with every minute detail in accordance with the exam
Practical experience with Hands-on labs
The next and most important stage is getting hands-on experience. The GCP Cloud Developer exam’s scenario-based questions call for prior practical experience. The free GCP tier is accessible to candidates who sign up for the free GCP goods, services, and technologies trials. The USD 300 in free credit can also be used to get practical experience. One can even sign up for paid hands-on training to gain deeper knowledge.
Join a Community
Maintaining connections with others who share your goals is crucial. You will not only be able to get your questions answered, but you will also be able to learn more about the Google Professional Cloud Developer test. Join some study groups so you may talk about the ideas with others who share the same objectives. The applicant will follow this throughout their preparation.
Evaluate with Practice Test
When you are done with all your preparation it is always advisable to go for some mock test before you plan to sit for the actual examination. This will not only boost your confidence but will also make you aware of the weak portions in your preparation and which require some more focus and hard work. Taking real-time practice tests will also release you from exam fear and exam pressure. Start your learning with Google Professional Cloud Developer Free Practice Test now!
Tips for studying effectively
Studying for the Google Professional Cloud Developer Exam can be challenging, but with the right approach, it is possible to succeed. Some tips for studying effectively include:
- Create a study plan: Create a study plan that includes a schedule of what topics to study and when to study them. This will help ensure that you cover all the necessary topics before the exam.
- Use practice exams: Use practice exams to identify knowledge gaps and areas that require more attention.
- Hands-on experience: Gain hands-on experience with the Google Cloud Platform by creating and deploying applications using various services.
- Join study groups: Join online study groups or communities to discuss topics and share knowledge with other exam candidates.
- Take breaks: Taking regular breaks during study sessions can help improve concentration and retention of information.
Final Words
The difficulty level of Google Professional Cloud Developer Exam can be challenging, but with the right preparation and experience, it is achievable. Candidates who have a good understanding of cloud computing concepts, experience with Google Cloud Platform services, and proficiency in one or more programming languages may find the exam less challenging than those who lack these skills.
It is essential to allocate sufficient time for studying, gain hands-on experience with Google Cloud Platform services, and use practice exams to identify knowledge gaps and areas that require more attention. Candidates should also be familiar with the exam format, which includes multiple-choice and scenario-based questions and be prepared to manage time pressure during the exam.
Overall, the Google Professional Cloud Developer Exam is an excellent way for individuals to validate their expertise in developing and managing cloud applications on the Google Cloud Platform and advance their careers in cloud computing.
