For more than a decade, I have been using Google’s infrastructure, including App Engine, Cloud Storage, Firebase, GKE, and others. Despite my extensive experience with these tools and while architecting my own startup or consulting others, I still felt there were some knowledge gaps as it is a huge eco system. To bridge these gaps and get a complete understanding, I am preparing to become a certified Google Cloud engineer. Part of this journey is about gaining a deep understanding of the various tech stacks that Google Cloud offers and knowing the right scenarios to use each one effectively.
Google Cloud provides an array of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) products to meet different application and infrastructure needs. Let’s break down the main options:
1. Google App Engine (PaaS)
Google App Engine is a fully managed platform that lets you build and deploy applications without worrying about the underlying infrastructure. It handles scaling automatically based on traffic, so developers can focus on writing code.
• Pros: Great for rapid deployment, fully managed, auto-scaling.
• Cons: Limited control over infrastructure. If you need specific versions of runtimes, it may not always be available.
• Use Case: App Engine is perfect for deploying web applications and APIs with minimal operational overhead. For example, building a multi-language blog or a simple e-commerce platform.
2. Google Cloud Run (PaaS)
Cloud Run allows you to run stateless containers that are HTTP-triggered. It’s built on Knative and abstracts away infrastructure, making it easy to deploy applications in a serverless environment.
• Pros: Container support, scalability, fully managed.
• Cons: Slightly more complex setup compared to App Engine.
• Use Case: Great for teams already using Docker or container-based workflows. Ideal for deploying small microservices or a backend service that processes user data.
3. Google Cloud Functions (FaaS)
Cloud Functions is Google’s Function-as-a-Service offering, allowing you to deploy small units of code triggered by HTTP requests or cloud events. It is fully serverless and scales automatically.
• Pros: Cost-efficient for infrequent tasks, event-driven architecture.
• Cons: Limited run time and stateless execution. Not ideal for long-running jobs.
• Use Case: Perfect for lightweight backend operations like data transformations, webhook handling, and microservices that execute on demand. Or in other words: a lightweight script you want to run somewhere, but don’t want to deploy a full AppEngine instance.
Example #1: Real-time File Processing
Suppose you have a website that allows users to upload images. You want to generate a thumbnail every time a new image is uploaded. A Google Cloud Function can be triggered when a new file is uploaded to a specific Cloud Storage bucket. It will then automatically generate and store a thumbnail of the uploaded image.
• Trigger: File upload to a Google Cloud Storage bucket.
• Use Case: Automating image processing, such as resizing or watermarking.
Example #2: Security Automation
If you want to enhance security by auditing your cloud resources, Google Cloud Functions can be used to respond to security-related events. For example, a function could be triggered when there is an unexpected change in Cloud IAM policies, such as unauthorized granting of permissions, and send alerts or take corrective action.
• Trigger: Cloud Logging event.
• Use Case: Monitoring security policies and enforcing compliance in real-time.
4. Firebase (PaaS)
Firebase is a mobile and web app development platform offering several tools, including Firebase Authentication, Firestore (database), Cloud Functions, and more. It’s often categorized as Backend-as-a-Service (BaaS) because it abstracts most backend complexities.
• Pros: Realtime synchronization, authentication, integrated services.
• Cons: Limited flexibility compared to custom backends.
- Use Case: Firebase is great for building MVPs and real-time applications. For instance, a chat app or a real-time collaborative tool. Or hosting a single-page application (SPA) that uses Firebase Authentication and Firestore as a backend.
Difference between Firebase functions and Cloud Functions:
Firebase Functions offers a streamlined developer experience for those using Firebase, especially with features like the Firebase CLI, which makes it easy to deploy functions along with other Firebase services.
Google Cloud Functions provides flexibility in the broader GCP context, making it a better choice for enterprises or projects that are not limited to mobile/web app use cases. It can be used independently for a variety of use cases across the entire GCP ecosystem. It is suitable for cloud-level tasks, event-driven architectures, and use cases that are not restricted to Firebase.
5. Google Kubernetes Engine (GKE)
Google Kubernetes Engine is a managed Kubernetes service that allows you to deploy, manage, and scale containerized applications using Kubernetes.
• Pros: Full Kubernetes support, integrates well with other Google Cloud services, automatic scaling and updates.
• Cons: Requires Kubernetes expertise, more complex compared to fully serverless options.
• Use Case: GKE is ideal for running containerized applications that require complex orchestration, or when you need fine-grained control over workload deployment and scaling. For example, deploying a microservices-based architecture with advanced networking and scaling requirements.
Google Cloud IaaS Offerings
1. Google Compute Engine (IaaS)
Compute Engine offers virtual machines (VMs) running in Google’s data centers. You have full control over the server environment, including the operating system and software installed.
• Pros: Full flexibility to configure servers, full control over the environment.
• Cons: Requires significant management effort compared to managed services.
- Use Case: Compute Engine is suitable when you need a custom infrastructure setup or need to run legacy applications that require specific OS configurations.
Comparison Table:
Choosing the Right Solution
For event-driven code execution or when you need simple backend functions that trigger based on an event (e.g., a new file upload or an HTTP request), Cloud Functions is the best choice.
For web applications with minimal infrastructure management, App Engine is ideal, especially if you need auto-scaling and don’t want to worry about server configurations.
For purely static content, Google Cloud Storage or Firebase Hosting are the best choices, depending on the integration requirements. Google Cloud Storage is cost-effective and easy for basic use cases, while Firebase Hosting adds more features if you’re already in the Firebase ecosystem or need serverless backend capabilities.
For containerized applications or services, Cloud Run is a perfect blend of simplicity and flexibility. Cloud Run and Google Kubernetes Engine (GKE) are both great options for running containerized applications on Google Cloud, but they serve different purposes and suit different levels of complexity and requirements.
Choose Cloud Run if you want a simple, fully managed environment for containerized services with minimal operational overhead and predictable scaling.
Choose GKE if you need full control over your container orchestration, advanced features for a large-scale microservices architecture, or plan to work with hybrid/multi-cloud solutions.
If you want an all-in-one solution that includes authentication, database, and real-time updates for mobile and web apps, Firebase provides rapid development.
When control over the VM and OS is important, Compute Engine provides full control for running legacy apps or custom environments.
Conclusion
Google Cloud offers a wide variety of IaaS and PaaS services that cater to different development needs. Whether you need a fully managed platform, container orchestration, or event-driven functions, there’s a solution for you. By understanding the specific pros, cons, and use cases for each service, you can choose the right tools to bring your project to life efficiently.
