Google Cloud's Architecture Framework describes best practices, makes implementation recommendations, and goes into detail about products and services. The framework aims to help you design your Google Cloud deployment so that it best matches your business needs.

The framework was created by seasoned experts at Google Cloud, including customer engineers, solution architects, cloud reliability engineers, and members of the professional service organization. It consists of the following series of articles:

Why Google Cloud?

With Google Cloud, you can leverage the years of work Google has spent on improving its internal infrastructure and open source technology.

Security first

At Google Cloud we've set a high bar for what it means to host, serve, and protect customer data. Security and data protection are fundamental to how we design and build our products. We start from the premise that as a customer of Google Cloud you own your data and control how it is used.

Google has robust internal controls and auditing to protect against insider access to customer data. You receive near real-time logs of Google administrator access on Google Cloud. In addition to continuous security monitoring, all your data stored in Google Cloud is encrypted at rest and in transit by default. You can use Cloud Key Management Service (Cloud KMS) to manage your own encryption keys, using the customer-managed encryption keys (CMEK) feature.

For more information, see Trust and security.

Open cloud

Google believes that being tied to a particular cloud shouldn't get in the way of achieving your goals. An open cloud gives you the power to deliver your apps to different clouds while using a common development and operations approach. You can meet your priorities—whether they are making the most of skills shared widely across your teams, or rapidly accelerating innovation. Open source enables open clouds because open source in the cloud preserves your control over where you deploy your IT investments. For example, you can use Kubernetes to manage containers and TensorFlow to build machine learning models on-premises and on multiple clouds.

Google is a pioneer in open source technologies. Open source is so important to Google that we call it out twice in our corporate philosophy. We encourage our employees and all developers to engage with open source. This means you don't have to worry about vendor lock-in or any blockers in data takeout.

For more information, see Open API platforms attain better cloud outcomes.

Analytics and artificial intelligence

Google Cloud's fully managed serverless analytics empower your business while eliminating constraints of scale, performance, and cost. You gain real-time insights that improve your decision-making and accelerate innovation. Without infrastructure to manage, you can scale up the amount of data that your business can analyze without sacrificing speed.

Google has a long history of innovations in the analytics and artificial intelligence (AI) domain including MapReduce, Dremel, Apache Beam, and TensorFlow. This work has translated into intelligent features in Google consumer products, such as Google Search and Google Workspace, and in core Google Cloud products such as Cloud Bigtable, Dataflow, and AI Platform. You can use the powerful AI Platform capabilities to develop better product recommendations, improve customer service experience and efficiency, and develop more accurate marketing campaigns.

For more information, see Smart analytics.

Global data centers and network

Choosing Google Cloud, you can build on the same future-proof infrastructure that allows Google to return billions of search results in milliseconds, serve 6 billion hours of YouTube video per month, and provide storage for more than 1 billion Gmail users. Our infrastructure is protected by more than 700 experts in information, application, and network security.

Google Cloud provides fast and consistent performance across the range of computing, storage, and application services. With powerful processing, access to the memory you need, and high IOPS, your application delivers consistent performance to your users. You enjoy the benefits of reduced latency and avoid noisy-neighbor problems.

Finally, Google has one of the largest and most advanced software-defined computer networks. Google's backbone uses advanced software-defined networking, and has edge caching services to deliver fast, consistent, and scalable performance.

For more information, see Global locations, Global infrastructure, and the Google Cloud difference.

Principles of system design

Designing robust, secure, and scalable systems is a critical first step in developing applications and using cloud infrastructure. In Site Reliability Engineering, the chapter on Introducing non-Abstract Large System Design highlights the importance of proper design:

"Based on Google's experience developing systems, we consider reliability to be the most critical feature of any production system. We find that deferring reliability issues during design is akin to accepting fewer features at higher costs. By following an iterative style of system design and implementation, we arrive at robust and scalable designs with low operational costs."

This Google Cloud architecture framework helps you evaluate the advantages and disadvantages of design choices and provides guidance on how to optimize, secure, and tune services while controlling the cost of deployment. The framework describes a foundation for building and improving your deployments using 4 principles:

Each principle section provides details on strategies, best practices, design questions, recommendations, key Google Cloud services, and links to resources.

These principles apply to cloud-native applications as well as migrations from on-premises applications to public cloud, hybrid, and multi-cloud deployments. Building a well-designed architecture is critical for applications that support your business.