Course summary
1. Course summary
Congratulations on completing the Google Cloud Fundamentals: Core Infrastructure training course. Before you go, let’s take a few minutes to review what we’ve covered. In module 1, you were introduced to Google Cloud and cloud computing. Specifically, you explored: The concept of managed infrastructure and managed services, through IaaS, infrastructure as a service, and PaaS, platform as a service. The Google Cloud network. Google Cloud’s focus on security throughout our infrastructure. How Google publishes key elements of technology using open source licenses. And Google Cloud’s pricing structure and billing tools. In module 2, you learned about the Google Cloud Resource Hierarchy, which is made up of four levels: resources, projects, folders, and an organization node. You also learned about: Defining policies and their downward inheritance. When to use Identity and Access Management, or IAM, And the four ways to access and interact with Google Cloud: through the Google Cloud console, the Cloud SDK and Cloud Shell, APIs, and the Google Cloud App. In module 3, you explored how Compute Engine works, with a focus on virtual machines and virtual networking. You were introduced to: The VPC, or virtual private cloud. Compute Engine’s Autoscaling feature. And important Google Virtual Private Cloud compatibility features, like routing tables, firewalls, VPC peering, and shared VPC, all of which result in the need for less network management. You also explored Cloud Load Balancing, a fully distributed, software-defined, managed service for all your traffic. Finally, you compared how on-premises or other-cloud networks can be interconnected with a Google VPC. In module 4, you explored Google Cloud's five core storage options: Cloud Storage, Bigtable, Cloud SQL, Spanner, and Firestore. You also examined the four storage classes that make up Cloud Storage: Standard Storage, which is used for frequently accessed hot data, Nearline Storage and Coldline Storage, which are used for less-frequently accessed cool data, and Archive Storage. In module 5, you learned about containers, which are invisible boxes around your code and its dependencies. You were introduced to containers, along with: Kubernetes, an open-source platform for managing containerized workloads and services. And Google Kubernetes Engine (GKE), a Google-hosted managed Kubernetes service in the cloud. In module 6, the focus was on developing applications in the cloud. You explored: Cloud Run, a managed compute platform that lets you run stateless containers via web requests or Pub/Sub events. And Cloud Run functions, a lightweight, event-based, asynchronous compute solution to create single-purpose functions. Finally, in module 7, you explored how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses. You discovered answers to the following questions: What is generative AI? What is a large language model? And what is prompt engineering? You ended the module by identifying prompt engineering best practices. We hope that this course is just the beginning of your Google Cloud journey. For more training and hands-on practice, explore the different learning paths available at cloud.google.com/training. And if you’re interested in validating your expertise and showcasing your ability to transform businesses with Google Cloud technology, you might consider working toward a Google Cloud certification. You can learn more about Google Cloud’s certification offerings at cloud.google.com/certification. Thanks for completing this course. We’ll see you next time!2. Let's practice!
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