Google Kubernetes Engine is one of the leading hosted container orchestration solutions. It provides a hosted environment for running containerized applications and managing workloads to your specifications, while integrating with other Google Cloud services for secure, highly available, and scalable deployments. In this course you'll explore Google Kubernetes Engine (GKE), deploy a containerized application to GKE, and control access to cluster resources using role-based access control (RBAC) and identity and access management (IAM). Next, you will practice configuring Kubernetes namespaces, identify workload profiles and specifications, and build container images using Cloud Build. You will configure Kubernetes network policy and Kubernetes services and explore how to manipulate the GKE Pod life cycle. Finally, you'll explore how Kubernetes resources and configurations are defined. This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.

Google Compute Engine (GCE) offers various advantages for deploying your applications, such as throughput, stability, pricing, backup, and security. Containers on Compute Engine instances allow you to conveniently run your apps on host virtual machines (VMs) with fewer dependencies. In this course, learn about the different types of containers that can be run on Compute Engine instances. Next, discover how to install applications and manage service accounts for VMs, bootstrap applications on Compute Engine, and configure and manage sinks. Finally, practice exporting metrics, using operating system images to create boot disks for instances, and configuring a Binary Authorization policy with Google Kubernetes Engine (GKE). This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.

Google Cloud Functions is a serverless, event-driven computing service that lets you treat all cloud services as building blocks. Developers can use it to create and implement functions without needing to provision other infrastructures like servers, storage, and other resources. In this course, learn about Google Cloud Functions and its triggers and events, including Pub/Sub and Cloud Storage triggers. Next, discover how to write and deploy Cloud Functions, the types of triggers for calling Cloud Functions, and use HTTP functions. Finally, practice creating an event that triggers CloudEvent and secure Cloud Functions using identity and network-based approaches. This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.

Google Cloud Compute Engine allows you to create and run virtual machines (VMs). Compute Engine instances can be used to run the public images for both Linux and Windows Server. In this course, learn about managing Google Compute Engine VMs. Next, discover how to debug custom VMs, debug using a serial console, and debug a failed VM startup. Finally, explore how to install the Cloud Logging agent on individual VMs, work with the Logs Explorer to analyze logs, and view a resource utilization report. This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.

Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling containerized applications. GKE consists of multiple machines grouped to form a cluster. In this course, you'll explore the use of GKE workloads, and configure Cloud Logging and Cloud Monitoring. You'll access the monitoring dashboard to view container life cycle events, troubleshoot issues with deployed workloads, and view GKE logs. You will explore how to manage GKE metrics, use custom metrics to capture application-specific data, and identify external metrics. Finally, you will see how to use Pub/Sub to receive notifications from your GKE clusters and autoscale your GKE clusters. This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.

The Google Performance Dashboard gives you visibility into all of the Google Cloud network. It shows you the performance of the entire network as well as any of your project's resources. In this course, you'll learn about the Google Performance Dashboard, create a monitoring dashboard, write custom metrics, create log-based metrics, and use Cloud Debugger. You'll review stack traces for error analysis, setup service log exports to BigQuery, view logs in the Google Console, monitor health and performance using Cloud Monitoring, and review application performance using Cloud Trace. You'll also use Prometheus to monitor and alert you on your workloads and OpenTelemetry to monitor and analyze your applications. Finally, you'll measure app performance using Cloud Profiler and use documentation, forums, and Google Cloud support. This course is one of a collection that prepares learners for the Google Professional Cloud Developer exam.