In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance.
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
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來自APP DEPLOYMENT, DEBUGGING, AND PERFORMANCE的熱門評論
The Course was really helpful in understanding statck driver monitoring and different types of applications . The labs were really helpful in understanding the debugging applications etc
This course was really nice. It helped me to learn basics of docker, kubernetes. Also, learnt how to debug apps in GCP. It's really nice learning experience. Thanks a lot!
Loved the course. It helped me put a lot of features together. One feedback for Coursera is to include all PDFs in a resource area like they did for the first course.
The Course slides are not readily downloadable from the Course overview. This is something very useful when studying for a certification exam for instance.
關於 Developing Applications with Google Cloud 專項課程
In this specialization, application developers learn how to design, develop, and deploy applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Learners can choose to complete labs in their favorite language: Node.js, Java, or Python.