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.
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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.
- 5 stars67,38 %
- 4 stars24,82 %
- 3 stars5,82 %
- 2 stars1,25 %
- 1 star0,71 %
Top-Bewertungen von APP DEPLOYMENT, DEBUGGING, AND PERFORMANCE
Add more information on slide and make a demo lecture of GCP projects plzz
Another excellent course. The only issue is that volume on some videos are significantly lower than others. I was startled several times haha
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!
Über den Spezialisierung Developing Applications with Google Cloud
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.
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