| Kubernetes In Seven Steps | Using hands-on labs, demos and presentations, this course will introduce Kubernetes core concepts, deployment and administration of Kubernetes and the usage of the Google GKE service.
This course will cover seven key learning steps:
● Getting started with Kubernetes
● Hello Kubernetes with GKE
● Building a complex cluster
● Monitoring and health checks
● Persistence and databases
● Security and access control
● CI / CD solutions
This course assumes that the participant has some exposure to Google or Cloud technologies and can work with the command line, git and other development tools. | ● Cloud Solutions
Architects, DevOps
Engineers
● Software engineers | Classroom | 2 days | Advanced |
| API development with Istio | Designed for API developers, this is a hands-on introduction to the Istio service mesh, its key concepts, development model and extensions. The course will take a web application and supporting APIs that “work on my machine” and make them production ready using Istio. This course assumes that the API developer has a basic working knowledge of Kubernetes, are familiar with interacting with Kubernetes via kubectl, and can author and deploy standard Kubernetes resources such as Deployment, Service and Ingress. | ● Software Developers
● API Developers | Classroom | 2 days | Advanced |
| Machine Learning for Software Engineers | Introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
This course teaches participants the following skills:
● Consider the entire range of Google Cloud Platform technologies in their plans.
● Learn methods to develop, implement, and deploy solutions.
● Distinguish between features of similar or related products and technologies.
● Recognize a wide variety of solution domains, use cases, and applications.
● Develop essential skills for managing and administering solutions.
● Develop knowledge of solution patterns -- methods, technologies, and designs that are used to implement security, scalability, high availability, and other desired qualities. | ● Cloud Solutions
Architects
● DevOps Engineers | Classroom | 1 day | Fundamentals |
| GCP BigData and Machine Learning | This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, participants get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
This course teaches participants the following skills:
● Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.
● Use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
● Employ BigQuery and Cloud Datalab to carry out interactive data analysis.
● Train and use a neural network using TensorFlow.
● Employ ML APIs.
● Choose between different data processing products on the Google Cloud Platform
This class is intended for the following:
● Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform.
● Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports.
● Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists. | ● Data Engineers and
Analysts
● Business Analysts | Classroom | 1 day | Fundamentals |
Developing
solutions for
GCP | In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
This course teaches participants the following skills:
● Use best practices for application development.
● Choose the appropriate data storage option for application data.
● Implement federated identity management.
● Develop loosely coupled application components or microservices.
● Integrate application components and data sources.
● Debug, trace, and monitor applications.
● Perform repeatable deployments with containers and deployment services.
● Choose the appropriate application runtime environment; use Google Kubernetes Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex. | ● Application Developers | Classroom | 2 days | Advanced |
