Running Production Workloads in Google Cloud Platform
Four Corners
Florida
34747
United States
Description
Running your own datacenter leads to wasted resources, higher capital expense and less flexibility in running workloads. These limitations block the use of DevOps principles, tooling and technologies, as well as slow down application development and deployment. Migrating to public cloud leads to much faster application development and enables continuous integration and deployment so you can stay ahead of your competitors.
- Introduction to Public Cloud
- Datacenter to Public Cloud evolution
- Infrastructure as a Service
- Platform as a Service
- Public Cloud comparison
- Introduction to Google Cloud Platform
- Compute
- Storage
- Networking
- Load Balancers
- Cloud application principles
- Modular design
- Decouple tiers
- RESTful API
- Google App Engine
- App Engine features
- Cloud Endpoints
- Storing and retrieving data
- Advanced Datastore topics
- Advanced App Engine tips
- Monitoring
- Overview
- Monitoring options
- Configuring Stackdriver
- Hybrid Cloud with Stackdriver
- Autoscaling
- Autoscaling concepts
- Compute instance group
- Stackdriver custom metrics
- Application concerns when autoscaling
- Google Container Engine (GKE)
- Introduction to containers
- Introduction to Kubernetes
- Container Engine advantages
- Deploying containers on GKE
- Serverless
- What is serverless?
- Advantages of serverless
- Google App Engine (FaaS)
- Deploying a serverless application
Who is this course for?
This is an intermediate -level class for developers, DevOps team members, architects and any other Engineering personnel interested in running production applications in public cloud environments and specifically utilizing Google Cloud’s services.This class does not require prior experience with cloud technologies, but experience with command-line tools and text editors is helpful.
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