4 Hour Live Virtual Training on MultiCloud IaaS, PaaS, Serverless, and Kubernetes Workloads
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Training TypeLive Training
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CategoryDevOps
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Duration04 Hours
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Rating4.6/5


Course Introduction
About the Course
Multi-cloud IaaS, PaaS, Serverless, and Kubernetes - There are several possible solutions for maintaining cloud interoperability:
Run workloads on virtual machines without a dependency on cloud-specific services
Make use of Platform as a Service
Deploy workload using Serverless or Function as a Service
Leverage Kubernetes as a Service
The purpose of this course is to analyze the pros and cons of the different approaches
And to experience the different approaches with pragmatic hands-on labs and group discussions
Course Objective
Review the common design patterns deployment models: IaaS, PaaS, KaaS, and FaaS
Highlight best design practices for the cloud-native applications: the twelve factors app
Automate deployment of IaaS to a couple of public cloud providers: Aws, GCP or Azure leveraging terraform
Demonstrate the process of authoring a Dockerfile to run the end-point application in a container
Make use of Kubernetes as a service to deploy and monitor the created image
Convert the end-point to a serverless function and deploy to a couple of cloud providers: AWS, GCP, or Azure
Who is the Target Audience?
Software architects evaluating the strategies for an inter-cloud and multi-cloud deployment models
Software developers writing code that needs to run on different or multiple cloud providers
DevOps engineers that will be implementing inter-cloud ci/cd
Basic Knowledge:
Previous experience with public cloud providers: Aws, GCP, or Azure
Familiarity with Micro-services concepts
Recent hands-on experience with terminal/command line
Access to AWS, GCP, Azure account, a free trial is sufficient
Available Batches
Pricing
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Introduction
Service Models: IaaS, PaaS, CaaS, Kubernetes, DBaaS, and Serverless
Distributed and decentralized workloads
The twelve factors app
Micro-services principles
Infrastructure as a Code
Objectives, Motivation and principles
Tools and approaches
Introduction to Terraform
IaaS deployment using Terraform
Docker and Kubernetes
Motivation and Enthusiasm
Compare Containers to Virtual Machines
Author a Dockerfile
Build Image and Run Container
Kubernetes as a Container Platform
Author and deploy a pod
Kubernetes Monitoring
Multi-Cloud PaaS
Motivation and Premise
PaaS vs. IaaS vs. KaaS
PaaS Design Considerations
Deployment automation
Serverless
Best of Containers and PaaS or a hype
Architectural principles
Coding practices
Convert end-point to a function
Cloud specific platforms