DevOps Courses
Deploying Applications to the Cloud using Terraform
This class is designed to teach DevOps engineers, Production Support staff and developers how to effectively use Terraform to manage infrastructure in a cloud environment. The course covers the best practices around the concept of infrastructure as code and then introduces how this can be best be applied using Terraform.
Docker Fundamentals
This course focuses on taking real applications from on premises, and then leveraging Docker to automate the deployment process into a containerised environment. You will learn how Docker actually works and how to manage and create images and then the related containers. You will see how to customise the network environment and how to access the filesystem from the containers. In addition you will see how to manage a docker repository and also how to create custom images from Dockerfiles.
Devops Fundamentals
This course focuses on the principles and practices around Devops. The course will introduce you to the Continuous Integration, Continuous Delivery and Continuous Deployment. You will learn how to use CI technologies to automate the build process and how to use Docker to automate the deployment process. You will also learn how to use Kubernetes to manage the deployment of your containers. You will also learn how to use Terraform to automate the deployment of your infrastructure.
DevOps Engineering on AWS
DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization’s ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers continuous integration (CI), continuous delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included.
MLOps Engineering On AWS
Could your Machine Learning (ML) workflow use some DevOps agility? MLOps Engineering on AWS will help you bring DevOps-style practices into the building, training, and deployment of ML models. ML data platform engineers, DevOps engineers, and developers/operations staff with responsibility for operationalizing ML models will learn to address the challenges associated with handoffs between data engineers, data scientists, software developers, and operations through the use of tools, automation, processes, and teamwork. By the end of the course, go from learning to doing by building an MLOps action plan for your organization.
Accreditations:
