Course is closed
Lead Instructor(s)
Date(s)
TBD
Course Length
2 Days
Course Fee
$2,500
CEUs
1.3
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In order to keep your company at the cutting edge of technology, you need to think like a software company. That's where DevOps comes in. With this course, you will learn the key attributes of software development methodology and how to apply these methods in a way that aligns with your most important business objectives. These attributes include: continuous development, continuous delivery, theory of constraints, value streams, telemetry, A/B testing, information security, change management, and compliance.

In 2011, Marc Andreessen famously wrote, “software is eating the world.” Seven years later, and the five largest companies in the world are all software companies.

Today, as technology becomes pervasive across industries and functions, companies from all different sectors are competing to become technology companies as well. Yet, there is a growing digital divide between digital ready companies and the traditional enterprise. Companies in the Fortune 500 deploy once every 1.5 months, digital ready companies using DevOps make over 1000 deployments per month.

DevOps is the combination of processes, technology, tools, and culture that increases an organization's ability to deliver applications and services at high velocity, with the goal of shortening the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives. With this course, you will gain the knowledge necessary to keep your business on the cutting edge of technology while remaining competitive against other digital ready companies.

Participant Takeaways

  • You will able to describe DevOps and DevOps platforms key principles, the Theory of Constraints, how to use DevOps in cybersecurity, DevOps applications to fields other than software development, legal and regulatory aspects of DevOps, and the implementation of DevOps tools
  • You will be able to describe and apply Systems Thinking, Feedback Loops, Containers, Container Orchestration, CI/CD, and Continual Learning & Experimentation
  • You will be able to make effective decisions taking into account the key trends of DevOps implementations
  • You will be able to create containers, CI/CD pipelines, kubernetes clusters, spinnaker deployments, and skaffold deployments

Who Should Attend

This course is ideal for C-suite and strategic leaders and decision makers in a wide variety of industries including finance, law, education, and government.

Requirements

Laptops or Chromebooks with a modern operating system for which you have administrator privileges are required. An updated version of Google Chrome is required as well. Tablets will not be sufficient for the computing activities in this course.

Program Outline

Program Overview: DevOps trends, fundamentals, and course overview

One-hour DevOps Pipeline: Build a one-hour "DevOps" pipeline to explore components and principles

CI/CD Chronicle: We started with VMs in the cloud, then we added containers, then microservices and serverless architectures. The journey chronicles the pursuit of faster product development and agility in our platforms

DevOps Platforms: Leading DevOps tools, open source, platforms, and ecosystems

DevOps in Financial Markets: Softwares, architectures, and applications of DevOps to financial markets

DevOps in Insurance Markets: Software, architectures, and applications of DevOps to insurance markets

Spinnaker: Open source, multi-cloud continuous delivery platforms for releasing software changes with high velocity and confidence

Kubernetes: Open-source systems for automating deployment, scaling, and management of containerized applications

Containers: A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another

Skaffold: Platforms to facilitate continuous development for Kubernetes applications

Intelligent Testing: Modern quality assurance (QA) groups struggle to play their role in a world of continuous delivery. Innovations in machine intelligence and test automation for a better model that will allow QA to keep pace with development, increase productivity

Data Science Acceleration: For a data scientist, moving a model from a laptop to a highly scalable cloud cluster is effectively impossible without significant re-architecture. Session presents Cloud Native alternatives. New building blocks that have the potential to accelerate data science across industry and academia

Theory of Constraints: Application of the theory of constraints helps to identify the organization's goal, the chain of interdependent activities that achieve it, and the weaknesses in the chain

Systems Thinking: A holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems

Amplify Feedback Loops: A core tenet of modern process improvement methodologies. The principle maximizes the opportunities for organizations to learn and improve

Continual Experimentation and Learning: The processes that enable continuous creation of individual knowledge, used to transform team and organization knowledge

Cybersecurity: Simultaneously achieve DevOps and information security goals. Create a high degree of assurance for confidentiality, integrity, and availability of services and data

Containerization: Any size application and dependencies can be containerized. Over time, companies should aspire towards splitting suitable applications and writing future functionality as microservices

CI/CD: Set up Continuous Integration/Continuous Delivery (CI/CD) so that changes to your source code automatically result in a new container being built, tested, and deployed to staging and eventually, perhaps, to production. Set up automated rollouts, rollbacks, and testing

Orchestration & Application Definition: Systems for automating deployment, scaling, and management of containers

Observability & Analysis: Monitoring, logging, and tracing

Content

The type of content you will learn in this course, whether it's a foundational understanding of the subject, the hottest trends and developments in the field, or suggested practical applications for industry.

Fundamentals: Core concepts, understandings, and tools - 30%|Latest Developments: Recent advances and future trends - 30%|Industry Applications: Linking theory and real-world - 40%
30|30|40
Delivery Methods

How the course is taught, from traditional classroom lectures and riveting discussions to group projects to engaging and interactive simulations and exercises with your peers.

Lecture: Delivery of material in a lecture format - 65%|Labs: Demonstrations, experiments, simulations - 35%
65|35
Levels

What level of expertise and familiarity the material in this course assumes you have. The greater the amount of introductory material taught in the course, the less you will need to be familiar with when you attend.

Introductory: Appropriate for a general audience - 50%|Specialized: Assumes experience in practice area or field - 50%
50|50