LernIX Solutions

Course Overview

If you are an experienced Nutanix administrator, this course will serve as a deep dive that gives you a rich, nuanced understanding of the Nutanix platform, and will help you get the most out of your Nutanix solutions. AAPM is divided into six major sections, each focused on performance improvements and advanced administration techniques for different aspects of your clusters:

– Storage: Take a deep dive into AOS storage services, different aspects of Acropolis Distributed Storage, storage optimization, and storage best practices for application workloads.

– Networks: Learn how to optimize physical and virtual workloads, as well as how to implement Flow Virtual Networking and Virtual Private Clouds (VPCs).

– VMs: Learn about sizing the CVM and Prism Central VMs, alternate methods of VM provisioning (such as via CLI), how to work with GPUs, and how to improve VM storage and network performance.

– Security: Understand important features such as authentication, RBAC, IAM, and encryption. Learn how to use essential security products, such as Flow Security Central and Flow Network Security.

– Analyzing Problems: Explore ways to monitor and identify health issues, network performance, VM performance, and cluster performance.

– Business Continuity and Disaster Recovery: Learn about Nutanix data backup, web-scale data protection, protection from ransomware, self service restore, and third-party integrations. You will also learn how to use protection domains and Nutanix Leap for disaster recovery.

Course Content

1: Exploring Nutanix Storage Features

Understanding Nutanix AOS Services and AOS Storage Services
Exploring Storage Components
AOS Storage Data Pathing

Hands-on Labs of 1

Creating a Storage Container
Updating Reported Capacity

2: Creating a Highly Available, Performant, and Resilient Storage Layer

Creating Highly Available, Resilient Infrastructure
Storage Optimization and Data Efficiency
Optimizing and Planning for New Workloads
Storage Best Practices for Application Workloads

Hands-on Labs of 2

Observing Nutanix Cloning Efficiency
Reserving Rebuild Capacity in AHV
Observing the Rebuild Process
Disabling Rebuild Capacity Reservation
Creating a Storage Container with Deduplication Enabled
Reviewing Deduplication Savings
Enabling Replication Factor 1 and Creating a Storage Container

3: Optimizing Physical and Virtual Networks in AOS

Optimizing Physical & Virtual Networks
Best Practices

Hands-on Labs of 3

Managing Virtual Switches and Uplinks
Viewing Virtual Switches from Prism Element
Configuring CVM Network Segmentation
Configuring QoS Traffic Marking

4: Optimizing Overlay Networks Using Flow Networking

Optimizing Physical & Virtual Networks
Implementing Flow Networking
Implementing VPCs
Overlay Network Use Cases

Hands-on Labs of 4

Enabling Flow Networking
Creating an External Subnet
Creating a VPC
Creating VMs using the Overlay Subnets
Configuring Local and Remote Gateways
Establishing a VPN Connection
Verifying VPN Connectivity

5: Optimizing VM Performance

Sizing the CVM & Prism Central
Alternate Methods of Provisioning User VMs
Working with GPUs in AHV
Improving VM Storage and Network Performance

Hands-on Labs of 5

Creating VMs with the REST API
Configuring VirtIO Multi-Queue
Configuring Volumes Block Storage

6: Analyzing Nutanix Cluster Security Options

Nutanix Security Technologies
User Authentication and Permissions
Hardening AHV and the CVM
Using Flow Network Security & Flow Security Central
Data Encryption with Nutanix
Managing Log Files

Hands-on Labs of 6

Configuring Cluster Lockdown
Replacing Default SSL Certificates
Configuring Syslog Integration
Managing User Permissions

7: Microsegmentation with Flow Network Security

Flow Policy Constructs
Security Policy Models and Types
Enabling Microsegmentation
Creating and Applying Policies

Hands-on Labs of 7

Enabling Flow Microsegmentation
Creating Categories
Creating VMs and Assigning Categories
Configuring Isolation and Application Security Policies

8: Microsegmentation with Flow Network Security

Evaluating Cluster Health
Network Packet Capture and Inspection
Acropolis Service Failures
Ensuring Efficient Physical Resource Consumption with Machine Learning
Application Monitoring and Discovery
Monitoring Performance

Hands-on Labs of 8

Creating a Prism Central Performance Monitoring Dashboard
Creating Charts to Analyze Metrics Using Prism Central
Creating Charts to Analyze Entities Using Prism Element

9: Business Continuity

Assessing Business Continuity and Disaster Recovery
High Availability and Data Protection
Third Party Backup Integrations
Best Practices

Hands-on Labs of 9

Configuring Self Service Restore

10: Implementing Disaster Recovery

Replicating Data with AOS
Disaster Recovery Orchestration
Disaster Recovery with Protection Domains
Getting Started with Nutanix Leap
Protecting Against Ransomware

Hands-on Labs of 10

Enabling Nutanix Leap
Configuring an Availability Zone
Configuring a Protection Policy
Creating Production and Test VLANs
Preparing VMs for Nutanix Leap
Configuring a Recovery Plan
Performing Test and Planned Failover

Course Overview

Learn how to use Red Hat Ansible Automation for Networking to remotely automate configuration of network devices, test and validate the current network state, and perform compliance checks to detect and correct configuration drift.

Course Objectives

Deploy AnsibleInstall
Ansible and create Ansible inventories.

Run commands and plays
Execute ad hoc commands and prepare Ansible playbooks.

Parameterize Ansible
Control tasks with loops and conditions.

Administer Ansible
Safeguard information with Ansible Vault and manage inventories.

Automate simple network operations
Gather network information with Ansible and configure network devices.

Automate complex operations
Solve new MACD challenges and overcome real-world challenges.

Note: Course outline is subject to change with technology advances and as the nature of the underlying job evolves. For questions or confirmation on a specific objective or topic, please contact us.

Course Content

Install and configure Red Hat Ansible Automation for Networking on a management system
Use Ansible to run ad hoc commands and playbooks to automate tasks
Write effective Ansible playbooks for network automation
Gather information about network infrastructure configuration and backup
Automate specific network administration use cases, including configuration of routers and switches, ports, VLANs, SNMP monitoring, and routing protocols
Use Ansible playbooks to target devices from various hardware vendors, including Cisco, Juniper, and Arista

Course Overview

This course complies with instructional designing principles for all the 3 lessons. This will ensure that you repeat and reinforce your gained knowledge at every step. Each and every minute spent during this 1-day course will incrementally take you to a next level.

Course Objectives

ensure that your container-based applications sail into production without hiccups, you need robust container orchestration. This course teaches you the art of container management with Kubernetes.

The course will provide enough knowledge of the following:

Understand and classify software designs patterns as per the cloud-native paradigm
Apply best practices in Kubernetes with design patterns
Access the Kubernetes API programmatically using client libraries
Extend Kubernetes with custom resources and controllers
Integrate access control mechanisms and interact with the resource lifecycle in Kubernetes
Develop and run custom schedulers in Kubernetes

Course Content

LESSON 1: KUBERNETES DESIGN PATTERNS

Software Design Patterns
Kubernetes Design Patterns

LESSON 2: KUBERNETES CLIENT LIBRARIES

Accessing Kubernetes API
Official Client Libraries
Community Maintained Client Libraries

LESSON 3: KUBERNETES EXTENSIONS

Kubernetes Extension Points
Extending Kubernetes Clients
Extending Kubernetes API
Kubernetes Dynamic Admission Control
Extending Kubernetes Scheduler
Extending Kubernetes Infrastructure

Course Overview

The Implementing DevOps Solutions and Practices Using Cisco Platforms course teaches you how to automate application deployment, enable automated configuration, enhance management and improve scalability of cloud microservices and infrastructure processes on Cisco® platforms. Learn to integrate Docker and Kubernetes to create advanced capabilities and flexibility in application deployment.

Course Objectives

After completing this course you should be able to:

Describe the DevOps philosophy and practices, and how they apply to real-life challenges
Explain container-based architectures and available tooling provided by Docker
Describe application packaging into containers and start building secure container images
Utilize container networking and deploy a three-tier network application
Explain the concepts of configuration item (CI) pipelines and what tooling is available
Implement a basic pipeline with Gitlab CI that builds and deploys applications
Implement automated build testing and validation
Describe DevOps principles applied to infrastructure
Implement on-demand test environments and explain how to integrate them with an existing pipeline
Implement tooling for metric and log collection, analysis, and alerting
Describe the benefits of application health monitoring, telemetry, and chaos engineering in the context of improving the stability and reliability of the ecosystem
Describe how to implement secure DevOps workflows by safely handling sensitive data and validating applications
Explain design and operational concepts related to using a mix of public and private cloud deployments
Describe modern application design and microservices architectures
Describe the building blocks of Kubernetes and how to use its APIs to deploy an application
Explain advanced Kubernetes deployment patterns and implement an automated pipeline
Explain how monitoring, logging, and visibility concepts apply to Kubernetes

Course Content

Introducing the DevOps Model

DevOps Philosophy
DevOps Practices

Introducing Containers

Container-Based Architectures
Linux Containers
Docker Overview
Docker Commands

Packaging an Application Using Docker

Dockerfiles
Golden Images
Safe Processing Practices

Deploying a Multitier Application

Linux Networking
Docker Networking
Docker Compose

Introducing CI/CD

Continuous Integration
CI Tools
DevOps Pipelines

Building the DevOps Flow

GitLab Overview
GitLab CI Overview
Continuous Delivery with GitLab

Validating the Application Build Process

Automated Testing in the CI Flow

Building an Improved Deployment Flow

Post deployment Validation
Release Deployment Strategies

Extending DevOps Practices to the Entire Infrastructure

Introduction to NetDevOps
Infrastructure as Code

Implementing On-Demand Test Environments at the Infrastructure Level

Configuration Management Tools
Terraform Overview
Ansible Overview
Ansible Inventory File
Use the Cisco IOS Core Configuration Module
Jinja2 and Ansible Templates
Basic Jinja2 with YAML
Configuration Templating with Ansible

Monitoring in NetDevOps

Introduction to Monitoring, Metrics and Logs
Introduction to Elasticsearch, Beats and Kibana
Introduction to Prometheus and Instrumenting Python Code for Observability

Engineering for Visibility and Stability

Application Health and Performance
AppDynamics Overview
Chaos Engineering Principles

Securing DevOps Workflows

DevSecOps Overview
Application Security in the CI/CD Pipeline
Infrastructure Security in the CI/CD Pipeline

Exploring Multicloud Strategies

Application Deployment to Multiple Environments
Public Cloud Terminology Primer
Tracking and Projecting Public Cloud Costs
High Availability and Disaster Recovery Design Considerations
IaC for Repeatable Public Cloud Consumption
Cloud Services Strategy Comparison

Examining Application and Deployment Architectures

The Twelve-Factor Application
Microservices Architectures

Describing Kubernetes

Kubernetes Concepts: Nodes, Pods and Clusters
Kubernetes Concepts: Storage
Kubernetes Concepts: Networking
Kubernetes Concepts: Security
Kubernetes API Overview

Integrating Multiple Data Center Deployments with Kubernetes

Kubernetes Deployment Patterns
Kubernetes Failure Scenarios
Kubernetes Load-Balancing Techniques
Kubernetes Namespaces
Kubernetes Deployment via CI/CD Pipelines

Monitoring and Logging in Kubernetes

Kubernete Resource Metrics Pipeline
Kubernetes Full Metrics Pipeline and Logging

Labs:

Interact with GitLab Continuous Integration
Explore Docker Command-Line Tools
Package and Run a WebApp Container
Build and Deploy Multiple Containers to Create a Three-Tier Application
Explore Docker Networking
Build and Deploy an Application Using Docker Compose
Implement a Pipeline in Gitlab CI
Automate the Deployment of an Application
Validate the Application Build Process
Validate the Deployment and Fix the Infrastructure
Build a YAMl IaC Specification for the Test Enviroment
Manage On-Demand Test Environments with Terraform
Build Ansible Playbooks to Manage Infrastructure
Integrate the Testing Enviroment in the CI/CD Pipeline
Implement Pre-Deployment Health Checks
Set Up Logging for the Application Servers and Visualize with Kibana
Create System Dashboard Focused on Metrics
Use Alerts Through Kibana
Instrument Application Monitoring
Use Alerts and Thresholds to Notify Webhook Listener and Webex Teams Room
Secure Infrastructure in the CI/CD Pipeline
Explore Kubernetes Setup and Deploy an Application
Explore and Modify a Kubernetes CI/CD Pipeline
Kubernetes Monitoring and Metrics – ELK

Course Overview

This five-hour class equips you to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. Students also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.

Learn to containerize workloads in Docker containers, deploy them to Kubernetes clusters provided by Google Kubernetes Engine, and scale those workloads to handle increased traffic. You also learn how to continuously deploy new code in a Kubernetes cluster to provide application updates.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Objectives

At the end of the course, you will be able to:

Understand container basics.
Containerize an existing application.
Understand Kubernetes concepts and principles.
Deploy applications to Kubernetes using the CLI.
Set up a continuous delivery pipeline using Jenkins

Course Content

This course includes presentations and hands-on labs.Module 1: Introduction to Containers and Docker

Acquaint yourself with containers, Docker, and the Google Container Registry.

Create a container.
Package a container using Docker.
Store a container image in Google Container Registry.
Launch a Docker container.

Module 2: Kubernetes Basics

Deploy an application with microservices in a Kubernetes cluster.

Provision a complete Kubernetes cluster using Kubernetes Engine.
Deploy and manage Docker containers using kubectl.
Break an application into microservices using Kubernetes’ Deployments and Services.

Module 3: Deploying to Kubernetes

Create and manage Kubernetes deployments.

Create a Kubernetes deployment.
Trigger, pause, resume, and rollback updates.
Understand and build canary deployments.

Module 4: Continuous Deployment with Jenkins

Build a continuous delivery pipeline.

Provision Jenkins in your Kubernetes cluster.
Create a Jenkins pipeline.
Implement a canary deployment using Jenkins.

Course Overview

PROMOTION: until the end of December 2023 you will receive a 50% discount when booking and participating in this training. To claim this discount you must use the promotional code ECDE50. Only at Global Knowledge!

This 3-day EC-Council training is a course that will prepare you for the EC-Council’s Certified DevSecOps Engineer (E|CDE) certification. EC-Council’s Certified DevSecOps Engineer is a hands-on, comprehensive DevSecOps certification program designed by SMEs that helps professionals build the essential skills for designing, developing, and maintaining secure applications.

Benefits EC-Council’s Certified DevSecOps Engineer certification:

Adding security to a DevOps skill set enhances career prospects.
The information provided in the E|CDE course is complemented with labs to help learners hone their practical skills and become industry ready.
This course teaches students how to use various DevSecOps tools and create secure code throughout the software development life cycle.
Participants gain familiarity with DevSecOps tools that enable the secure development of software and web applications, both on premises and in the cloud.
The E|CDE course focuses on application DevSecOps and also provides insights into infrastructure DevSecOps.
The integration of today’s most popular and important tools is illustrated at each stage of the DevOps life cycle.
The E|CDE program helps DevSecOps engineers develop and enhance their knowledge and skills in securing applications at all stages of the DevOps pipeline.

Course Objectives

Understand the DevSecOps toolchain and security controls in the DevOps automated pipeline.
Adopt security practices such as gathering security requirements, modeling threats, and securing code reviews within the development workflow.
Learn AWS and Azure DevSecOps tools for securing applications.
Integrate tools and practices to build continuous feedback in the DevSecOps pipeline using Jenkins and Microsoft Teams email notifications.
Audit code pushes, pipelines, and compliances using various logging tools and monitoring logs like Sumo Logic, Datadog, Splunk, ELK, and Nagios.

Course Content

This EC-Council course covers the integration and automation of all the widely used DevSecOps tools, processes, and methodologies that help organizations quickly build secure applications. E|CDE trains students in DevSecOps for cloud-based networks, including Amazon Web Services and Microsoft Azure. Our program has over 80 skill-based labs that teach security and tools integration at all eight DevOps stages.

MODULE 01 | Understanding DevOps Culture
MODULE 02 | Introduction to DevSecOps
MODULE 03 | DevSecOps Pipeline—Plan Stage
MODULE 04 | DevSecOps Pipeline—Code Stage
MODULE 05 | DevSecOps Pipeline—Build and Test Stage
MODULE 06 | DevSecOps Pipeline—Release and Deploy Stage
MODULE 07 | DevSecOps Pipeline—Operate and Monitor Stage

Course Overview

The Value Stream Management Foundation course from Value Stream Management Consortium, and offered in partnership with DevOps Institute, is an introductory course taking learners through a value stream management implementation journey. It considers the human, process, and technology aspects of this way of working and explores how optimizing value streams for flow and realization positively impacts organizational performance.

Course Objectives

Describe the origins of value stream management and key concepts such as flow, value, and delivery
Describe what value stream management is, why it’s needed and the business benefits of its practice
Describe how lean, agile, DevOps, and ITSM principles contribute to value stream management
Identify and describe value streams, where they start and end, and how they interconnect
Identify value stream roles and responsibilities
Express value streams visually using mapping techniques, define current and target states and hypothesis backlog
Write value stream flow and realization optimization hypotheses and experiments
Apply metrics such as touch/processing time, wait/idle time, and cycle time to value streams
Understand flow metrics and how to access the data to support data-driven conversations and decisions
Examine value realization metrics and aligning to business outcomes, and how to
sense and respond to them (outcomes versus outputs)
Architect a DevOps toolchain alongside a value stream and data connection points
Design a continuous inspection and adaptation approach for organizational evolution

Course Overview

The SRE (Site Reliability Engineering) Practitioner course introduces ways to economically and reliably scale services in an organization. It explores strategies to improve agility, cross-functional collaboration, and transparency of health of services towards building resiliency by design, automation and closed loop remediations.

The course aims to equip participants with the practices, methods, and tools to engage people across the organization involved in reliability through the use of real-life scenarios and case stories. Upon completion of the course, participants will have tangible takeaways to leverage when back in the office such as implementing SRE models that fit their organizational context, building advanced observability in distributed systems, building resiliency by design and effective incident responses using SRE practices.

The course is developed by leveraging key SRE sources, engaging with thought-leaders in the SRE space and working with organizations embracing SRE to extract real-life best practices and has been designed to teach the key principles & practices necessary for starting SRE adoption.

This course positions learners to successfully complete the SRE Practitioner certification exam.

Course Objectives

At the end of the course, the following learning objectives are expected to be achieved:

Practical view of how to successfully implement a flourishing SRE culture in your organization.
The underlying principles of SRE and an understanding of what it is not in terms of anti-patterns, and how you become aware of them to avoid them.
The organizational impact of introducing SRE.
Acing the art of SLIs and SLOs in a distributed ecosystem and extending the usage of Error Budgets beyond the normal to innovate and avoid risks.
Building security and resilience by design in a distributed, zero-trust environment.
How do you implement full stack observability, distributed tracing and bring about an Observability-driven development culture?
Curating data using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build clean data lineage.
Why is Platform Engineering so important in building consistency and predictability of SRE culture?
Implementing practical Chaos Engineering.
Major incident response responsibilities for a SRE based on incident command framework, and examples of anatomy of unmanaged incidents.
Perspective of why SRE can be considered as the purest implementation of DevOps.
SRE Execution model
Understanding the SRE role and understanding why reliability is everyone’s problem.
SRE success story learnings

Course Content

Course Introduction

Module 1: SRE Anti-patterns

Module 2: SLO is a Proxy for Customer Happiness

Module 3: Building Secure and Reliable Systems

Module 4: Full-Stack Observability

Module 5: Platform Engineering and AIOPs

Module 6: SRE & Incident Response Management

Module 7: Chaos Engineering

Module 8: SRE is the Purest form of DevOps

Post-class assignments/exercises

Course Overview

Microservices and Cloud-Native architectures have been goals of many organizations to help increase speed and agility, but as complexity grows, systems become increasingly challenging to observe. When issues occur, these issues are often difficult to triage and identify the root causes. This course introduces a range of practices for advancing resilience and how to architect end-to-end Observability for Cloud-Native applications. The advantages of building full-stack metrics, events, logs, and distributed tracing are introduced, along with the impact of DevSecOps on Observability and how AIOPs enhance Observability capabilities. This course also covers how Network and Security Observability plays a key role in building reliability, the key aspects of security operations and automated responses are covered,

The course aims to equip participants with the practices, methods, and tools to engage people across the organization involved in Observability by using real-life scenarios and case stories. Upon completion of the course, participants will have tangible takeaways to leverage situations such as implementing MELT models effectively, that fit their organizational context, building distributed tracing and resiliency by design.

The course is developed by leveraging key experts in the fields of telemetry, sources of knowledge and engaging with thought-leaders in the Observability space, and working with organizations who have crossed the chasm of modern Observability to extract real-life best practices.

This course positions learners to successfully complete the Observability Foundation certification exam.

Course Objectives

At the end of the course, the following learning objectives are expected to be achieved:

Practical view of how to successfully implement a flourishing Observability culture in your organization
The underlying principles of Observability and an understanding why monitoring on its own will not provide the required results in microservices based containerized environments
Understanding the three pillars of Observability
Adopting open Telemetry standards helps achieve innovation and distributed tracing in a seamless manner
Observability Maturity Model and the measurement of practical observability
Implementing full stack Observability and distributed tracing will enable a DevSecOps culture
Curating Observability using AI to move from reactive to proactive and predictive incident management. Also, how you use DataOps to build a clean data lineage of observable data.
Implementing Network, Container level Observability and why is security a first class citizen in building the Observability culture
What is Time based Topology, and how does it add value in Observability for a distributed environment
The Data paradox,and how we address data issues using a systematic approach (DataOps) to build a clean Observability pipeline
How do we feedforward DevSecOps wisdom into Observability
Observability practices for DevSecOps and SRE

Course Content

Course Introduction

Module 1: Exploring Observability

Module 2: Pillars of Observability

Module 3: Open Source Landscape for Observability

Module 4: Service Maps and Topology

Module 5: DataOps Helps Get Observability Right

Module 6: Building Observability with AIOps

Module 7: Security and Networking with Observability

Module 8: Observability Practices for DevOps and SRE

Course Overview

The DevSecOps Practitioner course is intended as a follow-on to the DevSecOps Foundation course. The course builds on previous understanding to dive into the technical implementation. Each section highlights useful metrics as well as integrating new techniques into differing practices. These modules offer suggestions on how to overcome people, process, and technological issues to develop better DevSecOps outcomes. Beginning with a deeper dive into the surrounding concepts, the course then considers either using existing metrics or developing unique expressions suitable to each DevOps experience. The middle section looks at architecture transitions, building an infrastructure, and tuning the CI/CD pipeline to best effect. Finally, the course offers ways to get the best from your experimentation practices and considers where the future of DevSecOps may lead.

The DevsecOps Practitioner course introduces more advanced ways to explore DevSecOps in your organization. Each section covers practical maturity guides, and then discusses how people, process and technology can be combined to improve outcomes.

The course aims to equip participants with the practices, methods, and tools to engage people across the organization involved in reliability through the use of real-life scenarios and case stories. Upon completion of the course, participants will have tangible takeaways to leverage when back in the office such as implementing DevSecOps practices to their organizational structure, building better pipelines in distributed systems, and having a common technological language.

The course is developed by leveraging key DevSecOps sources, engaging with thought-leaders in the space and working with organizations to extract real-life best practices and has been designed to teach the key principles & practices necessary for successful DevSecOps practices.

This course positions learners to successfully complete the DevSecOps Practitioner certification exam.

Please note: It is highly recommended that learners complete the DevOps Institute DevSecOps Foundation course and certification prior to taking the DevSecOps Practitioner course and exam.

Course Objectives

At the end of the course, the following learning objectives are expected to be achieved:

Comprehend the underlying principles of DevSecOps
Distinguish between the technical elements used across DevSecOps practices
Demonstrate how practical maturity concepts can be extended across multiple areas.
Implement metric-based assessments tied to your organization.
Recognize modern architectural concepts including microservice to monolith transitions.
Recognize the various languages and tools used to communicate architectural concepts.
Contrast the options used to build a DevSecOps infrastructure through Platform as a Service, Server-less construction, and event-driven mediums
Prepare hiring practices to recognize and understand the individual knowledge, skills, and abilities required for mature Dev.
Identify the various technical requirements tied to the DevSecOps pipelines and how those impact people and process choices.
Review various approaches to securing data repositories and pipelines.
Analyze how monitoring and observability practices contribute to valuable outcomes.
Comprehend how to implement monitoring at key points to contribute to actionable analysis.
Evaluate how different experimental structures contribute to the 3rd Way.
Identify future trends that may affect DevSecOps

Course Content

Course Introduction
Module 1: DevSecOps Advanced Basics
Module 2: Understanding Applied Metrics
Module 3: Architecting and Planning for DevSecOps
Module 4: Creating a DevSecOps Infrastructure
Module 5: Establishing a Pipeline
Module 6: Observing DevSecOps Outcomes
Module 7: Practical 3rd Way Applications
Module 8: The Future of DevOps