Course Overview

This course provides an introduction to Agile Service Management, the application and integration of agile thinking into service management processes. Agile thinking improves IT’s effectiveness and efficiency and enables IT to continue to deliver value in the face of changing requirements.

IT Service Management (ITSM) focuses on ensuring IT services deliver value by understanding and optimizing their end-to-end value streams. This course cross-pollinates Agile and ITSM practices to support end-to-end Agile Service Management by scaling to “just enough” process leading to improved flow of work and time to value.

Agile Service Management helps IT to meet customer requirements faster, improve the collaboration between Dev and Ops, overcome constraints in process workflows by taking an iterative approach to process engineering that will improve the velocity of process improvement teams to get more done.

This course positions learners to successfully complete the CASM exam.

Certified Agile Service Manager (CASM)® is a registered trademark of the PeopleCert group. Used under licence from PeopleCert. All rights reserved.

Course Objectives

After you complete this course you will be able to:

Recognise the learning objectives for Certified Agile Service Manager (CASM) include an understanding of:

  • What does it mean to “be agile?”
  • The Agile Manifesto, its core values, and principles
  • Adapting Agile thinking and values into service management
  • Agile concepts and practices including DevOps, ITIL®, SRE, Lean and Scrum
  • Scrum roles, artifacts and events as it applies to processes
  • The two aspects of Agile Service Management:
    • 1 – Agile Process Improvement – ensuring processes are lean and deliver “just enough” control
    • 2 – Agile Process Engineering – applying Agile practices to process engineering projects

Course Content

Module 1: Why Agile Service Management?

  • Challenges Today
  • What is IT Service Management?
  • What is Agile?
  • Agile Manifesto and Principles
  • What Does It Take To Be Agile?

Module 2: Agile Service Management

  • What is Agile Service Management?
  • Agile Service Management Goals, Objectives and Benefits
  • Two Aspects
    • Agile Process Engineering
    • Agile Process Improvement

Module 3: Leveraging Related Guidance

  • DevOps
  • ITIL
  • Site Reliability Engineering
  • Lean
  • Scrum

Module 4: Agile Service Management Roles

  • Relationship to Scrum roles
  • Agile Practice Owner
  • Agile Service Management Team
  • Agile Service Manager

Module 5: Agile Process Engineering

  • Agile Processes
  • How Processes Deliver Value
  • Waterfall vs Agile Process Engineering
  • Relationship to Scrum Events & Artifacts
  • Minimum Viable Process
  • Microprocess Architectures
  • Service Management Architecture

Module 6: Agile Service Management Artifacts

  • Practice Backlog
  • Spring Backlog
  • Increment

Module 7: Agile Service Management Events

  • Planning
  • The Sprint
  • Sprint Planning
  • Process Standups
  • Sprint Review
  • Sprint Retrospective

Module 8: Agile Process Improvement

  • Why Process Improvement is Important
  • Process Improvement Goals
  • Process Improvement Reviews
  • Sustaining Improvements
  • Automation

Course Overview

This AIOps Foundation (AIOF)®  course aims to cover the origins of AIOps including the history behind the term, patterns that preceded it and the technology context in which it has evolved. Learners will gain an understanding of the processes of combining big data analytics, machine learning algorithms, automation, and optimization into a single platform.

This course introduces key principles and foundational concepts along with the core technologies of AIOps: big data and machine learning. The course will provide students with an understanding of how and why digital transformation, together with the evolution of machine learning, have brought about the rise of AIOps as an indispensable tool in today’s IT Operational landscape.

Core technologies of machine learning and big data will be discussed, as well as the basic concepts of artificial intelligence, different types of machine learning models that can be implemented, and the relationship between AIOps and MLOps, DevOps and Site Reliability.

This foundation course will also provide the student with a solid understanding of the benefits of implementing AIOps in the organization, including common challenges and key steps in ensuring valuable and successful integration of artificial intelligence in the day to day operations of information technology solutions.

Unique and exciting exercises will be used to apply the concepts covered in the course and sample documents, templates, tools, and techniques will be provided to use after the class.

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

AIOps Foundation (AIOF)® is a registered trademark of the PeopleCert group. Used under licence from PeopleCert. All rights reserved.

Course Objectives

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

  • Clear understanding of the history, origins and current developments of AIOps
  • Define and comprehend basic concepts and key principles within AIOps
  • Understand general concepts of big data and artificial intelligence, and how they relate to AIOps
  • Recognize the relationship between AIOps and MLOps
  • Understand the effectiveness of AIOps deployment and possible benefits
  • Understand the changes in mindset, collaboration and skills for AIOps to be applied in the organization
  • Quantify outcomes of an AIOps implementation leveraging industry standard metrics
  • Understand usual challenges and opportunities of applying AIOps in the organization
  • Visualize the challenges, trends and ethical considerations organizations might face while deploying an AIOps initiative

Course Content

Course Introduction

Module 1: AIOps Foundation

Module 2: AIOps in the Organization

Module 3: Core Technologies: Data

Module 4: Core Technologies: Machine Learning (ML)

Module 5: AIOPs and Operations Metrics

Module 6: AIOps Use Cases and Organizational Mindset

Module 7: Evaluating AIOps Impact

Module 8: Implementing AIOps in the Organization

Course Overview

This 2-day course provides a comprehensive introduction to DASA DevOps Fundamentals – Agile DevOps principles, as defined by the DevOps Agile Skills Association (DASA). In this course, you will learn the DevOps vocabulary, principles and practices. Using DevOps key concepts and terminology, real-life case studies, examples, group discussions and exercises you will get a basic understanding of DevOps.

Course Objectives

After completion of the course, students will be familiar with the following aspects of DevOps:

 Core concepts

  • The rise of DevOps
  • Core concepts and principles of DevOps
  • Meaning of DevOps as a professional for you and for your organization

 Culture

  • The essence of a DevOps culture
  • The most important elements of a DevOps culture
  • The important aspects in creating a DevOps culture

 Organization

  • The operational models of DevOps
  • The need for autonomous teams
  • The impact of DevOps on Architecture in relation to deployment
  • Governance within DevOps teams

 Processes

  • Relations between Agile, Scrum and Kanban
  • ITSM processes relating to the practices in a DevOps culture
  • Use of lean to optimize processes
  • Delivering a Value Stream Folder for a particular process
  • Initiating new and innovative ideas

 Automation

  • The impact of automation on Software Delivery processes
  • The benefits and core principles of Continuous Delivery
  • The main cloud principles for DevOps organizations

 Measuring & Improvements

  • Importance of monitoring and logging of DevOps

Course Content

In the training covers the following topics:

Module 1: Introduction

Module 2: DevOps Introduction

  • Emergence of DevOps
  • Core concepts of DevOps
  • DevOps Agile Skills Association (DASA)

 Module 3: Culture

  • Introduction DevOps Culture
  • Key elements of DevOps
  • Implementation of a DevOps culture

 Module 4: Organization

  • Organizational model
  • Autonomous teams
  • Architecture within DevOps
  • Governance

 Module 5: Processes

  • Defining Agile, Scrum and Kanban
  • DevOps in relation to ITSM
  • Scrum, in more detail
  • Optimizing processes – Lean
  • Business Value Optimization and Business Analysis – Story Mapping
  • Software Delivery Lifecycle in a DevOps organization

 Module 6: Automation

6a. Automation Concepts

  • Software Delivery Automation
  • Continuous Delivery Core concepts
  • Continuous Delivery Automation concepts
  • Continuous Delivery Automation focus topics

6B. Data Centre Automation

  • Emergence of Cloud technology and principles
  • Cloud Services concepts in a DevOps organization
  • Automated Provisioning concepts
  • Platform Product Characteristics and Application Maturity

Module 7: measuring and improving

  • Importance of Measurements
  • Choosing the right Metrics
  • Monitoring and Logging

 Tips for the exam

Sample exam

Course Overview

Explore DevOps practices using GitHub.

Your development and operations teams will experience improved collaboration, agility, continuous integration, continuous delivery, automation, and operational excellence throughout all phases of the application lifecycle.

Course Objectives

Students will learn to:

  • Discover DevOps
  • Plan with DevOps
  • Develop with DevOps
  • Deliver with DevOps
  • Operate with DevOps

Course Content

Module 1: Discover DevOps

  • Describe the DevOps approach.
  • Explore best practices for fostering DevOps culture.
  • Identify DevOps goals and benefits.
  • Understand the DevOps application lifecycle.

Module 2: Plan with DevOps

  • Describe the components of and the path to a DevOps culture.
  • Define the frameworks and methods of the Agile methodology.
  • Implement DevOps practices.
  • Use GitHub to plan a project.

Module 3: Develop with DevOps

  • Define source control and version control.
  • Describe how to manage source control with Git.
  • Describe how to manage source control with GitHub Flow.
  • Define the concept of continuous integration.
  • Explore DevOps shift-left testing scenarios.
  • Explore DevOps shift-left security scenarios.

Module 4: Deliver with DevOps

  • Define the concept of continuous delivery.
  • Describe the concept and implementation methods of IaC.
  • Review the progressive exposure techniques and deployment practices.
  • Explore DevOps shift-right testing scenarios.
  • Describe how to implement continuous delivery with GitHub Actions.

Module 5: Operate with DevOps

  • Explore the concepts of operational excellence.
  • Review infrastructure and application monitoring solutions.
  • Review infrastructure and application security monitoring solutions.
  • Describe the correlation between SRE and DevOps.

Course Overview

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.

Course level: Intermediate

Duration: 3 days

Course Objectives

In this course, you will:

  • Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS
  • List the advantages, roles and responsibilities of small autonomous DevOps teams
  • Design and implement an infrastructure on AWS that supports DevOps development projects
  • Leverage AWS Cloud9 to write, run and debug your code
  • Deploy various environments with AWS CloudFormation
  • Host secure, highly scalable, and private Git repositories with AWS CodeCommit
  • Integrate Git repositories into CI/CD pipelines
  • Automate build, test, and packaging code with AWS CodeBuild
  • Securely store and leverage Docker images and integrate them into your CI/CD pipelines
  • Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications
  • Implement common deployment strategies such as “all at once,” “rolling,” and “blue/green”
  • Integrate testing and security into CI/CD pipelines
  • Monitor applications and environments using AWS tools and technologies

Course Content

Day 1

Module 0: Course overview

  • Course objective
  • Suggested prerequisites
  • Course overview breakdown

Module 1: Introduction to DevOps

  • What is DevOps?
  • The Amazon journey to DevOps
  • Foundations for DevOps

Module 2: Infrastructure Automation

  • Introduction to Infrastructure Automation
  • Diving into the AWS CloudFormation template
  • Modifying an AWS CloudFormation template
  • Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection

Module 3: AWS Toolkits

  • Configuring the AWS CLI
  • AWS Software Development Kits (AWS SDKs)
  • AWS SAM CLI
  • AWS Cloud Development Kit (AWS CDK)
  • AWS Cloud9
  • Demonstration: AWS CLI and AWS CDK
  • Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure

Module 4: Continuous integration and continuous delivery (CI/CD) with development tools

  • CI/CD Pipeline and Dev Tools
  • Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline
  • Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy

Day 2

Module 4: Continuous integration and continuous delivery (CI/CD) with development tools

  • AWS CodePipeline
  • Demonstration: AWS integration with Jenkins
  • Hands-on lab: Automating code deployments using AWS CodePipeline

Module 5: Introduction to Microservices

  • Introduction to Microservices

Module 6: DevOps and containers

  • Deploying applications with Docker
  • Amazon Elastic Container Service and AWS Fargate
  • Amazon Elastic Container Registry and Amazon Elastic Kubernetes service
  • Demonstration: CI/CD pipeline deployment in a containerized application

Module 7: DevOps and serverless computing

  • AWS Lambda and AWS Fargate
  • AWS Serverless Application Repository and AWS SAM
  • AWS Step Functions
  • Demonstration: AWS Lambda and characteristics
  • Demonstration: AWS SAM quick start in AWS Cloud9
  • Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline

Module 8: Deployment strategies

  • Continuous Deployment
  • Deployments with AWS Services

Module 9: Automated testing

  • Introduction to testing
  • Tests: Unit, integration, fault tolerance, load, and synthetic
  • Product and service integrations

Day 3

Module 10: Security automation

  • Introduction to DevSecOps
  • Security of the Pipeline
  • Security in the Pipeline
  • Threat Detection Tools
  • Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector

Module 11: Configuration management

  • Introduction to the configuration management process
  • AWS services and tooling for configuration management
  • Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS)

Module 12: Observability

  • Introduction to observability
  • AWS tools to assist with observability
  • Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations

Module 13: Reference architecture (Optional module)

  • Reference architectures

Module 14: Course summary

  • Components of DevOps practice
  • CI/CD pipeline review
  • AWS Certification

Course Overview

Automate and streamline your DevOps processes with expert guidance and hands-on experience.

DevOps Automation is designed to equip IT professionals and DevOps practitioners who want to enhance their skills in automating and streamlining software development and deployment processes. This course covers a broad spectrum of topics, including Continuous Integration and Continuous Deployment (CI/CD) pipelines, Infrastructure as Code (IaC), containerization, orchestration, monitoring, and security practices. Participants will learn to use tools like Jenkins, GitHub Actions, Terraform, Docker, Kubernetes, Prometheus, and Grafana to automate the creation, modification, and deletion of infrastructure resources, ensuring efficient and scalable deployments.

Through hands-on labs and real-world scenarios, participants will gain practical experience in implementing DevOps best practices and optimizing cloud automation strategies. This course also highlights the importance of integrating security into DevOps workflows, ensuring that automated processes are secure and compliant.

By the end of the course, attendees will be equipped to design and implement fully automated DevOps workflows that integrate CI/CD, IaC, monitoring, and security, ultimately improving the efficiency and reliability of their software development and deployment processes. This course is ideal for professionals aiming to stay ahead in the rapidly evolving field of DevOps and automation.

Course Objectives

  • Explain the core principles of DevOps and the role of automation in modern software development
  • Configure CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI to automate software builds and deployments  
  • Implement Infrastructure as Code (IaC) using Terraform or Ansible to automate provisioning and configuration  
  • Containerize applications using Docker and deploy them with Kubernetes for automated orchestration.  
  • Monitor and analyze system performance using Prometheus, Grafana, and log management tools.
  • Secure DevOps workflows by integrating DevSecOps practices, including automated security scans and policy enforcement.  
  • Optimize cloud automation strategies by leveraging AWS, Azure, or GCP services for efficient resource management.  
  • Design a fully automated DevOps workflow that integrates CI/CD, IaC, monitoring, and security 

Course Content

1- Introduction to DevOps and Automation

  • Overview of DevOps principles and practices.
  • Importance of automation in DevOps.

2- CI/CD Pipelines

  • Setting up and configuring CI/CD pipelines.
  • Integrating CI/CD with version control systems. 

3- Version Control Systems

  • Using Git for version control.
  • Branching and merging strategies. 

4- Infrastructure as Code (IaC) Concepts and Tools

  • Introduction to IaC and its benefits.
  • Using Terraform and other IaC tools.

5- Containerization and Orchestration

  • Introduction to Docker and Kubernetes.
  • Deploying applications using containers and orchestration tools. 

6- Monitoring and Logging Tools

  • Setting up monitoring and logging for infrastructure.
  • Using tools like Prometheus, Grafana, and ELK stack. 

7- Automation Scripting and Tools

  • Writing scripts to automate tasks.
  • Using tools like Ansible and Chef. 

8- Configuration Management and Provisioning

  • Managing infrastructure configurations.
  • Provisioning resources using configuration management tools. 

9- Best Practices for Scaling and Optimizing Deployments

  • Ensuring efficient and scalable deployments.
  • Tools and techniques for optimization.

Course Overview

Gain expertise in Git and GitHub to streamline your development workflow and enhance team collaboration.

Developing with Git and GitHub is designed to provide software developers, DevOps engineers, cybersecurity specialists, technical project managers, and data scientists with a comprehensive understanding of Git and GitHub. This intermediate-level course spans three days and offers a blend of theoretical knowledge and hands-on practice, ensuring participants gain practical skills in version control and collaborative development.

Throughout the class, participants will learn to define Git’s architecture, execute foundational Git operations, and implement effective remote repository operations. You will also explore advanced GitHub features such as project management tools, security best practices, and CI/CD pipelines using GitHub Actions. By the end of the course, attendees will be proficient in leveraging GitHub’s capabilities to enhance team collaboration, manage code changes, and streamline development workflows.

This course is ideal for professionals looking to deepen their understanding of version control systems and improve their collaborative development skills. Participants will leave with the ability to set up and utilize GitHub’s project management tools, design effective CI/CD pipelines, and develop custom development environments with GitHub Codespaces. Whether you’re aiming to enhance your team’s productivity or advance your career, this course provides the essential knowledge and skills needed to succeed in today’s fast-paced development environment.

Course Objectives

  • Define Git’s architecture including Working Directory, Staging Area, and Repository
  • Explain how Git’s backtracking and recovery mechanisms work for code safety
  • Describe GitHub’s role in enabling team collaboration through remote repositories
  • Execute foundational Git operations including staging, committing, and managing branches
  • Implement effective remote repository operations including fetch, pull, and push
  • Set up and utilize GitHub’s project management tools including Issues and Project Boards
  • Examine repository histories to track and understand code changes over time
  • Investigate and resolve merge conflicts in collaborative environments
  • Compare different security approaches including SSH keys and two-factor authentication
  • Design effective CI/CD pipelines using GitHub Actions
  • Develop custom development environments with GitHub Codespaces
  • Construct efficient coding workflows leveraging GitHub Copilot’s AI capabilities

Course Content

Git Fundamentals

  • Introduction to Version Control and Git
  • What is Git?
  • Git vs Other Version Control Systems
  • Git Architecture Overview
  • Working Directory, Staging Area, and Repository
  • Basic Git Workflow
  • Git Configuration and Setup (git config)
  • Git Operations
  • Repository Initialization (git init)
  • Staging Files (git add, git status)
  • Creating Meaningful Commits (git commit)
  • Viewing and Understanding History (git log)
  • Understanding HEAD
  • Best Practices for Commits
  • .gitignore Files
  • Backtracking and Recovery
  • Git Reset Types (git reset)
  • Git Checkout (git checkout)
  • Reverting Changes
  • Managing the Staging Area (git diff)
  • Temporary Storage with Stash (git stash)
  • Recovery Strategies
  • Git Reflog
  • Branching and Merging
  • Branch Concept and Purpose
  • Creating and Managing Branches (git branch)
  • Branch Naming Conventions
  • Merging Fundamentals (git merge)
  • Handling Merge Conflicts

GitHub Fundamentals and Collaboration

  • Introduction to GitHub
  • What is GitHub?
  • Creating and Setting Up Account
  • GitHub vs Git
  • Repository Creation and Settings
  • GitHub Interface Overview
  • Repository Templates
  • Remote Operations
  • Connecting Local to Remote (git remote)
  • Remote Repository Management
  • Cloning Repositories (git clone)
  • Fetch vs Pull (git fetch, git pull)
  • Push Operations (git push)
  • Tracking Branches
  • File Management Commands (git rm, git mv)
  • Collaborative Workflows
  • Understanding Fork vs Clone
  • Pull Requests
  • Code Review Process
  • Branch Protection Rules
  • Contributing Guidelines
  • Merge Strategies
  • Resolving Conflicts in Pull Requests
  • GitHub Project Management
  • Issues and Milestones
  • Project Boards
  • Markdown Documentation
  • Wiki Pages
  • README Best Practices

Advanced GitHub Features

  • GitHub Security (1.5 hours)
  • Personal Access Tokens
  • SSH Keys Setup
  • Two-Factor Authentication
  • Repository Security Settings
  • Access Management
  • Security Best Practices
  • GitHub Actions
  • CI/CD Concepts
  • Understanding Workflows
  • Creating Custom Actions
  • Workflow Triggers
  • Environment Variables and Secrets
  • Common Use Cases
  • Testing and Deployment
  • Advanced History Commands (git rebase, git show)
  • GitHub Codespaces
  • Development Environments
  • Customizing Codespaces
  • github.dev Overview
  • Performance Considerations
  • Cost Management
  • Best Practices
  • GitHub Copilot
  • AI-Assisted Development
  • Setting Up Copilot
  • Effective Prompting
  • Code Suggestions and Completions
  • Best Practices and Limitations
  • Security Considerations

Course Overview

In this course, application developers learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

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

This course teaches participants the following skills:

  • Use best practices for application development.
  • Choose the appropriate data storage option for application data.
  • Implement federated identity management.
  • Develop loosely coupled application components or microservices.
  • Integrate application components and data sources.
  • Debug, trace, and monitor applications.
  • Perform repeatable deployments with containers and deployment services.
  • Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex.

Course Content

Module 1: Best Practices for Application Development

  • Code and environment management
  • Design and development of secure, scalable, reliable, loosely coupled application components and microservices
  • Continuous integration and delivery
  • Re-architecting applications for the cloud

Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK

  • How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
  • Lab: Set up Google Client Libraries, Google Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials

Module 3: Overview of Data Storage Options

  • Overview of options to store application data
  • Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner

Module 4: Best Practices for Using Cloud Datastore

  • Best practices related to the following: Queries, Built-in and composite indexes, Inserting and deleting data (batch operations), Transactions, Error handling
  • Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow
  • Lab: Store application data in Cloud Datastore

Module 5: Performing Operations on Buckets and Objects

  • Operations that can be performed on buckets and objects
  • Consistency model
  • Error handling

Module 6: Best Practices for Using Cloud Storage

  • Naming buckets for static websites and other uses
  • Naming objects (from an access distribution perspective)
  • Performance considerations
  • Setting up and debugging a CORS configuration on a bucket
  • Lab: Store files in Cloud Storage

Module 7: Securing Your Application

  • Cloud Identity and Access Management (IAM) roles and service accounts
  • User authentication by using Firebase Authentication
  • User authentication and authorization by using Cloud Identity-Aware Proxy
  • Lab: Authenticate users by using Firebase Authentication

Module 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application

  • Topics, publishers, and subscribers
  • Pull and push subscriptions
  • Use cases for Cloud Pub/Sub
  • Lab: Develop a backend service to process messages in a message queue

Module 9: Adding Intelligence to Your Application

  • Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API.

Module 10: Using Cloud Functions for Event-Driven Processing

  • Key concepts such as triggers, background functions, HTTP functions
  • Use cases
  • Developing and deploying functions
  • Logging, error reporting, and monitoring

Module 11: Using Cloud Endpoint to Deploy APIs

  • Open API deployment configuration
  • Lab: Deploy an API for your application

Module 12: Debugging Your Application by Using Google Stackdriver

  • Stackdriver Debugger
  • Stackdriver Error Reporting
  • Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting

Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager

  • Creating and storing container images
  • Repeatable deployments with deployment configuration and templates
  • Lab: Use Deployment Manager to deploy a web application into Google App Engine Flex test and production environments

Module 14: Execution Environments for Your Application

  • Considerations for choosing an execution environment for your application or service: Google Compute Engine, Container Engine, App Engine Flex, Cloud Functions, Cloud Dataflow
  • Lab: Deploying your application on App Engine Flex

Module 15: Monitoring and Tuning Performance

  • Best practices and watchpoints for performance
  • Key concepts related to Stackdriver Trace and Stackdriver Monitoring
  • Detecting and resolving performance issues
  • Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance

Course Overview

This course complies with instructional designing principles for all the 6 lessons. This will ensure that you repeat and reinforce your gained knowledge at every step. Each and every minute spent during this 2-day course will incrementally take you to a next level.

Course Objectives

If you are interested in gaining a good grasp of Jenkins in a systematic and hands-on way by working through a real-world project, then this course is for you.

The course will provide enough knowledge of the following:

  • Illustrate continuous integration and continuous delivery concepts
  • Analyse how to install and setup Jenkins on Windows
  • Administer and secure Jenkins
  • Set up projects on Jenkins
  • Build continuous delivery pipelines with Jenkins
  • Identify how to setup distributed builds and scale Jenkins

Course Content

LESSON 1- Installing and Setting up Jenkins

  • Continuous Delivery
  • Installing Jenkins
  • The Jenkins Dashboard
  • User Management

LESSON 2 Administering Jenkins

  • Plugin Management
  • Updating & Upgrading Jenkins
  • Configuring Jenkins for Production
  • Creating a Form with a Select Element

LESSON 3- Jenkins Views and Setting up Freestyle Projects

  • Setting up a Freestyle Project
  • Setting up a View to Manage our Projects

LESSON 4- Parameterized Projects and Upstream/Downstream Projects

  • Configuring Parameters for our Projects
  • Creating & Accessing Build Parameters
  • Build Triggers

LESSON 5- Multibranch and Declarative Jenkins Pipelines

  • The CI Workflow
  • The Jenkinsfile
  • Creating Multi-Branch Pipelines

LESSON 6- Distributed Builds on Jenkins

  • Setting up Our Slaves
  • Securely Connecting To Our Slaves
  • Configuring Tasks To Run On Our Slaves

Course Overview

This is a 1-day course packaged with the perfect balance of theory and hands-on activities that will help you learn Docker from scratch.
 
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 the next level.

Course Objectives

If you are interested in gaining a good grasp of Docker in a systematic and hands-on way by working through a real-world project, then this course is for you.

The course will provide enough knowledge of the following:

  • Docker and DevOps, why and how they integrate
  • What containers are, how to create and manage them
  • Scaling a delivery pipeline and multiple deployments with Docker
  • Orchestration and delivery of containerized applications

Course Content

Course Outline
 
Lesson 1: Images and Containers

  • How Docker Improves a DevOps Workflow
  • Basic Docker Terminal Commands
  • Dockerfile Syntax
  • Building Images
  • Running Containers From Images
  • Versioning Images and Docker Hub
  • Deploying a Docker Image to Docker Hub

Lesson 2: Application Container Management

  • The docker-compose Tool
  • Overview of a Multi-Container Application Setup
  • Managing Multiple Containers and Distributed Application Bundles
  • Networking with docker-compose

Lesson 3: Orchestration and Delivery

  • An Overview of Docker Swarm
  • Using Docker Engine to Create a Swarm
  • Managing Services and Applications in a Swarm
  • Scaling Services Up and Down