Kubernetes Custom Training

Public Training

Designed for employees working remotely, these training courses provide a quick overview of core Kubernetes topics. During the courses, students will get the necessary theoretical and practical knowledge in a short period of time. Below, you can choose a program that fits your needs.

Kubernetes Custom Training

Duration

2 days

Delivery format

Online, Hands-on, Instructor-led

Price

$2,300

Who should attend

  • Developers, DevOps engineers, and application architects

Why enroll

Transfer an application from code to a container running in Kubernetes

Acquire experience in different approaches to deploying Kubernetes workloads

Learn to enable application stability, manage configuration, ensure statefulness, and implement repeatable deployments

Benefits

Remote training requirements

  • Access to Zoom. You can install a client (preferable) or use a web application.
  • Access to either Amazon Web Services (AWS) or Google Cloud Platform (GCP). The accounts will be provided.
  • Access to GitHub.

Training program

No better time to maximize your team's talent! Design custom program

Mandatory topics
- Cannot be unselected

  • Course introduction

    10 min

    Theory

    • An introduction
    • Useful links for the course
    • The agenda
    • The schedule
    • An overview of the training methodology
  • Introduction to Kubernetes

    0.5 hour

    Theory

    • Problem statement
    • Kubernetes features
    • Cloud Native Computing Foundation
    • Infrastructure as a Service vs. Containers as a Service vs. Platform as a Service

    Practice

    • Setting up Google Cloud Shell
    • Deploying Kubernetes with Google Kubernetes Engine

Kubernetes basics

  • Kubernetes API objects

    0.5 hour

    Theory

    • Pods
    • Deployments
    • StatefulSets
    • DaemonSets
    • Jobs
    • ConfigMaps
    • Other objects

    Practice

    • Introducing API objects and providing a basic layout
    • Demonstrating kubectl explain, exploring various objects
  • Containers

    1.5 hours

    Theory

    • Different ways of packaging software
    • Container benefits
    • Container implementation
    • A sample application architecture

    Practice

    • Using Dockerfile to package a sample application into a container
    • Running the application in the container
    • Exposing ports
    • Mounting volumes
    • Switching between containers using DNS
    • Deploying the container using the host and bridge modes, examining the difference
    • Uploading an image to a container registry
  • Pods

    1.5 hours

    Theory

    • Pods
    • Pod’s life cycle
    • A multi-container pod design
    • Kubernetes patterns (Ambassador, Adapter, and Sidecar)

    Practice

    • Deploying a sample application to Kubernetes
    • Deploying a pod with a custom image
    • Using the exec command to connect to the deployed container, running inside a pod
    • Deploying an init container that runs application database migrations
  • Deployments

    1.5 hours

    Theory

    • Deployments and ReplicaSets
    • The behavior of rolling updates in a Deployment

    Practice

    • Redeploying a sample application using the Deployment object
    • Scaling a Deployment
    • Updating and rolling out a Deployment
    • Viewing Deployment history
    • Rolling back a Deployment
    • Configuring rollover parameters of a Deployment

Advanced pod configurations

  • Secrets and ConfigMaps

    0.75 hour

    Theory

    • Use cases for Secrets and ConfigMaps
    • Different ways of mapping Secrets into containers

    Practice

    • Modifying the sample application to use Secrets and ConfigMaps to externalize application credentials and configuration
  • Health checks

    1 hour

    Theory

    • The difference between livenessProbe and readinessProbe
    • Health check types (the exec command, TCP connections, and HTTP requests)

    Practice

    • Defining a custom livenessProbe
    • Defining a custom readinessProbe
    • Testing the workability of the probes
    • Experimenting with probe types
  • Container resource usage management

    0.5 hour

    Theory

    • The difference between request and limit settings in a pod
    • Limit types
    • The default behavior when limits and requests are unset

    Practice

    • Setting limits on a sample application
    • Testing the limits, observing the results
  • Volumes and data

    0.5 hour

    Theory

    • Persistence in Kubernetes
    • PersistentVolumes and PersistentVolumeClaims
    • Storage classes

Additional workloads

  • Batch processing

    0.5 hour

    Theory

    • Jobs use cases
    • The difference between jobs and CronJobs

    Practice

    • Creating a CronJob to enable automated backup of the sample application database
  • Management of clustered stateful applications

    1.5 hours

    Theory

    • StatefulSets (use cases and their difference from Deployments)
    • Using headless services in combination with StatefulSets
    • Using readinessProbes in a combination with StatefulSets

    Practice

    • Preparing a Docker image in a MySQL Galera cluster
    • Preparing a headless service to perform service discovery during the cluster bootstrap
    • Deploying the MySQL Galera cluster as a StatefulSet
    • Attaching PersistentVolumeClaim as a template to each node in a StatefulSet
  • Autoscaling

    0.75 hour

    Theory

    • The working principle of pod autoscaling
    • Horizontal vs. vertical autoscaling

    Practice

    • Defining a horizontal autoscaler for the sample application
    • Testing Autoscaler

Networking

  • Labels, selectors, and annotations

    0.5 hour

    Theory

    • Labels use and format
    • How to use selectors
    • Annotations
    • The difference between labels and annotations
    • Scenarios for choosing labels over selectors

    Practice

    • Labelling pods
    • Using selectors
    • Annotating pods
  • Services

    1 hour

    Theory

    • Service types
    • Proxy modes
    • Service discovery (the env command, DNS)

    Practice

    • Connecting sample application components together using a Service
    • Using the DNS service discovery
    • Using the LoadBalancer service to expose an application
    • Implementing a blue-green deployment pattern
  • Ingress

    0.75 hour

    Theory

    • The Ingress service vs. the LoadBalancer service
    • Types of Ingress controllers (Google Cloud Load Balancing, NGINX, etc.)
    • Configuring Ingress
    • Ingress in on-prem installations

    Practice

    • Serving the application traffic from the Ingress service instead of the LoadBalancer service
    • Using a static IP with Ingress
    • Specify an application domain
    • Adding the SSL support
  • Service meshes

    2 hours

    Theory

    • An introduction to a service mesh (common features)
    • A service mesh interface
    • Comparison of service meshes
    • Service mesh tooling (Jaeger, Kiali, and Flagger)

    Practice

    • Deploying Istio
    • Deploying sample applications
    • Observing the results with Kiali and Jaeger
  • Networking

    0.75 hour

    Theory

    • CNI plugins
    • A network policy
    • Cluster DNS
    • External load balancers

    Practice

    • Setting and testing an ingress/egress network policy

Operations

  • Managing kubernetes clusters

    0.5 hour

    Theory

    • Kubernetes installers (kubeadm, kops, Kubespray, and other services provided by a cloud platform)
    • Managed Kubernetes services
    • Cluster updates and upgrades
    • Isolating nodes with different characteristics (node pools)
  • Kubernetes components

    1 hour

    Theory

    • Kubelet
    • Kube-apiserver
    • Etcd
    • Kube-scheduler

    Practice

    • Creating a kops cluster
    • Exploring kubelet
    • Manually accessing the API
    • Manually connecting to etcd
    • Manually scheduling a pod
  • Namespaces

    0.25 hour

    Theory

    • Managing multiple teams/resources
    • Providing virtual clusters
  • Quotas

    0.5 hour

    Theory

    • Namespace level resource control
    • Stability in a cluster

    Practice

    • Creating a namespace
    • Creating a quota
    • Testing a quota
  • CI/CD

    0.5 hour

    Theory

    • Building CI/CD pipelines for Kubernetes
    • Deployment patterns (canary deployments, blue-green deployments)
  • Helm

    1.5 hours

    Theory

    • The Helm architecture
    • How to secure Helm

    Practice

    • Using Helm to deploy the ELK stack logging and Prometheus
    • Reviewing the ELK stack Helm chart
    • Writing a sample Helm chart
  • Logging and monitoring

    1.5 hours

    Theory

    • A logging architecture in Kubernetes
    • Logging patterns (the sidecar pattern, a node agent, etc.)
    • An example of the ELK architecture
    • How to monitor the architecture
    • Metric sources (container metrics, API metrics, etc.)
    • The Prometheus architecture

    Practice

    • Deploying the ELK stack and Prometheus-Operator
    • Accessing cluster components logs
    • Accessing application logs
    • Using filters in Kibana
    • Viewing dashboards in Grafana
  • Affinity and anti-affinity

    0.75 hour

    Theory

    • Pod/node affinity/anti-affinity
    • Taints and tolerations
    • Use cases

    Practice

    • Configuring node/pod affinity and anti-affinity to see how Kubernetes schedules containers

Security

  • Security overview

    0.75 hour

    Theory

    • An overview of the CIS benchmark
    • Authentication and authorization methods
    • Admission controllers
    • Securing API access
    • Pod security policies
    • Securing Docker images
  • Securing Docker images

    0.25 hour

    Theory

    • Image signing with Docker Notary
    • Common Vulnerabilities and Exposures scanning
    • Application code scanning
  • Admission controllers

    0.5 hour

    Theory

    • How to ensure images are certified and scanned for vulnerabilities
    • The ways to control what gets deployed in each namespace
  • Authentication and authorization

    1.5 hours

    Theory

    • An overview of authentication methods
    • Service accounts
    • Authorization methods
    • Role-based access control (RBAC)

    Practice

    • Creating a namespace
    • Creating ServiceAccount
    • Binding RBAC roles to ServiceAccount
    • Using a kubectl container to access Kubernetes API inside a cluster
    • Testing RBAC roles
  • Security contexts and pod security policies

    0.75 hour

    Theory

    • Security contexts
    • Pod security policies
    • How to configure a security context for a pod or container

    Practice

    • Deploying an application that needs specific root access
    • Configuring a fully restricted security context
    • Adding a required root permission to SecurityContext
  • Service accounts

    0.25 hour

    Theory

    • How to configure service accounts for pods
  • Network policies

    0.25 hour

    Theory

    • How to declare network policies

Review and recap

  • Game: “You are an architect” (optional)

    0.5 hour

    Theory

    • A review of topics discussed. Using a whiteboard, we will describe an application with Kubernetes objects.
  • Game: “Pin the tail on the Donkey”

    0.5 hour

    Theory

    • ArReview of the Kubernetes component architecture in an interactive game
  • Questions and answers

    0.5 hour or more

    Theory

    • An ask-me-anything session

Additional topics

  • Machine learning workloads

    1 hour

    Theory

    • An Introduction to machine learning on Kubernetes
    • CI/CD practices in machine learning
    • Tooling
    • How to manage special hardware, such as GPUs
  • A multi-cluster design (across clouds)

    0.75 hour

    Theory

    • An introduction to a multi-cluster design
    • Management tools
    • Scaling requirements
  • Working with compliance requirements

    0.75 hour

    Theory

    • An introduction
    • The Health Insurance Portability and Accountability Act
    • Personally identifiable information
    • Payment Card Industry Data Security Standard
  • Downward API

    0.5 hour
  • Custom resource definitions (CRDs) and operators

    1 hour

Maximize your team's talent with customized hands-on training

Maximize your team's talent with customized hands-on training

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Public classes are not scheduled at the moment. Please contact us at training@altoros.com if you’d like to join our waitlist or request private training for your team.

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Prerequisites. Altoros recommends that all students have a laptop with:

  • An SSH terminal client (like SSH or Putty)
  • A tool to transfer files over SSH (like scp)
  • A web browser (Chrome/Firefox)
  • Internet connection (outgoing connections on TCP ports 22, 80, 8080, and 443)
  • Access to Google Cloud Platform and Google Cloud Console

Get updates on upcoming events and new courses, discounts and special offers

Why train with Altoros?

Through expertly led, hands-on custom training courses, Altoros helps IT professionals around the globe to advance their skills in cloud-native development and PaaS, blockchain, artificial intelligence, and deep learning.

500+

Professionals trained

14

Training programs

23

Cities in 7 countries

19+

Years of experience

23

World-class trainers

1.2k+

Corporate customers

What our customers say

/
01

“This program is really good and gives a deep understanding of Kubernetes. Christian (the trainer) was very friendly and helpful.”

Lead DevOps Engineer at Accenture

Kubernetes Deep Dive training in San Francisco

02

“Ryan was very knowledagle & made the training interesting. He focuses on enabling us to actually use the technology in the field with practical examples, highlighting common problems & solutions to the same.”

Senior Solutions Architect at State Farm

Kubernetes Deep Dive Training in NYC

03

“It was great to interact face to face with instructor and ask questions, the training was very intensive and hands-on.”

Lead Architect at Macy's

Kubernetes Deep Dive Training in Chicago

04

“Training was fantastic. Everything was great and the trainers were great guys.”

Platform Architect at IBM

Kubernetes Deep Dive Training in Los Angeles

05

“What was the biggest value of the course? Definitely understanding the basics of Kubernetes, and doing some troubleshooting of problems.”

DevOps Engineer at Hanu

Kubernetes Deep Dive Training in Los Angeles

06

“What was the biggest value of the course? Lots of hands-on exercises and adding additional topics as we asked before.”

Kubernetes Deep Dive training

Seoul

07

“The format is great, training customization content is appreciated too. The trainer was accommodative and adaptive, he was good at going around and helping everyone to work through exercise.”

Lead Platform Architect at Nestle

Kubernetes Deep Dive training in San Francisco

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What trainees say about Altoros courses

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01
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02
Kubernetes Deep Dive Training in San Jose
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Frequently asked questions

Did not find the answer to your question? Drop us a line at training@altoros.com

  • Will I get a certificate after completion?

    Yes! Once you have completed our training, you will be issued a certificate that you can print or add to your LinkedIn profile for others to see.

    Note: the certificate does not represent official academic credit.

  • What are the available payment options?

    We accept all major credit cards including Visa, American Express, MasterCard, Discovery, and more. You can pay by credit card, bank transfer, PayPal or check.

    If you would like to get an invoice for your company to pay for this training, please email to training@altoros.com and provide us with the following info:

    • Name of your Company/Division which you would like to be invoiced
    • Name of the person the invoice should be addressed to
    • Billing Address
    • Purchase order # to put on the invoice (if required by your company)
  • Do you offer discounts?

    Yes, we offer discounts of up to 20% off for early birds who register for the training in advance. Each discount tier has a limited number of seats and all of our discounts are available in limited quantities. Once we sell all of our discounted seats, we move to full price.

  • Do you offer group discounts?

    Yes, we also offer a discount for groups of 3 or more people who register together.

  • What size are the groups?

    The standard group size is 7-10 people. Small class sizes provide students unparalleled access to instructors. This way each student can have enough attention and assistance from the instructor.

    Note: The class is contingent upon having 7 attendees. If there aren’t enough students, we will offer you to attend the class in a different location or make a full refund. That is also the reason why we ask not to buy flight tickets before the class is confirmed.

  • I need to travel to participate in training. Do you help with visa?

    We do not participate in the process of application for visa. However, we can provide a confirmation that you have registered for our class and bought a ticket for it. This should support your visa application.

    If your application is declined, we will refund the ticket, except for a small administrative fee.

  • What services do you offer after the training?

    Advanced training options or classes on different domain to widen your expertise and technical skill set (Kubernetes, Cloud Foundry, Microservices)

  • Why should I trust Altoros Training?

    We have 19 years of experience in the delivery of various projects with wide range of technologies.

    Our trainers are first of all engineers and developers who build Kubernetes solutions for our clients on daily basis

    We’ve already trained 500+ people all over the world.

Contact us

Looking for a top-notch training course to enhance your team's tech skills, Altoros experts can help. Level up your tech skills with the latest tools and frameworks!

Alexandra Mironova

Alexandra Mironova

Training Coordinator

training@altoros.com617 841-2121

830 Stewart Dr., Suite 119 Sunnyvale, CA 94085