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Production Deployment with Kubernetes

This course offers an introduction to Kubernetes and includes technical instructions on how to deploy a stand-alone and multi-tier application. We’ve designed this course to both cover the fundamentals of cloud-native development with Kubernetes and ensure that you can deploy a scalable, production service on any cloud provider. We’ll cover the basics of containerization, pod deployments, scale-up, networking and dev-ops to have a holistic overview of the necessary components of deploying and maintaining a production system. We’ll then cover some advanced topics around integrating your kubernetes service with common tools used at large companies running production workloads, including Prometheus, Grafana and Splunk.

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Samir Sen
Founder & CEO, Flair Labs
Real-world projects that teach you industry skills.
Learn alongside a small group of your professional peers
Part-time program with 2 live events per week:
Monday @ 5:00 PM UTC
Project Session
Wednesday @ 5:00 PM UTC
Next Cohort
November 7, 2022
4 weeks
US$ 400
or included with membership

Course taught by expert instructors

Instructor Photo
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Samir Sen

Founder & CEO, Flair Labs

Samir is currently the Founder and CEO of Flair Labs, backed by YCombinator. His previous industry experience focused on building and deploying large-scale cloud infrastructure on the ML Platform teams at Apple and Microsoft. He received his bachelor’s and master’s in CS and AI from Stanford University where he was a TA for machine learning and NLP courses.

The course

Learn and apply skills with real-world projects.

Kubernetes cluster setup with kubeadm on lab VM. You will create, deploy and experiment with cloud-based cluster turn-up and a simple pod deployment.
    • Kubernetes overview and industry use-cases
    • How to build and manage docker containers
    • Pods and manifests
    • Advanced pods features
    • Deploy a simple, load-balanced API service endpoint
    • Scale the deployment across regions and instances
    • ConfigMaps, Secrets, YAML configs for pods
    • Scaling deployments with ReplicaSets
    • Setting up namespaces
    • Setting up network policies
    Scavenger hunt to RCA pod and node level issues for an error-prone service running on a lab Kubernetes cluster. You will explore init-containers, pod / node log explorers, health-checks as you follow the best practices for debugging kubernetes applications.
      • Application, platform, orchestrator and system logs and metrics
      • Pod debugging workflow
      • Scheduling debugging workflow
      • Networking and services debugging workflow
      Integrate Prometheus and Grafana for metrics logging and visualization to your Kubernetes service.
        • Overview of tools for Kubernetes
        • How to install and configure Prometheus for a Kubernetes service
        • How to use Grafana for service usage visualizations
        • Logging system outputs with Splunk

        Real-world projects

        Work on projects that bring your learning to life.
        Made to be directly applicable in your work.

        Live access to experts

        Sessions and Q&As with our expert instructors, along with real-world projects.

        Network & community

        Core reviews a study groups. Share experiences and learn alongside a global network of professionals.

        Support & accountability

        We have a system in place to make sure you complete the course, and to help nudge you along the way.

        Course success stories

        Learn together and share experiences with other industry professionals

        Samir was my instructor for my Stanford CS course, and there is no one better at explaining complex topics in bite-sized and fully understandable pieces. He helped go through many hands-on examples for each of the course concepts so students could get a deep and intuitive understanding of all of the course materials. I highly recommend Samir for anyone looking to get the most out of their learning experience.

        Sujeet KumarFormer Stanford CS Student & Architect at JP Morgan

        An experienced developer and cloud expert. Early on, we consulted Samir for his expertise in production software development at Apple and Microsoft to help us deploy our real-time ML system. He laid out the foundations for our Kubernetes architecture that we use to host our production-scale service.

        Mayank KishoreFounder, MirageML

        This course is for...

        Software engineers looking to gain skills necessary to deploy production systems on cloud infrastructure.

        SRE engineers who want to understand the details of kubernetes architecture and service deployment.


        Ability to write Python, Go, or another programming language

        Basic familiarity with Docker and command line

        GCP / AWS / Cloud experience are recommended but NOT required

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