Kubernetes for Data Engineering: Hands on End to End Guide

Boost the efficiency of your Data Engineering Solutions by Deploying them on Kubernetes Cluster.

Created by: Ganiyu Yusuf
Big Data Engineer | Solutions Architect

What Will I Learn?

• Understand the core concepts of Kubernetes, including pods, services, deployments, and more. Learn how to set up and manage a Kubernetes cluster
• Gain practical experience in deploying and managing the Kubernetes Dashboard, a powerful tool for managing Kubernetes clusters through a user-friendly interface
• Learn how to deploy Apache Airflow in a Kubernetes environment. Understand how to schedule and monitor data pipelines efficiently using Airflow.
• Dive into the world of Directed Acyclic Graphs (DAGs) and learn how to create, schedule, and monitor them in an Airflow environment running on Kubernetes.
• Understand how to secure your Kubernetes cluster and monitor its performance. Learn about Kubernetes namespaces, RBAC, secrets, and network policies.
• Learn how to scale your data applications and ensure high availability within your Kubernetes cluster.
• Develop skills to troubleshoot common issues in Kubernetes and optimize the performance of your data pipelines.

Requirements

• Basic Programming Experience

Target audience

• Everybody interested in building scalable and efficient infrastructures