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Kubernetes Workloads and Application Management

Packt via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

9 weeks, 1 hour a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Overview

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Kubernetes is the backbone of modern cloud-native infrastructure, enabling organizations to deploy, scale, and manage containerized applications efficiently. Mastering workloads and application management is critical for IT professionals to ensure reliable, high-performance systems. This course covers stateless and stateful workloads, persistent storage, and cluster orchestration using Deployments, StatefulSets, and DaemonSets. You’ll also work with Helm charts and operators to streamline application management and deploy production-ready workloads. Hands-on exercises across Google Kubernetes Engine, Amazon EKS, and Azure Kubernetes Service bridge theory with real-world application, preparing you to handle multi-cloud environments confidently. Ideal for DevOps engineers, software developers, and cloud architects, the course assumes basic familiarity with containers and cloud concepts, offering an intermediate-level learning path. By the end of the course, you will be able to deploy, manage, and scale Kubernetes workloads, configure persistent storage, and operate multi-cloud clusters efficiently. This course is part two of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization.

Syllabus

Persistent Storage in Kubernetes

This module delves into how Kubernetes manages persistent storage for stateful applications, covering PersistentVolume and PersistentVolumeClaim objects, their lifecycle, and provisioning methods. Learners will explore the role of the Container Storage Interface (CSI), dynamic storage provisioning, and advanced features like volume cloning and snapshots. By the end, you'll understand how to ensure data persistence and flexibility in Kubernetes environments.

Running Production-Grade Kubernetes Workloads

This module delves into strategies for achieving high availability and fault tolerance in Kubernetes by leveraging ReplicaSets and ReplicationControllers. Learners will gain hands-on experience managing production workloads, testing ReplicaSet behavior, and enhancing reliability with liveness probes. By the end, you'll be equipped to orchestrate scalable and resilient containerized applications in a Kubernetes environment.

Using Kubernetes Deployments for Stateless Workloads

This module guides learners through managing stateless workloads in Kubernetes using Deployments. You will explore how to create, scale, expose, and roll back Deployments, as well as the benefits of declarative object management for robust and scalable applications.

StatefulSet – Deploying Stateful Applications

This module introduces the Kubernetes StatefulSet resource, highlighting its unique features for managing stateful applications, such as persistent storage, stable network identities, and ordered deployment. Learners will explore how StatefulSets differ from Deployments, manage scaling and updates, and implement best practices for reliable stateful workloads.

DaemonSet – Maintaining Pod Singletons on Nodes

This module introduces DaemonSets in Kubernetes, focusing on how they ensure single Pod replicas on each node for essential cluster-wide tasks. Learners will discover how to deploy, manage, and prioritize DaemonSets for critical system operations and explore common real-world use cases.

Working with Helm Charts and Operators

This module introduces learners to deploying and managing applications in Kubernetes using Helm charts and Operators. You will gain hands-on experience with installation, security best practices, and lifecycle management, including configuring monitoring tools like Prometheus and Grafana. By the end, you'll be equipped to streamline application deployment and automate operational tasks in Kubernetes environments.

Kubernetes Clusters on Google Kubernetes Engine

This module guides learners through launching and managing Kubernetes clusters using Google Kubernetes Engine (GKE). You will configure your local environment, explore cloud-native deployment tools, and understand key concepts such as services, gateways, ingress, and cluster node architecture within Google Cloud Platform.

Launching a Kubernetes Cluster on Amazon Web Services with Amazon Elastic Kubernetes Service

This module guides learners through the process of setting up a Kubernetes cluster on AWS using Amazon EKS. You will learn how to create an AWS account, install and use eksctl, and manage cloud-native workloads via the AWS Console. By the end, you'll be equipped to deploy and explore Kubernetes clusters in a real cloud environment.

Kubernetes Clusters on Microsoft Azure with Azure Kubernetes Service

This module guides learners through configuring the Azure CLI, deploying and managing Azure Kubernetes Service (AKS) clusters, and comparing AKS with other major cloud Kubernetes offerings. Participants will gain hands-on experience with installation, resource management, and workload monitoring in a cloud-native environment.