DevSecOps Mastery with Docker and Kubernetes
What you'll learn
- Secure Docker and Kubernetes container platforms
- Acquire expertise in Docker security principles
- Develop a private image registry to restrict image accessibility
- Investigate Docker Content Trust and Docker Registry for security
- Share images on Docker Hub, Quay, and Harbor
- Establish Docker daemon security measures
- Implement AppArmor and Seccomp security profiles to enhance Linux kernel protection
- Execute Docker Bench Security for safeguarding
- Learn about optimal Docker security strategies
- Identify vulnerabilities in Docker with Clair and Anchore
- Familiarize yourself with static security analysis tools
- Explore primary Docker container threats
- Master the creation of Docker secrets
- Establish links between Docker containers
- Enhance Docker networking security
- Effectively manage CPU, memory, and RAM performance for your containers
- Administer Docker containers using Portainer and Rancher
- Deploy Kubernetes with Minikube
- Apply the least privilege principle for safeguarding Kubernetes clusters
- Utilize the CIS Kubernetes Benchmark guide
- Analyze security and vulnerabilities in Kubernetes pods, clusters, and nodes
- Monitor Kubernetes in production with Prometheus and Grafana for optimal security.
- Computer and Internet Access
- Willingness to Learn
- Basic Programming and Scripting Skills
DevSecOps, short for Development, Security, and Operations, represents a holistic approach encompassing culture, automation, and platform design. It intertwines security as a collective responsibility across the entire IT lifecycle. DevOps goes beyond development and operations teams. To fully harness the agility and responsiveness of DevOps, IT security must be an integral part of the entire application lifecycle.
This comprehensive course provides a step-by-step roadmap for implementing robust security practices and tools within your DevOps framework. The journey begins with an exploration of DevOps architecture and its connection to DevSecOps, followed by a deep dive into two key container management platforms: Docker and Kubernetes. You will become proficient in container management, mastering tasks such as handling Docker files, acquiring and constructing custom container images, and optimizing them for efficiency.
In the subsequent sections, the course covers fortifying your DevOps tools with an added layer of security. You'll discover how to utilize Docker Registry, create your own registry, employ Docker Content Trust, safeguard your Docker daemon and host through Apparmor and Seccomp security profiles, implement Docker Bench Security, and perform audits on your Docker host. You'll also gain insights into protecting and analyzing vulnerabilities within your Docker images to prevent corruption, employing tools like Clair, Quay, Anchore, and the CVE database. You'll explore the creation and management of Docker secrets, networks, and port mapping. The course equips you with security monitoring tools like cAdvisor, Dive, Falco, as well as administration tools such as Portainer, Rancher, and Openshift.
The final part focuses on Kubernetes Security practices. You'll learn how to identify, address, and prevent security risks within Kubernetes and apply best security practices. The course delves into the usage of KubeBench and Kubernetes Dashboard to enhance your Kubernetes Security, while also introducing Prometheus and Grafana for monitoring and scrutinizing your Kubernetes clusters for vulnerabilities.
The course content is structured into:
Examining the challenges, methodologies, and tools of DevSecOps, emphasizing the integration of security early in the DevOps application design and delivery processes.
Investigating prominent container platforms, such as Docker and Kubernetes, which underpin both development and operations teams, with a glance at alternative tools like Podman.
Mastering Docker, including image and container management, Dockerfile commands, and image optimization to reduce the attack surface.
Delving into security best practices, Docker capabilities, and the creation of private registries for image protection. The section also covers Docker Content Trust and Docker Registry for secure image uploads.
Understanding Docker daemon, AppArmor, Seccomp profiles, Docker bench security, and Lynis for adhering to security best practices in a production Docker environment.
Building container images securely with open-source tools like Clair and Anchore to detect vulnerabilities before deployment.
Identifying Docker container threats, vulnerabilities in Docker images, and tools for gathering vulnerability information in container applications.
Learning Docker secrets, networking components, port mapping, and how to expose container services to the host.
Establishing a comprehensive monitoring strategy for Docker infrastructure, covering event collection, performance metrics, and network statistics.
Utilizing open-source administration tools like Portainer, Rancher, and Openshift for Docker container management.
Exploring Kubernetes architecture, components, objects, and networking, along with tools like minikube for cluster deployment.
Implementing Kubernetes security best practices, emphasizing the principle of least privilege for components and pods.
Executing security controls as documented in the CIS Kubernetes Benchmark guide using Kubernetes bench for security project, and reviewing critical vulnerabilities in Kubernetes.
Assessing production capabilities when running Kubernetes, with a focus on observability, monitoring, and tools like Kubernetes dashboard, Prometheus, and Grafana for cluster metrics.
Who this course is for:
- Software Developers
- DevOps Engineers
- System Administrators
- Students and Learners
Hello, I'm an experienced AI engineer and natural language processing enthusiast with a passion for building intelligent chatbot applications. I hold a Master's degree in Computer Science and have spent over a decade in the field of artificial intelligence, specializing in language modeling and chatbot development. My teaching style is all about making complex AI concepts accessible and practical for learners of all levels. I believe in providing clear explanations, real-world examples, and hands-on projects that reinforce the concepts learned. You'll find a supportive and engaging learning environment in my courses, where questions are encouraged, and curiosity is nurtured.