Kubernetes Security & Optimising Workload
Elevate your Kubernetes expertise with our "Helm for Kubernetes Resource Management" course. Perfect for IT professionals and DevOps engineers, this course provides in-depth knowledge of Helm, enabling you to manage and deploy applications with ease. Through hands-on labs and expert instruction, you’ll learn to create, customize, and optimize Helm charts. Gain practical skills to handle complex resource configurations and streamline your Kubernetes workflows.
About the course
Certified Kubernetes Application Developer course provides a comprehensive dive into Kubernetes, covering everything from container design and deployment strategies to application observability, security, and networking. Designed for developers, DevOps engineers, and IT professionals, the course equips learners with the skills to effectively build, deploy, and manage applications within Kubernetes environments. Topics include working with container images, implementing advanced deployment strategies, maintaining application health, securing configurations, and understanding Kubernetes networking. By the end of the course, participants will be well-prepared to handle Kubernetes in production settings, ensuring scalable, secure, and resilient applications. 4o
Course details
- Level: Beginner
- Duration: 2 Months
What's included
- Online Training
- Classroom Training
- WhatsApp Support
- Mock Exams
- Course Certificate
Course content
Securing Kubernetes Cluster
- Understanding Kubernetes Attack Surface
- CNCF Projects
- 4C's of Security
- Cluster Hardening
- CIS Benchmarks
- LAB: Using CIS CAT-Lite
- LAB: Using Docker Bench Security
- LAB: Using Kube Bench Security
- LAB: Using Tracee
- Securing Image Supply Chain
- LAB: Exploring Container Images with Dive
- LAB: Scanning Container Images with Trivy
- LAB: Scanning Kubernetes Resources using Kubesec
- LAB: Auditing Kubernetes Configurations using Polaris
- Minimise Microservice Vulnerabilities
- Understanding Security Context
- LAB: Applying Security Context to Pods
- Understanding Pod Security Admission
- LAB: Applying PSA to namespaces
- Admissions Controllers
- Understanding AppArmor Security Profiles
- LAB: Applying AppArmor Profiles to Pods
- Open Policy Agent in Enterprise
- LAB: Using OPA with Kubernetes
- Encrypting Secrets in etcd
- LAB: Encrypting Data at Rest in etcd
- Backup. Auditing & Monitoring Kubernetes Cluster
- LAB: Velero Backup Tool
- LAB: Dynamic Scanning of Pods using Falco
- LAB: Monitoring using Prometheus & Grafana
Performance Tuning & Optimising
- Efficient Pod Scheduling
- LAB: Using NodeSelector
- LAB: Applying Affinity / Anti Affinity for Pods & Nodes
- LAB: Using Taints & Tolerations for Nodes
- LAB: Using Pod Disruption Budget
- Scaling Resources with Load
- LAB: Manual Scaling of Applications
- LAB: Configuring Horizontal Pod Auto-Scaling
- Optimizing Networking
- LAB: Applying Network Policies
- Load Balancing Strategies
- Logging & Monitoring
- LAB: Enabling Auditing on Kubernetes
- Log Management
Prioritizing Resources for Critical Workloads
- Quality of Service - Best-effort, Burstable, Guaranteed
- LAB: Changing QoS in Pods
- Understanding Priority Classes
- LAB: Creating Priority Classes & Applying to Workloads
- Understanding Topology Spread for Deployments
- LAB: Configuring Topology Spread
- Understanding De-scheduler for Dynamic Clusters
- LAB: Applying De-scheduler
- Importance of Namespaces
- LAB: Resource Quota on Namespace
- LAB: Resource Quota with Scope on Namespace
- LAB: Configuring Limit Ranges on Namespace
Service Mesh with Kubernetes
- Introduction to Service Mesh
- Understanding Istio - Service Mesh
- LAB: Installing Istio on Kubernetes
- LAB: Running Kubernetes Application with Istio
- Understanding Istio Gateway - Traffic Ingress Concepts
- LAB: Istio Ingress Gateway
- Traffic Control
- LAB: Routing specific requests to different version
- LAB: Traffic Shifting to specific version of application
- Visualising Network Behaviour with Grafana, Jaeger & Kiali
- LAB: Using Grafana to visualize Control Plane & Data Plane
- LAB: Distributed Tracing using Jaeger
- LAB: Visualising Service Communication with Kiali
Ingress Controllers
- Introduction to Ingress Controllers
- LAB: Installing Nginx Ingress Controller
- LAB: Using Kubernetes Ingress to Expose Service
- LAB: Using Ingress to Load Balance Traffic
- LAB: Using Ingress to Route Traffic
Helm Charts
- Introduction to Helm Chart
- LAB: Installing Helm with Kubernetes
- LAB: Using Custom Values with Helm Chart
- LAB: Upgrading Application using Helm
- LAB: Rollback Application using Helm
- LAB: Uninstalling Application using Helm
- Deploying Application with Helm
- LAB: Constructing New Helm Chart
Advance CNI & CSI
- Introduction to CNI
- Relation between CNI & CRI
- Intra-pod Communication
- Pod-to-Service Communication
- External Access & DNS in Kubernetes
- Kubernetes Network Plugins
- Load Balancing Options:
- External load balancer
- Service load balancer
- Ingress
- HA Proxy
- MetalLB
- Kubernetes Gateway API
- Introduction to CSI
- Understanding Volumes
- LAB: Using emptyDir for intra-pod communication
- LAB: Using HostPath for intra-node communication
- Understanding Persistent Volumes
- Understanding Persistent Volume Claim
- Raw Block Volumes
- LAB: Ephemeral Volumes Configuration
- LAB: Storage Classes Configuration
Kubernetes Operators
- Introduction to Kubernetes Operators
- Operator Eco-system: Operator SDK, OLM & OperatorHub
- How Operators work with Kubernetes
- LAB: Building & Deploying Custom Operator
- Understanding Operator Lifecycle Manager (OLM)
- LAB: Running your Operator
Kubevirt on Kubernetes
- Introduction to Kubevirt
- Kubevirt Architecture
- LAB: Installing Kubevirt
- LAB: Deploying VM on Kubernetes
Frequently asked questions
- Is this training live or pre-recorded?
- The training is live instructor led training which is available in classroom as well as online format. We also record every training session which is then uploaded to our student portal.
- How will I join the live online training?
- The live online training is conducted via the zoom software, we will be providing you with the zoom meeting link to join the training.
- How many students are there in a single batch?
- On an average one batch will have a maximum of 18 students. We keep smaller batch sizes to promote interaction between the students and the instructor.
- How can I practice the labs?
- We will provide you with online labs. If needed, we can also provide you with the software required to create your own labs.
- Do you offer payment flexibility?
- Yes, we provide zero interest EMI options.
- Can I attend the training in classroom?
- Yes, our classroom training location is in New Delhi near Lajpat Nagar metro staton.