Longhorn Trainers
Longhorn Trainers For : Online - Classroom - Corporate Training in Worldwide
What is Longhorn?
Longhorn is an open-source, cloud-native distributed block storage system designed
specifically for Kubernetes environments. Originally developed by Rancher, Longhorn enables
persistent storage for containerized applications by providing reliable, scalable, and
fault-tolerant volumes that run entirely within Kubernetes clusters. It allows users to
create persistent volumes that are replicated across multiple nodes, ensuring data
availability even if a node fails. Longhorn is lightweight, easy to deploy, and does not
require external storage systems, making it ideal for organizations that want simple yet
powerful storage directly integrated with Kubernetes.
In practical use, Longhorn manages storage by creating replicated block volumes that can be
attached to pods, ensuring high availability and data durability. It supports features such
as automatic backups, snapshots, disaster recovery, and volume expansion, all managed through
Kubernetes Custom Resource Definitions (CRDs) and a user-friendly dashboard. Longhorn works
well in on-premises, edge, and cloud environments, providing consistent storage behavior
across different infrastructures. By simplifying persistent storage management and offering
built-in resilience, Longhorn helps DevOps and platform teams run stateful Kubernetes
workloads—such as databases and applications with persistent data—securely and efficiently.
Importance of Quality Trainer for Longhorn?
A Quality Trainer for Longhorn is essential because Longhorn is a cloud-native distributed block storage system for Kubernetes, and storage is one of the most critical and sensitive layers in any production environment. While Longhorn simplifies persistent storage management, improper configuration or lack of understanding can lead to data loss, performance degradation, failed backups, or application downtime. A skilled trainer ensures learners clearly understand how Longhorn works internally, how volumes are created and replicated, and how storage reliability is maintained in Kubernetes clusters.
A quality trainer provides hands-on, real-world learning, teaching how to install Longhorn, create and manage persistent volumes, configure replication, and attach storage to stateful applications like databases. Learners practice real production scenarios such as node failures, disk failures, volume recovery, snapshots, and backups, which are critical for running stateful workloads safely. This practical exposure builds confidence and reduces risk when Longhorn is used in live environments.
A good Longhorn trainer also emphasizes backup, disaster recovery, and data protection strategies. Learners understand how to configure backups to object storage, manage snapshots, perform restores, and test recovery procedures. They also learn how to monitor storage health, analyze performance metrics, and troubleshoot common storage-related issues that can impact application stability.
Another key value of a quality trainer is performance tuning and scalability guidance. Learners are taught how to choose the right replication factors, disk types, and resource limits to balance performance and cost. They also learn how Longhorn behaves under load, how to scale storage as clusters grow, and how to avoid common mistakes that lead to storage bottlenecks.
Finally, a quality Longhorn trainer ensures learners are production-ready and confident. By combining strong conceptual understanding with hands-on labs and real-world failure scenarios, learners gain the skills to design, operate, and maintain reliable Kubernetes storage systems. This makes them highly valuable to DevOps, SRE, and platform engineering teams, where stable, secure, and recoverable storage is critical for running modern cloud-native applications.
How DevopsSchool's Trainer is best in industry for Longhorn?
DevOpsSchool's trainers are considered among the best in the industry for Continuous Delivery (CD) due to their deep industry expertise, practical experience, and hands-on teaching approach. They possess extensive real-world knowledge in Longhorn, Longhorn, and IT automation, often having implemented large-scale Longhorn solutions in enterprise environments. The training curriculum they provide is comprehensive and up-to-date with the latest tools and methodologies, ensuring learners gain practical skills that are immediately applicable. DevOpsSchool emphasizes hands-on learning, where trainers guide participants through real-world scenarios and projects, making complex topics more accessible. Moreover, these trainers offer personalized guidance, tailoring their teaching to the learner's specific needs and goals. With recognized certifications and a proven track record of producing successful Longhorn professionals, DevOpsSchool's trainers stand out for their ability to provide both deep technical insights and practical, career-boosting knowledge.
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OUR POPULAR CERTIFICAITON
| CERTIFICAITON / COURSES NAME | AGENDA | FEES | DURATION | ENROLL NOW |
|---|---|---|---|---|
| DevOps Certified Professional (DCP) | CLICK HERE | 24,999/- | 60 Hours | |
| DevSecOps Certified Professional (DSOCP) | CLICK HERE | 49,999/- | 100 Hours | |
| Site Reliability Engineering (SRE) Certified Professional | CLICK HERE | 49,999/- | 100 Hours | |
| Master in DevOps Engineering (MDE) | CLICK HERE | 99,999/- | 120 Hours | |
| Master in Container DevOps | CLICK HERE | 34,999/- | 20 Hours | |
| MLOps Certified Professional (MLOCP) | CLICK HERE | 49,999/- | 100 Hours | |
| Container Certified Professional (AIOCP) | CLICK HERE | 49,999/- | 100 Hours | |
| DataOps Certified Professional (DOCP) | CLICK HERE | 49,999/- | 60 Hours | |
| Kubernetes Certified Administrator & Developer (KCAD) | CLICK HERE | 29,999/- | 20 Hours |
Features of DevOpsSchool:-
- Known, Qualified and Experienced Longhorn Trainer.
- Assignments with personal assistance.
- Real time scenario based projects with standard evaluation.
- Hands on Approach - We emphasize on learning by doing.
- The class is consist of Lab by doing.
- Life time access to all learning materials & Lifetime technical support.
Profiles - Longhorn Trainers
Longhorn Course content designed by our Longhorn Trainers
1. Introduction to Longhorn
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Overview of Longhorn as a cloud-native distributed block storage system for Kubernetes
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Why persistent storage is critical in containerized and Kubernetes environments
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Problems with traditional storage solutions in Kubernetes
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Key benefits of Longhorn: simplicity, high availability, and cloud-native design
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Real-world use cases of Longhorn in production Kubernetes clusters
2. Kubernetes Storage Fundamentals
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Understanding Kubernetes storage concepts: Volumes, Persistent Volumes (PV), and Persistent Volume Claims (PVC)
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Storage classes and dynamic provisioning in Kubernetes
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Stateful vs stateless applications and storage requirements
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CSI (Container Storage Interface) overview and its role in Kubernetes storage
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Where Longhorn fits in the Kubernetes storage ecosystem
3. Longhorn Architecture Overview
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Core architecture of Longhorn and its design principles
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Longhorn components: Manager, Engine, UI, CSI Driver, and Replicas
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How Longhorn stores and replicates data across nodes
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Control plane vs data plane in Longhorn
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Understanding volume lifecycle and data flow in Longhorn
4. Installing Longhorn
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System and Kubernetes prerequisites for Longhorn installation
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Installing Longhorn using Helm and kubectl
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Verifying Longhorn installation and cluster readiness
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Exploring the Longhorn UI and dashboard
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Best practices for installation in development and production environments
5. Longhorn Storage Concepts
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Longhorn volumes and replicas
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Understanding replication factor and fault tolerance
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Read-write-many (RWX) vs read-write-once (RWO) support
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Scheduling and placement of replicas across nodes
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Storage performance considerations and tuning basics
6. Persistent Storage with Longhorn
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Creating Persistent Volumes using Longhorn StorageClass
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Managing Persistent Volume Claims backed by Longhorn
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Attaching and mounting volumes to Kubernetes pods
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Handling pod restarts, rescheduling, and node failures
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Best practices for running stateful workloads with Longhorn
7. High Availability and Data Protection
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How Longhorn ensures high availability for persistent volumes
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Replica rebuilding and self-healing mechanisms
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Node failure handling and automatic recovery
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Disk failure scenarios and data protection strategies
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Configuring anti-affinity and replica placement rules
8. Backup and Restore with Longhorn
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Overview of Longhorn backup architecture
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Configuring backup targets (S3-compatible object storage, NFS)
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Creating manual and scheduled backups
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Restoring volumes from backups
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Disaster recovery scenarios using Longhorn backups
9. Snapshots and Volume Management
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Understanding snapshots in Longhorn
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Creating and managing volume snapshots
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Snapshot-based backups and restores
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Cleaning up unused snapshots and managing storage space
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Use cases for snapshots in DevOps and production workflows
10. Longhorn UI and CLI Management
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Navigating the Longhorn UI for storage management
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Managing volumes, replicas, nodes, and disks via UI
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Monitoring volume health and performance
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Using kubectl and Longhorn CRDs for advanced operations
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Automating storage operations using scripts and YAML
11. Performance Optimization and Tuning
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Understanding Longhorn performance characteristics
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Disk types and performance impact (SSD vs HDD)
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Tuning replica count, snapshot frequency, and rebuild settings
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Monitoring IOPS, latency, and throughput
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Best practices for optimizing Longhorn in production workloads
12. Security in Longhorn
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Securing Longhorn components and access
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Kubernetes RBAC considerations for Longhorn
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Securing backup targets and credentials
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Network security considerations in storage traffic
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Best practices for running Longhorn in secure environments
13. Monitoring and Observability
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Monitoring Longhorn using built-in metrics
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Integrating Longhorn with Prometheus and Grafana
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Understanding alerts and health indicators
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Troubleshooting common storage and volume issues
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Capacity planning and storage utilization tracking
14. Longhorn in Production Environments
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Best practices for deploying Longhorn in production clusters
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Multi-node and multi-zone cluster considerations
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Running databases and stateful services on Longhorn
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Upgrade strategies and version compatibility
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Scaling Longhorn as cluster size grows
15. Upgrading and Maintaining Longhorn
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Longhorn versioning and release lifecycle
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Performing safe Longhorn upgrades
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Backup and validation before upgrades
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Rolling upgrades and minimizing downtime
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Maintenance best practices for long-term stability
16. Troubleshooting and Debugging Longhorn
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Common Longhorn issues and failure scenarios
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Debugging replica failures and rebuild problems
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Volume attach/detach issues
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Log analysis and diagnostic tools
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Recovery strategies for corrupted or degraded volumes
17. Integrating Longhorn with CI/CD and DevOps
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Using Longhorn with GitOps workflows
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Storage automation in CI/CD pipelines
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Persistent storage for Kubernetes-based CI systems
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Supporting blue-green and canary deployments with snapshots
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DevOps best practices for storage management
18. Hands-on Labs and Practical Exercises
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Installing Longhorn on a Kubernetes cluster
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Creating and managing persistent volumes
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Running stateful applications with Longhorn storage
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Configuring backups, restores, and snapshots
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Simulating node failures and observing self-healing behavior
19. Real-world Use Cases and Case Studies
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Enterprise use cases of Longhorn in Kubernetes platforms
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Running databases, message queues, and CMS workloads
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Lessons learned from production deployments
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Comparing Longhorn with other Kubernetes storage solutions
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Cost and operational benefits of Longhorn
20. Career Guidance and Industry Readiness
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Roles and responsibilities: Kubernetes Administrator, SRE, DevOps Engineer
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How Longhorn skills fit into Kubernetes and cloud-native careers
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Resume building and interview preparation tips
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Real-world expectations from Longhorn professionals
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Trainer guidance on mastering Kubernetes storage concepts
Training Flow
The Longhorn Course is designed to help participants understand and implement Longhorn, a cloud-native distributed block storage system built for Kubernetes. This training focuses on deploying Longhorn, managing persistent storage for containerized applications, ensuring high availability, handling backups and restores, and operating Longhorn in production Kubernetes environments. By the end of the course, participants will be confident in managing Kubernetes storage using Longhorn with real-world operational practices.
Training Flow (High Level):
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Requirement Gathering & Training Need Analysis (TNA)
Understand participants’ background in Kubernetes, containers, and storage concepts, and identify use cases such as stateful workloads, backups, and high availability. -
Curriculum Finalization + Agenda Approval
Finalize the course structure covering Longhorn architecture, installation, volume management, backups, upgrades, and best practices aligned with participant needs. -
Environment Setup (Labs, Tools, Accounts)
Prepare Kubernetes clusters, install Longhorn, configure nodes, storage classes, and ensure access to dashboards and CLI tools for hands-on labs. -
Content Preparation (Slides, Demos, Code, Exercises)
Create learning materials including architecture diagrams, deployment demos, configuration examples, troubleshooting scenarios, and guided lab exercises. -
Delivery of Training (Live Sessions / Longhorn)
Conduct live instructor-led sessions explaining concepts and performing real-time demonstrations of Longhorn deployment, volume creation, and storage operations. -
Daily Recap + Assignments + Lab Reviews
Summarize daily learnings, review lab outcomes, clarify doubts, and assign practical tasks such as configuring volumes, snapshots, and backups. -
Assessment / Quiz / Project Submission
Evaluate learning through quizzes and a hands-on project involving deploying Longhorn, attaching volumes to workloads, and implementing backup and recovery. -
Feedback Collection
Collect participant feedback on content clarity, labs, pacing, and overall training effectiveness for continuous improvement. -
Post-Training Support (Q&A, Slack/Telegram Group)
Provide post-training assistance for real-world implementation, troubleshooting storage issues, and advanced Longhorn usage scenarios. -
Training Report Submission to Corporate Client
Submit a detailed report covering attendance, assessments, project completion, and readiness of participants to use Longhorn in production Kubernetes clusters.
