DevOps

Docker and Kubernetes Bootcamp

Online

On-site

Hybrid

Docker and Kubernetes Bootcamp

Build a strong foundation in Docker and Kubernetes, from container fundamentals to production-ready deployment and operations. Learn how to troubleshoot real-world failures, apply security best practices, and build reliable workloads with scalable, enterprise-grade Kubernetes patterns.

Duration:

5 days

Level:

Intermediate

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1500+ users onboarded

Who will Benefit from this Training?

Software Engineers containerizing and deploying applications
DevOps and SRE Engineers managing Kubernetes operations
Cloud and Platform Engineers building scalable delivery platforms
QA and Automation Engineers creating consistent test environments
Technical Leads driving cloud-native adoption and reliability practices

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Training Objectives

Containerize applications using Docker with production-ready practices.
Create optimized Docker images using multi-stage builds and tagging strategies.
Deploy multi-service applications using Docker Compose.
Understand Kubernetes architecture and core objects.
Deploy applications using Deployments, Services, ConfigMaps, and Secrets.
Configure storage and persistence using PersistentVolumeClaims (PVC).
Manage safe deployments using probes, rolling updates, and rollback strategies.
Implement Kubernetes security basics using securityContext and runAsNonRoot.
Configure resource requests and limits for controlled CPU and memory usage.
Diagnose and fix common Kubernetes failures including CrashLoopBackOff and OOMKilled.
Deploy applications using Helm charts with values overrides.
Troubleshoot broken workloads and fix misconfigurations confidently.
Deliver a production-style Kubernetes capstone aligned with real enterprise practices.

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Key training modules

Comprehensive, hands-on modules designed to take you from basics to advanced concepts

Module 1: Containerization Fundamentals with Docker
1. What containers are and why Docker is used in modern delivery
2. Docker architecture (images, containers, registry basics)
3. Writing a production-ready Dockerfile (layers, caching, best practices)
4. Running and managing containers (logs, exec, environment variables)
5. Hands-on: Containerize a simple application and run it locally using Docker
Module 2: Production-Ready Docker Image Optimization
1. Multi-stage builds for smaller, faster, safer images
2. Choosing minimal base images and reducing attack surface
3. Tagging strategies (semantic versioning, git-sha tags, avoiding latest)
4. Image hygiene (pin versions, remove secrets, least privilege runtime)
5. Hands-on: Build an optimized multi-stage Docker image and compare size + performance
Module 3: Deploying Multi-Service Apps with Docker Compose
1. Why Compose is used for local multi-service development environments
2. Compose fundamentals (services, networks, volumes)
3. Managing app dependencies (database + backend + frontend)
4. Environment handling using .env and configuration patterns
5. Hands-on: Deploy a multi-service application using Docker Compose
Module 4: Kubernetes Architecture and Core Concepts
1. Why Kubernetes exists (orchestration, scaling, reliability)
2. Kubernetes architecture (control plane, nodes, kubelet, scheduler)
3. Core objects overview (Pods, Deployments, Services, Namespaces)
4. kubectl workflow (apply, get, describe, logs, exec)
5. Hands-on: Setup a Kubernetes cluster environment and deploy your first app
Module 5: Deploying Applications with Deployments and Services
1. Deployments explained (replicas, rolling updates, self-healing)
2. Service types (ClusterIP, NodePort, LoadBalancer)
3. Labels and selectors (how Kubernetes connects resources)
4. Zero-downtime rollout concepts
5. Hands-on: Deploy an app using Deployment + Service and access it from outside the cluster
Module 6: Configuration Management with ConfigMaps and Secrets
1. Why configuration must be externalized from images
2. ConfigMaps for app configuration (env vars and mounted files)
3. Secrets for sensitive values (base64 storage concept)
4. Safe practices for managing secrets (no hardcoding in YAML)
5. Hands-on: Deploy an app using ConfigMaps and Secrets and validate configuration injection
Module 7: Storage and Persistence with PersistentVolumeClaims (PVC)
1. Why stateful workloads need persistent storage
2. Volumes vs PersistentVolumes vs PersistentVolumeClaims
3. StorageClass concepts and dynamic provisioning basics
4. Common storage patterns for databases and shared storage
5. Hands-on: Deploy a database workload using PVC and validate persistence after restart
Module 8: Safe Deployments with Probes, Rolling Updates, and Rollbacks
1. Readiness vs liveness probes (why both matter)
2. Startup probe concepts (optional intro)
3. Rolling update strategy (maxSurge, maxUnavailable)
4. Rollback strategies and deployment history inspection
5. Hands-on: Add probes to an app and simulate a failed rollout followed by rollback
Module 9: Kubernetes Security Basics (securityContext and runAsNonRoot)
1. Why Kubernetes hardening matters (runtime risks and privilege escalation)
2. securityContext essentials (runAsNonRoot, readOnlyRootFilesystem)
3. Dropping Linux capabilities and disabling privilege escalation
4. Safe runtime defaults checklist for workloads
5. Hands-on: Harden a Deployment YAML using securityContext best practices
Module 10: Resource Requests and Limits for Stability
1. Requests vs limits explained
2. CPU and memory management fundamentals
3. Preventing noisy neighbor issues and cluster instability
4. Right-sizing strategy for dev vs production environments
5. Hands-on: Configure requests and limits and observe scheduling + performance behavior
Module 11: Diagnosing Kubernetes Failures (CrashLoopBackOff and OOMKilled)
1. Common failure states (CrashLoopBackOff, ImagePullBackOff, Pending)
2. Debug workflow using kubectl describe, logs, events
3. Root cause analysis patterns (bad config, missing env vars, wrong ports)
4. OOMKilled debugging and remediation (increase memory or optimize app)
5. Hands-on: Fix a broken workload scenario with CrashLoopBackOff and OOMKilled issues
Module 12: Helm Charts Fundamentals + Values Overrides
1. Why Helm is used (packaging, reuse, environment consistency)
2. Helm chart structure (Chart.yaml, templates, values.yaml)
3. Install, upgrade, rollback workflows
4. Values override strategies per environment (dev, stage, prod)
5. Hands-on: Deploy an application using Helm and override values for different environments
Module 13: Troubleshooting Broken Workloads and Misconfigurations
1. Debugging misconfigured Deployments and Services
2. Common YAML mistakes (labels mismatch, wrong selectors, wrong ports)
3. Debugging failed readiness and liveness probes
4. Step-by-step troubleshooting checklist for production incidents
5. Hands-on: Troubleshoot a broken Kubernetes app and fix end-to-end connectivity issues
Module 14: Capstone Project (Production-Style Kubernetes Deployment)
1. Capstone goal: Deliver a production-style microservice deployment on Kubernetes
2. Containerize application using Docker multi-stage build and safe tagging
3. Deploy multi-service stack (API + DB + frontend) on Kubernetes
4. Use Deployments, Services, ConfigMaps, Secrets, PVC
5. Apply probes, rolling updates, rollback, requests/limits, and securityContext hardening
6. Hands-on: Build and present a complete end-to-end Kubernetes deployment with troubleshooting demonstration

Hands-on Experience with Tools

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Training Delivery Format

Flexible, comprehensive training designed to fit your schedule and learning preferences

Opt-in Certifications

AWS, Scrum.org, DASA & more

100% Live

on-site/online training

Hands-on

Labs and capstone projects

Lifetime Access

to training material and sessions

How Does Personalised Training Work?

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Skill-Gap Assessment

Analysing skill gap and assessing business requirements to craft a unique program

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Personalisation

Customising curriculum and projects to prepare your team for challenges within your industry

2

Implementation

Supplementing training with consulting support to ensure implementation in real projects

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Why Docker and Kubernetes for your business?

Faster delivery: Docker standardizes runtime environments and Kubernetes makes deployments repeatable and automated.
High availability and reliability: Self-healing workloads, health-based routing, and safe rolling updates reduce outages.
Cost efficiency at scale: Right-sizing resources and scaling only when needed improves infrastructure governance.
Security readiness: Safer defaults like runAsNonRoot reduce risk and improve compliance posture.
Standardization across teams: Common deployment patterns and troubleshooting workflows simplify onboarding.
Scalable platform foundation: Enables microservices, APIs, jobs, and event-driven architectures without changing deployment strategy.

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Frequently Asked Questions

1. What are the pre-requisites for this training?

The training does not require you to have prior skills or experience. The curriculum covers basics and progresses towards advanced topics.

2. Will my team get any practical experience with this training?

With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.

3. What is your mode of delivery - online or on-site?

We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.

4. Will trainees get certified?

Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.

5. What do we do if we need further support after the training?

We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.

Docker and Kubernetes Bootcamp

Who will Benefit from this Training?

Training Objectives

Build a high-performing, job-ready tech team.

Key training modules

Hands-on Experience with Tools