Docker and Kubernetes – Running, Orchestrating, and Securing Containerized Applications

Course Description

Overview

Docker is an open platform for building, deploying, and running applications in containers. Kubernetes takes it a step further by providing the mechanisms necessary to automate the deployment, scaling, and management of containerized applications within a cluster, addressing networking, security, observability, and high availability.

During the training, participants will walk through a complete, practical scenario: from launching a container and working with Docker images, to building fundamental Kubernetes objects (Pods, Volumes, Deployments, Services), and advancing to more complex topics such as Namespaces and environment isolation, security (authentication and authorization), networking (CNI), monitoring and logging, scaling, updates, and troubleshooting common issues.

This training is hands-on: each topic is reinforced with exercises that reflect real-world scenarios encountered by DevOps teams, SREs, and administrators of containerized environments.

Learning Outcomes

Configure and run a Docker container, and intelligently select images for server and database workloads.
Deploy containerized servers and databases, and learn common pitfalls (volumes, data persistence, parameterization).
Install a Kubernetes cluster and understand its architecture and the role of various API objects.
Use Kubernetes to deploy and manage multiple environments within the same cluster (Namespaces, separation best practices).
Apply basic security mechanisms (authentication and authorization), as well as risk minimization best practices.
Design networking and service exposure (including non-HTTP services), and understand the differences between Docker and Kubernetes networking.
Configure cluster monitoring and logging (e.g., Prometheus, cAdvisor, Elasticsearch + Fluentd) and build basic observability.
Perform application scaling and updates with minimal user impact, and practice troubleshooting techniques.

Reserve Your Spot

Format: Remote
Language: English
Type: Open, Guaranteed Training
Date: 12-13.03.2026
Duration: 2 days (7 hours/day)
Mode of Delivery: Lecture + discussion + intensive hands-on exercises

RESERVE - 2450 PLN

Net price per participant.

Who Should Attend

System administrators and infrastructure engineers who deploy or maintain containerized applications.
DevOps / SRE professionals responsible for CI/CD, reliability, automation, and environment scaling.
Developers and tech leads who want to better understand Kubernetes deployments and collaborate with platform teams.
Individuals preparing for the role of Platform Engineer or working with microservices.

Prerequisites

Basic knowledge of Linux systems (navigation, file editing, permissions).
Networking basics (TCP/IP, DNS, ports, firewall – general level).
Preferably: basic command-line usage and understanding of terms such as image, container, and repository.
Lab environment: computer with internet access, toolset per instructor instructions (e.g., Docker, kubectl, cluster environment).

Methodology and Working Style

Short introductory lecture + discussion (joint exploration of 'why' and 'what for').
Step-by-step practical exercises with the instructor (hands-on labs).
Mini-operational scenarios: deployment, service exposure, scaling, updates, and problem diagnosis.
Production best practices: checklists, common errors, and recommended patterns.

Technical Notes

During the training, various Docker images may be used as example daemons (e.g., Nginx, MongoDB, Tomcat). If your organization prefers to work with a specific stack (e.g., custom images, a specific database, or a specific CNI), we can plan customization within a dedicated training session.

What Participants Take Away

Practical skills for working with Docker and Kubernetes in deployment and maintenance scenarios.
A set of recommendations and best practices applicable to your organization's environment (naming, separation, monitoring, security).
Exercise materials and sample manifests (as agreed with the trainer).

Customization and Consultation

If you would like the workshop to be embedded in your environment (specific images, CI/CD tools, security policies, CNI, cloud provider), we can conduct a brief needs assessment prior to the training and tailor the exercises to real use cases.

Training Program

Introduction

Course objectives and workshop rules.
Containerization vs. virtualization – where we gain real value and where complexity increases.

Overview of Container Orchestration with Kubernetes

Why orchestration is needed when working at scale.
Key use cases: microservices, multi-team environments, variable traffic.

Kubernetes Architecture Overview

Pods, labels/selectors, replication controllers, services, API.
Controller, scheduler, etcd – the role of control plane components (operational context).

Installing a Kubernetes Cluster

Installation options and environments: local, cloud, on-premise.
Verifying cluster status and basic administrative commands.

Pulling Docker Images from the Internet

Repositories, tags, digests – how to control versions and risk.
Image scanning and hygiene (introduction to best practices).

Creating Pods, Volumes, and Deployments in Kubernetes

Pods and containers: specification, resources, restart policies.
Volumes and data persistence: where errors commonly occur.
Deployments and deployment strategy basics.

Grouping and Organizing the Cluster

Labeling, selectors, resource organization – order that scales with the team.
Basics of policies and naming standards.

Using Kubernetes Namespaces to Manage Different Environments

Managing test, staging, and production environments within the same cluster.
Best practices for using Namespaces (isolation, order, limiting blast radius).

Locating and Connecting to Containers

Diagnostics: exec, logs, describe – the 'first 10 minutes' in an incident.
Common pitfalls: access rights, namespaces, networking.

Locating and Exposing Services

Service, endpoints, ingress – how users reach applications.
Non-HTTP services (Passive FTP, SMTP, LDAP, etc.) – when and how to expose them.

Kubernetes Security

Authorization and authentication – practical basics.
Least privilege and common configuration risks.

Updating a Kubernetes Cluster

Minimizing impact – planning maintenance windows and update strategies.
Controlling component compatibility.

Advanced Networking

Docker networking vs. Kubernetes networking – differences that matter.
Basics of debugging cluster networking.

Interfacing Network Providers with Kubernetes Networking

Best practices for isolating services within the cluster.
Comparing CNI providers (performance, features) – selection criteria.

Kubernetes Monitoring

Cluster logging: Elasticsearch and Fluentd (introduction).
Container monitoring: cAdvisor UI, InfluxDB, Prometheus – what to measure and why.

Best Practices for Running Containerized Servers and Databases

Data persistence, backup, versioning, and parameterization.
Anti-patterns: what not to do in production.

Scaling a Kubernetes Cluster

When to scale horizontally, when to scale vertically.
Cost and operational dependencies (informed decision-making).

Infrastructure for Kubernetes

Deployment, splitting, networking – foundations for a stable cluster.
Infrastructure dependencies that often surface 'late'.

Building a High-Availability Cluster

Load balancing and service discovery.
Critical HA points – how to identify them and mitigate risk.

Deploying a Scalable Application

Horizontal pod auto-scaling.
Database clustering in Kubernetes – basic approaches and limitations.

Application Updates

Versioning in Kubernetes – rollout/rollback strategies and minimizing downtime.

Troubleshooting

Diagnosing and fixing common Kubernetes issues.
Practical checklist: symptom -> hypothesis -> verification -> action.

Summary and Takeaways

Review of key concepts and best practices.
Recommendations for further development: toolchain path and topics to deepen.

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Why Guaranteed Training?

Execution guarantee – the training takes place regardless of the number of participants.
Knowledge exchange and networking with professionals from various industries.
Interactive, live-led sessions – not just theory, but also exercises and discussions.
Flexible online format – join from anywhere.