DevOps Engineer | Ingress Academy
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DevOps & Linux Engineering

DevOps Engineer

Understand DevOps culture, continuous integration and deployment pipelines, infrastructure as code, and automation tools. This course prepares professionals to improve collaboration between development and operations teams. Delivered by expert instructors using practical labs and industry examples.

Продвинутый Очно 16 недель 64 часов Следующая группа: Апрель 9, 2026

О курсе

DevOps is a modern software engineering culture and set of practices that integrates software development (Dev) and IT operations (Ops) to enable faster, more reliable, and automated delivery of applications. It focuses on improving collaboration, shortening the software development lifecycle (SDLC), and ensuring continuous delivery with high quality and scalability. In today’s cloud-native environments, DevOps plays a key role in managing complex systems consisting of hundreds or even thousands of microservices. It enables organizations to automate infrastructure provisioning, application deployment, monitoring, and operational tasks using modern tools and practices. This training program is designed to provide both foundational knowledge and strong hands-on experience using real-world microservice-based applications. It covers modern DevOps practices and tools such as Git, CI/CD pipelines, Docker, Kubernetes, GitOps, observability, and automation tooling. Throughout the course, participants will work on real scenarios and industry-standard tools, gaining practical experience in building, deploying, securing, and monitoring cloud-native applications.

Требования

  • DevOps engineers often come from different backgrounds such as software development or
  • system administration. This course is designed to be hands-on, but a basic understanding of the
  • following concepts:
  • ● Basic knowledge of Linux operating systems (file system, processes, permissions, and
  • basic commands)
  • ● Fundamental understanding of networking concepts (IP addressing, DNS, HTTP/HTTPS,
  • ports, and basic troubleshooting)
  • ● Familiarity with software development concepts is beneficial but not required
  • ● Basic understanding of how applications are built and deployed is an advantage

Преимущества

🧑‍🏫

Practical teaching

In addition to class hours, you will practice the topics covered with your instructor and mentor dur

🤝

Mentors

The knowledge and skills you learn at the academy will be further strengthened with the mentor syste

📋

Academic transcript

Assignments and projects are checked by the instructor, and your knowledge and skills are determined

Программа обучения

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  1. 1 Monolithic Architecture
  2. 2 Microservice Architecture
  3. 3 Introduction to Cloud Computing
  4. 4 Introduction to Container Orchestration
  5. 5 Introduction to DevOps & CI/CD
  6. 6 Overview of DevOps Toolchain
  7. 7 DevSecOps Fundamentals and Shift-Left Security
  8. 8 SRE Fundamentals (SLA, SLO, and SLI Concepts)
  9. 9 Introduction to Platform Engineering and Internal Developer Platforms
  1. 1 Git Overview
  2. 2 Git Installation and Initial Configuration
  3. 3 Git File Lifecycle and Management
  4. 4 Working with Local and Remote Repositories
  5. 5 Core Git Concepts and Workflows
  6. 6 Advanced Git Concepts and Git Hooks
  7. 7 Git Branching Best Practices and GitFlow with SDLC
  8. 8 Hands-on Git Exercises
  1. 1 Benefits of Containers
  2. 2 Docker Overview
  3. 3 Docker Images and Containers
  4. 4 Docker Image Optimization and Multi-Stage Builds
  5. 5 Container Security Scanning (Trivy/Snyk Fundamentals)
  6. 6 Distroless and Minimal Container Images
  7. 7 Docker Volumes
  8. 8 Docker Networking
  9. 9 Writing Dockerfiles
  10. 10 Dockerfile Instructions (ENTRYPOINT, CMD, RUN)
  11. 11 Docker-in-Docker (DinD)
  12. 12 Docker Compose
  13. 13 LAB: Running Sample Microservices Locally with Docker Compose
  1. 1 Kafka Overview
  2. 2 Kafka Architecture and Core Concepts
  3. 3 Kafka Partitioning and Replication Strategy
  4. 4 High Availability and Fault-Tolerant Kafka Clusters
  5. 5 Kafka Monitoring and Lag Analysis
  6. 6 Kafka UI and Cluster Management
  7. 7 LAB: Provisioning a Kafka Cluster and Integrating Producer/Consumer Microservices
  1. 1 HashiCorp Vault Overview
  2. 2 Vault Architecture and Core Concepts
  3. 3 Provisioning a Vault Cluster
  4. 4 Consul Overview (Service Discovery and Distributed KV Store)
  5. 5 Configuration Management with Consul
  6. 6 LAB: Microservices Deployment with Vault and Consul Integration
  1. 1 Kubernetes Overview
  2. 2 Kubernetes Architecture (API Server, Scheduler, Controller Manager, etcd)
  3. 3 Kubernetes Namespaces
  4. 4 Resource Quotas in Kubernetes
  5. 5 Kubectl Tips, Tricks, and Best Practices
  6. 6 Labels and Selectors
  7. 7 Kubernetes Core Workload Resources and Controllers
  8. 8 Kubernetes troubleshooting methodologies
  9. 9 Debugging CrashLoopBackOff, OOMKilled and Pending Pods
  1. 1 Helm Overview
  2. 2 Working with Helm Charts
  3. 3 Custom Helm Charts
  4. 4 Advanced Helm Templating Techniques
  5. 5 Multi-Environment Deployments with Helm
  6. 6 Helm Best Practices and Chart Standards
  7. 7 LAB: Packaging and Deploying Sample Microservices on Kubernetes using Helm Charts
  1. 1 Network Overview
  2. 2 Pod-to-Pod and Intra-Pod Communication
  3. 3 Kubernetes Services and Service Discovery
  4. 4 Load Balancing with MetalLB
  5. 5 Ingress Controller and HTTP Routing
  6. 6 External Traffic Management in Kubernetes
  7. 7 Network Policies and Pod Security
  8. 8 LAB: Expose Sample Microservices through Ingress
  1. 1 ConfigMaps and Secrets
  2. 2 Config and Secret Volume Mounting
  3. 3 Liveness, Readiness and Startup Probes
  4. 4 Requests vs Limits Deep Dive and Resource Optimization
  5. 5 Horizontal Pod Autoscaler (HPA)
  6. 6 Vertical Pod Autoscaler (VPA) Overview
  7. 7 LAB: Hands-on Kubernetes Resource Management in a Cluster Environment
  1. 1 Taint and Toleration
  2. 2 Node Affinity
  3. 3 Node Selector
  4. 4 Metrics Server
  5. 5 Application Logs
  6. 6 Command and Arguments
  7. 7 Init Containers
  8. 8 CronJobs
  9. 9 OS and Kubernetes Upgrades
  10. 10 Backup and Restore methods
  11. 11 Disaster Recovery concepts
  12. 12 LAB: Rolling Updates and Rollback in Kubernetes Deployments
  1. 1 Role and Role Bindings
  2. 2 Kubernetes RBAC (Roles and RoleBindings)
  3. 3 EmptyDir and HostPath Volumes
  4. 4 Kubernetes Storage Types Overview
  5. 5 Persistent Volumes and Persistent Volume Claims
  6. 6 StorageClasses and dynamic provisioning
  7. 7 CSI Drivers Overview
  8. 8 LAB: Persisting Data for Sample Microservices
  1. 1 Introduction to Service Mesh
  2. 2 Service Mesh Architectures and Implementations
  3. 3 Setting Up Istio as a Service Mesh
  4. 4 Traffic Routing with Istio
  5. 5 Monitoring LMS Microservices with Service Mesh
  6. 6 Creating Destination Rules
  7. 7 Canary Deployments with Istio
  8. 8 LAB: End-to-End Service Mesh Setup and Observability for Sample Microservices
  1. 1 Introduction to Object Storage Concepts
  2. 2 S3 Architecture and Core Concepts
  3. 3 S3 Buckets, Objects, Versioning, and Lifecycle Policies
  4. 4 S3 Access Management and Security Basics
  5. 5 MinIO Overview
  6. 6 Deploying and Managing MinIO Clusters
  7. 7 Pure Storage Object Storage Overview
  8. 8 Pure Storage Replication and Disaster Recovery Concepts
  9. 9 Cross-Site Replication and DR Scenarios for Object Storage
  10. 10 LAB: Deploying and Managing S3-Compatible Storage with MinIO
  1. 1 Elasticsearch Overview
  2. 2 Centralized Log Collection with EFK Stack
  3. 3 Log Parsing and Structured Logging Best Practices
  4. 4 Centralized Logging Architecture
  5. 5 LAB: End-to-End Observability with EFK Stack for Microservices
  1. 1 Prometheus Overview
  2. 2 Setup and Configuration
  3. 3 PromQL (Prometheus Query Language)
  4. 4 Metrics Collection and Monitoring
  5. 5 Alertmanager configuration
  6. 6 Golden Signals and RED Metrics
  7. 7 Grafana Dashboard Best Practices
  8. 8 LAB: End-to-End Monitoring of Microservices with Prometheus and Grafana
  1. 1 CI/CD Tools Overview (Gitlab and Ecosystem)
  2. 2 Gitlab CI Overview
  3. 3 Deep Dive into LMS CI/CD Implementation
  4. 4 Gitlab runners
  5. 5 Pipeline optimization and caching strategies
  6. 6 Parallel jobs and dynamic pipelines
  7. 7 GitLab Upstream and Downstream Pipelines
  8. 8 Multi-Module Build and Test Pipelines
  9. 9 Security Scanning in CI/CD (SAST, DAST, Secret Detection)
  10. 10 Artifact Repositories (Nexus Overview)
  11. 11 End-to-End SDLC Automation with CI/CD
  12. 12 LAB: Building a Fully Functional CI/CD Pipeline for Sample Microservices in Gitlab
  1. 1 GitOps Tooling Overview
  2. 2 ArgoCD Overview
  3. 3 Deploying Applications with ArgoCD
  4. 4 Git Repository and Application Management in ArgoCD
  5. 5 Manual and Automated Sync in ArgoCD
  6. 6 ApplicationSets
  7. 7 ArgoCD Generators (List, Cluster, Git, Matrix, Merge)
  8. 8 Notifications (Slack, Email, Webhooks)
  9. 9 Authentication and SSO Integration
  10. 10 Multi-cluster GitOps management
  11. 11 Progressive Delivery with Argo Rollouts
  12. 12 LAB: Deploying Microservices with ArgoCD
  1. 1 Jenkins Overview and Automation Use Cases
  2. 2 Jenkins Architecture (Controller, Agents, Executors)
  3. 3 Jenkins Configuration as Code (JCasC)
  4. 4 Jenkins Pipelines as Code (Declarative & Scripted Pipelines)
  5. 5 Parameterized Jobs and Dynamic Job Configuration
  6. 6 Jenkins Integration with External Systems
  7. 7 LAB: Creating Parameterized Jenkins Jobs and Automation Pipelines

Ближайшие группы

Апрель 9, 2026

Офис

Записаться
Дни
Mon- Thu
Часы
19:00 - 21:00

Преподаватели

Samad Zeynalli

Samad Zeynalli

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Kapital Bank

 Murad Aslanli

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 Emin Bayramzade

Emin Bayramzade

DevOps Team Lead

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