Most GitOps tutorials teach you to deploy a single app to one cluster. Then you join a platform team managing 1,000+ clusters across multiple environments, and you realize the gap between "GitOps 101" and enterprise reality is enormous. This new course from industry expert Artem Lajko bridges that gap - teaching the multi-cluster, policy-driven, culturally-aware GitOps that platform engineering actually requires.
Why platform teams need specialized GitOps training
GitOps has become foundational infrastructure for platform engineering. According to the State of Platform Engineering Volume 4, 56.5% of platform teams now prioritize GitOps as a top-four capability - ranking alongside CI/CD, Infrastructure as Code, and Kubernetes itself. Yet most training treats GitOps as a developer tool, not the enterprise-scale orchestration layer that platform teams actually build.
The gap is cultural as much as technical. You can master Argo CD's sync waves and Flux's Kustomize overlays, but if your organization hasn't adopted trunk-based development or your security team blocks pull-based reconciliation, your GitOps implementation will stall. Platform engineers need training that addresses both the technical patterns for scaling to hundreds of clusters and the organizational strategies for driving adoption across skeptical stakeholders.
This is especially urgent as AI workloads reshape platform requirements. The State of AI in Platform Engineering report shows 75% of platform teams now host or prepare to host AI workloads - environments that benefit from the declarative, auditable infrastructure that mature GitOps can provide.
What makes this course different from generic GitOps training
GitOps for Platform Engineering is taught by Artem Lajko, Head of Platform Engineering at iits, CNCF Kubestronaut, and author of Implementing GitOps with Kubernetes. Artem brings practitioner credibility that generic DevOps instructors lack - he teaches patterns for scaling GitOps to 1,000-cluster fleets and has navigated the cultural adoption challenges that derail implementations.
The course spans six comprehensive modules, progressing from fundamentals through enterprise scaling. You'll start with the four GitOps principles and the evolution from "Wild West" operations through Infrastructure as Code to agent-based reconciliation. But unlike introductory courses that stop at basic Argo CD deployments, you'll tackle the real challenges platform teams face: config sprawl across multi-repo setups, policy enforcement at scale, secrets management for multi-tenant environments, and the shift from Git to OCI as artifact stores in "Gitless GitOps" architectures.
Module highlights include:
- Foundations and principles: Understanding GitOps as a contract between agents and humans, not just "CI/CD with Git"
- Architecture and patterns: Multi-cluster topologies, progressive delivery strategies, and avoiding common anti-patterns
- Tooling deep-dive: Hands-on with Argo CD, Flux CD, and Sveltos, including building a platform catalog for self-service
- Enterprise scaling: Managing 1,000+ clusters, implementing policy-as-code, and solving config sprawl with manifest rendering
- AI integration: Combining GitOps with AI-powered platforms and building platforms for AI workloads
- Cultural adoption: Bringing stakeholders in early, establishing shared vocabulary, and iterating based on feedback
The course also features an exclusive interview with Alexis Richardson, founder of RabbitMQ, a leading open-source message broker, which was acquired by VMware in 2010, CEO at ConfigHub and the person who coined the term "GitOps" in 2017. This provides historical context and industry perspective you won't find in vendor-specific training.
Who should take this course
This isn't beginner training. The typical student is a senior platform engineer who already understands basic GitOps concepts but needs validation and shared language for enterprise implementations. You might be a Head of Platform responsible for aligning your team on best practices, or a technical leader evaluating GitOps tooling for a multi-cluster migration.
The course serves two distinct needs. First, it provides validation for experienced practitioners. You've probably implemented GitOps already, but you're unsure if you're following best practices or if your architecture will scale. The course confirms what you know, corrects misconceptions (like confusing GitOps with simple Git-triggered pipelines), and fills gaps in areas like policy enforcement or cultural adoption.
Second, it establishes shared language across platform teams. A common pattern: a Head of Platform completes the course first, confirms the content matches their understanding, then enrolls their entire team - often 20-30 engineers. This isn't about training junior engineers; it's about ensuring everyone uses the same terminology for concepts like "pull-based reconciliation," "drift detection," and "progressive delivery." When your team shares a vocabulary, strategy discussions become more efficient, documentation becomes more consistent, and new members onboard faster.
This aligns with findings from the Platform Engineering University's first year: nearly 2,000 students enrolled, but senior engineers seeking validation - not career transitioners - became the primary audience. Teams adopt courses together to solve communication problems, not skill gaps.
How this fits into your platform engineering learning path
GitOps for Platform Engineering integrates with the broader Platform Engineering University ecosystem, which now offers a four-tier certification architecture: Practitioner, Professional, Leader, and Architect. The GitOps course complements these certifications by providing deep expertise in a specific domain that cuts across all platform roles.
If you've completed the Certified Practitioner course, you understand platform fundamentals like abstraction layers, golden paths, and the Minimum Viable Platform progression. GitOps training builds on this by showing how to implement those concepts through declarative, version-controlled infrastructure. If you're pursuing the Certified Architect certification, GitOps provides the integration and delivery plane expertise you need for production-grade platform design.
The course also connects to specialized domain training in Security Platform Engineering, Observability Platform Engineering, and AI in Platform Engineering. GitOps serves as "the glue" that enables these domains - you can't enforce security policies at scale without GitOps-driven policy-as-code, and you can't build reliable AI platforms without the drift detection and auditability that GitOps provides.
Why GitOps skills matter for career advancement
Platform engineering is expanding beyond classical DevEx into new domains like AI, security, observability, and FinOps. The State of Platform Engineering Volume 4 identifies emerging specialized roles: Security Platform Engineer, Observability Platform Engineer, and AI-focused platform engineers. GitOps expertise is increasingly valuable across these roles.
Consider the Security Platform Engineer role. You're responsible for embedding security guardrails directly into the platform through policy-as-code. This requires understanding how GitOps reconciliation loops interact with admission controllers like OPA Gatekeeper, how to version and audit policy changes through Git, and how to enforce "only signed runs" using OCI artifact stores. Generic security training won't teach this - you need platform-specific GitOps knowledge.
Or consider the AI-focused platform engineer role. You're building platforms that support ML workloads for data scientists and MLOps engineers. These platforms require specialized GitOps patterns: managing GPU-accelerated workloads, integrating ML pipelines with continuous training workflows, and handling the unique drift challenges of model registries and feature stores. The GitOps course covers these emerging patterns in Module 6, including the intersection of GitOps with AI-powered platforms.
Industry data validates this career trajectory. The Platform Engineering community has grown to 270,000 members, with security and observability as the fastest-growing segments. Organizations are hiring for these specialized roles, and they're looking for practitioners who understand how to apply GitOps principles to domain-specific challenges - not just run kubectl apply against a production cluster.
Getting started with the course
The course is available now through Platform Engineering University. You can enroll individually or as a team - many organizations enroll their entire platform team to establish shared practices and vocabulary.
The course includes hands-on exercises using the kubara General Distro to build a platform catalog, implement multi-cluster topologies, and solve the config sprawl challenges that plague production GitOps implementations. Setup details and environment requirements are provided in the course materials.
Beyond the course itself, you'll gain access to the Platform Engineering community's Slack workspace, where you can connect with peers, ask questions during implementation, and share lessons learned. The community also hosts PlatformCon, the world's largest platform engineering conference, and publishes Platform Weekly, a newsletter reaching 100,000 practitioners.
If you're a platform leader evaluating training options for your team, the Platform Engineering community also offers tailored workshops and advisory services. These combine the course curriculum with hands-on deployment support specific to your organization's platform challenges.
Frequently asked questions
Who is Artem Lajko?
Artem is Head of Platform Engineering at iits, a CNCF Kubestronaut, and author of Implementing GitOps with Kubernetes. He teaches patterns for scaling GitOps across 1,000+ cluster environments.
Is this course suitable for beginners?
No. It's designed for senior platform engineers who already understand basic GitOps concepts but need enterprise-scale expertise.
Can my entire team enroll together?
Yes. Many organizations enroll 20-30 engineers together to establish shared vocabulary and best practices across their platform team.
Does the course cover AI workloads?
Yes. Module 6 addresses GitOps for AI-powered platforms and platforms for AI, including GPU orchestration and ML pipeline integration.
Join the Platform Engineering community and connect with peers on Slack.
