16 Weeks
Top Rated Program · 4.9
Duration
Format
Projects
AI-Powered DevOps Engineering
A premium cohort program focused on resilient delivery systems, cloud automation, observability, and incident excellence for modern engineering teams.
Live + Recorded
4 Portfolio Projects
Learning Outcomes
- Design reliable CI/CD pipelines with rollback confidence.
- Implement observability stacks aligned to service objectives.
- Build infrastructure modules with reusable cloud patterns.
- Lead incident response with clear communication workflows.
Tools & Skills Covered
GitHub Actions Terraform Docker Kubernetes Prometheus Grafana SLO Design Incident Ops
Curriculum
Module 1: Modern Delivery Foundations
Branching strategy, deployment confidence metrics, and rollback playbooks.
Module 2: Infrastructure as Code
Terraform architecture, state strategy, and reusable module design.
Module 3: Reliability by Design
SLO frameworks, alert quality, and post-incident communication patterns.
Module 4: Production Observability
Instrumentation standards, useful dashboards, and anomaly response loops.
Module 5: Incident Leadership
War-room workflow, role ownership, and postmortem quality systems.
Module 6: Capstone Deployment
Deploy and defend an end-to-end resilient platform implementation.
Instructor
Led by Anika Shah, Principal Platform Engineer with 11+ years in cloud-native platforms and high-scale delivery teams.
Student Reviews
“The best part was feedback quality. I shipped solutions that felt production-grade.” — Marcus, DevOps Analyst
“I used the capstone in interviews and got callbacks from three companies.” — Nina, Platform Candidate
Course FAQs
Do I need prior Kubernetes experience?
Basic container familiarity is enough; module 1 includes essential readiness refreshers.
Will I get mentor feedback on every project?
Yes, each milestone includes structured review with action points for improvement.
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