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Welcome to the course
- Module 1: Introduction: Why Kubernetes cluster lifecycle management matters
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Introduction: Why Kubernetes cluster lifecycle management matters
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A short Kubernetes history
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Deploying software: before and after Kubernetes
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The reality of Kubernetes clusters today
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Multi-cluster architecture patterns
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Kubernetes clusters in platform engineering
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Challenges: The real-world pressure cooker
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Snowflakes and configuration drift
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Introducing cluster lifecycle management
- Module 2: Building clusters the declarative way
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Module 2: Building clusters the declarative way
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The full tech stack of a Kubernetes cluster
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Different clusters? Different setups!
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Keeping dev/test close to production
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Beware of unintended interactions
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Achieving full-stack visibility and transparency
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The politics of infra and platform teams
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How do you build a Kubernetes cluster?
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How do you get the full payload deployed?
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Intentionality is key
- Module 3: Day 2 operations
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Module 3: Day 2 operations
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Day 2 challenges
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Scheduled vs. event-driven Day 2 tasks
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Operational challenges at scale
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Observability: Your window into Day 2 reality
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Automation and declarative control
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AI and its current limitations
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Cost management
- Module 4: Multi-cluster governance, policy and security
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Module 4: Multi-cluster governance, policy and security
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Multi-cluster architectures: Benefits
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Multi-cluster architectures: Challenges
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Trade-offs: autonomy vs. control
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How to make it manageable
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Security best practices at fleet scale
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Course Feedback Survey
- Wrap-up
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It's a wrap - key takeaways
Kubernetes Cluster Lifecycle Management in Platform Engineering
Learn how to manage Kubernetes clusters across their full lifecycle. This course covers declarative management, Day 2 operations, and governance practices to reduce toil and scale platform reliability across teams
DURATION 2 hours
PRICE Free
FORMAT On-demand
What you'll learn
During this course, you'll learn:
Establish declarative Kubernetes cluster lifecycle management practices Manage Kubernetes clusters from provisioning through Day 2 operations at fleet scale Design and operate multi-cluster architectures with clear governance and control Use automation, GitOps, and policy-as-code to enable safe self-service for application teams
Curriculum
4 MODULESMODULE 1
Why Kubernetes cluster lifecycle management matters
A short Kubernetes history Deploying software: before and after Kubernetes The reality of Kubernetes clusters today Multi-cluster architecture patterns Kubernetes clusters in platform engineering Challenges: The real-world pressure cooker Snowflakes and configuration drift Introducing cluster lifecycle managementMODULE 2
Building clusters the declarative way
The full tech stack of a Kubernetes cluster Different clusters? Different setups! Keeping dev/test close to production Beware of unintended interactions Achieving full-stack visibility and transparency The politics of infra and platform teams How do you build a Kubernetes cluster? How do you get the full payload deployed? Intentionality is keyMODULE 3
Day 2 operations
Day 2 challenges Scheduled vs. event-driven Day 2 tasks Operational challenges at scale Observability: Your window into Day 2 reality Automation and declarative control AI and its current limitations Cost managementMODULE 4
Multi-cluster governance, policy and security
Multi-cluster architectures: Benefits Multi-cluster architectures: Challenges Trade-offs: autonomy vs. control How to make it manageable Security best practices at fleet scaleMeet your Instructor
Ant Newman
Course instructor and Product @ SpectroCloud
- Technology speaker and storyteller with deep experience shaping platform and cloud narratives for senior technical and business audiences
- Thought-leadership specialist who turns large, messy problem spaces into clear points of view that resonate with engineers, leaders, and executives
- Journalist-turned marketer, interviewer, and podcast host who connects platform engineering decisions to real organizational and business outcomes
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