Platform engineering is the discipline of designing and building self-service internal developer platforms that abstract infrastructure complexity and accelerate software delivery.
Key takeaways
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Platform engineering shifts security, compliance, and infrastructure complexity away from developers onto dedicated platform teams.
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A successful internal developer platform balances standard automation with modular flexibility, avoiding rigid PaaS limitations.
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AI agents and automated tools in Kubernetes require strict RBAC and policy-as-code governance to ensure production safety.
Video transcript
Video transcript
One thing that I'm going to ask is, which may not make sense too much, is AI. You know, so talk a bit about how is AI changing, transforming, whether for better or for worse, the whole, you know, platform engineering discipline right now.
I think if anyone tells you they know the answer to this, they're not being truthful. I think more of it is like, what am I seeing in the industry? And the reality of it is, during the keynote yesterday here, they talked about like what AI and like the zero-day findings that we've seen over the last few months, really highlights the practices that we need and reliability and resilience that we've done for, should have been doing for 20 years, are just getting highlighted, right?
And so this is true in platform engineering, right? So having policy as code in your stack, right? Having appropriately scoped RBAC. These things are what's going to allow us again, to basically feel comfortable allowing AI agents, MCP servers inside of our stacks, pushing changes to it, right? Because everything's appropriately scoped. It's no different than giving an intern access to your cluster, no different than giving a senior developer access or an SRE access to your cluster, right? And so that's kind of the mentality is having the appropriately scoped system so that when you start enabling these services, you can feel comfortable.
How are you folks using AI, you know, internally to build a platform or of course, Akamai serves a lot of customers. So how are you also building the platform to serve AI workloads?
Frequently Asked Questions (FAQ)
Frequently Asked Questions (FAQ)
Modern stacks frequently combine Kubernetes, Argo CD for GitOps, Crossplane for infrastructure provisioning, Kyverno for policy enforcement, and OpenTelemetry for observability.
Unlike a rigid PaaS, a modular internal developer platform provides extensible components that allow engineering teams to customize infrastructure capabilities when required.
Policy-as-code ensures that both human engineers and AI agents operate within strictly defined RBAC boundaries, preventing unauthorized or unsafe cluster modifications.
Akamai Cloud provides scalable, cloud-native infrastructure primitives—including managed Kubernetes (LKE) and distributed compute—that serve as foundation layers for custom developer platforms.