How Are You Managing Increased AI Code Delivery at Scale?

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Asked By CodeCrafter42 On

With the rapid advancements in AI, my team is experiencing a significant increase in code delivery demands, particularly for both existing and new internal applications. This surge has led to more requests for diverse tools and managed cloud services, sparking concerns around availability and security. I'm curious how others are tackling this issue—are you granting development teams more control over their infrastructure, or focusing on self-service solutions with pre-defined modules? Additionally, since we're primarily utilizing a Kubernetes-based platform, I'm interested in whether others are opting for multi-tenancy clusters instead of creating separate clusters and accounts for every team. For those using an Identity Provider (IDP), which one are you using? And for teams managing these transitions smoothly, what do you believe is the key to their success?

5 Answers

Answered By InfrastructureGuru On

It sounds like your developers are using AI tools like Claude to generate Terraform configurations, and now you're facing the challenges of this sudden influx of changes. The solution often lies in a boring but effective approach: providing clear self-service modules, policies that don’t frustrate your team, and accepting that multi-tenancy can be a bit messy but sometimes necessary.

Answered By DevOps_Dynamo On

For IDPs, I've found Port to be very useful in managing AI agents by regulating permissions, usage limits, and activities. If you're open to it, Backstage can offer similar functionality if you have the resources to build it out.

Answered By TestDrivenDev On

It's crucial that all code comes with valid tests. Only code that passes tests should be promoted. Incorporating these tests into something like GitHub Actions makes it more transparent and manageable.

Answered By CodePulse_Insider On

With the rise of AI-driven delivery, the bottleneck has shifted from writing code to reviewing and integrating it. This means platform teams need to manage not just infrastructure, but also a substantial amount of rapid, uncertain changes. In this new landscape, metrics regarding who is effectively handling ‘AI hallucinations’ become crucial for maintaining stability.

Answered By CloudWhisperer89 On

I'd recommend looking into a self-service IDP where developers can create their own namespaces and deploy with templated helm charts or something similar. It's important to set sensible defaults and guardrails; if they want to deploy malfunctioning applications, that's on them, not on DevOps. Just make sure to integrate some security scanning!

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