Hidden Costs of Self-Hosting AI Agents

"We'll just deploy it on Kubernetes." If you've ever been in a meeting where AI agent infrastructure came up, you've probably heard this. It sounds reasonable. Your team already runs services on K8s, how hard can it be to add one more?

The answer, as many teams discover 6 months and $300k later, is: harder than expected. Let's break down the actual costs of self-hosting AI agents, with real numbers.

The Visible Costs (What Everyone Budgets For)

These are the costs teams typically account for when planning AI agent infrastructure:

Looks manageable, right? Here's where it gets interesting.

The Hidden Costs (What Actually Kills Budgets)

1. Engineering Time to Build It

Self-hosting AI agents isn't just "deploy a container." You need to build:

• •Webhook ingestion layer: Accept external events, validate signatures, handle retries
• •Queue consumers: Process messages reliably with error handling and dead-letter queues
• •Agent orchestration: Manage concurrent runs, timeouts, and state
• •Deployment pipelines: CI/CD for agent code with versioning and rollback
• •Observability stack: Logging, tracing, metrics, dashboards

Conservative estimate: 2-3 months of senior engineer time. At $180k/year fully loaded, that's $30k-$45k just to get to "it works."

2. Ongoing DevOps Burden

Infrastructure doesn't run itself. Someone needs to:

• →Monitor for outages and performance degradation
• →Apply security patches and updates
• →Scale infrastructure as usage grows
• →Debug production issues at 3am
• →Handle on-call rotations

This typically requires at least 20-30% of a DevOps engineer's time. That's $3k-$5k/month in ongoing cost, often from your most expensive engineers.

3. Tools and Software

4. The Opportunity Cost

This is the hidden cost that doesn't show up on any invoice: what could your engineers have built instead?

Every hour spent debugging Kubernetes networking is an hour not spent on product features that differentiate your business. Every sprint dedicated to "agent infrastructure improvements" is a sprint your competitors are using to ship customer-facing features.

The 12-Month TCO Calculation

Let's add it all up for a realistic scenario: a mid-size team running moderate AI agent workloads.

"But We Already Have Kubernetes"

This is the most common objection, and it's worth addressing directly.

Yes, you have K8s. But AI agents aren't just "another microservice." They have unique requirements:

• •Unpredictable execution times: A simple query might take 2 seconds, a complex one might take 5 minutes
• •Token tracking: You need to know exactly how many tokens each run consumed for cost control
• •Execution traces: Standard APM doesn't capture LLM reasoning steps or tool calls
• •Hot-reload development: Your existing CI/CD isn't built for 2-second iteration cycles

You'll end up building a custom platform on top of your existing infrastructure, which brings you right back to the cost estimates above.

When Self-Hosting Does Make Sense

To be fair, there are legitimate reasons to self-host:

• 1.Extreme data sensitivity: Regulated industries where data cannot leave your infrastructure (though even here, private cloud options exist)
• 2.Massive scale: If you're running millions of agent invocations daily, the math might favor self-hosting
• 3.Core competency: If AI infrastructure IS your product, building expertise makes sense

For everyone else (teams where AI agents are a feature, not the product), the math strongly favors managed platforms.

Try Before You Buy (Into Self-Hosting)

Here's our recommendation: start with a managed platform and validate your use case before committing to infrastructure investment.

With Connic's free tier, you can:

• ✓Deploy agents in minutes, not months
• ✓Validate your integration patterns work
• ✓Get real usage data to inform build-vs-buy decisions
• ✓Ship AI features while evaluating long-term options

If your usage eventually justifies self-hosting, you'll have learned exactly what you need to build. If it doesn't (and for most teams, it won't), you've saved yourself a very expensive learning experience.

See our detailed breakdown on replacing self-hosted AI agents with a managed platform, check out our pricing page for the full cost comparison, or get started with the quickstart guide.