Bring Your Own Agent: the beating heart of your observability AI, inside your cloud

When we built Tsuga on a Bring Your Own Cloud model, the reasoning was simple. Your telemetry is some of the most sensitive operational data you hold, and it should live inside your environment, under your keys, within your security boundary. We manage the platform so you get the ergonomics of a service without giving up ownership of the data underneath it.

The same reasoning now applies to AI. As agents become primary consumers of observability data, the intelligence layer sitting on top of your telemetry is becoming as sensitive as the telemetry itself. It carries your prompts, your production context, your incident history, and increasingly your institutional knowledge about how your systems behave. That is not something to hand over. It is something to own.

So alongside AI-native resilient observability, we deploy everything you need to Bring Your Own AI.

Your model, your environment, your rules

We do not ship an AI SRE agent and ask you to trust it. We provide the infrastructure that lets you build your own: an MCP server that gives agents structured, scoped access to your telemetry, a CLI designed for agent workflows, and a growing library of Skills that encode observability expertise your agents can draw on. You plug in the model you already use, or the one your organization has approved, and it operates entirely inside your environment.

This matters more than it might first appear. AI-assisted investigation is not primarily a model problem. It is a context problem, and we wrote about this in depth in our recent post on AI-assisted root cause analysis. An agent investigating an incident needs to move through your telemetry, your deployment history, and your operational context in recursive, high-volume loops. When that context is complete and the interfaces are built for machine consumption, the agent can work from the alert through the causal chain and surface a clear, evidence-based picture of what changed and why. When the context is sampled, fragmented, or locked behind interfaces designed for dashboards, the agent produces confident answers built on incomplete evidence.

With Tsuga, the context is complete because the data is complete. There is no sampling, no dropped signal, no rationing of what your agents can see. And because the whole system runs inside your cloud, the investigation loop never crosses your boundary. Your codebase context, your prompts, your telemetry, and your agents' reasoning all stay where they belong.

Boundaries as a feature, not a constraint

Agents need context, but they also need boundaries. Giving an autonomous system raw access to everything is not a strategy, it is a liability. The Tsuga platform includes an intelligence layer that scopes agent behaviour, controls token usage, and ensures your agents get structured access to what they need rather than unfiltered dumps of everything you hold.

That scoping is not just a safety measure. It is what makes agentic observability economically sane. Agents do not sample and they do not slow down, and an unscoped agent querying an unbounded dataset is a cost problem waiting to happen. Structured interfaces, scoped access, and controlled consumption mean your agents stay fast, focused, and predictable.

Observed, like everything else

Here is a detail we think matters. Your AI workloads on Tsuga are themselves fully observed. Every query an agent runs, every investigation loop, every Skill invocation lands in the same telemetry layer as the rest of your systems. You can see what your agents are doing, measure what they cost, and understand how they behave, with the same completeness you expect for any other workload. The intelligence layer is not a black box sitting beside your observability. It is part of it.

One model, one price, no surprises

All of this is included in our single price per gigabyte. The MCP server, the CLI, the Skills, the intelligence layer, and the observability of your AI workloads themselves come with the platform. There is no AI add-on tier, no per-agent fee, and no separate meter running on your investigations. One number covers the whole platform, and our success depends on the return you get from it. We have no incentive to make your telemetry noisier, encourage waste, or turn your agents' activity into billable volume.

Managed by Tsuga. Owned by you.

The pattern is the one we started with. We run and manage the platform so your teams do not have to, and everything that matters stays yours. Your telemetry lives in your object storage. Your agents run in your environment. Your model choices remain your own. Your operational intelligence, which is increasingly the most valuable thing your observability produces, never leaves your control.

The AI era of observability will belong to teams whose agents can see everything and share nothing. We built Tsuga so that is exactly what yours can do.