Operational Agents Aren’t Just Orchestrators
Agents, when armed with the right telemetry data, represent the next evolution of operational excellence. By integrating OpenTelemetry deeply into your agent frameworks, you are not just mitigating risk; you are building a foundation where human ingenuity and machine intelligence can truly collaborate. The future is not about replacing operators, but empowering them to solve problems faster, adapt quicker, and operate with unprecedented precision.
These “Operational Agents” at present are typically thought of as decision makers, or orchestrators. This definition is incomplete. A true operational agent must be grounded in rich telemetry data. Without telemetry, agents operate without the context they need to make reliable, meaningful decisions. The gap for most organizations is not agent frameworks or large language models. It is the integration of telemetry as a first-class input into the agent's thought and action.
Common Concerns About Agents in Ops
There are three core risks that come up when teams consider using agents for operations: the non-deterministic nature of their decisions, the shifting context around what counts as a valid response, and the fact that agents aren't yet common in production. Let’s break down these concerns and explore why they aren’t barriers to using agents.
Systemic non-determinism is already baked into modern infrastructure. Anyone running distributed systems knows this. If your team handles eventual consistency, unpredictable latency, and cross-region failover, you're already navigating the kinds of uncertainty agents bring. You’re more ready than you think.
Operational decisions are rarely clean. That’s why rolling back to the last known good state is usually the fastest path during an incident. In practice, incident response is a blur of hunting down changes and staring at dashboards to guess when things are healthy again. One way to bring clarity is to treat remediation and root cause analysis as separate jobs. Remediation protects your customers. Root cause protects your future. Trying to do both at once weakens both. Yes, agents are still new in this space. But new doesn’t necessarily mean dangerous. Ubiquity isn’t the same as safety, it just feels that way. The tools we’re comfortable with aren’t always the ones that serve us best.
We’ve built strong processes and abstractions to manage complex distributed systems, but the sentiment is that these tools are not applicable when running agents at scale. This is false. The common thread around managing any complex system is understanding the internal state of that system. The practice around this is Observability. And the current standard, OpenTelemetry, is already widely supported in agentic frameworks. Smolagents and LangChain have native OTel support, and vendors like Langfuse and LangSmith already ingest it.
Telemetry Is Rocket Fuel for Agents
This is rocket-fuel. OTel gives your agents access to the same telemetry humans use to operate at scale. That means richer context, more accurate predictions, and a feedback loop grounded in real-world data. If your agents can see what you see, they can act with far more precision; and they don’t need hours of debugging or dashboards to do it. While your teams have intervened in the order of minutes or hours, observability empowered agents can do more in a matter of seconds.
That said, we’re not yet at a point where you can simply pipe telemetry data to an agent and automatically reap the benefits. Even as agents become more common, you’ll need to innovate around domain-specific use cases for your telemetry data. More importantly, the data you're generating is critical for future advancements in agent capabilities.
Those aspirational, sci-fi scenarios where multitudes of agents write code, self-heal, auto-scale, and remediate production? High-fidelity telemetry data will be shipped between these actors to accomplish their tasks. The value of a mature Observability practice cannot be understated. Observability becomes the conduit for managing the magnitude of work your agents will be able to accomplish.
Where You Position Agents Matters
Feeding OpenTelemetry data to agents isn’t as simple as flipping a switch. If you've managed observability at scale, you know that data volume isn't the problem. The real challenge is delivering the right context to your agents at the right time and in a consistent format. Where you position agents in the telemetry pipeline is key. Too close to the source, and they’re overwhelmed by raw data. Too far downstream, and they miss critical signals. The sweet spot is across the pipeline, providing agents the right tools and context to act according to the signals they receive.
As these patterns evolve, we’ll need a control plane to manage agent placement, orchestration, and policy. Agents will need to collaborate across systems, just like services do today.
Why This Matters Now
In the end, operational agents are most powerful when they are equipped with OpenTelemetry data. By integrating this rich telemetry directly into your agents, you're enabling them to make smarter, faster decisions with immediately relevant context. The key investment is observability. It will become the central engineering practice. Investing in it now future-proofs your ability to unlock agents as active collaborators in the operational ecosystem.
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