The rise of coding agents is changing where software engineering teams spend their time. As AI takes on more of the work of generating code, the harder problem is increasingly deciding which changes are safe to release and understanding what happens when they reach production.
Hud says AI now generates or assists with 42% of the code developers ship, a figure expected to reach 65% by 2027. The company’s new integration with ClickHouse is aimed at that transition, connecting production observability with code-level runtime intelligence.
The integration brings together ClickStack, ClickHouse’s open-source observability stack, and Hud’s Runtime Code Sensor. The companies say the combination gives engineering teams the production context needed to assess AI-generated changes, verify releases, and investigate production issues.
“AI is accelerating how quickly teams can generate code, but safely shipping it with high confidence requires production context,” said May Walter, CTO of Hud. “Hud and ClickHouse bring real production behavior at an unparalleled breadth and depth, so teams can build a production-aware AI SDLC: gating changes before they ship, proactively verifying them once deployed, and fixing issues as they arise – all using real runtime truth. Together with ClickHouse, we are bringing that intelligence across the entire AI SDLC.”
From What Broke to What Changed
ClickStack and Hud approach production from different layers.
ClickStack provides visibility across applications and infrastructure, helping teams identify the service, deployment, or endpoint associated with an issue. Hud works at the code layer, following function-level behavior and connecting production activity to the code changes responsible for it.
The systems can be connected through shared trace IDs, allowing a coding agent to move from an issue in ClickStack to the relevant code-level context in Hud.
“Our users already trust ClickHouse to store and query their Open Telemetry data at scale,” said Mike Shi, Head of Observability of ClickHouse. “The shift now underway is from simply watching systems or investigating issues to using that data to make day-to-day engineering decisions. Hud connects observability data to the code and changes behind it, making the entire stack more useful for teams building and shipping software with AI.”
That connection changes the role of observability. Rather than being used only after something goes wrong, production data can become part of engineering decisions before a change is released.
Using Runtime Data Before Deployment
The Hud+ClickStack integration supports pre-deployment risk assessment for code changes. Changes can be evaluated against real-time information about how affected code behaves in production.
Higher-risk changes can be held for additional review and deeper context, while safer changes can move faster or be automatically merged. The integration also supports release verification, automatic reversion when regressions occur, automated detection and investigation, and agentic workflows that create pull requests to address underlying issues.
This gives engineering teams a way to connect the speed of AI-generated development with information from the systems already running in production.
Closing the Loop After Release
Runtime intelligence also becomes relevant when a deployment causes an unexpected problem.
A production issue can originate with a small change: a query becomes slower, a code path consumes more resources, or a function behaves differently under a specific workload. Hud is designed to identify these issues at the function level and provide forensic context, while ClickStack provides the broader operational picture.
Together, the platforms are designed to help teams move from detection to investigation and resolution without separating the operational problem from the code responsible for it.
“Like every modern engineering organization, a growing share of our code is now written with AI,” said Rom Kadria, Senior Software Engineer at monday.com. “We write code much faster, but the challenge has shifted to shipping just as quickly while maintaining confidence that new code won’t cause harm. ClickHouse gives us the wide operational picture at scale, while Hud gives us the runtime intelligence and next-level introspection needed to evaluate and ship AI-generated code confidently. When issues do arise, combining ClickHouse and Hud allows us to triage and resolve them quickly. For a company building with AI, that combination is the obvious choice.”
A More Connected AI Development Cycle
Engineering teams can get started by installing the Hud SDK and connecting it to their ClickStack service. Hud’s runtime intelligence then flows alongside the OpenTelemetry data teams already collect.
The companies are ultimately positioning the integration around a straightforward idea: as AI makes software development faster, production behavior needs to become a more important part of the development process.
For engineering teams using coding agents, the ability to understand what code does in production can be as important as the ability to generate it. ClickHouse and Hud are combining their respective views to bring that context into decisions before deployment, during releases, and when problems emerge.
