AI-assisted software development is moving quickly enough that writing code is no longer necessarily the slowest part of the engineering process. As coding agents take on a larger share of development work, teams face a different question: how can they determine whether those changes will behave as expected once they are running in production?
Hud says AI now generates or assists with 42% of the code developers ship, with that share expected to reach 65% by 2027. The company is addressing the resulting challenge through a new integration with ClickHouse that connects production observability with runtime code intelligence.
The integration combines ClickStack, ClickHouse’s open-source observability stack, with Hud’s Runtime Code Sensor. Together, the companies say the products can give engineering teams the context needed to evaluate changes before deployment, verify releases, and investigate problems after they appear.
“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.”
Two Different Views of the Same System
ClickHouse and Hud are approaching the problem from different points in the technology stack.
ClickStack provides broad visibility across applications and infrastructure. It can help teams identify the service, deployment, or endpoint associated with an issue. Hud focuses on the code itself, connecting production behavior to the functions and code changes responsible for it.
The integration allows a coding agent to connect the two through shared trace IDs. An engineering team can therefore move from an operational issue identified in ClickStack toward the corresponding 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.”
The significance is less about adding another monitoring layer and more about connecting operational information with the decisions engineers make about code.
Putting Production Data Before the Release
The integration is designed to move runtime intelligence earlier in the development process.
Hud and ClickHouse support pre-deployment risk assessment for code changes, allowing teams to evaluate changes against real-time information about affected code 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 workflow extends into deployment as well. The integration supports release verification, automatic reversion when regressions occur, automated detection and investigation, and agentic workflows that can create pull requests containing code-level fixes.
That creates a continuous connection between development decisions and production behavior rather than treating them as separate stages.
When a Small Change Causes a Big Problem
The same approach applies when something goes wrong.
Production issues can begin with a relatively narrow change. A query may slow down, a function may behave unexpectedly under a particular workload, or a code path may begin consuming more resources.
Hud is designed to detect such issues at the function level and provide forensic context about what caused them. ClickStack contributes the broader operational picture across the application.
The combined workflow supports rollback and remediation, while agentic workflows can automatically investigate issues and create fix pull requests.
“Like every modern engineering organization, a growing share of our code is now written with AI,” said Rom Kadria, Senior Software Engineer, 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.”
Turning Runtime Behavior Into Context
The broader goal is to give AI-powered engineering workflows access to more than static code or isolated alerts. With the integration, coding agents can work with runtime operational data, function-level context, and the history of how an application behaves.
Engineering teams can begin by installing the Hud SDK and connecting it to their ClickStack service, allowing Hud’s runtime intelligence to flow alongside the OpenTelemetry data they already collect.
As AI-generated code becomes a larger part of software development, the value of runtime context may increasingly extend beyond troubleshooting. For ClickHouse and Hud, it becomes part of the process of deciding what to ship, verifying that it works, and determining how to respond when production says otherwise.
