Measure provides the high-fidelity telemetry required for the next generation of AI-assisted mobile development and autonomous debugging. While existing AI coding agents can write UI components or fix logic errors, they struggle with production-only bugs that lack sufficient context. By capturing detailed event sequences—including gestures, network states, and system resource usage—Measure creates a rich data set that can be used to ground AI agents in the actual execution state of a mobile app.
In the agent stack, Measure acts as the telemetry layer for autonomous debugging agents. An agent equipped with Measure's API can analyze a crash report, correlate it with preceding user actions, and propose a fix based on the device's state at the time of failure. As companies move toward autonomous maintenance of mobile apps, the availability of open and detailed telemetry becomes a prerequisite for reliable agentic workflows.
Mobile development is notoriously difficult to debug. Unlike web development, where you can often reproduce an issue by opening a console, mobile apps fail in the wild across thousands of device and OS combinations. Measure is an open source observability tool designed specifically to solve this visibility gap for Android, iOS, Flutter, and React Native applications. Founded in early 2024 by Ragunath Jawahar and Sutirth Chakravarty, the project targets developers who are tired of manually piecing together fragmented logs and crash reports.
The core of Measure is its SDK, which automatically captures a broad range of telemetry without requiring developers to manually instrument every single interaction. This includes standard crash reports and exceptions, but goes much deeper into the actual user experience. The SDK monitors Application Not Responding (ANR) events, gesture interactions like clicks and long presses, and lifecycle changes for activities, fragments, and view controllers. By recording these events alongside system metrics like CPU usage, memory consumption, and network changes, Measure provides a chronological trace of exactly what happened leading up to a failure.
One of the defining characteristics of Measure is its open source nature. In a market dominated by proprietary SaaS solutions, Measure allows teams to self-host their monitoring infrastructure. This is particularly relevant for companies with strict data privacy requirements or those who want to avoid the high costs associated with data ingestion in cloud-based observability platforms. The platform exposes a REST API for both its SDK and its dashboard, allowing developers to build custom integrations or extract raw data for external analysis.
The dashboard focuses on reducing the time to resolution by presenting events in a unified timeline. When a developer investigates a crash, they aren't just looking at a stack trace; they are looking at the user's journey—the buttons they clicked, the screens they navigated, and the memory spikes that occurred. This level of detail is intended to eliminate the "cannot reproduce" status that plagues many mobile bug reports.
Measure sits in a competitive space but differentiates itself through its focus on deep context and developer autonomy. While incumbents often focus on broad application performance monitoring (APM) across the entire stack, Measure is built from the ground up for the mobile engineer. It handles mobile-specific nuances, such as cold versus warm app launches and low-memory warnings, which are often overlooked by general-purpose tools.
The project has already gained traction among companies in the Indian tech ecosystem, including Country Delight, Turtlemint, and hoichoi. These teams use Measure to gain visibility into production environments where network conditions and device performance vary wildly. By providing a clear alternative to the standard mobile monitoring stack, Measure is positioning itself as a foundational layer for mobile reliability and maintenance.
Open source mobile app monitoring and observability.
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