Measure helps mobile teams monitor and fix crashes, ANRs, bugs, and performance issues. The open source alternative to Firebase Crashlytics.
A startup from dover, the United States that is founded by Gandharva Kumar, Abhay Sood, Anup Cowkur, Debjeet Biswas.
This page is designed to help you find out whether Measure.sh is good and if it is the right choice for you.
Measure is an open source mobile observability platform built for production debugging. It helps mobile teams find and fix crashes, ANRs, UI freezes, slow API chains and edge-case state bugs, the failures that crash reporters never show you.
Most crash tools tell you that an app broke. Measure shows you what happened before it broke: a Session Timeline reconstructs the full user session- user actions, screen navigations, network calls, logs, lifecycle events, CPU and memory signals. So you can replay the path to a failure instead of guessing from a stacktrace.
What you get
Session Timelines & replays: every click, navigation, HTTP call, log line and system metric, captured automatically Crash & ANR reporting: symbolicated stacktraces, grouping and impact analysis App health metrics: crash-free rate, cold/warm launch times, app size, adoption by version Performance traces: break down slow flows and find the bottleneck span Bug reports: users shake the device; you get the report plus the session that led to it User journeys: see how people actually move through the app, and where they drop Network monitoring: request latency, status codes, failing endpoints Adaptive Capture: dial data collection up or down remotely, without shipping a new release AI debugging: Measure Agent and an MCP server so your coding agent can read production sessions
Platforms & deployment Android, iOS/iPadOS, Flutter, Kotlin Multiplatform and React Native. Available as managed cloud or fully self-hosted, the whole platform is Apache 2.0 licensed on GitHub.
Pricing
Usage-based (per GB ingested), with no per-seat charges. Because Adaptive Capture lets you control collection remotely, teams can tune cost without a release cycle.
Measure is built by mobile engineers who led mobile platform work at high-scale consumer apps including Gojek, Rapido and Groww.
Listed in
Crash Reporting
Crashes and ANRs with symbolicated stacktraces, grouping and version impact
Session Replay
Session Timeline replays every user action, screen, network call, log and system metric
Performance Monitoring
Traces, app launch times, network latency and app health metrics per release
Bug Reporting
Shake the device to file a bug, attached to the full session that led to it
Network Monitoring
Request latency, status codes and failing endpoints, tied to the session
User Journeys
See how users move between screens and where they drop off
AI Debugging
Measure Agent plus an MCP server so coding agents can read production sessions
Adaptive Capture
Dial data collection up or down remotely, without shipping a new release
Porsche, Astro, Hoichoi
Measure grew out of a problem its founders kept running into. Between them they had led mobile engineering at companies including Gojek, Rapido and Groww, including the years when Gojek's app scaled from around 10,000 to 35 million daily active users. At each company they ended up building similar internal tooling to answer the same question: why is the app slow, frozen or broken for a real user in production when crash reporting shows nothing wrong? After rebuilding versions of the same tool more than once, they decided to apply the DRY principle to the problem itself and turn it into a product instead of another internal project. Measure was released publicly in September 2024 and is developed in the open under the Apache 2.0 license, with the roadmap and issues visible on GitHub.
Mobile engineering teams running consumer apps in production, especially at high growth companies where app quality has a direct effect on revenue and retention. Typical users are Android and iOS engineers, mobile platform and foundation teams, mobile leads and engineering managers who are accountable for crash free rates, ANRs, startup time and release health, along with the CTOs and VPs of Engineering who own those outcomes. Because Measure is open source and can be self hosted, it also fits teams with strict data residency or privacy requirements, and smaller teams looking for an open alternative to Firebase Crashlytics.
Measure.sh is an open source observability platform built specifically for mobile apps, rather than a mobile SDK attached to a backend monitoring product. Its defining capability is the session timeline, which reconstructs a complete user session including interactions, navigations, network calls, logs, lifecycle events and CPU and memory signals. This allows teams to diagnose problems that never produce a crash, such as ANRs, UI freezes, slow API chains and edge case state bugs. Measure also provides Adaptive Capture, which lets teams change what data is collected remotely without shipping an app update, and an MCP server that exposes crashes, traces and sessions to coding agents. It is available as a managed cloud service or fully self hosted, and is licensed under Apache 2.0.
We have collected here some useful links to help you find out if Measure.sh is good.
Check the traffic stats of Measure.sh on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Measure.sh on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Measure.sh's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Measure.sh on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
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