An influxDB front end made for engineers

Hacker News

Hey HN! I met many engineers using InfluxDB ( https://www.influxdata.com/ ) for storing test and measurement data. InfluxDB is awesome. But the UI confuses them sometimes. I see people struggling to - find the time range of their data - make sense of window periods & aggregation functions - compare measurements across different time ranges - and much more... Grafana does not plug the gap, because it is mainly aimed at monitoring real-time stuff. Engineers need to interact in a much more interactive way with their test data. We have solved these challenges in the past for files in Marple. Today we bring the same UI to people using an Influx database. This gives users - speed: Marple optimises the queries for you - UX: no windows, no aggregate functions to worry about - engineering workflow: data exports, statistics, compare time ranges, ... - projects: reuse plots and share interactively with your team Fun fact: the refactor to generalise our data engine proved quite the challenge, feel free to ask our lead dev Jan (jan@marpledata.com) about this! Make sure to try it out if you are using Influx - we have a free product tier! Nero (Co-founder)

Visit product View on Hacker NewsOct 27, 2022

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best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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