water company would outsource the analysis of their fixed network loggers to me

Bootstrapped VC backed

20 Apr 2025

Tech

water company would outsource the analysis of their fixed network ...

...loggers to me

Confidence

Engagement

Net use signal

Net buy signal

Idea type: Run Away

Multiple attempts have failed with clear negative feedback. Continuing down this path would likely waste your time and resources when better opportunities exist elsewhere.

Should You Build It?

Don't build it.

Your are here

The idea of outsourcing fixed network logger analysis for water companies faces significant headwinds. We categorized it under 'Run Away' due to previous failures and negative feedback. The existence of 4 similar products indicates some interest in the space, but the high engagement (19 comments per product) reveals potentially contentious issues. Unfortunately we don't have use or buy signal metrics, so we have no signals on if users would want to use this. Given the existing challenges and the availability of alternative solutions, pursuing this path might lead to wasted effort and resources. A pivot may be necessary to discover if your skillset can better solve a different, related problem. It is not recommended that you build this, based on what the data is telling us about this idea category.

Recommendations

Carefully review the criticisms from similar products to understand the pain points and why previous attempts may have failed. For instance, the discussion around Splunk alternatives highlights concerns about overcomplicated software and high costs. Try to identify if these concerns apply to your proposed service.
Consider whether your skills and the technology you plan to use can be adapted to solve a related but different problem. Could you focus on a specific niche within water management or offer a more streamlined and cost-effective solution compared to existing alternatives?
If you've already developed some technology for this idea, explore if it can be repurposed for a different application. Perhaps the data analysis techniques could be applied to other types of sensor data or infrastructure monitoring.
Speak with at least three potential customers (e.g., water companies) who have tried similar services or solutions. Understand their specific needs, pain points, and what they are actually looking for in a network logger analysis service. Do they see value in outsourcing this task, and what would make your offering stand out?
Use the insights you gained from customer interviews and competitive analysis to refine your value proposition and identify a potentially more viable business model. Ensure that you are addressing a clear need and offering a compelling advantage over existing solutions.
Consider focusing on a smaller niche within the water management sector to validate your solution before scaling up. A targeted approach might allow you to address specific customer needs more effectively and build a stronger reputation.
Explore potential partnerships with existing players in the water management industry. Collaborating with established companies could provide access to a wider customer base and valuable industry expertise.

Questions

Given the criticisms of overcomplication in existing logging solutions, how can you ensure your service remains simple and easy to use for water companies, especially those with limited technical expertise?
Considering the concerns about high costs associated with solutions like Splunk, how will you price your service to be competitive and attractive to water companies of different sizes, while still ensuring profitability?
Based on the needs you uncovered from your interviews with water companies, how will you adapt your existing analysis techniques to better cater to their needs?

Your are here

Recommendations

Carefully review the criticisms from similar products to understand the pain points and why previous attempts may have failed. For instance, the discussion around Splunk alternatives highlights concerns about overcomplicated software and high costs. Try to identify if these concerns apply to your proposed service.
Consider whether your skills and the technology you plan to use can be adapted to solve a related but different problem. Could you focus on a specific niche within water management or offer a more streamlined and cost-effective solution compared to existing alternatives?
If you've already developed some technology for this idea, explore if it can be repurposed for a different application. Perhaps the data analysis techniques could be applied to other types of sensor data or infrastructure monitoring.
Speak with at least three potential customers (e.g., water companies) who have tried similar services or solutions. Understand their specific needs, pain points, and what they are actually looking for in a network logger analysis service. Do they see value in outsourcing this task, and what would make your offering stand out?
Use the insights you gained from customer interviews and competitive analysis to refine your value proposition and identify a potentially more viable business model. Ensure that you are addressing a clear need and offering a compelling advantage over existing solutions.
Consider focusing on a smaller niche within the water management sector to validate your solution before scaling up. A targeted approach might allow you to address specific customer needs more effectively and build a stronger reputation.
Explore potential partnerships with existing players in the water management industry. Collaborating with established companies could provide access to a wider customer base and valuable industry expertise.

Questions

Given the criticisms of overcomplication in existing logging solutions, how can you ensure your service remains simple and easy to use for water companies, especially those with limited technical expertise?
Considering the concerns about high costs associated with solutions like Splunk, how will you price your service to be competitive and attractive to water companies of different sizes, while still ensuring profitability?
Based on the needs you uncovered from your interviews with water companies, how will you adapt your existing analysis techniques to better cater to their needs?

Confidence: Medium

Number of similar products: 4

Engagement: High

Average number of comments: 19

Net use signal: -4.0%

Positive use signal: 7.4%
Negative use signal: 11.4%

Net buy signal: -5.7%

Positive buy signal: 1.4%
Negative buy signal: 7.1%

Help

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

YDrip – An open source water meter that detects leaks

28 Sep 2023 Tech

Hi HN,I'm developing an open-source water meter for Home Assistant and thought the HN community might be interested. I've been using some version of it after a few costly toilet leaks that my city meter missed. Recently, I decided to polish it up so others could use it. It might also function as a gas meter reader (https://youtu.be/9Dso4EBAoiE), but this is still experimental.The device runs on 3 AA batteries and utilizes an ESP32-S3. It works by measuring the spinning magnet inside the brass housing. It stays in deep sleep until it needs to transmit usage or leak information. It's not an ideal CPU for battery-powered devices, but I chose it because it has a lot of support in the home automation community. To compensate for the power-hungry CPU, I am handling rotation counting and leak detection in programmable hardware. Currently, it consumes 50-75uA while the ESP32 is sleeping. The programmable hardware makes it an interesting platform for other use cases like electricity meter monitoring.I'm planning on selling the hardware and potentially offering a hosted solution for those who don't want to set up Home Assistant if there is demand.There is still a lot to do, like designing a waterproof case and completing the software. If you're interested in the details, I have a project log on Hackaday. Feedback, feature requests, and contributors are always welcome.Website: https://y-drip.comGithub: https://github.com/YDripShort demo: https://youtu.be/7eXRLN7OWA0

Great idea, excited for finished product.

Existing solutions have major caveats.

100.0%

Relevance

Analyze utility data and get alerts

04 Dec 2024 Analytics

We started this product to analyze water usage which was too high for a house. We ended up improving it to support gas and electricity and provide insights and usage information.It can also detect abnormal increase weak over weak and send an email, e.g. for a water leak or over use.It can show electricity usage with separation from EV, AC and everything else. It's not perfect but it works.Account required (you also need to download your utility data) but it is free for 2 weeks.To get data, you need a Green Button compatible utility, or one compatible with our Sync Companion app (HTTP client to log in to your utility and download a CSV); feel free to reach out if you want to add your utility.Thanks HN!

Relevance

My Single-File Python Script I Used to Replace Splunk in My Startup

21 Sep 2023 Developer Tools

Description
Criticism

My immediate reaction to today's news that Splunk was being acquired was to comment in the HN discussion for that story:"I hated Splunk so much that I spent a couple days a few months ago writing a single 1200 line python script that does absolutely everything I need in terms of automatic log collection, ingestion, and analysis from a fleet of cloud instances. It pulls in all the log lines, enriches them with useful metadata like the IP address of the instance, the machine name, the log source, the datetime, etc. and stores it all in SQlite, which it then exposes to a very convenient web interface using Datasette.I put it in a cronjob and it's infinitely better (at least for my purposes) than Splunk, which is just a total nightmare to use, and can be customized super easily and quickly. My coworkers all prefer it to Splunk as well. And oh yeah, it's totally free instead of costing my company thousands of dollars a year! If I owned CSCO stock I would sell it-- this deal shows incredibly bad judgment."I had been meaning to clean it up a bit and open-source it but never got around to it. However, someone asked today in response to my comment if I had released it, so I figured now would be a good time to go through it and clean it up, move the constants to an .env file, and create a README.This code is obviously tailored to my own requirements for my project, but if you know Python, it's extremely straightforward to customize it for your own logs (plus, some of the logs are generic, like systemd logs, and the output of netstat/ss/lsof, which it combines to get a table of open connections by process over time for each machine-- extremely useful for finding code that is leaking connections!). And I also included the actual sample log files from my project that correspond to the parsing functions in the code, so you can easily reason by analogy to adapt it to your own log files.As many people pointed out in responses to my comment, this is obviously not a real replacement for Splunk for enterprise users who are ingesting terabytes a day from thousands of machines and hundreds of sources. If it were, hopefully someone would be paying me $28 billion for it instead of me giving it away for free! But if you don't have a huge number of machines and really hate using Splunk while wasting thousands of dollars, this might be for you.

Users criticize the overcomplication of software, particularly with Ansible's inability to achieve true declarative management and the resulting inconsistent states. There's a consensus on the high cost and complexity of Splunk, with doubts about its value post-Cisco acquisition. The product is also seen as having excessive logging, poor maintainability due to global states, and a lack of documentation. Some users prefer simpler tools and question the spending on expensive SaaS solutions like Splunk and DataDog. There's also mention of outdated tools and the need for structured logging.

313

-9.9%

-8.5%

313

9.9%

2.8%

Relevance

Simple Log Alerts to Slack

06 Mar 2023 SaaS

There are many log alerting systems on the market. The best known is probably Datadog. There’s also Logtail, Papertrail, Splunk, Logstash and others.These are well put together products with a host of great features, such as excellent UIs, sophisticated live searching via web interfaces and sometimes query languages and alerting. They require various levels of installation and they have costs, either through volume-based tiered systems or monthly payments.For a bootstrapped business, this can be problematic, for instance when a surge of logs - indicating a possible important problem that needs to be solved - pushes volume on to another tier. Should the “log ransom” be paid?Instead, I recalled from earlier times surely the simplest log watcher: Swatchdog [1]. It is rather venerable software. Its file history from its source download shows dates in 2015, but it was written much earlier - the 90s or possibly 80s by Todd Atkins [2].We wanted to have alerts in Slack - the blog explains how we did it. In short: *very simply*. The code is available [3].[1]: https://github.com/ToddAtkins/swatchdog[2]: https://www.linkedin.com/in/toddatkins/[3]: https://github.com/profitviews/swatchdog

Users appreciate the hybrid approach and simplicity of the product, suggesting improvements like better notification customization and simpler setups. They recommend considering tools like fluentd for local log processing and custom log handlers for Python. Some users prefer GrayLog2 over DataDog or Logtail, and advise looking beyond the pricing page for clarity on 'genuinely free' services. Concerns about Slack's rate limits and the need for an allowlist for unexpected events are also mentioned.

Users criticized the product for not being suitable for cattle or high-turnover servers, having contentious executables location, and lacking journald support. There were concerns about errors being indistinguishable from regular messages, outdated email notifications, and unclear meaning of 'genuinely free'. Comparisons with Datadog and Splunk highlighted that the product is seen as less comprehensive. Slack's rate limits causing missed notifications and the lack of rate limits in other notification tools were also mentioned. Some users felt that tools like DataDog and Logtail are unnecessary for most businesses.

0.0%

-16.7%

16.7%

Menu