Hi all!
I built Spikelog because I kept wanting to track simple numbers over time but every time I looked at proper observability tools, I'd bounce off the setup complexity. I wanted to make something that didn't require a lot of thinking to use.
Spikelog is made to be as simple as possible:
- POST a JSON with chart name + value (you can add some tags as well but I've not tested this part works yet)
- Chart appears automatically
- 1,000 point rolling window per chart (old data expires, no retention config)
- Max 10 charts
That's basically the whole product.
I built it in about a day using Cursor. The API is intentionally minimal so AI assistants can use it too.
I have a prompt that lets your coding agent analyze a codebase and add tracking automatically (after you approve the plan).
I used it to make Spikelog track itself: https://spikelog.com/p/spikelog
There's no alerting yet (that's next), no complex aggregations, no dashboards beyond the auto-generated charts. If you need real observability use something fully featured like Axiom or Datadog. This is for people who just want to see if a number went up or down and don't want to build that themselves. i.e. they want something slightly better than just logging the number.
You can also share the charts publicly and I might add some password protection if there is demand for that.
I haven't battle-tested it under heavy load. The rolling window deletion is naive (deletes oldest points on insert). There are probably edge cases I haven't hit yet.
Would love feedback, especially if you try it and hit something broken.
avocadosword3 hours ago
I find interesting that you have added the AI prompt as an example integration guide. Will this become a new trend that products not only provide API, SDK but also prompts for your coding agent of choice.
dsmurrellop3 hours ago
A lot of products are giving some agent instructions as a guide to using them... e.g. https://electric-sql.com/docs/agents
This really helps if they've had large version changes and the coding agents (without a search) only know about the old docs.
In that sense, adding prompt instructions for Spikelog feels like a natural extension of this trend. I mainly added them to share what worked for me when integrating another product with Spikelog.
lionkor3 hours ago
> See Spikelog's own metrics ← Generated with one prompt
Ah, that's why it shows user count (an integer) as a floating point? Or is that an inherent limitation somehow?
dsmurrellop3 hours ago
Yep, that's not ideal... if all the numbers are integers, it would be better if Spikelog recognised the chart as a chart of ints and remove the floating points. Thanks for the feedback!
lionkor3 hours ago
How did you go about building this? What was your process, and how did you use AI to aid you?
dsmurrellop3 hours ago
I used Cursor and Opus 4.5. What made it faster for me was symlinking in a few on-going projects that I've been working on which gave Cursor a reference for how I set things up in these projects.
I also have this method for helping Cursor see the realtime output of services I'm running while developing locally which really speeds things up: https://foundinglean.substack.com/p/the-best-improvement-ive...
This substack is pretty new for me, but I'm planning on sharing more things there which may (or may not) help others. Next article there will just be sharing the symlinking setup (not rocket science - but some people don't know ln -s exists).
lionkor3 hours ago
So is this app essentially written by an LLM, not by you?
intev2 hours ago
What appeared as a good faith question, was answered in good faith and of course was later revealed to be a "gotcha" question. It's all so tiring.
"Oh so you drove all the way to my house? You couldn't walk?"
kordlessagainan hour ago
Poster literally says in the comment you replied to that they used other code they had to speed the development, so no it doesn't appear they wrote it entirely with an LLM, not that would matter if they did as long as it did what it was suppose to do (and what it was suppose to do isn't being defined by a gatekeeper).
dsmurrellop2 hours ago
Coding agents might get there someday, but today they still need quite a bit of assistance.
imiric2 hours ago
This looks neat, thanks for building and sharing it.
I do agree that observability stacks are usually a deep pit of things to configure and services to run, but there are tools that simplify things considerably. I can personally vouch for OpenObserve, and I've heard good things about SigNoz as well. They're essentially a single-binary deployment, and all it requires is configuring otel-collector on each machine you want to send data from. I know that OpenObserve has a REST API as well, so you can just send the data via plain HTTP if you prefer to not use OpenTelemetry.
So while I'm sure your project is useful for very simple use cases, it will be difficult to support anything slightly more sophisticated. And you'll have to reinvent the wheel for most of this, of course. But good luck, regardless!
dsmurrellopan hour ago
Thank you! and I appreciate the mentions... they’ll definitely be useful for my projects that need more than simple tracking. I might choose to link them instead of Axiom after doing more research into the options!
I’m very aware there are a lot of mature solutions in this space. Almost too much choice - which gave me decision paralysis when my need was simple. I’m not aiming to compete with full observability stacks like that. My goal with this was to intentionally stay on the extremely simple end of the spectrum. I'm aiming for something that’s quick to integrate, easy to understand, and focused on lightweight metrics rather than deep operational telemetry.
I’m also a big fan of Plausible and the idea of making select projects or charts publicly viewable in a dynamic way. Their public dashboard here was a big inspiration: https://plausible.io/plausible.io
That’s the model I borrowed for Spikelog as well: https://spikelog.com/p/spikelog
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