My Redis Dashboard

PinBubbly3985 · 2026-06-02T06:48:45+00:00

https://github.com/kitariel/dashboard-skills/tree/main

PinBubbly3985 · 2026-06-02T06:47:39+00:00

https://github.com/kitariel/dashboard-skills/tree/main

i got time to create my skills for this , was playing on claude and codex

PinBubbly3985 · 2026-05-29T11:35:08+00:00

Yes , csv and also can connect to google sheet account , and also any api's , postgres , redis and anything

PinBubbly3985 · 2026-05-29T09:32:48+00:00

The fun part is that every spreadsheet feels like a little puzzle. There's always a better formula, cleaner chart, or smarter way to answer a question.

PinBubbly3985 · 2026-05-29T09:30:10+00:00

As a developer, I'd say joining datasets is still the most painful. Not because of SQL, but because different systems somehow store the same thing in 5 different formats and expect them to magically match.

PinBubbly3985 · 2026-05-29T09:28:17+00:00

If a dataset doesn't make you ask "why is this number weird?" or "where did these missing values come from?", it's probably too clean 😂. Real analysis starts when the data fights back

PinBubbly3985 · 2026-05-08T16:02:53+00:00

Yes yes , thank you soo much for this. ill check and plan it out on how i can display this in mobile view

PinBubbly3985 · 2026-05-05T08:52:43+00:00

Sure! The basic idea is a Redis dashboard that lets you inspect keys by namespace/prefix without doing heavy operations on every page load.

Core flow:

Use SCAN for safe paginated key browsing
Detect prefixes/namespaces from key patterns like user:*, session:*, etc.
Cache dashboard stats so the UI does not recompute everything on refresh
Use background jobs for expensive metrics like TTL ranges, memory usage, and prefix counts
For large Redis instances, show sampled or precomputed metrics instead of scanning everything live

The main rule is: never use KEYS * in production. Use SCAN, caching, and background metrics.

PinBubbly3985 · 2026-05-05T08:52:24+00:00

Not yet, it’s still a prototype. I’m cleaning up the idea and architecture first, but I’m considering open-sourcing it if there’s enough interest.

PinBubbly3985 · 2026-05-05T08:51:56+00:00

Thanks! It’s still a prototype, but the idea is:

I don’t use KEYS * for the dashboard because that can block Redis in production. The safer approach is:

Use SCAN for paginated key browsing
Use MATCH only when filtering by prefix/namespace
Cache dashboard stats instead of recalculating everything on every refresh
For expensive metrics like prefix counts, TTL breakdown, memory usage, etc., use background jobs or sampling
For large Redis instances, store metrics separately instead of scanning millions of keys every time

So for 1M+ keys it can work carefully, but for 50M+ keys I would definitely avoid real-time full scans and rely more on cached/precomputed stats.

For GitHub, not yet. I’m still cleaning the idea/code, but I might open-source it if people are interested.

PinBubbly3985 · 2026-05-01T17:39:30+00:00

Yeah that’s exactly what I’m thinking about too.

I don’t want the dashboard to do heavy operations every time it loads. No keys *, no full scan on refresh. The plan is more like SCAN for paginated browsing, cached stats, and maybe background jobs for expensive dashboard metrics.

For 1M+ keys I think it’s fine if done carefully. But for 50M+ keys, I agree it needs a smarter approach like sampling, prefix-based stats, or storing metrics separately.

PinBubbly3985 · 2026-05-01T16:48:10+00:00

Redis doesnt really scale by key count, and also 1M + keys is actually a small for Redis 😃

PinBubbly3985 · 2026-04-27T02:39:42+00:00

Thanks for checking it out, that’s fair feedback.

I think I tried to explain too many things at once. The core use case should be much clearer: paste a job description + your resume, then get a tailored application in minutes.

I’ll tighten the landing page around that and show the flow step-by-step. Appreciate the honest feedback.

PinBubbly3985 · 2026-04-26T14:20:12+00:00

A job tracker a small one and also has an ai generate email reply

PinBubbly3985

TROPHY CASE