Show HN: Supapool – a Supabase per coding agent in ~400 ms
6 by kevo1ution | 0 comments on Hacker News.
hi HN, I built supapool.io, an ephemeral full copy of supabase's services that you can spin up in ~400 ms (Auth, postgres, storage, realtime). so if you run multiple coding agents in parallel in different worktrees, they can now have their own copy of supabase without making changes that conflict with eachother. > why not use supabase docker locally? when I run 3-4 instances locally, my macbook gets hot and sometimes freezes. > why not use supabase branches? branches take minutes to setup, and are designed for persistence. this is expensive, and for a dev environment, it is too slow. > why not use mocks? mocks are bad for agents. i expect agents to test their migrations, SQL against real prod service behavior. agents hallucinate working mocks often. However, upside of mocks is that its faster and runs locally, but with supapool, the upside is less convincing. > how does it work/how is this economically viable? starting supabase in 400ms requires a few things:
1. a pool of ready supabase instances running warm, and colocated with region failover (us-east, us-west, europe-west, asia-southeast)
2. fast autoscaling when pool starts to shrink with microVM/firecracker
3. gutting strong persistence guarantees. dev agents don't need WAL, fsync, PITR, replication. anything for HA on a ephemeral supabase instance is bloat its in beta right now, and i'm using our gcp credits to bankroll this, so its free. the eventual pricing will be something like $/instance second and more cost effective than branching or self hosting/maintaining a supabase cluster. would love to get your feedback if you use supabase, and if you think there's something better that would fit your local coding agent setup. Thanks!
Thursday, 30 July 2026
Wednesday, 29 July 2026
New top story on Hacker News: Show HN: CheapFoodMap – A map of good meals under $10
Show HN: CheapFoodMap – A map of good meals under $10
16 by jaep1 | 15 comments on Hacker News.
I was recently laid off after 18 years, and gave myself 100 days to build soething useful in public. CheapFoodMap is a crowdsourced map of meal under $10, excluding franchises, local good eats only. It's inspried by 거지맵 (Begger's Map) a Korean crowdsourced map students use to find cheap eats. Ocverage is heaviest in Texas, since I live in Dallas, but have 1200 meals across 15 US cities. Seed data came from Google Review, 4.2 star or higher with at least 500 reviews, and verified price under $10 per menu item. Things I would love feedback on : whether the price-freshness model makes sense, and what would make you trust the price on a site like this. How to encourage people to update prices, since inflation is making food price very frequent. https://ift.tt/fLsUuRk Any and all suggestion will be super helpful. Thank you!
16 by jaep1 | 15 comments on Hacker News.
I was recently laid off after 18 years, and gave myself 100 days to build soething useful in public. CheapFoodMap is a crowdsourced map of meal under $10, excluding franchises, local good eats only. It's inspried by 거지맵 (Begger's Map) a Korean crowdsourced map students use to find cheap eats. Ocverage is heaviest in Texas, since I live in Dallas, but have 1200 meals across 15 US cities. Seed data came from Google Review, 4.2 star or higher with at least 500 reviews, and verified price under $10 per menu item. Things I would love feedback on : whether the price-freshness model makes sense, and what would make you trust the price on a site like this. How to encourage people to update prices, since inflation is making food price very frequent. https://ift.tt/fLsUuRk Any and all suggestion will be super helpful. Thank you!
Tuesday, 28 July 2026
Monday, 27 July 2026
Sunday, 26 July 2026
Saturday, 25 July 2026
New top story on Hacker News: Show HN: I made some transistor animations
Show HN: I made some transistor animations
30 by stunningllama | 2 comments on Hacker News.
Hi HN, I made some animations of the most important kinds of transistors using my semiconductor simulation, details of which are on the page. I tried to make the visuals as realistic as possible while also aiming for clarity. If you want to go beyond the charge carriers and look at, for example, the electric field, you can do so in the simulation software. The desktop software also has less common devices like IBGTs and SCRs that have similar animations. The last thread about my software was posted here about a year ago: https://ift.tt/XfaPcrG
30 by stunningllama | 2 comments on Hacker News.
Hi HN, I made some animations of the most important kinds of transistors using my semiconductor simulation, details of which are on the page. I tried to make the visuals as realistic as possible while also aiming for clarity. If you want to go beyond the charge carriers and look at, for example, the electric field, you can do so in the simulation software. The desktop software also has less common devices like IBGTs and SCRs that have similar animations. The last thread about my software was posted here about a year ago: https://ift.tt/XfaPcrG
Friday, 24 July 2026
New top story on Hacker News: Nvidia, Microsoft, Meta warn against overregulating open-weight models
Nvidia, Microsoft, Meta warn against overregulating open-weight models
43 by louiereederson | 74 comments on Hacker News.
Letter: https://ift.tt/qUFdC5D... [pdf] https://ift.tt/tuRMXnb , https://ift.tt/MCLlro4 https://ift.tt/AzDPijF... , https://ift.tt/plf8Kk9
43 by louiereederson | 74 comments on Hacker News.
Letter: https://ift.tt/qUFdC5D... [pdf] https://ift.tt/tuRMXnb , https://ift.tt/MCLlro4 https://ift.tt/AzDPijF... , https://ift.tt/plf8Kk9
Thursday, 23 July 2026
New top story on Hacker News: Show HN: Trifle – Open-source analytics that stores answers, not events
Show HN: Trifle – Open-source analytics that stores answers, not events
7 by iluzone | 0 comments on Hacker News.
Trifle is an open-source time-series analytics library that aggregates nested counters instead of storing raw events. All in the database you already have. After rebuilding it twice over 10 years, it now tracks ~1B events a day at my day job. It started in 2015 as my own Rails APM. I plugged into ActiveSupport::Notifications, got a few small users, and one bigger one whose scraping app broke everything. That sparked the core idea: aggregate counters into pre-defined time buckets, so a single write increments multiple buckets at once. The APM eventually faded away without much traction. Later in 2021 I needed analytics at my day job. Instead of going for something out there I revised the idea of Trifle as a more generic analytics library, borrowing some data warehouse ideas. First used Redis, then Postgres, eventually MongoDB. Hence why Trifle::Stats comes with multiple drivers that keep the DSL unified while storage layer changes with your needs. In our case (huge write volume, some reads) PG read faster but slowed on large writes. The nested values are the whole trick here. Single: Trifle::Stats.track( key: 'requests::aws::s3_uploads', values: { count: 1, status: { request.response_code => 1 }, size: payload.bytes, duration: { sum: request.duration, count: 1 } } ) builds up counts for requests, success rate, result status codes, duration for multiple time buckets at once. Single bucket from 2am then looks like: { count: 14, status: { 200: 12, 500: 2 }, size: 5628341, duration: { sum: 43, count: 14 } } If request.duration is in seconds, then sum stored under duration would be in seconds as well. Success rate is never stored, but it is calculated by dividing 200s over total number of requests. Same with average duration: sum over count. You ask for a metrics key, granularity and timeframe and you get back aggregated values at each point. Ready for charts or to answer "Average response time over last 30 days". There's a Series wrapper for aggregating and formatting values for charts in a simple call. And as building dashboards is not as much fun for other devs as I thought, I built Trifle App - a visual layer with dashboards, scheduled digests and alerts. It's written in Elixir, so I ported the library to Elixir too. And later to Go for a CLI. All three are compatible, write in one and read in another. Today we track activity from over 100M background jobs a day which turns into about 1B events. It runs surprisingly cheap when you're willing to trade some safety away (turn off journaling and write concerns in Mongo). 3-node Hetzner MongoDB cluster where the primary does 20% utilization costs us around $1k/month. It has its limitations. Payloads can't hold tens of thousands of keys. Documents becomes too large to update efficiently. Some planning ahead is needed. And then there are no dimensions. Sometimes you can nest them (country - there are only so many countries), sometimes it's better to have dedicated metrics key per dimension (customer - growing forever). That multiplies tracked events, hence 1B events from 100M jobs. The libraries are MIT. The App is source-available under ELv2 - free to self-host and paid cloud if you want it managed. I build this on the side with no investor money to burn on a free service. Happy to answer anything about architecture, storage models, my failures or why I didn't give up on this yet.
7 by iluzone | 0 comments on Hacker News.
Trifle is an open-source time-series analytics library that aggregates nested counters instead of storing raw events. All in the database you already have. After rebuilding it twice over 10 years, it now tracks ~1B events a day at my day job. It started in 2015 as my own Rails APM. I plugged into ActiveSupport::Notifications, got a few small users, and one bigger one whose scraping app broke everything. That sparked the core idea: aggregate counters into pre-defined time buckets, so a single write increments multiple buckets at once. The APM eventually faded away without much traction. Later in 2021 I needed analytics at my day job. Instead of going for something out there I revised the idea of Trifle as a more generic analytics library, borrowing some data warehouse ideas. First used Redis, then Postgres, eventually MongoDB. Hence why Trifle::Stats comes with multiple drivers that keep the DSL unified while storage layer changes with your needs. In our case (huge write volume, some reads) PG read faster but slowed on large writes. The nested values are the whole trick here. Single: Trifle::Stats.track( key: 'requests::aws::s3_uploads', values: { count: 1, status: { request.response_code => 1 }, size: payload.bytes, duration: { sum: request.duration, count: 1 } } ) builds up counts for requests, success rate, result status codes, duration for multiple time buckets at once. Single bucket from 2am then looks like: { count: 14, status: { 200: 12, 500: 2 }, size: 5628341, duration: { sum: 43, count: 14 } } If request.duration is in seconds, then sum stored under duration would be in seconds as well. Success rate is never stored, but it is calculated by dividing 200s over total number of requests. Same with average duration: sum over count. You ask for a metrics key, granularity and timeframe and you get back aggregated values at each point. Ready for charts or to answer "Average response time over last 30 days". There's a Series wrapper for aggregating and formatting values for charts in a simple call. And as building dashboards is not as much fun for other devs as I thought, I built Trifle App - a visual layer with dashboards, scheduled digests and alerts. It's written in Elixir, so I ported the library to Elixir too. And later to Go for a CLI. All three are compatible, write in one and read in another. Today we track activity from over 100M background jobs a day which turns into about 1B events. It runs surprisingly cheap when you're willing to trade some safety away (turn off journaling and write concerns in Mongo). 3-node Hetzner MongoDB cluster where the primary does 20% utilization costs us around $1k/month. It has its limitations. Payloads can't hold tens of thousands of keys. Documents becomes too large to update efficiently. Some planning ahead is needed. And then there are no dimensions. Sometimes you can nest them (country - there are only so many countries), sometimes it's better to have dedicated metrics key per dimension (customer - growing forever). That multiplies tracked events, hence 1B events from 100M jobs. The libraries are MIT. The App is source-available under ELv2 - free to self-host and paid cloud if you want it managed. I build this on the side with no investor money to burn on a free service. Happy to answer anything about architecture, storage models, my failures or why I didn't give up on this yet.
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