This is a submission for DEV's Summer Bug Smash: Smash Stories powered by Sentry.
For about a day I thought AgentRAM was slow in a way I couldn't fix.
The whole pitch of the thing is that it's simple. A memory API for AI agents, one call to store, one to recall, no vector database, no embeddings, no model sitting in the request path adding half a second every time. The entire reason to pick it over something heavier is that it should feel instant. So when a plain store-then-recall started taking three seconds, it wasn't just a bug. It felt like the premise was wrong.
Three seconds. For a key-value read. I want to walk through how I chased it, because I went after the wrong suspect twice before I found the real one, and the real one was almost boring.
First suspect: my own code
The obvious thing to blame is your own code, and usually you're right. So I read the request path line by line. Every step that touched the database was a single operation. Nothing looped. Nothing waited on anything it didn't need. There was no query hiding inside a helper that ran ten more, no accidental full scan, no work being done twice. I counted the trips to the database on one hand, and every one of them had a reason to be there.
I added timing around each step anyway, because reading code and measuring it are two different things, and only the measuring counts. The timings came back fine. Everything I'd actually written was doing its work in a few milliseconds. So the three seconds were coming from somewhere I wasn't looking, and that's the bad kind of three seconds.
Second suspect: the database
If it's not my code and the time is going somewhere between my code and the data, the database is the natural next place to point. Maybe the query planner was doing something dumb. Maybe I was missing an index and the two rows in my test table were lying to me about how a real query would behave.
So I ran the queries directly against the database with timing on. They came back almost instantly. Of course they did, there was barely anything in the tables. The database wasn't slow. If anything it was sitting there wondering why I was accusing it.
This is the part of debugging nobody warns you about. You rule out two suspects and instead of feeling closer you feel worse, because the time is definitely being spent, it's right there on the clock, and you've just proven it isn't going to either of the two places it should be going. It was real and I couldn't find where it lived.
The thing I wasn't measuring
I had been timing the work. I had not been timing the distance.
My API runs on one managed platform. My database runs on another. Both are good and I'd pick both again. But I had set them up at different times, on different days, thinking about different things, and I had never once stopped to ask where each of them physically was. They were in different regions. Every single query my API made was leaving one part of the world, crossing to another, and coming back. Not once per request. Once per query, and a request makes several.
A few milliseconds of real database work, wrapped in a round trip that went most of the way around the planet and back, several times over, for one request. That was the three seconds. Not my code, not the query. Just distance I'd never thought to check, because the gap between two services feels like it should be nothing right up until the day it isn't.
There was a second, smaller offender next to the first. The very first request after a quiet stretch was always the worst, clearly worse than the ones right after it. A cold connection. Nothing was keeping the path warm, so the first visitor after any lull paid to wake everything up.
The fix was smaller than the hunt
I moved the API to the same region as the database. That was most of it gone immediately. The queries still do the same tiny amount of work, they just no longer take a world tour to do it.
Then I gave the health check something useful to do. There's already a monitor pinging the service to check it's up, so I let that ping keep the path warm. Now the first real user of a quiet morning isn't the one who pays to start the engine. The monitor pays it instead, on a schedule.
Three seconds went to about three quarters of one. Same code, same database, same two rows. All I changed was where things sat relative to each other and whether the path stayed awake. I didn't optimize a single query or rewrite anything. I moved two things closer together and stopped letting the connection go cold.
What stayed with me
Here's the part I didn't expect to matter.
When it was fixed and I sent the test request and watched it come back in under a second, it was very late and I was the only one awake. And that fast response came back from a service I had built by myself, that other people, developers I will probably never meet, were going to call from their own agents. That landed harder than the fix did. The number on the screen was small. The distance it had just closed, between me and whoever ends up using this, was the part I sat with.
Then I closed the laptop, because it was late.
If you're running two managed services and something feels slow for no reason you can find, check where they physically are before you start tearing your own code apart, and check whether the first request after a quiet stretch is the slow one. Distance and cold starts don't show up in a code review, because they aren't in your code. They're in the space between the two boxes, which is the part you never think to look at.
I almost rewrote a thing that was never the problem. The problem was that I'd never asked my two services if they lived in the same city.
What's the one that got you? The bug you spent hours accusing your own code over, before you found out the real culprit was somewhere you'd never thought to look. I want to hear it.
(I hit this one building AgentRAM, a memory API for AI agents, in the open. The story's the point here though, tell me yours.)
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