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Search - "even when taking down the server"
I’m surrounded by idiots.
I’m continually reminded of that fact, but today I found something that really drives that point home.
Gather ‘round, everybody, it’s story time!
While working on a slow query ticket, I perused the code, finding several causes, and decided to run git blame on the files to see what dummy authored the mental diarrhea currently befouling my screen. As it turns out, the entire feature was written by mister legendary Apple golden boy “Finder’s Keeper” dev himself.
To give you the full scope of this mess, let me start at the frontend and work my way backward.
This function allows the user to better see the rows in the API Calls table, for which there is a also search feature — the very thing I’m tasked with fixing.
It’s worth noting that above the search feature are two inputs for a date range, with some helpful links like “last week” and “last month” … and “All”. It’s also worth noting that this table is for displaying search results of all the API requests and their responses for a given merchant… this table is enormous.
This search field for this table queries the backend on every character the user types. There’s no debouncing, no submit event, etc., so it triggers on every keystroke. The actual request runs through a layer of abstraction to parse out and log the user-entered date range, figure out where the request came from, and to map out some column names or add additional ones. It also does some hard to follow (and amazingly not injectable) orm condition building. It’s a mess of functional ugly.
The important columns in the table this query ultimately searches are not indexed, despite it only looking for “create_order” records — the largest of twenty-some types in the table. It also uses partial text matching (again: on. every. single. keystroke.) across two varchar(255)s that only ever hold <16 chars — and of which users only ever care about one at a time. After all of this, it filters the results based on some uncommented regexes, and worst of all: instead of fetching only one page’s worth of results like you’d expect, it fetches all of them at once and then discards what isn’t included by the paginator. So not only is this a guaranteed full table scan with partial text matching for every query (over millions to hundreds of millions of records), it’s that same full table scan for every single keystroke while the user types, and all but 25 records (user-selectable) get discarded — and then requeried when the user looks at the next page of results.
What the bloody fucking hell? I’d swear this idiot is an intern, but his code does (amazingly) actually work.
No wonder this search field nearly crashed one of the servers when someone actually tried using it.
What an absolute fucking disaster of a day. Strap in, folks; it's time for a bumpy ride!
I got a whole hour of work done today. The first hour of my morning because I went to work a bit early. Then people started complaining about Jenkins jobs failing on that one Jenkins server our team has been wanting to decom for two years but management won't let us force people to move to new servers. It's a single server with over four thousand projects, some of which run massive data processing jobs that last DAYS. The server was originally set up by people who have since quit, of course, and left it behind for my team to adopt with zero documentation.
Anyway, the 500GB disk is 100% full. The memory (all 64GB of it) is fully consumed by stuck jobs. We can't track down large old files to delete because du chokes on the workspace folder with thousands of subfolders with no Ram to spare. We decide to basically take a hacksaw to it, deleting the workspace for every job not currently in progress. This of course fucked up some really poorly-designed pipelines that relied on workspaces persisting between jobs, so we had to deal with complaints about that as well.
So we get the Jenkins server up and running again just in time for AWS to have a major incident affecting EC2 instance provisioning in our primary region. People keep bugging me to fix it, I keep telling them that it's Amazon's problem to solve, they wait a few minutes and ask me to fix it again. Emails flying back and forth until that was done.
Lunch time already. But the fun isn't over yet!
I get back to my desk to find out that new hires or people who got new Mac laptops recently can't even install our toolchain, because management has started handing out M1 Macs without telling us and all our tools are compiled solely for x86_64. That took some troubleshooting to even figure out what the problem was because the only error people got from homebrew was that the formula was empty when it clearly wasn't.
After figuring out that problem (but not fully solving it yet), one team starts complaining to us about a Github problem because we manage the github org. Except it's not a github problem and I already knew this because they are a Problem Team that uses some technical authoring software with Git integration but they only have even the barest understanding of what Git actually does. Turns out it's a Git problem. An update for Git was pushed out recently that patches a big bad vulnerability and the way it was patched causes problems because they're using Git wrong (multiple users accessing the same local repo on a samba share). It's a huge vulnerability so my entire conversation with them went sort of like:
"We have to."
"Fine, here's a workaround, this will allow arbitrary code execution by anyone with physical or virtual access to this computer that you have sitting in an unlocked office somewhere."
"How do I run a Git command I don't use Git."
So that dealt with, I start taking a look at our toolchain, trying to figure out if I can easily just cross-compile it to arm64 for the M1 macbooks or if it will be a more involved fix. And I find all kinds of horrendous shit left behind by the people who wrote the tools that, naturally, they left for us to adopt when they quit over a year ago. I'm talking entire functions in a tool used by hundreds of people that were put in as a joke, poorly documented functions I am still trying to puzzle out, and exactly zero comments in the code and abbreviated function names like "gars", "snh", and "jgajawwawstai".
While I'm looking into that, the person from our team who is responsible for incident communication finally gets the AWS EC2 provisioning issue reported to IT Operations, who sent out an alert to affected users that should have gone out hours earlier.
Meanwhile, according to the health dashboard in AWS, the issue had already been resolved three hours before the communication went out and the ticket remains open at this moment, as far as I know.5