I was at my very first job, Linden Lab, when EC2 and S3 came out in 2006. We were running Second Life out of three datacenters, where we racked and stacked all the servers ourselves. At the time, we were tangling with a slightly embarrassing data problem in that there was no real way for users to delete objects (the Trash folder was just another folder), and by the time we implemented a delete function, our ability to run garbage collection couldn’t keep up with the rate of asset creation. In desperation, we spun up an experimental project to try using S3 as our asset store. Maybe we could make this Amazon’s problem and buy ourselves some time?
Why yes, we could. Other “experimental” projects sprouted up like weeds: rebuilding server images in the cloud, running tests, storing backups, load testing, dev workstations. Everybody had shit they wanted to do that exceeded our supply of datacenter resources.
By 2010, the center of gravity had shifted. Instead of “mainstream engineering” (datacenters) and “experimental” (cloud), there was “mainstream engineering” (cloud) and “legacy, shut it all down” (datacenters).
Why am I talking about the good old days? Because I have a gray beard and I like to stroke it, child. (Rude.)
And also: it was just eight months ago that Fred Hebert and I were delivering the closing keynote at SRECon. The title is “AIOps: Prove It! An Open Letter to Vendors Selling AI for SREs”, which makes it sound like we’re talking to vendors, but we’re not; we’re talking to our fellow SREs, begging them to engage with AI on the grounds that it’s not ALL hype.
We’re saying to a room of professional technological pessimists that AI needs them to engage. That their realism and attention to risk is more important than ever, but in order for their critique to be relevant and accurate and be heard, it has to be grounded in expertise and knowledge. Nobody cares about the person outside taking potshots.
This talk recently came up in conversation, and it made me realize—with a bit of a shock—how far my position has come since then.
That was just eight months ago, and AI still felt like it was somehow separable, or a satellite of tech mainstream. People would gripe about conferences stacking the lineup with AI sessions, and AI getting shoehorned into every keynote.
I get it. I too love to complain about technology, and this is certainly an industry that has seen its share of hype trains: dotcom, cloud, crypto, blockchain, IoT, web3, metaverse, and on and on. I understand why people are cynical—why some are even actively looking for reasons to believe it’s a mirage.
But for me, this year was for AI what 2010 was for the cloud: the year when AI stopped being satellite, experimental tech and started being the mainstream, foundational technology. At least in the world of developer tools.
It doesn’t mean there isn’t a bubble. Of COURSE there’s a fucking bubble. Cloud was a bubble. The internet was a bubble. Every massive new driver of innovation has come with its own frothy hype wave.
But the existence of froth doesn’t disprove the existence of value.
Maybe y’all have already gotten there, and I’m the laggard. 😉 (Hey, it’s an SRE’s job to mind the rear guard.) But I’m here now, and I’m excited. It’s an exciting time to be a builder.
Hey that's a good beard!