Recent submissions

Comment · 5 years ago
Comment · 5 years ago
We've been using Sleuth at LaunchDarkly as a single pane of glass for all changes going out into production. The addition of DORA metrics is exciting-- as an engineering leader, Accelerate (https://itrevolution.com/accelerate-book/) is one of the few books I've read where the practices described meet reality. Having a tool track those metrics is a welcome addition.

One thing I'm curious about is Sleuth's approach to the "garbage in, garbage out" problem-- if I'm tracking (e.g.) MTTR, I've found that our teams aren't always perfect about tracking the start / end times of an incident. If the data's incorrect, can I modify it in manually?

Comment · 9 years ago
Comment · 9 years ago
There's VSCO, Fluid, Roofstock, LaunchDarkly, and Uber coming soon. There's probably a few more great companies that I'm forgetting.
Comment · 10 years ago
Fun fact-- it was started by one the founders of HipChat.
Comment · 10 years ago
That's mostly right. We don't use ES as a primary datastore, though.
Comment · 10 years ago
I mentioned this briefly in the article, but we thought about doing something with Lambda + API Gateway. But doing the math, 5k RPS pushed through API Gateway is about $1500 daily just to authenticate.
Comment · 10 years ago
Comment · 10 years ago
We had a lot of operational experience with Mongo from our previous jobs at Atlassian, and started out storing almost everything in Mongo. As we scaled out, we migrated all of our high volume data into other stores-- analytics into DynamoDB, searchable data into ElasticSearch, etc.

The last remaining piece is our core data, and there's no strong push to move it out of Mongo.

Comment · 10 years ago
I think it depends on the workload. Serving 4.6k static pages per second, cached on a CDN, is not too difficult. However, handling an analytics workload of 4.6K RPS is a little harder.
Comment · 10 years ago
I was being cheeky :)

Events are stored in DynamoDB. We use mongo for "core" data like accounts, feature flags, etc, but none of the high throughput stuff touches MongoDB.

Comment · 10 years ago
For temporary feature flags, we try to clean up as soon as possible. As part of the rollout plan for a new feature, we'll have defined what metrics we're trying to achieve, and once we're confident that we've met those marks, we clean up the flag.

We eagerly create "cleanup branches" and corresponding pull requests to remove a flag-- that front-loads the cleanup work and means we aren't context switching back to try and remember how to clean up a flag.

Also, we've found that in practice flags are usually independent-- testing permutations of flags shouldn't typically be necessary. People usually take an analogous shortcut with feature branches-- we test branches in isolation but don't usually re-test after merging.

Comment · 10 years ago
Comment · 10 years ago
Our goal is to build a developer-focused platform that gives teams the ability to adopt feature flags as a core part of their dev cycle-- including pretty much all of the use cases described in Fowler's article (ops, permissioning, etc.). Many of our customers are not using us for A/B testing at all.

re: conditionals, DI: our SDKs focus on the base technique (flags based on conditionals), but it's possible to wrap that core with higher-level approaches like DI, etc. We're considering going down that path, but where it makes sense to do so, and not have to re-implement higher-level wrappers for every framework out there. So, e.g.-- in Ruby, I can see us providing higher-level APIs specific to Rails.

Dependent feature flags are also an interesting problem-- we don't have a solution to that yet, but we do spend a lot of time thinking about feature flags, and I hope we'll have something on that front soon :)

Comment · 10 years ago

Live from the official Hacker News API

A modern reader for Hacker News · SvelteKit + Skeleton