1. For reducing outliving, I always create a ticket to remove the flag at the same time it gets added in. This way there's documented work that will get scheduled. YMMV depending on how your team does planning.
2. For flag branch implementations, it's often fine to do an if/else, but I've seen this blow up into a real headache. When I can, I like having two implementations of an interface that get swapped between. Code calls the interface as normal the the underlying implementation is the same. Works for React components and larger implementations/changes that already have an interface. Don't want to force an interface where it feels wrong.
Every project should have flags, but many projects need just the basics and a service is overkill.
Rolling your own JSON still feels like something we ought avoid though. Yes to start out it’s 95% booleans. But then you want a rollout. And then you want some targeting rules. And then you want non booleans… maybe some json. Oo wouldn’t it be nice if the json could conform to a schema… and then eventually you are like damn I really want to change these without deploying. Or you want to read the same flag from multiple services.
I’ve tried to incorporate this lowest common denominator into https://quonfig.com Use it totally free & open source as SDK, and it’s just loading JSON that you can track in git. Agents love it, hot reloads, SDK in lots of languages. But vs rolling your own you’ve got a lot of headroom on the design. A bunch of targeting operators. Segments etc. And then if you do want to get a nice UI / delivery network for real time updates, then you can use the paid side of things.
Local use description: https://docs.quonfig.com/docs/how-tos/open-source-local
> Yes to start out it’s 95% booleans. But then you want a rollout. And then you want some targeting rules. And then you want non booleans… maybe some json. Oo wouldn’t it be nice if the json could conform to a schema… and then eventually you are like damn I really want to change these without deploying. Or you want to read the same flag from multiple services.
There can be whole UIs and tooling and infrastructure to manage around them and that’s what the sass offer
The config approach is critical for using feature flags as a software development lifecycle tool. It is how you manage having a codebase which contains the unfinished code for new feature x, but can still be deployed and pass all tests without feature x being turned on.
In this model you need a mechanism which allows a developer who is working on feature x to enable it for local testing, and for your CI system to be able to interact with the flag system to test that the application works in both states - with x turned on and off.
This is ideal for trunk based development models; feature branches are an alternative approach that doesn’t really benefit from this (indeed it adds complexity to working in feature branches).
Meanwhile feature flag services are to solve the problem that different people using the same software need different features turned on. That can be as simple as internal testers or beta users, it can be holding features to roll out in fixed update windows per tenant, or it can be part of a risk management strategy where features are rolled out through progressive exposure.
It can also be tempting to mix up your feature flags system with an A/B testing system - you can use a feature flag service to expose a feature to a test cohort and measure performance changes.
There can be reasons for doing that but it’s really important not to tie all these things together: not every development lifecycle change is an ab test hypothesis. Not every ab test hypothesis is a development lifecycle change (often it is really about testing changes in data, and feature config is just one piece of data you might want to change). Similarly some other data changes than code changes need to roll out progressively to mitigate risk.
So all these things might be feature-flag shaped, but that doesn’t mean you can substitute different feature flag solutions in and solve the same problems.
This post is saying ‘it’s okay not to have an exposure control solution; you can have a config file’ - which is obviously true, if what you have is a config management problem, not an exposure control problem.
For Quonfig I landed on:
- Data model wise they are identical. Flags and configs can both be targeted. They can both use segments. They can both do partial rollouts. They can both have the same range of values (bool/number/duration/json/json-w-schema/etc)
- Its fine to use Flags for your Experiments/AB Tests, but that's just the "allocation engine". The rest of experimentation is the exposure tracking and goal tracking. Those ought live in your product analytics stack, because they are really just events. But its helpful to have a single place (flags) for the experiment allocation because then you can re-use segments for things like hold out groups / and just general targeting.
- The only real difference is that Flags are intended to be ephemeral and configs are intended to be permanent. A good UI should show you how long a flag has been alive and help you clean it up (or convert it to a config) if it's been true for everyone for too long.
- The use cases are different enough that it's worth keeping them in two separate UI.
Examples:
Experiment flags for A/B testing
Permission checks at a user level
Product flags for feature gating by plan
Rollout flags to launch a new feature gradually
Configuration for an account/system/feature
The number of times I had to push against the “just put it behind hasFeatureFlag(user, flag)” is more than I can count at this point! I think it comes from a misunderstanding of the DRY principle, to be honest.
In my experience, engineers aren't using them to account for managerial dithering, they're doing it for safe deployments and experiments and rollouts and such. A product with millions of users can easily have a tens or even hundreds of active switches at any moment (I'm assuming a large engineering team behind said product), and that's not necessarily a bad thing.
However, as someone else noted here, you absolutely MUST delete and clean up your flags/gates/whatever when you've completed that effort. That part can be tricky because not everyone has the discipline to pay off tech debt.
Usually, a flag/gate should not live in code for more than a few months. If it does, it should have robust justification.
Immediately create story to remove said feature flag controlling access to the feature and review it during backlog refinements.
There are no solutions, only tradeoffs.
I'll give some examples:
Firm 1 had a single server running tron [0] for ALL scheduling of processes.
Pros: very easy to see what should run when and made audits a breeze
Cons: the central server died and it was a giant outage response to make sure that when the server came up it didn't start killing processes that should be running
Firm 2 used a management gui to create custom cron entries on each machine
Pros: each node had a local copy of the schedule and could keep going even if the central system died
Cons: each node had a local copy of the schedule which could "drift" from other nodes, a node could be forgotten etc
So, more generally, I agree that it's good to label things as "ok" so that we don't get into flame wars etc. That being said, the more important point is to say that if you are going to pick a strategy, do the work to support, build tooling and plan for outages related to that strategy.
Any configuration read out of a JSON file is not hardcoded. Hardcoded means you need to recompile to change it.
(And yes, hardcoded, as in flags set with #define or equivalent, are totally fine depending on what you're doing.)
The blogspam marketing behind them is so strong
Simple, effective, cheap, easy to understand and manage. Not dependent on an external service, not dependent on a third-party.
That covers a lot of uses of feature flags without the bloat.