And context can be extremely tailored to your niche: specific inventory, from a specific supplier, for a specific user of a specific B2B client of a specific business model subtype, who should or shouldn’t see certain features on that specific inventory at certain times.
When you can write your own logic, and just run this in a tight loop as easily and performantly as you can use a constant, it makes your business incredibly agile. Think some text might change for some customers? Just write the code to make it configurable, and you get tests and flags for free.
Sadly, that zero-hop setup requires a sophisticated client execution engine, which it doesn’t appear Cloudflare has implemented here. Makes sense for their memory constrained workers, less sense for traditional infrastructure.
Statsig has an approach here that I quite like:
> To be able to do this, Server SDKs hold the entire ruleset of your project in memory - a representation of each gate or experiment in JSON. On client SDKs, we evaluate all of the gates/experiments when you call initialize - on our servers.
https://docs.statsig.com/sdks/how-evaluation-works
You can also roll your own - just sync your rulesets to a few data structures every few seconds in a background thread and atomically swap the reference to them. Then you just need a CRUD interface over the applicability ruleset dimensions.
Just be careful to have governance on who can play with which would-be constants. Great power and great responsibility and all that!
It doesn't have to be sophisticated and they don't need to implement it themselves. They piggy-back on OpenFeature where the client libraries have a simple targeting rule evaluation engine integrated.
The per-seat billing we have in our agreement is a bit rough but it's workable.
https://www.stigg.io/blog-posts/entitlements-untangled-the-m...
wait what? what kind of logic do you need to do that CF Workers can't do?
I agree that problem is not particularly hard in the grand scheme of things, but it is actually quite big, meaning it requires a lot of features that aren't obvious at first glance.
Edit: Thought of another analogy that may help explain the complexity. At their heart, feature flags are really a permissioning system: only certain users get access to certain pieces of functionality. Anyone who has ever dealt with permission systems know how complex they can be: group membership, including hierarchical groups, roles, ACLs, etc. All of those things are really analogous (actually, a subset really) to the various types of targeting rules that can be used in a feature flags system.
To me the main appeal of feature flags is that they allow to work on large features that often require months and many commits to finish in a main branch. This, at least to me, results in a more lightweight and more iterative development process. This contrasts with maintaining a separate branch, with perhaps separate deployment target for a large in-development features.
Cloudflare themselves even uses them internally as such, by shipping new features/builds to their free customers first, and then progressively larger customers after a settling period.
Feature flags can also be randomly turned on, for a sort of fuzz testing. Don't think of them just as 'new things' - it could be 'changed behavior'.
I guess you could think of them as a boolean on every client but they're generally not implemented that way.
Oh, that's right, you just spouted a "big company bad" mantra without bothering to read the article. Look, I know saying RTFA goes against the HN guidelines, but the amount of increasingly lazy spew i see from folks (or bots) who haven't bothered to read the article is so tiresome and annoying.
How do you set a boolean to only return true for queries to 5% of the fleet? And which 5% of the fleet? And then ramp up on a predefined cadence? Or how about returning true only for customers in the preview group for the feature? Does the database return false automatically if the 5% of the fleet where it's true start crashing or throwing exceptions? Does it hook into your observability stack?
Fundamentally, sure, you could just implement it as a boolean in the database. It's the integration and tooling that works with the rest of your stack that makes it worthy of the name "feature flag".
> The client provider requires an API token to fetch flag values. This token is not scoped to a single app, so anyone with the token can evaluate flags across all apps in your account. Use the client provider with caution in public-facing applications.
https://developers.cloudflare.com/flagship/sdk/client-provid...
Can anyone clarify... why the client SDK, designed to be deployed to browsers, requires caution? Does this mean that any client could send requests with a new targetingKey and observe other users' flags?
While flags probably shouldn't be critical information, this seems like an interesting design choice.
There is no way 6 months ago someone at CloudFlare thought it was a good idea to build a competitor to say LaunchDarkly.
Their recent features / announcements have been equivalent to:
(LaunchDarkly)
Resend, Firecrawl, CrewAI, Helicone, Replicate, Pinecone
-
Which like… many companies have a painful procurement process. If all you need is Cloudflare, and prices are within reason- why not use them
Here's why we built it!
How many minutes do I need to wait until app-scoped tokens are live?
https://blog.cloudflare.com/enterprise-grade-features-for-al...
—-
I don’t believe a single enterprise only feature has made its way to lower tier (paid) account yet.
I’m most interested in:
https://developers.cloudflare.com/speed/optimization/content...
https://community.cloudflare.com/t/making-enterprise-product...
Check a config, bdd value, env var to dynamically go one path or the other.
That’s all, you must either have a small feature or refactor the code to easily switch at a high level.
If you are not able to do so easily, then yes, complex feature flags implementations might help you, to coordinate feature activation between micro services.
Or if you have many features then a dashboard might be useful.
But I would argue that both are serious indicators that you should avoid feature flags, they are better for local and temporary changes, otherwise the complexity compounds and it become hard to manage and maintain.
Ofcourse you don't want users to lose the feature once they exceeded your revenue threshold or cross the border so you'll need to implement some kind of tracking. Your analytics and error tracking also needs to communicate with the feature flag service.
Definitely not rocket science but more complex than a environment variable.
That is, features are contractual and when you've only got 50 customers but they're all paying high 6 figures does anyone really care about feature flag complexity?
"The customer would like the main page blue and another one the red". Would it be feature flag for you?
Not just an argument, it's the entire point of feature flags for ui experiments which is an essential practice. Dynamic adjustment of the cohorts (or even just an immediate kill switch if it's a disaster) is required.
Still using AWS for email sending so that will be great when it comes
> It is in the works. The billing team has been sprinting to fix a lot of debt in this area. I don’t have a date.
It took like 2 weeks to build a full custom backend. SDKs across languages worked flawlessly (okay, we did find one bug, reported it, and it was fixed within the day)
We used Statsig at Function. It started out as 2 of us using it on one product and within 12 months, large amounts of our product copy and rollouts were driven off of it.
Statsig has client side evals so you can write rules and rollouts based on internal concepts without Statsig’s servers processing a piece of user data. Hoping Cloudflare can build a sophisticated product here so I don’t have use another product in the future!
- anyone have comments/comparisons about launchdarkly vs posthog vs statsig (is it still alive after openai?) vs _____ vs cloudflare flagship?
like a "beginner/intermediate/advanced" progression of what to look out for/what you will want when it comes to feature flags would be highly helpful for me and many others here
I feel strong inclination too but its also way too early before any real users can prove PMF. I've been using Google stuff but wonder if Flagship and perhaps other Cloudflare offerings can help.
The other side is that again it feels too early for this stuff and I just want to ship something quickly.
The work ivnvolved
and im sure they can drive down the cost , compared to say launchdarkly
Can't even ship with app-scoped tokens...
Q.Data.variant()
And on the back end, you'd use it like this:
https://github.com/Qbix/Platform/blob/main/platform/classes/...
Essentially, this can support a huge number of "variants" and within each variant you can have N equal segments. That will help you do A/B testing and flipping features on or off.