We've built an open-source feature flag server for 11 years | Hacker News Reader

We've built an open-source feature flag server for 11 years

github.com

163 pointsivarconr111 comments

Had a look at their website [1]. Initial thoughts: this is a bit ridiculous, I can just build that myself. And in fact, I have done already.

Thoughts after about 3 minutes of browsing: OK, this actually makes sense and I see why people would pay for this. The value proposition is definitely there

[1] https://www.getunleash.io/

Hmm, after 5 minutes of browsing I still don't get it.

Thanks, "I could build that" → "oh, that's what the other 90% is" is pretty much how Unleash started for us too. What does your homegrown version do? Always interested in where people draw the line between building and adopting.

Great comeback!

Just basically various means of turning features on/off based on static rules. Settings mostly but occasionally user based or URL params.

Your platform has that and a ton of other things that would be useful for larger platforms, but it would be a pain to develop when you're already building a complicated roadmap.

If it's settings, its better off being in your apps settings rather than implemented as a long running feature flag.

Feature flags are meant to be temporary.

Well, I mean.. settings can also be temporary. Could be constants or from the DB, etc.

I pay for it for my team... it's expensive to be honest, but worth it IMHO. Building it would be a ok, supporting it a pain.

If you work on a small startup, not worth it... on a Big corp with a lot of bureaucracy? It's worth it I think.

We have tried self-hosting it, but it's always a pain to allocate people on infra to do it, so I gave up and started paying for it for my teams, and they love it.

From the infra side, it’s something I don’t think makes a lot of sense to self-host. Metrics are the other notable one here.

They have non-linear scaling complexity, so they work fine with bumping up resources until they don’t and now you’re looking at queueing metrics on Kafka or something equally complicated. They’re horrible to change out because a lot of the APIs aren’t compatible and literally everything uses them.

They’re also awful to maintain. Everything uses them so there’s never a window when it’s convenient to shut down the feature flag system for upgrades or to test backup restores. People are much more accepting of “the vendor will be down for 2 hours on Saturday” than “I’m taking the system down for 2 hours on Saturday”.

I'm not sure which provider you are paying for metrics, that you think has acceptable pricing.

We are on ~400k series, and switching to any hosted provider would instantly make that our single biggest infrastructure expense.

Instead we're self-hosting with less than $100/month for hosting and ~less than a hour per month of maintenance with Victoriametrics (have also switched fron singe-node to cluster over time), and it's a breeze.

The things I most disliked about our in house feature toggle system were:

1) the line between toggle and reloadable config is always fuzzy, in part because you don’t know for sure if it’s a toggle until users give their feedback. About half a percent of toggles stick around in perpetuity as either preferences or emergency relief valves for the operations team. That seems small but when you are doing CD aggressively that’s happening to you once a month or every few weeks which makes it a constant companion.

2) you need a system to track and complain about old toggles. If they survive the end of the Epic that birthed them, they become immortal. And you can see variations on Knight Capital play out when they get toggled years after they were supposed to be static.

Regarding number two, that's what I designed featureflip to handle. It tracks dead flags and will submit a pull request to your repository to remove it for you. That's always been a big pain point of mine with launch darkly.

Feels like something that should be a solved problem though.

Part of my last job was winnowing down a convoluted feature toggle system, rebuilding parts of it on top of a FOSS library that did a fraction of the same work. It had become convoluted enough though that it was materially affecting both our deployment time and our cluster density.

To be a little fair to the original author, despite not really respecting him, I had to file a couple serious PRs upstream to simplify the most tortured parts. He worked around a couple of bug/misfeatures but took the scenic route to do it. Guy “never met an abstraction he didn’t like” is not true because his favorite thing was replacing one abstraction with three. And he was one of those guys who learned big words all from books and so he used definitions nobody under 65 has ever used in conversation.

I thought LLMs were supposed to be the death knell for services like this, since you could replicate them and maintain your own code-base with little effort?

At least that's what the AI boosters keep saying.

Lots of tools work like that: You can get to 80% of the value with 20% of the work. I kid, it's even better than that! Sometimes, 80% of the value comes from 2% of the effort to build what they built.

But over time, you realize that half of the remaining 20% matters to you, and it turns out that the remaining 10% you care about is harder than it seems, and until you have it doing everything you need, you're stuck with an ad hoc, informally-specified, bug-ridden, slow implementation of half of LaunchDarkly.

————

Personally, I have worked on an in-house feature flag system, and I told everyone who would listen that its purpose was needs validation, and that as soon ass we were 100% sure we knew EXACTLY what we needed, we could go shopping. And that was in the hand-written code era. Today, you could vibe an 80% solution and do your needs assessment from there.

Yesterday I saw that LaunchDarkly is a $3B company. How crazy is that?!

A million monthly active users, even free ones, would cost you ~$10K/month on LaunchDarkly. A million sounds like a lot, but "active" can mean one visit, even anonymous users. ~$120K/year for feature flags is a ridiculous line item.

These SaaS companies are only valued this much because they charge based on MAUs, not request-based. I prefer PostHog's model. 100M requests/month is ~$2K [*].

[*] I'm not affiliated with PostHog.

Launch Darkly charges on volume across multiple dimensions, including MAU and server-side connections, plus log, trace and error counts. It's bonkers and anyone who can actually predict what it will cost (good luck) will run away as fast as they can.

There is no way a Feature Flag system is a multi Billion dollar company based on the tech, and if there IS a Saas-pocalypse it's coming for players like LD first.

What would you recommend as an alternative?

Biased answer since I work on Unleash, but the pricing point is something we thought about deliberately:

- Self-hosted open source is free, with no usage limits. Run it on your own Postgres and you pay for a small VM.

- Paid plans are priced per seat (people using the admin UI), not per end user or per request. One million MAUs or a hundred million costs the same (we have some protection for high traffic volumes)

- Server-side SDKs evaluate locally, so a flag check never hits our servers and there's nothing to meter. Frontend traffic goes through Edge, which you can also self-host.

If you'd rather not lock into any vendor, put flags behind OpenFeature. Unleash, Flagsmith, GrowthBook and others all have providers, so switching later is a config change, not a rewrite.

Unleash Cloud ?

Put flags in your own DB(s)?

What if your DB is down?

Have a safe default fallback.

Wouldn't you be having bigger problems if the DB is down (especially if you have good defaults for the flags)?

My website company 20 years ago was running Memcached keys for each of the feature flags so they only had to be loaded about once per session from the DB most of the time.

Scaling things like this is a mostly solved problem. Having your website load when the DB is down is not.

Ex-LD engineer here. This was a classic mistake we saw most of our customers make, before they had to switch to LD or its competitors when they scaled a little bit more. Using a db is fine but can put heavy load on the server depending on the number of flags. In addition, it doesn't give you various features such as tagetting by users, segments, etc. Nor does it give you things like progressive rollout or automated rollback (yes we were using that in house and had saved us at least a few times).

I'm not advocating for LD, I'm advocating for any feature management system.

I've designed such a "classic mistake".

> In addition, it doesn't give you various features such as tagetting by users, segments, etc. Nor does it give you things like progressive rollout or automated rollback (yes we were using that in house and had saved us at least a few times).

These are things you can think of quite easily, or you just survey the landscape of what challenges other implementations run into and they inform you of this. The first iteration of our design had all of those; we could target users, always-subscribe internal users, we could have two features have the same segment/ordering of rollout, etc.

Database load wasn't ever a problem, because you're talking about quite literally a single SELECT on an already established & otherwise in use DB connection. But caching is not that much to bolt on afterwards should it become an issue.

It's never been clear to me that the simplicity of understanding that a single query has, even if it might be short a few features, is outweighed by the complexity of a full dependency to an external service.

As it was, our FF system outlived the company, and was sunset when the company ended.

Eh, I built a feature flagging system for service with millions of daily active users and it: wasn't hard to do, was easy to extend to support targeting, segments, and progressive rollout, and on top of it flags are easy to cache, so the database pressure was not that big. We did this long before LLMs, and it occupied maybe a month of engineering time for me, here and there as we needed new features, while I was doing other things. We did choose the wrong hash for bucketing in the beginning, but we noticed the stairstep patterns in our buckets quickly (an advantage of having millions of requests per day to measure) and picked a better one. It was much better this way since it meant backend flags without a roundtrip to a 3rd party service (that was the main motivation, we wanted this kind of control without adding latency to our requests). I remain baffled by launch darkly or other such services. And today, with LLMs, just build it yourself is hard to argue against.

As I mentioned, I'm not advocating for LD. I'm advocating for feature management systems (over env vars/db values and other similar naive implementations). The build vs buy is a separate argument.

> that was the main motivation, we wanted this kind of control without adding latency to our requests

Right, and most, if not all, off the shelf feature management systems have this problem solved already. For example LD uses a streaming architecture by default to push out flags to your application within 200ms, for client facing applications (android/ios/web), flags were retrieved once on load from a CDN, keeping the rest of your application snappy. I believe Unleash also has some sort of streaming architecture.

this was almost a decade ago, the options were imo pretty bad

Posthog is absolutely awesome. Its free tier is insanely generous - 91% of its users don't pay anything or something.

We use it at a startup I'm involved in (~5k MAU) and we have never paid a penny which I am constantly surprised by since it's such a backbone for us.

There are a number of providers that provide flat-rate or near flat-rate pricing in this space. I'll go ahead and recommend featureflip.io as one such example. ConfigCat is another common one.

I am affiliated with featureflip but it does a ton of the same things for a sane price.

This seems entirely too dismissive of what LaunchDarkly's service does.

I don't know about first. Feature flags is somewhere down the list, behind email and comms and scheduling and todo's. AI can vibe code the shit out of a Todo app. Google Workspace wants $7/$14/or $22 per user per month. Times 50 or 100 people, that's not insignificant. Closely behind that there's the (financial) books. QuickBooks is the 800 lb gorilla of that industry and everyone just goes with them because book keepers know how to use them. There's no shortage of competition, especially AI competition to replace the human bookkeeper with an LLM. We'll just have to see where things go though.

On Unleash Cloud: 100M request per month on Unleash cloud would be $235 + 75$ per seat ($53 Million requests included).

Shoutout to ConfigCat, https://configcat.com/

Same features as all these big guys, EU hosted, and down-to-earth pricing. Even the free tier got me quite far.

I'm unaffiliated btw.

The ConfigCat team is great!

Unleash also originates from Europe.

A file syncing app "that could be an FTP server or USB stick" is over double that ;)

Are most feature flag systems really just simple Boolean checks like this with no feedback loop? In 2009 Amazon’s equivalent supported multi-variate flags (run test with more than 2 options), a feedback loop for performance/attribution, and weighting. I don’t see any of that on the unleash home page, but also haven’t seen it in other feature config systems either.

usually some “data science” team takes the results and decides what to do. really heavy process for something that is usually quite simple.

We have automatically generated readouts that run hourly and daily, show metrics between control and variant across a ton of core business metrics, and we can even opt into measurement of some super esoteric stuff.

Granted we have a whole team supporting just that experimentation platform, but it's pretty cool. They even expose an MCP server for us to have agents do experiment analysis for us using.

Attributing an event to a flag is a heavy process? Oof.

What you are describing is usually part of analytics platforms (Mixpanel, etc.). A feature flag toggle only plays a small part in this (but it may also be used for a lot of other scenarios of how you may want to control feature flags).

Audience is decided by analytics tool -> Feature flag server maps audience to feature flag value -> Analytics tool tracks its events and includes feature flag value as attribute

So if you want to slowly roll out a feature flag, you need to get a different app involved that can do everything the feature flag tool can do and a whole lot more? What’s the point of the feature flag tool?

Analytics is a much broader set of tooling. It can (and should) report similar things.

The point of the feature flag tool is to control feature flags. They are not just for A/B testing and slow rollouts, and most products are not on the scale of Amazon, where you need to have a feedback loop for the rollout. Of course there is always going to be some overlap between tools, where many analytics platform allow you to do the rudimentary version of this.

The main point of a FF system is that you have a runtime-controllable mapping from user attributes to feature flags, where a set of logic rules can dictate who is exposed to what feature. With most analytics-tool based rollouts, you would be able to only directly set an attribute and you then hard-wire that attribute to the feature toggle in app code, which gives you a lot less flexibility and always requires a engineer in the hot path when it comes to doing rollouts.

Feature flag is a fancy name for a boolean value.

Besides checking if something is true or false what else is there to do ?

What else can it do aka "feedback loop" ?

I was just having the build vs buy conversation with my team this week. AI does make building much easier - which changes the argument some. But it doesn't eliminate the maintenance and all the other overhead that goes with infrastructure like this. Let someone else, like unleash, deal with all that and focus on what makes your product unique.

OpenFeature (https://openfeature.dev/) is very similar and backed by CNCF.

You can hardly compare an API specification with an implementing product. So, no, even if Unleash does implement OpenFeature.

Guess there is a reference being made to flagd:https://flagd.dev

This domain needs some better ontology and taxonomy, there's so many overlapping and conflated terms whenever I hear about it. To name a few:

- Feature Flags used as Configs;

- Configs used as Feature Flags;

- Live Ops, Control Groups, Experiments, Analytics, and more bundled as "extras" to Feature Flags as if they were the right parent term;

I think classical systems/engineering see feature flags as boolean state in some data store, but these PaaS are pushing it as a new thing and struggling with marketing.

I wish they took the gaming companies lesson and started using the term "Live Ops"

To me there two type of feature flag. For tech and not for tech.

If you have good CI/CD practices, an ENV for the environment has what feature is simplest. No new dependencies, change code commit deploy.

Non-tech folks need something else that allows them to switch it on and then off. For a variety of reasons.

We had a weird constellation of these things at a previous job of mine. In addition to our env variables, we had a config table for more business-side stuff (ie percent of margin to include in bids and quotes for work on the platform) that our business team would upload new values to on our admin GUI with a CSV file, and eventually we jammed into that same table a config check that would enable features just for certain users by email. I was very happy when we eventually moved to Launchdarkly and tossed out the hacky stuff.

This seems a bit reductive. What if you want to do a progressive rollout of the feature? What if it has a problem, and you want to disable it without needing to redeploy across multiple regions? What if you want to A/B test it?

Ex-LaunchDarkly engineer here.

Feature management goes well beyond an env var. Sure an env var change is fine on it's own, but a change of the feature flag (essentially a release) requires a deployment.

Feature management separates these two. You can deploy without releasing. Because the code is there, but dormant behind an if that can change at runtime, you can actually target users, segments, or even do progressive rollout, and so much more. What this also means is you can test your changes in production without causing prod to go down. Best of all, a release doesn't mean a bad deployment.

It's not just about non-tech folks. It separates deploy and release in the SDLC, and that opens up a whole new world.

I used LaunchDarkly I agree but it depends on your practices.

Proper CI/CD means potentials hundreds of deployments a week. A deployment is nothing in some environments. And the change gets tracked into the environment that has it switched, into our logs and other observaility platforms.

So we get the same info. LaunchDarkly was amazing when coordinating with stakeholders and product owners. Especially for testing features, A/B, etc.

I'm definitely not trying to downplay it, but starting with just ENVs for each place is simplest and then they can expand into tools they need like LaunchDarkly or PostHog.

But starting there for small engi teams isn't as valuable. That's all, not against it for a product that builds to it, but just too much churn for smaller teams to use. I still advise ENV first.

And yah the realtime flags of LaunchDarkly were amazing , I needed that a few times.

This article does exactly that, you might find it an interesting read: https://martinfowler.com/articles/feature-toggles.html

Oh wow I didn't know about this one, thanks for sharing! Great read

Cool! Feature flags are great when you need them. I’ve seen so many different implementations of flags over the years. Even made one myself couple years ago which uses a GitHub issue (and a list of checkboxes) as a persistent store for maintaining and toggling with flags. https://github.com/TimMikeladze/next-flag

Being able to do this from GitHub suddenly kind of makes sense that you would rewrite git if the main consumers of everything in the codebase will only be the LLMs and giving them a toggle it in a vcs system starts to cutout.

Does your vcs become a living and evolving organism eventually self updating via recursive feedback loops. At what point do they ever stop trying to improve?

I love this as an interface of where humans and LLMs meet. Thanks for sharing. Really set me down a fun pondering hole

I use Unleash at my job, can vouvh for it. It's one of those software that does its job how you expect it and it's not annoying to work with.

What's a feature flag?

Cool product!

This seem to be open source and self hostable (is it AGPL licensed?).

Can I, for personal use, fully self host every component? Or is it open core and e.g. multi tenancy isn't there etc.

Yes, AGPL. And yes, it’s open core. For personal use you can self-host the server and SDKs with no usage limits, and that covers flags, targeting, gradual rollouts and variants. The paid tiers add things that mostly matter to larger teams: SSO, RBAC, change requests, and Edge for high-volume frontend traffic. For a personal setup, the open source version should be all you need.

From the website. ``` Yes. Unleash Open Source is free, self-hosted, and has no limit on seats. It covers the core feature set, with a limit of 1 project, 2 environments, and 5,000 feature flags per instance. Thousands of teams run it in production.

It does not include single sign-on, SCIM provisioning, granular role-based access control, change request approvals... ```

1 project, 2 environments. Laughable.

Thanks for clarifying and good luck with this endeavour!

Some of your recent comments have been killed by our software because they've been classified as genai text, which is not allowed on HN itself (see https://news.ycombinator.com/newsguidelines.html#generated and https://news.ycombinator.com/item?id=47340079).

(Of course it's fine to use AI tools! We use them heavily ourselves. Just please don't use them to generate or edit text to be read by fellow humans on Hacker News.)

It's impossible to know for sure what was LLM generated or edited, but we have to rely on imperfect classifiers or else the site would be completely flooded by genai text, which is not what the community here wants to read, nor in the intended spirit of HN.

Got it, thanks. AI was used to clean up the language, not to generate content.

Yup, that's a case we hear a lot these days. Unfortunately the tools leave almost as many imprints on the text when used this way.

Past explanations, in case they're helpful: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

open core. Almost useless in the free license

Literally all their examples can be replaced by some sort of:

    if redis_client.get("staging.feature-flag"):
        ...

For frontend you add an endpoint that exposes this value.

I guess their frontend for managing these is 'nice', but at the end of the day it's a static page that sets flags on redis.

What else do you need for feature flags?

For one app and one team, honestly not much. It starts to matter when you want gradual rollouts where the same user stays in or out across services, different rules per environment or customer, an audit log of who flipped what when something breaks, and a way to find dead flags. And then the boring parts: not doing a network call on every check, and what happens when the store is down.

The flags are often not static, though. Varies between environments, markets, user cohorts and whatever rules you can come up with.

So plenty of parameters that could be exposed in Redis as well. No?

How do you edit them once it becomes complicated? Should everyone have access to everything, or do different teams own different toggles? How do you know they're unused and can be cleaned up? How do you roll out to 1 % but keep it persistent so that the same user has the feature on throughout?

All of these are of course possible to solve. But at some point just use something battle tested..

Configuration as a Service companies must be a having a tough time these days...

I couldnt imagine a lot of teams are debating anymore whether to build their own or use an off the shelf product like this. The former being a straight forward task for an LLM. And the latter being a point of failure/attack for any one want to mess with the core foundations of a product.

At a certain scale (probably bimodal distribution) it makes sense to have a provider you can shrug it off to and point the finger to when things are missing features or the system goes down, etc etc. On the big-co end of that spectrum I think you are right and AI makes this stuff easy to launch internally.

The owner at my current gig has multiple times said "software is over" as it being a sort of gravy train of rent seeking. Products are gonna have to offer real / significant value to attract new customers. Maybe even to keep them, too...

>> and point the finger to when things are missing features or the system goes down

This sounds good in theory but - and I speak from experience with a FF system causing a system-wide outage - clients don't care why YOU had an outage, or that it's not immediately your fault, and they really shouldn't have to. The reality is more like you're paying for a dependecy that you can't mitigate.

Being able to point fingers is also a moot point from a theoretical perspective.

Given that every FF system comes with a bunch of different mechanisms that prevent your system from being catastrophically impacted in case the provider goes down, its still the fault of the integrating party if you experience an outage due to a FF provider.

You miss where the value of software is nowadays. Just the hosting of this thing is worse to pay for.

Companies as well as people are still happy to pay for the second S in SaaS.

Building something, updating it, running it, testing etc. still requires resources and attention. One example for this would be taxis. You pay for the comfort of not having to drive the car, do maintenance, take into account road works, cleaning, etc. and not because you couldn't drive a car yourself. That time you can use instead to focus on your actual business.

Analytics, documentation, configuration, etc saas companies must be having the same hard time.

I build a B2B SaaS. I ran the same PDF through my product and a general-purpose AI. Both had zero number errors, and the AI's design was good enough. So I don't expect people to pay for the output. I think what's left is what happens after: who opened it, inquiries, spec changes, and team collaboration.

> Release, experiment, and kill anything AI ships

The only appealing marketing I've seen in the past three years

Wow a server that can help you manage your booleans. That's so useful. Let me just add one more thing to my infrastructure so my list of booleans can be managed.

managed in the sense that values keep getting thrown onto the pile and then people somehow manage to never think about or touch them ever again regardless of their temporary nature

This is the real problem in my experience. Creating flags is easy, removing them isn’t. We ended up building lifecycle tracking for it: each flag type has an expected lifetime, flags get marked potentially stale when they pass it, and you can see when a flag was last evaluated in each environment so you know it’s safe to delete. Someone still has to remove the code though :)

No, it gives you one pretty heavy way to not throw things into a pile. It doesn't keep people from making a mess anyway.

If you have the discipline to use this thing, you have the discipline to manage things yourself without this thing.

We are an unserious industry run by idiots and grifters. We deserve to be replaced by AI. AI isn't going to purchase a SaaS to store a fucking boolean.

My company has used 3 different feature flag services in 5 years, spent thousands of dollars, with multiple migrations and teams of engineers involved. All to basically implement `SELECT 1 FROM feature_flags WHERE team_id = ?`. Makes me want to blow my brains out.

I mean, well done. It's impressive work to provide such a service, that a surprising number of mid-to-large organisations _will_ seek out _and_ leverage. Quite a throwback this really, like the heyday of the SaaS hype; almost quaint. Thank you for an enjoyable read

I will take quaint. We started it as a sideproject in 2014, so the throwback argument is fair. What i find fascinating is the ability to runtime control featurs in production, particularly the ability to kill it, seems more important than ever these days, where AI has made it pretty cheap to produce software.

open-source = FIRE

“open source” but it’s the nonfree AGPL, and naturally RBAC and SSO are behind a paywall. I’m tired of fake open source projects that just want the street cred and free marketing.

AGPL is as free as it gets. Perhaps the word you're looking for is non-permissive?

Don’t believe the hype. AGPL violates free software freedoms 0 and 1. It was designed by people who think that receiving a free gift confers obligation to reciprocate.

https://en.wikipedia.org/wiki/The_Free_Software_Definition

https://sneak.berlin/20250720/the-agpl-is-nonfree/

Huh? FSF wrote AGPL and the 4 freedoms.

AGPL does not require you to share your changes if you use it (like most people) internally. It does if you host it for others as a service. Pretty fair trade.

Freedom to use, modify and distribute, clearly enforced for the Internet age.

> AGPL does not require you to share your changes if you use it (like most people) internally.

The text of the AGP License does not support this claim.

A lot of the arguments in this second link fall flat (e.g. "ohh you're violating the license if you npm run on your dev machine!") and it'd be more convincing if it spent less time trying to nitpick nonsense like that and just stuck to the moral argument it's trying to make

Hi HN, I'm Ivar, creator of Unleash.

Unleash started in 2014 as an internal tool at my company at the time, because we wanted to ship to production continuously without big-bang releases. It's an Open-Source feature flag platform with SDKs for >25 languages.

A few design choices that might be interesting:

- Local evaluation: server-side SDKs fetch the flag config and evaluate in-process, so user data never leaves your app and a flag check is a memory lookup, not a network call.

- Shared Rust engine (Yggdrasil): the evaluation logic is written once in Rust and embedded in the SDKs, so behaviour is the same across languages.

- Unleash Edge: a Rust proxy/cache for frontend and edge clients at scale. (Commercial)

- OpenFeature: supported if you don't want to lock into our SDKs.

I can see using something mature if you are starting from scratch.

if you already are in a platform capture situation, eg. Azure App Configuration or AWS AppConfig where you already integrate with platform tools using the native auth primitives, what is the benefit one can expect from switching to unleash?

If your current platform support (AppConfig etc) is sufficient, you should probably keep using it.

We see teams move when they have more complicated needs, either in terms of compliance, 4-eyes approvals, scalability and lifecycle tracking.

Anything you’re missing today, or is it working fine?

We were happy customers with my startup (before we died).

Unleash does a lot more than it seems on first look. It helped us a ton as we were shooting in all directions searching for pmf.

The local evaluation part is interesting. How do you keep the client’s evaluation engine up to date with the product features?

That's a great question, and the honest answer is that it is hard. We can easily add new capabilities in the UI, but for the Unleash protocol itself we need to make sure all changes are backward compatible, because we do not control the SDK version.

We have a few tricks we apply:

- Yggdrasil is the "Unleash SDK Engine". Written in rust and cross-compiled to multiple languages. This makes it easier to add features, and ensures all SDKs implements the protocol the same way. https://github.com/Unleash/yggdrasil

- Try to have a simple and generic protocol - This allows us to add new targeting capabilities later, without having to change the SDKs. In practice I must admit this is not easy and have only been possible in a few scenarios

- Make sure the SDK report their protocol version. This allows you do adapt the product to tell the user to upgrade to get new features. We also leveraged the SDK version when we introduced segments, as we could rewrite those to a less performant format in the API, to simplify the rollout.

Reply on news.ycombinator.com