Hey team, how have you been? I hope you're all doing well. I got involved in a project in which our client wants to run an experimentation program using GrowthBook. I have not much experience running the tool but I'm eager to learn more. After some back and forth, I have a few questions, that hopefully are not too dumb. 1. Write Permissions: GrowthBook doesn't write anything to the client's warehouse, right? I'm asking because it seems they created an empty table to be used as a "FACT TABLE" inside their Databricks environment. 2. Fact Table Definition: My understanding is that the Fact Table should actually be a SELECT query pointing to the client's existing raw events data (e.g., from Segment or Snowplow), not a new table created specifically for GrowthBook. Is that correct? 3. Databricks Permissions: Our current Access Token connection is "Connected," but the SQL Explorer shows "No tables found." Does this confirm that the token is missing

SHOW

and `USAGE`/`SELECT` permissions on the necessary Catalogs/Schemas, even if the basic connection works? Any guidance on these points would be hugely appreciated as we finalize the Databricks setup! Thanks a lot!

Hey all, just curious, but is there any way to remove or reduce the flickering when split testing a new page?

Hey everyone, I have two questions regarding the iOS SDK: 1. Does GrowthBook automatically cache feature payloads on disk? If yes, how long does the cache last by default, and is it possible to disable it or change the duration? 2. When using the SDK only for feature flags, does GrowthBook collect any user data (e.g., IP address or device identifiers) that I should declare in App Store Connect? Thanks!

Hi everyone 👋 I have a question regarding image uploads in experiment variations. We use a custom S3-compatible storage, which is causing upload failures on our instance. While investigating, I found a similar issue opened in GitHub about GrowthBook only supporting official AWS S3 endpoints. Just to confirm my understanding: • Does GrowthBook currently support only AWS S3, and not custom S3-compatible endpoints? • Are you still using AWS SDK v2, or has SDK v3 support already been introduced? • If SDK v3 has been added, does that enable specifying a custom S3 endpoint for uploads? • And finally, is support for custom S3 endpoints planned on the roadmap? Thanks in advance, just trying to understand whether this is currently supported natively or not.

Hi all 👋 I'm trying to host GrowthBook on Azure using Container Apps, but I keep getting the error: `Error connecting to the GrowthBook API at

http://{custom_domain}:3100

. Has anyone successfully hosted the project on Azure and has some pointers? 😅 I feel like Ingress might be the culprit, not allowing me to open up more than 1 http-port. (It only supports multiple TCP ports, afaik)

I'm trying to work out the best way of structuring my fact tables to work with the new product analytics dashboards. I generally tend to be interested in proportion metrics - e.g. conversion rates. Up until now I've had fact tables where one row represents each conversion event. When used in an experiment the metric value is then expressed as a % of the experiment audience, which is great. Is there a way I can reuse this metric to create a conversion rate in a product analytics dashboard? I can't work out how to do it as there doesn't seem to be a way to express what the total audience is. For example, I don't think I can specify the metric to show as a proportion of all site visitors - or other fact table values. So is there a way I can monitor an overall site conversion, without changing my existing fact table?

Background: I'm experiencing an issue with the Flags Explorer setup in Next.js where the

getProviderData()

function from

@flags-sdk/growthbook

doesn't seem to be mapping flag options from experiment variations tied to that flag in growthbook. There's a discrepancy between two different documentation approaches for next.js + vercel flags explorer: 1. Next.js and Vercel Feature Flags Tutorial - manual implementation of

getFlagApiData()

that explicitly loops through the GrowthBook payload to extract options from rules, variations, and force values. (older) 2. Next.js SDK (Vercel Flags) Documentation - Uses the built-in

getProviderData()

function from

@flags-sdk/growthbook

package, which should handle this automatically. (new) Issue: When using the SDK's

getProviderData()

function as shown in the newer docs, the flags appear in the toolbar with the default as their only option. Question: Is this a known limitation of

getProviderData()

, or did I miss something in the docs?

Hello growthbook👋 we want to start testing a new feature. We want to proceed very cautiously and initially only include 10% of the user base (with a 50:50 split). If we see after 1-2 days that there are no problems, we want to roll it out to 30% of the user base, and so on. What is the best approach here? For example, can we use a namespace and adjust it during the experiment? Looking forward to your feedback. Thank you in advance 🙏

Quick question; Is the Growthbook Proxy a requirement for streaming to work? Without a proxy, I can't seem to get it working. (I've not tested with a proxy)

Hey Growthbook Team, We were getting a lot of initialization failure for our growthbook setup in flutter, with the error

failed to lookup host

, and wanted to implement a retry mechanism when initialization fails. GBSDKBuilder provides a failure callback but seems like there is no init retry mechanism build around failure handling, our init logic is written in a singleton pattern so creation new object if init fails doesn't seem viable either, so wanted to understand how can we tackle this problem are there any helpful inbuild methods whcih gb provides for init retry?

We’ve been using growthbook for a few minutes with the client side SDK, but we’re looking to swap over to lambda edge. I’ve been trying to get it working but not having much luck. I’ve confirmed a basic lambda function is configured w/ our cloudfront, but once I add the growthbook specific handler, I run into errors. When I deploy the lambda version that uses growthbook, I’m seeing logs with this error:

2025-11-18T15:22:00.113Z	a762f8a1-1df6-4c0b-98aa-686ec37e6ff8	ERROR	Unhandled Promise Rejection 	
{
    "errorType": "Runtime.UnhandledPromiseRejection",
    "errorMessage": "TypeError: Invalid URL",
    "reason": {
        "errorType": "TypeError",
        "errorMessage": "Invalid URL",
        "code": "ERR_INVALID_URL",
        "input": "undefined",
        "stack": [
            "TypeError: Invalid URL",
            "    at new URL (node:internal/url:825:25)",
            "    at Ms (/var/task/index.js:31:69858)",
            "    at Object.w3 [as proxyRequest] (/var/task/index.js:31:75389)",
            "    at /var/task/index.js:31:65455",
            "    at Generator.next (<anonymous>)",
            "    at s (/var/task/index.js:31:64093)"
        ]
    },
    "promise": {},
    "stack": [
        "Runtime.UnhandledPromiseRejection: TypeError: Invalid URL",
        "    at process.<anonymous> (file:///var/runtime/index.mjs:1448:17)",
        "    at process.emit (node:events:519:28)",
        "    at emitUnhandledRejection (node:internal/process/promises:252:13)",
        "    at throwUnhandledRejectionsMode (node:internal/process/promises:388:19)",
        "    at processPromiseRejections (node:internal/process/promises:475:17)",
        "    at process.processTicksAndRejections (node:internal/process/task_queues:106:32)"
    ]
}

Nothing is growthbook specific in those logs, but I’m guessing it’s coming from something growthbook is doing. A couple of questions: 1. PROXY_TARGET — I’m pointing this to our S3 bucket that serves the website, which is

http

, not

https

— is that okay? If I use https, that’d point back to a cloudfront distro URL and I think it’d go into some kind of infinite redirect loop 2. Is there a way to test this w/o having to redeploy my cloudfront distro and wait for the website to break

I'm thinking about query cost/performance optimization with the pre-compute dimensions setting. What are the tradeoffs I'm making by selecting pre-compute??

Hi, I’m wondering why I’m getting this “Invalid experiment” error? I’ve set up a 50/50 experiment and am trying to associate it

Hey there, I am looking to implement a user retention metric after viewing an experiment. I'm using:

Metric: Retention

Fact table: Events, Row filter: event_name = 'page_view'

However the lowest time I am able to set is: Event must be at least

1 Minutes

after experiment exposure Which effectively is

timestamp >= (exposure_timestamp + '1 minutes')

However, I wish I could use:

timestamp > (exposure_timestamp)

Note: not equal Is this possible with a fact metric?

I have a question regarding the growthbook setup in nuxt 2. To make it work, I had to fetch features through url, as the setup in documentation did not work. Is it expected for nuxt2? Do I still get the cashing features of growthbook even if I dont follow the documentation for vue?

Hi. How fact table optimization feature works? I want to know details, and impact on user side.

----------------- Hi, I'm using the GrowthBook experiment platform with a fact table–based data source (BigQuery). When I define N metrics on top of the fact table, GrowthBook is able to compute all metrics with a single underlying query, which is very efficient. However, when I view Experiment → Results and apply a segment, GrowthBook stops using the single fact-table query and instead executes *N separate queries*—one for each metric. This makes the query execution significantly less efficient and increases BigQuery cost. Is this expected behavior? And is there any way to preserve the single-query optimization when segmentation is applied?

Hi all! We have a mobile app (Android and iOS). Share your experience running an A/B test on subscription pricing. What challenges did you encounter?

Hello, we are currently running on version 3.3.0 and would like to upgrade to the newest 4.2.0, is there any issues with doing that or is there any special considerations we should be aware of?

Hi, What is the difference between these two metric definitions? 1. Ratio metric with

Numerator = SUM(profit per order)

,

Denominator = Unique Users

2. Mean metric with

per user aggregation = SUM(profit per order)

. When defining the Mean metric (2), the Growthbook interface says:

The final metric value will be the average per-user value for all users in the experiment. Any user without a matching row will have a value of 0 and will still contribute to this average.

So I don't understand the difference between a denominator of "Unique Users" in 1 and "average per-user value" in 2. I would expect these two metrics to be identical. However, on the experiment overview page I can see they have the same numerator value (1.7m), but the Ratio (1) has 5k Unique Users for the Denominator, while Mean (2) has a denominator of 83k. We're doing an A/A test (no difference between the two treatments) and are seeing Growthbook report a statistically significant Relative uplift for the Ratio Metric, but not for the Mean metric. I would like to understand the details of what is happening behind the scenes a bit better.

Hi all, very simple question but haven't managed to get an answers from the docs. Is it possible to set up the end date / time of an experiment in advance?

Hello everyone. We're trying to connect our self hosted growthbook to AWS Athena, and it creates the data source, but gives an error of: "No Database Provided". Has anyone encountered this before?

Hello everyone, we’ve recently had to deal with an issue regarding Force rules that apparently cannot be edited on our self host version running v4.1.0. So, the case is we have a feature with a JSON value, it has different values depending on the environment, normally what we would do is edit the value that the rules returns for each environment, but since the last couple of weeks, on this particular feature, the edit option simply does not appear. Has anyone faced a similar issue or could maybe guide me through it? Thanks

Hi Team, We're debugging an issue at the moment where we've seen unbalanced assignments across multiple experiments (e.g. all users assigned to control in Experiment 1 are also assigned to control in Experiment 2). We've narrowed this down to an issue with the experiment seed used by the SDK in the following function:

val hash = GBUtils.hash(
            stringValue = hashValue,
            hashVersion = experiment.hashVersion ?: 1,
            seed = experiment.seed ?: experiment.key
        )

The experiment seeds provided by the Growthbook server to the SDK are not unique per experiment key, which is leading to a non-random allocation of users in an experiment. Is this a known bug / is there a fix for this?

Is the dashboard down? I can't seem to load the dashboard right now

Hi team! We're testing out Bandits, and noticed that the only decision options for Exploration and Updates are time-based (days/hours) as opposed to data-based. It doesn't look like there's currently a way to have anything else inform this, but is it in the roadmap to add a more data-based approach to this? (ie. Sample size for primary metric?)

Hello guys. I am Sinan. I need some help with using the Visual Editor in GrowthBook. I integrated GrowthBook through Google Tag Manager (GTM), but I’m getting a warning message and I’m unable to use the Visual Editor. The documentation says that I should verify the “Tracking via DataLayer and GTM” step in order for the Visual Editor to work, but even after checking that, the issue still persists. Has anyone experienced this before or knows how to fix it? Any guidance would be greatly appreciated. Thanks in advance!

Hi team. We are currently looking into implementing a feature request in the GrowthBook C# SDK related to Custom Fields. The request is to add Custom Fields as a property to the

Experiment

object within the SDK so that they can be retrieved in application code. Since Custom Fields is an Enterprise-level feature, we need to confirm the expected API behavior. When fetching the feature/experiment configuration (the main JSON payload), does the GrowthBook API include the customFields object directly within the experiment definitions?

Hi team, I'm trying to enable Metric Slices for one of the metric that our team created per guidance here. but I'm not able to find this surface from the metric's info page. May I know how should I find it? Thanks

👋 I recently upgraded to 4.2 and am now seeing this error on percentile capped metrics:

within group ORDER BY clauses for aggregate functions must be the same

. • DB: redshift • failing query section:

__capValue AS (
    SELECT
      PERCENTILE_CONT(0.999) WITHIN GROUP (
        ORDER BY
          m0_value
      ) AS m0_value_cap,
      PERCENTILE_CONT(0.999) WITHIN GROUP (
        ORDER BY
          m0_denominator
      ) AS m0_denominator_cap
    FROM
      __userMetricAgg
  )

The error arises from the capValue CTE calculating 2 percentiles with different order bys. If the pattern leveraged separate CTEs for each percentile, it would run Is this a known issues that is being worked on?