# How WePay uses Harness

**800K+ users**: “800K+ users, seamless migration”

As published on [harness.io](https://www.harness.io/case-studies/wepay-ramped-up-release-cadence-and-migrated-to-microservices), August 2026. Captured by usedby on 2026-10-07.

- Company: [WePay](https://www.usedby.ai/companies/wepay.md)
- Tool: [Harness](https://www.usedby.ai/tools/harness.md)
- Teams: Engineering

## What the story says

WePay uses Harness feature flagging (Split) to decouple feature rollouts from code deployments, release features gradually to select customer segments, and run old and new systems side by side while migrating from a PHP monolith to microservices. Control groups are also used to isolate issues after a release.

Summary written by usedby from the source page, in English. The figures are those of Harness and WePay, not ours.

> WePay transitioned from bi-weekly releases to deploying new features as often as needed. This enhanced their ability to:

> Tying feature accessibility to releasing code makes a lot of bad things happen, like releasing code at midnight to match a press release. Split lets us decouple these processes and release features with the click of a button.
>
> Chris Conrad, VP of Engineering

## What usedby checked

We compared the story with its live page on 2026-10-07.

- Checked: the figure 800K+ users is printed word for word on the page, near the name of WePay.
- Checked: the passage quoted above is copied word for word from the page, near the name of WePay.
- Checked: the publication date is read from the page’s own metadata, never guessed.
- Checked: WePay uses Harness. Confirmed line. Latest check across sources: 2026-10-07.
- Not checked: the result itself. We quote it; we did not measure it.

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Source: https://www.usedby.ai/case-studies/wepay-harness · How we check: https://www.usedby.ai/methodology