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title: Building a real-time PWA on Atlassian’s own stack
description: Atlassian built a React/TypeScript PWA for their Unleash 2026 tech summit that served 500+ concurrent users entirely on the Atlassian stack. Jira acted as the...
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og:description: Atlassian built a React/TypeScript PWA for their Unleash 2026 tech summit that served 500+ concurrent users entirely on the Atlassian stack. Jira acted as the...
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# Building a real-time PWA on Atlassian’s own stack

**[Atlassian](https://daily.dev/sources/atlassian)** · 13 min read · 1 upvotes · 0 comments

## Summary

Atlassian built a React/TypeScript PWA for their Unleash 2026 tech summit that served 500+ concurrent users entirely on the Atlassian stack. Jira acted as the system of record for sessions, leaderboards, and push notifications; Rovo powered an AI event guide; Loom served session recordings; and Bitbucket Pipelines let attendees ship real code to production live during the event. Key engineering challenges included modeling event data in Jira, handling eventual consistency with a durable local outbox and state machine, and aggressive performance optimization that cut initial load time from ~12 seconds to under 1 second by deduplicating API calls, fixing a missing minification build config (7.7 MB → 1.53 MB bundle), and breaking a sequential auth waterfall. The app achieved 80% attendee adoption with 8 features shipped live during the event.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.atlassian.com/blog/how-we-build/building-real-time-pwa-atlassians-own-stack>

## Questions this post answers

### How can I reduce duplicate API calls when multiple React components request the same data on mount?

Share the in-flight promise across components instead of caching completed responses, since a response cache does not help when the first request has not returned yet. When a second component requests the same endpoint while a request is already pending, it reuses that same promise so both callers receive the identical result once it resolves. Applying this to identity, project metadata, and leaderboard fetches cut page-load API calls from 24 to 16 and eliminated 8 duplicate calls entirely.

_daily.dev surfaces practical patterns like in-flight request deduplication for developers optimizing React data fetching._

### How do you handle eventual consistency in a frontend app right after a user logs in and permissions haven't propagated yet?

Model readiness as a state machine with a converging and a ready state rather than treating it as a boolean. In the converging state the app renders safe cached or bundled data, captures user intent in a durable local outbox before trusting the write path, and overlays that intent until a live read confirms it, avoiding empty screens or misleading errors during permission propagation delays.

_developers designing resilient post-login flows can find architecture patterns like this via daily.dev._

### What caused a JavaScript bundle to be 7.7MB unminified and how was it fixed?

A production build configuration bug caused the bundle to ship unminified and readable directly in DevTools, despite being a logic-free build issue. Fixing the build configuration reduced the bundle from roughly 7.7 MB to about 1.53 MB, an 80% reduction, and was one of several fixes that brought time to first useful content from about 12 seconds down to under 1 second.

_daily.dev helps engineers track down performance regressions like build misconfigurations before they ship._

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---

Tags: [#webdev](https://daily.dev/tags/webdev), [#react](https://daily.dev/tags/react), [#atlassian](https://daily.dev/tags/atlassian), [#jira](https://daily.dev/tags/jira)

[View this post on daily.dev](https://daily.dev/posts/building-a-real-time-pwa-on-atlassian-s-own-stack-8iip2lxb7)

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