Building a real-time chat application sounds pretty straightforward at first.
You create a login system, add a message input, connect a database, and display messages on the screen. That's basically it, right?
Well, that's what I thought when I started working on ChatLoop, my real-time messaging application built with React, Firebase, and WebRTC.
I wanted to create something more than a basic messaging demo. My goal was to build an application where users could connect with friends, exchange messages instantly, share files, make voice and video calls, and enjoy features you normally find in modern messaging platforms.
As development progressed, I added message reactions, typing indicators, read receipts, online status, voice messages, disappearing messages, and even an AI-powered chat assistant.
But behind those features were problems I hadn't fully anticipated.
Some bugs appeared only when two users were online simultaneously. Others involved network timing, browser restrictions, database synchronization, or React's component lifecycle.
Here are seven real challenges I faced while developing ChatLoop, how I approached them, and what they taught me about building real-world applications.
1. Managing Real-Time Messages Without Duplicates or Unexpected Updates
The first challenge was making real-time messaging reliable.
I used Firebase Firestore because its real-time listeners allow an application to receive database updates without constantly requesting new data.
At first, it seemed simple. Whenever someone sent a message, Firestore would update, and the conversation would immediately display the new message.
However, problems started appearing as the application became more complex.
Sometimes, changing between conversations created unexpected updates. I also had to deal with listener cleanup and situations where asynchronous updates could arrive after a component had changed.
The problem wasn't Firestore itself. It was how I managed real-time subscriptions inside React.
How I approached the problem
I focused on managing the lifecycle of every Firestore listener.
When a user opened a conversation, the application subscribed to the relevant messages. When they switched conversations or left the page, the previous subscription needed to be removed.
React's useEffect cleanup mechanism became particularly important.
I also had to think carefully about how messages were ordered and how incoming data updated the interface.
A real-time listener shouldn't automatically mean adding every received message to an existing array. Firestore snapshots need to be handled according to whether they represent the current dataset or individual changes.
What I learned: Real-time applications require more than fast database updates. They need proper subscription management, predictable state updates, and careful handling of asynchronous events.
2. Preventing Duplicate Conversations Between Two Users
Another interesting challenge involved managing private conversations.
ChatLoop includes a friend-request system where users can send, accept, reject, or cancel friend requests. Once two users become friends, they can start a private conversation.
But that introduces a question:
What happens if both users try to start the same conversation?
Imagine User A opens a chat with User B. Meanwhile, User B opens a chat with User A.
Without a consistent conversation identifier, the application could accidentally create two different chat threads for the same pair of users.
That would make message history, unread counts, and conversation management unnecessarily complicated.
How I solved it
I used a deterministic conversation ID based on the two users' identifiers.
Instead of generating a random ID every time someone opened a conversation, the application created a consistent ID from the same pair of users.
For example, the identifiers could be sorted before being combined:
- User A + User B → Same conversation ID
- User B + User A → Same conversation ID
The order of the users no longer mattered.
This made it easier to locate an existing conversation and associate its messages with the correct chat.
Of course, a predictable ID alone doesn't replace proper database access rules. Users should still only be able to access conversations they're authorized to view.
What I learned: Good data modeling can prevent entire categories of bugs before they happen.
Sometimes, solving a complicated UI problem starts with designing a better database structure.
3. Making Unread Messages and Read Receipts Work Correctly
Unread message counts seem like a tiny feature.
You receive a message, the unread counter increases, and when you open the conversation, the counter disappears.
Simple.
But implementing this correctly in a real-time environment turned out to be more challenging than I expected.
Consider these situations:
- A user receives multiple messages while viewing another conversation.
- The user opens a conversation while new messages are still arriving.
- Two browser sessions are active for the same account.
- A sender expects to see whether the recipient has read a message.
Suddenly, the application needs to keep track of more than just message content.
It needs to understand the relationship between messages, recipients, active conversations, and read status.
How I approached the problem
I worked with conversation-level unread information and message status updates.
When a message arrived, ChatLoop needed to determine whether it should count as unread for the recipient.
Opening a conversation also needed to update the relevant read state without incorrectly changing the sender's information.
I implemented visual indicators for message status, including read indicators, so users could better understand what was happening.
One important lesson was that delivering a message and reading a message are two different events.
A message existing in Firestore doesn't necessarily mean the recipient has seen it.
What I learned: Small features can require surprisingly careful state management, especially when multiple users interact with the same data.
4. Building Accurate Online Status and Typing Indicators
I wanted ChatLoop to feel like a real messaging platform rather than a static web application.
That meant showing when someone was online, when they were last active, and when they were typing.
These features make conversations feel more natural, but they also introduce a different kind of real-time problem.
For example, when should the application show someone as offline?
What happens if they close their browser without logging out?
What happens if their internet connection suddenly disappears?
A basic online/offline boolean cannot reliably answer all these questions.
How I approached the problem
For online presence, I worked with user activity and last-seen timestamps, using Firebase server timestamps where appropriate.
I also implemented typing information that could be displayed to the other participant.
Typing indicators need to be temporary. Otherwise, someone could stop typing, leave the conversation, and still appear to be typing indefinitely.
This required thinking about when typing state should begin, when it should stop, and how the interface should respond to changes.
Presence tracking has its own limitations, too. A last-seen timestamp is useful, but truly reliable online presence requires accounting for disconnects and inactive sessions.
What I learned: Real-time user experience isn't just about displaying fresh information. It's also about knowing when information is no longer valid.
5. Getting WebRTC Voice and Video Calls to Connect
This was one of the most challenging parts of building ChatLoop.
Text messaging was one thing. Real-time audio and video communication introduced an entirely different set of problems.
I used WebRTC for peer-to-peer media communication and Firebase Firestore for signaling.
WebRTC allows browsers to establish connections for real-time audio and video, but creating that connection involves several steps.
The calling user generates an offer, the receiving user responds with an answer, and both sides exchange ICE candidates to discover a working network connection.
It sounds manageable when explained in a few sentences.
In practice, timing matters enormously.
The ICE candidate problem
One issue I encountered involved ICE candidates arriving before the receiving peer connection was ready to process them.
This created connection failures that were difficult to reproduce consistently.
Sometimes a call would connect successfully. Other times, the connection would fail even though the same general process had worked before.
After investigating the signaling flow, I realized I needed to manage the order in which candidates were handled.
How I solved it
I introduced an ICE candidate queue.
Instead of trying to process every candidate immediately, the application could temporarily store candidates that arrived too early.
Once the remote session description was ready, the queued candidates could be processed.
I also worked with STUN and TURN server configuration to help establish connections across different network conditions.
TURN support is especially important because direct peer-to-peer connectivity isn't always possible.
What I learned: In asynchronous systems, having the correct data isn't enough. The data also needs to arrive—or be processed—at the correct stage.
WebRTC taught me a lot about signaling, network communication, race conditions, and error handling.
6. Fixing Audio Playback and Handling Browser Restrictions
After working through WebRTC connection problems, I discovered another issue.
A call could appear connected, but the remote audio wouldn't always play as expected.
From a user's perspective, that feels like a broken call.
From a developer's perspective, the connection itself might actually be working.
This was particularly confusing because I had to distinguish between a networking problem, a media-stream problem, and a browser playback problem.
Modern browsers place restrictions on automatic media playback, especially when audio is involved.
That means receiving a remote stream doesn't guarantee that the browser will immediately play it.
How I approached the problem
I reviewed how remote media streams were attached to media elements and how playback was initiated.
I also handled audio and video call states more carefully, including what should happen when a user accepts, minimizes, or ends a call.
The goal was to make the interface accurately reflect the actual call state.
A call shouldn't appear fully functional if the application hasn't properly initialized its media handling.
I also learned that media elements need careful lifecycle management. Streams and tracks should be cleaned up when a call ends so that resources aren't left running unnecessarily.
What I learned: A successful network connection doesn't automatically mean a successful user experience.
You have to consider how browsers handle permissions, playback, device access, and media cleanup.
7. Handling File Uploads and Firebase Storage CORS Errors
ChatLoop supports more than text messages.
I wanted users to exchange attachments and voice messages as part of normal conversations.
For file handling, I used Firebase Storage.
However, while developing the attachment features, I encountered CORS-related problems.
CORS, or Cross-Origin Resource Sharing, is a browser security mechanism that controls whether web applications can access resources from different origins.
An upload or resource request can fail when the required cross-origin permissions aren't configured correctly.
At first, these errors can be frustrating because the application code might look perfectly reasonable.
The problem may actually involve the interaction between the browser, storage service, and hosting configuration.
How I approached the problem
I investigated the storage requests and reviewed the configuration needed for the application's origin.
After addressing the relevant configuration issues, I continued working on the attachment experience.
But the experience also taught me that successful uploads are only part of the problem.
A production-ready file-sharing system needs to consider:
- File size and type validation
- Upload progress and error messages
- Storage access permissions
- Secure file retrieval
- Failed or interrupted uploads
Uploading a file is easy to demonstrate in a tutorial. Building an experience that users can depend on requires more planning.
What I learned: Frontend development doesn't stop at writing React components. Understanding browser security, cloud configuration, and access control is equally important.
What Building ChatLoop Taught Me About Real-World Development
Before building ChatLoop, I already had experience working with React, JavaScript, and modern frontend tools.
But this project pushed me to think differently.
I wasn't simply developing individual features anymore. I was connecting several systems that needed to work together.
React managed the user interface. Firebase handled authentication, data, and storage. WebRTC enabled real-time calls. And the application needed to keep all those pieces synchronized.
Every time I added a feature, I had to consider how it would affect the existing application.
Adding message reactions affected message rendering.
Adding voice messages introduced media permissions and file handling.
Adding calling features introduced connection states, signaling, and cleanup.
Even a simple feature like showing whether a friend was online raised questions about connection reliability.
I also integrated an AI chat feature using Google's Gemini API, which introduced another area to think about: connecting AI services to an existing application safely and predictably.
One of the biggest lessons was that building software isn't just about making features work once. It's about making them work consistently under different conditions.
Tutorials are useful for learning technologies, but real projects force you to understand how those technologies behave together.
My Advice to Developers Building Their First Real-Time Application
If you're planning to build a real-time chat application using React, Firebase, or WebRTC, here's what I'd recommend based on my experience.
Start with the data model. Think about users, friendships, conversations, messages, and permissions before creating a complicated interface.
Keep real-time listeners under control. Make sure subscriptions are cleaned up when they're no longer needed.
Test with multiple accounts. A chat application might work perfectly when you're testing alone, but behave differently when two users are sending messages at the same time.
Expect asynchronous problems. Database updates, network responses, and WebRTC signaling don't always happen in the order you expect.
Treat loading and error states as real features. Users should understand what's happening when something is connecting, uploading, or failing.
Don't ignore security. Authentication alone isn't enough. Database rules, storage permissions, and server-side API handling deserve attention.
Focus on reliability before adding more features. A basic messaging application that works consistently is more valuable than a feature-rich application with unpredictable behavior.
Final Thoughts
Building ChatLoop has been one of my most valuable learning experiences as a developer.
It gave me the opportunity to work with real-time databases, authentication, media communication, cloud storage, application state, and AI integration in a single project.
Some problems took longer to understand than I expected. Others taught me concepts that I probably wouldn't have explored through tutorials alone.
And that's what I enjoy most about building projects.
Every challenging bug is an opportunity to understand something more deeply.
If you're working on your own real-time application, don't be discouraged when features become more complicated than they initially seemed. Those difficult parts are often where the most useful learning happens.
Want to explore ChatLoop?
Live Application: https://chatloop-mu.vercel.app/
I'm Ehan Siddique, a full-stack web developer working with React, Next.js, Node.js, Firebase, and modern web technologies.
I share development experiences, technical lessons, and projects on my website:
Thanks for reading!
Top comments (2)
두 사용자가 동시에 대화를 열 때 ID를 정렬해 하나로 만들고, 대화 전환 때 Firestore 리스너를 정리한 부분이 실전적이네요. 특히 두 브라우저 세션이 동시에 열려 있을 때 읽음 수가 어긋나는 사례는 사용자별 마지막 읽은 메시지 ID를 기준으로 두고, 한 세션에서 읽은 직후 다른 세션에 새 메시지가 도착하는 순서를 자동 테스트로 고정해보면 재발을 잡는 데 도움이 될 것 같습니다.
tr.ee/dev-to