How We Implemented Groups for the Hoomanely Community

As the Hoomanely community grew, we ran into a familiar problem.

Our global feed initially worked well. It helped users discover content, ask questions, and engage with pet parents across the platform. But as activity increased, conversations started overlapping, important posts got buried, and engagement slowly shifted from participation to passive scrolling.

Users weren't disengaged—they were overwhelmed.

This is where Groups came in. But adding groups wasn't just a UI decision. It required us to rethink data models, permissions, feeds, notifications, and scalability across the system.

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1. Why We Needed Groups

The Problem With a Single Global Feed

A global feed optimizes for visibility, not relevance. As the number of users and posts grew, we noticed:

• Important discussions are disappearing quickly
• New users are hesitating to post
• Repeated questions with no continuity
• Engagement becoming shallow

People cared deeply about specific topics—breed-specific advice, nutrition discussions, first-time pet parenting—but had no dedicated space for them.

What Users Actually Wanted

From user behavior and feedback, a clear pattern emerged:

• Smaller, focused conversations
• Familiar names in discussions
• Context that persisted over time

Groups gave us a way to intentionally narrow context and create meaningful micro-communities inside the larger platform.

Internally, we framed it simply: Groups should turn users from consumers into contributors.

2. Defining the Scope (Before Writing Code)

We deliberately kept the first version of Groups minimal.

Our initial requirements were:

• Public and private groups
• Group membership with roles
• Posts scoped to a group
• Join/leave flows
• Basic moderation
• Group-specific notifications

We avoided advanced features like sub-groups, monetization, or analytics until the core behavior was stable.

This helped us keep the architecture simple and flexible.

3. Data Modeling Decisions

One of the earliest decisions was how to model groups without coupling them tightly to existing systems.

Core Entities We Introduced

Group

• group_id
• name
• visibility (public/private)
• created_by
• created_at

GroupMember

• group_id
• user_id
• role (owner/admin/member)
• status (active/pending/banned)
• joined_at

GroupPost

• post_id
• group_id
• author_id
• content
• created_at

Why Membership Is a Separate Model

We intentionally avoided embedding group IDs inside the user object.

A separate GroupMember model allowed us to:

• Query all groups for a user efficiently
• Enforce permissions cleanly
• Handle join requests and bans explicitly
• Evolve roles without migrations

This separation turned out to be one of the best early decisions we made.

4. Permissions: Enforced on the Backend, Always

Permissions were the trickiest part of the system.

At Hoomanely, we defined roles clearly:

• Owner: full control, including deletion
• Admin: moderation and member management
• Member: read and post access

All permission checks happen server-side, not in the UI.

Every sensitive API validates:

• Group membership
• Membership status
• Role permissions

We learned quickly that relying on frontend gating leads to subtle security bugs, especially when APIs start getting reused.

5. Feed Architecture: Reusing What Worked

We already had a post system powering the global feed. Rather than building a completely separate pipeline, we extended it.

This let us:

• Reuse existing post infrastructure
• Share pagination and indexing logic
• Keep analytics consistent

Group feeds are simply filtered queries with strict permission checks.

The tradeoff is stricter backend validation—but the simplicity was worth it at our stage.

6. Joining, Leaving, and Moderation Flows

Joining Groups

• Public groups → instant join
• Private groups → request + admin approval

We model join requests explicitly instead of inferring them, which simplifies moderation and auditing.

Leaving and Removal

We never hard-delete memberships immediately.

• Membership history is preserved
• Bans are explicit
• Re-join abuse is prevented

Moderation Tools

Admins can:

• Remove members
• Ban users
• Delete posts

All moderation actions are logged. This protects both users and moderators when disputes arise.

7. Notifications Without Overwhelming Users

Groups can easily become notification spam machines.

We were careful to limit notifications to:

• New posts (with batching)
• Mentions
• Admin announcements

Our guiding principle was simple: Notifications should pull users back—not push them away.

8. Scaling Challenges We Encountered

Groups introduced scaling problems that didn't exist before.

Large Groups

Some groups grew much faster than others, leading to:

• Hot partitions
• High read volume
• Pagination performance issues

We addressed this with:

• Cursor-based pagination
• Caching group metadata
• Read-optimized indexes
• Limits on fan-out behavior

Read vs Write Reality

Groups turned out to be:

• Write-light
• Extremely read-heavy

Optimizing for reads early saved us from painful refactors later.

9. Privacy and Security Lessons

Private groups raised the bar for access control.

Rules we enforced strictly:

• Membership validated on every read
• No group metadata leaked in global search
• No reliance on cached permissions alone
• Authorization handled at query level

A single privacy leak in a group feature can permanently damage trust. We treated this as a first-class concern.

10. Observability: Debugging Groups in Production

Groups added complexity to debugging.

We made sure to include:

• group_id in logs
• Per-group activity metrics
• Admin action audit trails
• Alerts for abnormal activity spikes

Observability wasn't an afterthought—it was essential for safe iteration.

11. What This Architecture Unlocks Next

Because we kept the core clean, Groups now give us room to evolve:

• Sub-groups and channels
• Group-level analytics
• Premium or expert-led groups
• Personalized group recommendations
• Deeper moderation tools

The system can grow without rewrites—and that was the goal.

Final Thoughts

At Hoomanely, Groups were not just a feature—they were a structural shift.

They changed:

• How users interact
• How content is scoped
• How permissions are enforced
• How the system scales

The key lesson we learned is this: Good community architecture is about constraints, not features.

By designing clear boundaries, simple models, and strong backend enforcement, we built a Groups system that supports meaningful conversations today—and growth tomorrow.