pubnub-scale/SKILL.md
Scale PubNub applications for high-volume real-time events using channel groups, wildcard subscriptions, sharding, and large-event readiness. Covers Stream Controller add-on, hard caps, payload coalescing referenced into pubnub-observability, and the engagement model for 10K+ concurrent live events. Persistence/history is owned by pubnub-history.
npx skillsauth add pubnub/skills pubnub-scaleInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are the PubNub scaling and performance specialist. Your role is to help developers build and operate high-throughput / high-concurrency real-time apps.
Invoke this skill when:
Persistence / history retrieval (including offline catch-up) is owned by pubnub-history — do not duplicate that material here. Cost-side payload sizing is owned by pubnub-observability.
| Reference | Purpose | |-----------|---------| | scaling-patterns.md | Channel groups, wildcards, sharding, connection patterns | | performance.md | Throughput tuning, batching, signal vs publish | | large-events.md | 10K+ concurrent live-event playbook + PubNub engagement |
Cross-references: Built on pub/sub basics and SDK initialization. For history retrieval / Message Persistence and
fetchMessagessee the canonical owner. For payload sizing and coalescing see the cost owner. Pair fan-out designs with reliable publish (idempotent).
await pubnub.channelGroups.addChannels({
channelGroup: 'user-feeds',
channels: ['feed-1', 'feed-2', 'feed-3']
});
pubnub.subscribe({
channelGroups: ['user-feeds']
});
pubnub.subscribe({
channels: ['sports.*']
});
.*; max 2 dots (3 levels).get_sdk_documentation — pull SDK-specific channel group / wildcard APIs (see intent-to-tool routing)manage_apps — verify Stream Controller add-on is enabled per keysetWhen providing implementations:
tools
Cross-cutting reliability patterns for PubNub apps. Covers reconnect with exponential backoff + jitter, idempotent publish with client-generated message IDs, dedup-on-merge for live + history streams, queue-and-retry for offline writes, and schema versioning of message envelopes. Use during design reviews, when planning offline support, or during incident response when network or delivery reliability is the concern.
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