Push vs. Pull Integration

Every integration between a knowledge system and a destination tool moves information in one of two directions: the knowledge system pushes updates to the destination, or the destination pulls from the knowledge system on demand. This is not a technical implementation detail — it is an architectural choice that determines the freshness characteristics, load distribution, and failure modes of the integration. Choosing the wrong model for the use case is the most common integration design error I see.

1. Push Integration The knowledge system sends updates to integrated tools as soon as the knowledge changes. Best for: tools that must reflect knowledge changes quickly (operational runbooks, compliance documentation, policy guides that change frequently). Trade-offs: the knowledge system bears the load of broadcasting to every integrated tool. Every new integration adds to the push burden. Tools that are offline at push time may miss updates. Requires webhook endpoints or event subscription on the destination side.
2. Pull Integration The destination tool requests knowledge from the knowledge system when it needs it. Best for: use cases where the tool queries for knowledge in the context of a specific workflow step (CRM looking up account-specific knowledge when a rep opens an opportunity, ticketing system retrieving relevant runbook at ticket creation). Trade-offs: latency at request time, load scales with usage patterns rather than change frequency, fresher data at query time because it is retrieved in the moment.
3. Hybrid: Event-Driven with Query Fallback Push critical updates proactively (policy changes, deprecated procedures) while allowing pull queries for on-demand knowledge retrieval. The push component ensures time-sensitive updates are distributed without depending on a tool making a query. The pull component serves the long-tail of knowledge requests that cannot be anticipated in push rules. This hybrid is the production pattern for most enterprise knowledge integrations.