Microsoft Technology Licensing, LLC

Daniel Veiga Kling

Russell Lee Simpson, Jr

Sridhar Raman

Giselli Panontini De Souza Sana

Jim R Van Eaton

Jason Lawrence Muramoto

Yuemei Zhang

Vidhyashankar Balasubramaniyan

Sana Rajeev Nagar

Stalinbabu Chennupati

A system and method for automatically scaling consumer servers in a data processing system. To build an automatic scaling system, the present disclosure allows consumers to obtain additional information, e.g., the number of events that await to be read from an aggregator when receiving an event from the aggregator. This additionally obtained number provides a direct gauge for the data processing system to determine when the consumers are over-provisioned, i.e., when the number of events left to be read is close to zero, as well as when the consumers are under-provisioned, e.g., when the number of events left to be read continues to increase. As a result, the consumers can be automatically scaled to handle the dynamic data processing demand while providing optimal resource allocation.

Automatic scaling for consumer servers in a data processing system

A server push model for client/server communications. The push architecture operates on top of a non-push (e.g., request/response) protocol (e.g., HTTP) to combine notifications from multiple data sources (e.g., email, text messaging, etc.). The server can be a middle-tier server (or proxy) to which a single web client registers interest in one or more notification types from one or more data sources. The mid-tier server aggregates the notifications from the various data sources and delivers the notifications to the requesting client via a single 'push' pipe. The web client then distributes each notification to the appropriate parts of the client user interface. A producer/consumer locking mechanism eliminates blocking threads waiting on a mutual exclusion lock. A notification throttling mechanism distinguishes different types of notifications in order to guarantee that the client is not overloaded with too much information.

Push mechanism for efficiently sending aggregated data items to client

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Redmond, WA, United States of America

Daniel Veiga Kling