Facebook engineers query multiple databases to monitor and analyze Facebook products and services. The fastest of these databases is Scuba, which achieves subsecond query response time by storing all of its data in memory across hundreds of servers. We are continually improving the code for Scuba and would like to push new software releases at least once a week. However, restarting a Scuba machine clears its memory. Recovering all of its data from disk --- about 120 GB per machine --- takes 2.5-3 hours to read and format the data per machine. Even 10 minutes is a long downtime for the critical applications that rely on Scuba, such as detecting user-facing errors. Restarting only 2% of the servers at a time mitigates the amount of unavailable data, but prolongs the restart duration to about 12 hours, during which users see only partial query results and one engineer needs to monitor the servers carefully. We need a faster, less engineer intensive, solution to enable frequent software upgrades.

Facebook takes performance monitoring seriously. Performance issues can impact over one billion users so we track thousands of servers, hundreds of PB of daily network traffic, hundreds of daily code changes, and many other metrics. We require latencies of under a minute from events occuring (a client request on a phone, a bug report filed, a code change checked in) to graphs showing those events on developers' monitors. Scuba is the data management system Facebook uses for most real-time analysis. Scuba is a fast, scalable, distributed, in-memory database built at Facebook. It currently ingests millions of rows (events) per second and expires data at the same rate. Scuba stores data completely in memory on hundreds of servers each with 144 GB RAM. To process each query, Scuba aggregates data from all servers. Scuba processes almost a million queries per day. Scuba is used extensively for interactive, ad hoc, analysis queries that run in under a second over live data. In addition, Scuba is the workhorse behind Facebook's code regression analysis, bug report monitoring, ads revenue monitoring, and performance debugging.

In this demo, we present the Microsoft Complex Event Processing (CEP) Server, Microsoft CEP for short. Microsoft CEP is an event stream processing system featured by its declarative query language and its multiple consistency levels of stream query processing. Query composability, query fusing, and operator sharing are key features in the Microsoft CEP query processor. Moreover, the debugging and supportability tools of Microsoft CEP provide visibility of system internals to users. Web click analysis has been crucial to behavior-based online marketing. Streams of web click events provide a typical workload for a CEP server. Meanwhile, a CEP server with its processing capabilities plays a key role in web click analysis. This demo highlights the features of Microsoft CEP under a workload of web click events.