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In the serverlessmodel, users upload application code to a cloud platform and the cloud provider undertakes the deployment, execution and scaling of the application, relieving users from all operational aspects. Although very popular, current serverless offerings offer poor support for the management of local application state, the main reason being that managing state and keeping it consistent at large scale is very challenging. As a result, the serverless model is inadequate for executing stateful, latency-sensitive applications. In this paper we present a high-level programming model for developing stateful functions and deploying them in the cloud. Our programming model allows functions to retain state as well as call other functions. In order to deploy stateful functions in a cloud infrastructure, we translate functions and their data exchanges into a stateful dataflow graph. With this paper we aim at demonstrating that using a modified version of an open-source dataflow engine as a runtime for stateful functions, we can deploy scalable and stateful services in the cloud with surprisingly low latency and high throughput.

Pico qlis an open source c/c++software whose scientific scope is real-time interactive analysis of in-memory data through sqlqueries. It exposes a relational view of a system’s or application’s data structures, which is queryable through sql. While the application or system is executing, users can input queries through a web-based interface or issue web service requests. Queries execute on the live data structures through the respective relational views. pico qlmakes a good candidate for ad-hoc data analysis in applications and for diagnostics in systems settings. Applications of pico qlinclude the Linux kernel, the Valgrind instrumentation framework, a gisapplication, a virtual real-time observatory of stellar objects, and a source code analyser.