Section: Research Program

Easily, safely and efficiently running large-scale distributed applications

Concerning runtime aspect, a first necessary step is to to provide a runtime that can run efficiently the application written using the programming model described in objective 1. The proposed runtime environment will rely on commodity hosting platforms such as testbeds or clouds for being able to deploy and control, on demand, the necessary software stacks that will host the different applications components. The ProActive platform will be used as a basis that we will extend. Apart from autonomic adaptation aspects and their proof of correctness, we do not think that any new major research challenges will be solved here. However it is crucial to perform the necessary developments in order to show the practical effectiveness of our approach, and to provide a convenient and adaptable runtime to run the applications developed in the third objective about application domains.

Mapping and deploying virtual machines

The design of a cloud native application must follow established conventions. Among other things, true elasticity requires stateless components, load balancers, and queuing systems. The developer must also establish, with the cloud provider, the Service Level Agreements (SLAs) that state the quality of services to offer. For example, the amount of resources to allocate, the availability rate or possible placement criteria. In a private cloud, when the SLA implementation is not available, the application developer might be interested in implementing its own. Each developer must then master cloud architecture patterns and design his/her code accordingly. For example, he must be sure there is no single point of failures, that every elastic components is stateless that the balancing algorithms do not loose requests upon slave arrival and departure or the messaging protocol inside the queuing system is compatible with his/her usage. To implement a SLA enforcement algorithm, the developer must also master several families of combinatorial problems such as assignment and task scheduling, and ensure that the code fits the many possible situations. For example, he must consider the implication of every possible VM state on the resource consumption. As a result, the development and the deployment of performant cloud application require excessive skills for the developers.

The first original aspect we will push in this domain is related to safety and verification. It is established that OS kernels are critical softwares and many works proposed design to make them trustable through kernels and driver verifications. The VM scheduler is the new OS kernel but despite the economical damages a bug can cause, no one currently proposes any solution other than unit testing to improve the situation. As a result, production clouds currently run defective implementations. To address this critical situation we propose to formalise the specifications of VM scheduling primitives. Any developer should be able to specify his/her primitives. To fit their limited expertise in existing formal language, we will investigate for a domain specific language. This language will be used to prove the specified primitives with respect to the scheduler invariants. Second, it will make possible to generate the code of critical scheduler components. Typically the SLA enforcement algorithms. Third, the language will be used to assist at debugging legacy code and exhibit implementation bugs. Fabien Hermenier is already developing a language for specifying constraints for our research prototype VM Scheduler BtrPlace. SafePlace will be the name of the verification platform, we started its design and development in 2014.

The second challenge in this domain is to investigate the relation between programming languages, VM placement algorithms, allocation of resources, elasticity and adaptation concerns. The goal here is to enable the programmer to easily write and deploy scalable cloud applications by hiding with our programming model, the mechanisms the developer currently has to deal with explicitly today. This includes among other things to make transparent the notion of elastic components, elasticity rules, load balancing, or message queuing.

Debugging and fault-tolerance

We also aim at contributing to aspects that usually belong to pure distributed systems, generally from an algorithmic perspective. Indeed, we think that the approach we advocate is particularly interesting to bring new ideas to these research domains because of the interconnection between language semantics, protocols, and middleware. Typically, the knowledge we have on the programming model and on the behaviour of programs should help us provide dedicated debuggers and fault-tolerance protocols.

In fact some research has already been conducted in those domains, especially on reversible debuggers that allow the navigation inside a concurrent execution, doing forward and backward steps (Causal-Consistent Reversible Debugging. Elena Giachino, Ivan Lanese, and Claudio Antares Mezzina. FASE 2014.). We think that those related works show that our approach is both relevant and timely. Moreover, little has been done for systems based on actors and active objects. The contribution we aim here is to provide debuggers able to better observe, introspect, and replay distributed executions. Such a tool will be of invaluable help to the programmer. Of course we will rely on existing tool for the local debugging and focus on the distributed aspects.