Section: New Results

Resource management in system software

Participants : Jonathan Lejeune, Marc Shapiro, Julien Sopena, Francis Laniel.

MemOpLight: Leveraging applicative feedback to improve container memory consolidation

The container mechanism supports consolidating several servers on the same machine, thus amortizing cost. To ensure performance isolation between containers, Linux relies on memory limits. However these limits are static, but application needs are dynamic; this results in poor performance. To solve this issue, MemOpLight reallocates memory to containers based on dynamic applicative feedback. MemOpLight rebalances physical memory allocation, in favor of under-performing ones, with the aim of improving overall performance. Our research explores the issues, addresses the design of MemOpLight, and validates it experimentally. Our approach increases total satisfaction by 13% compared to the default.

It is standard practice in Infrastructure as a Service to consolidate several logical servers on the same physical machine, thus amortizing cost. However, the execution of one logical server should not disturb the others: the logical servers should remain isolated from one another.

To ensure both consolidation and isolation, a recent approach is “containers,” a group of processes with sharing and isolation properties. To ensure memory performance isolation, i.e., guaranteeing to each container enough memory for it to perform well, the administrator limits the total amount of physical memory that a container may use at the expense of others. In previous work, we showed that these limits impede memory consolidation [26]. Furthermore, the metrics available to the kernel to evaluate its policies (e.g., frequency of page faults, I/O requests, use of CPU cycles, etc.), are not directly relevant to performance as experienced from the application perspective, which is better characterized by, for instance, response time or throughput measured at application level.

To solve these problems, we propose a new approach, called the Memory Optimization Light (MemOpLight). It is based on application-level feedback from containers. Our mechanism aims to rebalance memory allocation in favor of unsatisfied containers, while not penalizing the satisfied ones. By doing so, we guarantee application satisfaction, while consolidating memory; this also improves overall resource consumption.

Our main contributions are the following:

• An experimental demonstration of the limitations of the existing Linux mechanisms.

• The design of a simple feedback mechanism from application to the kernel.

• An algorithm for adapting container memory allocation.

• And implementation in Linux and experimental confirmation.

This work is currently under submission at a major conference. Some preliminary results are published at NCA 2019 [26].