Gear: Enable Efficient Container Storage and Deployment with a New Image Format
Hao Fan, Shengwei Bian, Song Wu, Song Jiang, Shadi Ibrahim, Hai Jin
Abstract
Containers have been widely used in various cloud platforms as they enable agile and elastic application deployment through their process-based virtualization and layered image system. However, different layers of a container image may contain substantial duplicate and unnecessary data, which slows down its deployment due to long image downloading time and increased burden on the image registry. To accelerate the deployment and reduce the size of the registry, we propose a new image format, named Gear image, that consists of two parts: a Gear index describing the structure of the image's file system and a set of files that are required when running an application. The Gear index is represented as a single-layer image compatible with the existing deployment framework. Containers can be launched by pulling a Gear index and on demand retrieving files pointed to by the index. Furthermore, the Gear image enables a file-level sharing mechanism, which helps remove duplicate data in the registry and avoid repeated downloading of identical files by a client. We implement a prototype of the container framework, named Gear, supporting the new image format. Evaluation shows that Gear saves 54 % storage capacity in the registry, speeds up container startup by up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${5\times}$</tex> , and reduces 84 % bandwidth demands.