LogLite: Lightweight Plug-and-Play Streaming Log Compression

TL;DR

LogLite is a new lightweight, plug-and-play streaming lossless log compression method that adapts to evolving log structures, significantly reducing storage costs with up to 67.8% better compression ratios.

Contribution

We introduce LogLite, a novel compression algorithm that requires no pre-training and adapts to both TEXT and JSON logs, outperforming existing methods.

Findings

Achieves up to 67.8% better compression ratio

Provides up to 2.7× faster compression speed

Demonstrates Pareto optimality compared to state-of-the-art baselines

Abstract

Log data is a vital resource for capturing system events and states. With the increasing complexity and widespread adoption ofmodern software systems and IoT devices, the daily volume of log generation has surged to tens of petabytes, leading to significant collection and storage costs. To address this challenge, lossless log compression has emerged as an effective solution, enabling substantial resource savings without compromising log information. In this paper, we first conduct a characterization study on extensive public log datasets and identify four key observations. Building on these insights, we propose LogLite, a lightweight, plug-and-play, streaming lossless compression algorithm designed to handle both TEXT and JSON logs throughout their life cycle. LogLite requires no predefined rules or pre-training and is inherently adaptable to evolving log structures. Our evaluation shows that, compared to state-of-the-art baselines, LogLite achieves Pareto optimality in most scenarios, delivering an average improvement of up to 67.8% in compression ratio and up to 2.7 $\times$ in compression speed.