English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Changes in operating environment may result in the performance degradation to a SaaS software. Analyzing running log is an efficient method to locate this problem. However, as a long-running software, SaaS may generate huge log data which is difficult to analyze, and it lacks a systematic approach to implement management of the running log. These all threaten the timeliness of SaaS performance analysis. In this paper, we define a log format to standardize multi-source heterogeneous log data and construct a log model to support SaaS software performance analysis, where the two performance metrics of average response time and request timeout rate in the model are calculated by statistical measurement. Furthermore, a log management framework is given to support real-time big log data collection, access, calculation, storage and service, and the technology implementation of the framework is also given. Finally, a case study is given to illustrate and validate the effectiveness of the approach. Keywords-big data; running log; log model; SaaS software performance

Model Construction and Data Management of Running Log in Supporting SaaS Software Performance Analysis