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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The existing resource allocation policy for application instances inKubernetes cannot dynamically adjust according to the requirement of business,which would cause an enormous waste of resources during fluctuations. Moreover,the emergence of new cloud services puts higher resource managementrequirements. This paper discusses horizontal POD resources management inAlibaba Cloud Container Services with a newly deployed AI algorithm frameworknamed AHPA -- the adaptive horizontal pod auto-scaling system. Based on arobust decomposition forecasting algorithm and performance training model, AHPAoffers an optimal pod number adjustment plan that could reduce POD resourcesand maintain business stability. Since being deployed in April 2021, thissystem has expanded to multiple customer scenarios, including logistics, socialnetworks, AI audio and video, e-commerce, etc. Compared with the previousalgorithms, AHPA solves the elastic lag problem, increasing CPU usage by 10%and reducing resource cost by more than 20%. In addition, AHPA canautomatically perform flexible planning according to the predicted businessvolume without manual intervention, significantly saving operation andmaintenance costs.

AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes