HyScale: Hybrid and Network Scaling of Dockerized Microservices in Cloud Data Centres

Jonathon Wong , Anthony Kwan, Hans-Arno Jacobsen, and Vinod Muthusamy.

In IEEE 39th International Conference on Distributed Computing Systems (ICDCS), June 2019.

Abstract

When designing modern software, care must be taken to allow for applications to scale based on the demands of its users while still accommodating flexibility in development. Recently, microservices architectures have garnered the attention of many organizations—providing higher levels of scalability, availability, and fault isolation. Many organizations choose to host their microservices architectures in cloud data centres to offset costs. Incidentally, data centres become over-encumbered during peak usage hours and underutilized during off-peak hours. Traditional microservice scaling methods perform either horizontal or vertical scaling exclusively. When used in combination, however, these methods offer complementary benefits and compensate for each other’s deficiencies. To leverage the high availability of horizontal scaling and the fine-grained resource control of vertical scaling, we developed two novel hybrid autoscaling algorithms and a dedicated network scaling algorithm and benchmarked them against Google’s popular Kubernetes horizontal autoscaling algorithm. Results indicated up to 1.49x speedups in response times for our hybrid algorithms, and 1.69x speedups for our network algorithm under high-burst network loads. Index Terms—Docker, microservices, autoscaling, cloud.

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Tags: auto-scaling, microservices, clouds, containers


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