The architectural style of microservices has been gaining popularity in recent years. In this architectural style, small and loosely coupled modules are deployed and scaled independently to compose cloud-native applications. Carrier-grade service providers are migrating their legacy applications to a microservice based architecture running on Kubernetes which is an open source platform for orchestrating containerized microservice based applications. However, in this migration, service availability remains a concern. Service availability is measured as the percentage of time the service is provisioned. High Availability (HA) is achieved when the service is available at least 99.999% of the time. In this paper, we identify possible architectures for deploying stateful microservice based applications with Kubernetes and evaluate Kubernetes from the perspective of availability it provides for its managed applications. The results of our experiments show that the repair actions of Kubernetes cannot satisfy HA requirements, and in some cases cannot guarantee service recovery. Therefore, we propose an HA State Controller which integrates with Kubernetes and allows for application state replication and automatic service redirection to the healthy microservice instances by enabling service recovery in addition to the repair actions of Kubernetes. Based on experiments we evaluate our solution and compare the different architectures from the perspective of availability and scaling overhead. The results of our investigations show that our solution can improve the recovery time of stateful microservice based applications by 50%.
Microservice architecture is the common choice for cloud applications these days since each individual microservice can be independently modified, replaced, and scaled. However, the complexity of microservice applications requires automated testing with a focus on the interactions between the services. While this is achievable with end-to-end tests, they are error-prone, brittle, expensive to write, time-consuming to run, and require the entire application to be deployed. Integration tests are an alternative to end-to-end tests since they have a smaller test scope and require the deployment of…
As an application usage grows, its owner scales up vertically by replacing old machines with more powerful ones. This methodology is expensive and leads to resource waste. In response to the business needs, internet giants have developed the microservice architecture, which lets developers divide up their application into smaller units that can be hosted on multiple machines, thus enabling horizontal scale up. We propose a triphasic incremental process to transform a traditional application into a microservice application that guarantees stability during the operation. Then we demonstrated suc…
We present the architecture of a cloud native version of IBM Streams, with Kubernetes as our target platform. Streams is a general purpose streaming system with its own platform for managing applications and the compute clusters that execute those applications. Cloud native Streams replaces that platform with Kubernetes. By using Kubernetes as its platform, Streams is able to offload job management, life cycle tracking, address translation, fault tolerance and scheduling. This offloading is possible because we define custom resources that natively integrate into Kubernetes, allowing Streams to…
Cloud computing is steadily growing and, as IaaS vendors have started to offer pay-as-you-go billing policies, it is fundamental to achieve as much elasticity as possible, avoiding over-provisioning that would imply higher costs. In this paper, we briefly analyse the orchestration characteristics of PaaSSOA, a proposed architecture already implemented for Jolie microservices, and Kubernetes, one of the various orchestration plugins for Docker; then, we outline similarities and differences of the two approaches, with respect to their own domain of application. Furthermore, we investigate some i…
Microservices have become the de-facto software architecture for cloud-native applications. A contentious architectural decision in microservices is to compose them using choreography or orchestration. In choreography, every service works independently, whereas, in orchestration, there is a controller that coordinates service interactions. This paper makes a case for orchestration. The promise of microservices is that each microservice can be independently developed, deployed, tested, upgraded, and scaled. This makes them suitable for systems running on cloud infrastructures. However, microser…
Multi-access Edge Computing (MEC) is booming as a promising paradigm to push the computation and communication resources from cloud to the network edge to provide services and to perform computations. With container technologies, mobile devices with small memory footprint can run composite microservice-based applications without time-consuming backbone. Service placement at the edge is of importance to put MEC from theory into practice. However, current state-of-the-art research does not sufficiently take the composite property of services into consideration. Besides, although Kubernetes has c…
SLO-Scaler: Uncertainty-Aware SLO-Driven Autoscaling for Microservices
Carnegie Mellon University（卡内基梅隆大学）；Duke University（杜克大学）；University of Cincinnati（辛辛那提大学）；University of Southern California（南加州大学）；Northeastern University（东北大学）
Auto-scaling Approaches for Microservice Applications: A Survey and Taxonomy
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院）；University of Chinese Academy of Sciences（中国科学院大学）；Tianjin University（天津大学）；Quantum Cloud Computing and Distributed Systems (qCLOUDS) Laboratory, School of Computing and Information Systems, the University of Melbourne（墨尔本大学计算与信息系量子云计算与分布式系统（qCLOUDS）实验室）；State Key Lab of IOTSC, University of Macau（澳门大学物联网智慧应用国家重点实验室）
Microservice-based architecture has become prevalent for cloud-native applications. With an increasing number of applications being deployed on cloud platforms every day leveraging this architecture, more research efforts are required to understand how different strategies can be applied to effectively manage various cloud resources at scale. A large body of research has deployed automatic resource allocation algorithms using reactive and proactive autoscaling policies. However, there is still a gap in the efficiency of current algorithms in capturing the important features of microservices fr…
Nowadays IoT applications consist of a collection of loosely coupled modules, namely microservices, that can be managed and placed in a heterogeneous environment consisting of private and public resources. It follows that distributing the application logic introduces new challenges in guaranteeing performance and reducing costs. However, most existing solutions are focused on reducing pay-per-use costs without considering a microservice-based architecture. We propose a cost-effective workload allocation for microservice-based applications. We model the problem as an integer programming problem…
Cloud Computing (CC) is the most prevalent paradigm under which services are provided over the Internet. The most relevant feature for its success is its capability to promptly scale service based on user demand. When scaling, the main objective is to maximize as much as possible service performance. Moreover, resources in the Cloud are usually so abundant, that they can be assumed infinite from the service point of view: an application provider can have as many servers it wills, as long it pays for it. This model has some limitations. First, energy efficiency is not among the first criteria f…
Cloud native computing paradigm allows microservice-based applications to take advantage of cloud infrastructure in a scalable, reusable, and interoperable way. However, in a cloud native system, the vast number of configuration parameters and highly granular resource allocation policies can significantly impact the performance and deployment cost. For understanding and analyzing these implications in an easy, quick, and cost-effective way, we present PerfSim, a discrete-event simulator for approximating and predicting the performance of cloud native service chains in user-defined scenarios. T…
