6,792 research outputs found
Performance Evaluation of Microservices Architectures using Containers
Microservices architecture has started a new trend for application
development for a number of reasons: (1) to reduce complexity by using tiny
services; (2) to scale, remove and deploy parts of the system easily; (3) to
improve flexibility to use different frameworks and tools; (4) to increase the
overall scalability; and (5) to improve the resilience of the system.
Containers have empowered the usage of microservices architectures by being
lightweight, providing fast start-up times, and having a low overhead.
Containers can be used to develop applications based on monolithic
architectures where the whole system runs inside a single container or inside a
microservices architecture where one or few processes run inside the
containers. Two models can be used to implement a microservices architecture
using containers: master-slave, or nested-container. The goal of this work is
to compare the performance of CPU and network running benchmarks in the two
aforementioned models of microservices architecture hence provide a benchmark
analysis guidance for system designers.Comment: Submitted to the 14th IEEE International Symposium on Network
Computing and Applications (IEEE NCA15). Partially funded by European
Research Council (ERC) under the European Union's Horizon 2020 research and
innovation programme (grant agreement No 639595) - HiEST Projec
Real-Time Containers: A Survey
Container-based virtualization has gained a significant importance in a deployment of software applications in cloud-based environments. The technology fully relies on operating system features and does not require a virtualization layer (hypervisor) that introduces a performance degradation. Container-based virtualization allows to co-locate multiple isolated containers on a single computation node as well as to decompose an application into multiple containers distributed among several hosts (e.g., in fog computing layer). Such a technology seems very promising in other domains as well, e.g., in industrial automation, automotive, and aviation industry where mixed criticality containerized applications from various vendors can be co-located on shared resources.
However, such industrial domains often require real-time behavior (i.e, a capability to meet predefined deadlines). These capabilities are not fully supported by the container-based virtualization yet. In this work, we provide a systematic literature survey study that summarizes the effort of the research community on bringing real-time properties in container-based virtualization. We categorize existing work into main research areas and identify possible immature points of the technology
CyberGuarder: a virtualization security assurance architecture for green cloud computing
Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation
Container network functions: bringing NFV to the network edge
In order to cope with the increasing network utilization driven by new mobile clients, and to satisfy demand for new network services and performance guarantees, telecommunication service providers are exploiting virtualization over their network by implementing network services in virtual machines, decoupled from legacy hardware accelerated appliances. This effort, known as NFV, reduces OPEX and provides new business opportunities. At the same time, next generation mobile, enterprise, and IoT networks are introducing the concept of computing capabilities being pushed at the network edge, in close proximity of the users. However, the heavy footprint of today's NFV platforms prevents them from operating at the network edge. In this article, we identify the opportunities of virtualization at the network edge and present Glasgow Network Functions (GNF), a container-based NFV platform that runs and orchestrates lightweight container VNFs, saving core network utilization and providing lower latency. Finally, we demonstrate three useful examples of the platform: IoT DDoS remediation, on-demand troubleshooting for telco networks, and supporting roaming of network functions
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