Comparing Containers versus Virtual Machines for Achieving High Availability

Nowadays production flows are modular, each module in the enterprise being specialized and used to achieve a particular task. In many cases the modules are interconnected and materials are sequentially processed in each module resulting a final, unique product or assembly. One typical such production module is a flexible cell/system using multiple robots. In such complex enterprise environments, providing continuous services for applications is a key component of a successful implementing of robotized manufacturing. High availability (HA) is one of the components contributing to continuous service provision for applications, by masking or eliminating both planned and unplanned downtime of systems and applications. This is achieved by eliminating hardware and software single points of failure (SPOF). The systems configured for high availability are a combination of hardware and software components configured to work together to ensure automated recovery in case of failure with a minimal acceptable downtime. A high availability solution will ensure that the failure of any component of the solution either hardware, software or system management, will not cause the application and its data to become permanently unavailable. High availability solutions should eliminate single points of failure through appropriate design, planning, hardware selection, software configuring, application control, carefully environment control and change management discipline. In short, one can define high availability as the process of ensuring an application is available for use by duplicating and/or sharing hardware resources managed by a specialized software component. A high availability solution in robotized manufacturing provides automated failure detection, diagnosis, application recovery, and node (robot controller) re integration. The chapter discusses the implementing of a high availability solution in a robotized manufacturing structure (cell, line). The solution is based on a High Availability Linux Cluster which is responsible for data availability and preservation on a NFS (Network File System) file system, and a second cluster – Fabrication Cluster (FC) which runs on Adept robot controllers, developed under the V+ programming language.

Cloud computing provides virtual resources so that end-users or organizations can buy computing power as a public utility. Cloud service providers however must strive to ensure good QoS by offering highly available services with dynamically scalable resources. HA-OSCAR is an open source High Availability (HA) solution for HPC/cloud that offers component redundancy, failure detection, and automatic fail-over. In this paper, we describe HA-OSCAR as a cloud platform and analyze system availability of two potential cloud computing systems, OSCAR-V cluster and HA-OSCAR-V. We also explore our case study to improve Nimbus, a popular cloud IaaS toolkit. The results show that the system that deploys HA-OSCAR has a significantly higher degree of availability.

In the last chapter, we talked about some basic things about MVCC in PostgreSQL, and what is bloat in the database and how it can be removed. We explained how autovacuum helps in removing bloat and improving performance. We also covered the best practices to execute maintenance activities like vacuum, reindex in detail. In this chapter, we will talk about the importance of High Availability (HA), and what information we need to build an HA solution and the procedures to implement it in PostgreSQL. We will cover some open source and enterprise tools to implement HA. We will also cover the importance of a pooler, and available poolers on the market and their implementation.

A large class of modern distributed file systems treat metadata services as an independent system component, separately from data servers. The availability of the metadata service is key to the availability of the overall system. Given the high rates of failures observed in large-scale data centers, distributed file systems usually incorporate high-availability (HA) features. A typical approach in the development of distributed file systems is to design and develop metadata services from the ground up, at significant cost in terms of complexity and time, often leading to functional shortcomings. Our motivation in this paper was to improve on this state of things by defining a general-purpose architecture for HA metadata services (which we call RMS) that can be easily incorporated and reused in new or existing file systems, reducing development time. Taking two prominent distributed file systems as case studies, PVFS and HDFS, we developed RMS variants that improve on functional shortcomings of the original HA solutions, while being easy to build and test. Our extensive evaluation of the RMS variant of HDFS shows that it does not incur an overall performance or availability penalty compared to the original implementation.

Cloud is a popular and attractive paradigm for providing online computing services to the end users. Recently many of the users move their business applications to the cloud and become tenants for the cloud service providers. Some tenants expect their applications that are provided as services to be highly available (HA) at any time. Managing HA of applications services in the cloud is a big challenge due to the dynamic nature and the huge number of the provision services in the cloud. Limited number of solutions address the HA of services in the cloud platforms that use containers instead of Virtual Machines (VMs). In addition, HA measurements are still missing by the proposed solutions in the literature. Therefore, in this article we propose a framework to incorporate the HA feature for the applications that are deployed in cloud platforms that use the containers. The framework depends on the novel idea of integrating HA middlewares OpenSAF and Pacemaker with the containers to manage HA of the applications services. As a proof of concept, we build a prototype for our framework using our private cloud Container-based platform. For the evaluation purposes, we compare the same framework using our cloud VM-based platform. The measurements show the ability of the proposed framework to manage HA of different services using the containers with faster service recovery time and shorter service outage time than using the VMs.

As businesses increasingly rely on IT for their mission-critical operations, continuous availability is a universal concern. Nowadays, virtualized platform has become the popular option to deploy complex enough services. Deployed services are expected to be always, available, but these long running services are especially sensitive to suffer from software aging phenomenon. Software aging of virtual machine monitors (VMMs) is becoming critical because performance degradation or crash failure of a VMM affects all virtual machines (VMs) on it. To counteract this issue, we deploy software rejuvenation methodology. To eliminate the service outage during software rejuvenation process, we combine the rejuvenation with live migration technology. Live VM migration enables a running VM on a host serer to move onto the other host server with very small interruption of the execution. Live VM migration depends on VMs placement and efficient resource available is required. The idea behind our paper is two-fold. First, we present the optimization of the resource usage as accepting as many services as in virtualized environment which support of VM live migration. Second, to demonstrate how much it can improve system availability, the stochastic Petri nets model a virtualized server system in case of using time based software rejuvenation for VMM is presented. Finally, we perform the numerical analysis to evaluate the model.

Cluster computing has recently gone through an evolution from single processor systems to multicore/multi-socket systems. This has resulted in lowering the cost/performance ratio of the compute machines. Compute farms that host these machines tend to become heterogeneous over time due to incremental extensions, hardware upgrades and/or nodes being purchased for users with particular needs. This heterogeneity is not surprising given the wide range of processor, memory and network technologies that become available and the relatively small price difference between these various options. Different CPU architectures, memory capacities, communication and I/O interfaces of the participating compute nodes present many challenges to job scheduling and often result in under or over utilization of the compute resources. In general, it is not feasible for the application programmers to specifically optimize their programs for such a set of differing compute nodes, due to the difficulty and time-intensiveness of such a task. The trend of heterogeneous compute farms has coincided with resurgence in the virtualization technology. Virtualization technology is receiving widespread adoption, mainly due to the benefits of server consolidation and isolation, load balancing, security and fault tolerance. Virtualization has also generated considerable interest in the High Performance Computing (HPC) community, due to the resulting high availability, fault tolerance, cluster partitioning and accommodation of conflicting user requirements. However, the HPC community is still wary of the potential overheads associated with virtualization, as it results in slower network communications and disk I/O, which need to be addressed. The live migration feature, available to most virtualization technologies, can be leveraged to improve the throughput of a heterogeneous compute farm (HC) used for HPC applications. For this we mitigated the slow network communication in Xen; an open source virtual machine monitor. We present a detailed analysis of the communication framework of Xen and propose communication configurations that give 50% improvement over the conventional Xen network configuration. From a detailed study of the migration facility in Xen, we propose an improvement in the live migration facility specifically targeting HPC applications. This optimization gives around 50% improvement over the default migration facility of Xen. In this thesis, we also investigate resource scheduling in heterogeneous compute farm with the perspective of dynamic resource re-mapping. Our approach is to profile each job in the compute farm at runtime, and propose a better resource mapping compared to the initial allocation. We then migrate the job(s) to the best-suited homogeneous sub-cluster to improve overall throughput of the HC. For this, we develop a novel heterogeneity and virtualization-aware profiling framework, which is able to predict the CPU and communication characteristics of high performance scientific applications. Our experimental setup consists of a 32 node virtualized cluster with machines having CPU frequency between 2 GHz to 3 GHz. The framework was tested with a subset of NAS parallel benchmarks with the workload generated from Dror Feitelson’s workload archives. The prediction accuracy of our performance estimation model is over 80%. The framework implementation is lightweight, with an overhead of 3%. Our experiments show that we are able to improve the throughput of the compute farm by 25% and the time saved by the HC with our framework is over 30%. The framework can be readily extended to HCs supporting a cloud computing environment.

인터넷 환경의 급속한 발전과 더불어 국내외 미션 크리티컬한 비즈니스 환경이 온라인에 의해 서비스 되고 있다. 따라서 웹 환경을 통해 처리되어야 할 정보의 양의 급증과, 이의 처리를 위해 여러 개의 단일 서버를 고속의 네트워크로 연결한 고가용성 구현이 가능한 클러스터 컴퓨팅 시스템이 등장하게 되었다. 그 결과 클러스터 기반 DBMS에 관한 연구와 상용화된 솔루션을 통해 국내외적으로 활발히 진행 중이며, 이에 따라 클러스터 기반 DBMS를 효율적이고 최적화된 상태의 관리 연구는 미흡한 실정이다. 따라서 본 논문에서는 클러스터 기반 DBMS를 위한 고가용성 클러스터 솔루션의 최적화된 관리 기법과 이론에 대해 알아본다. In these days, Internet environment are very quickly development as well On-line service have been using a online for the mission critical business around the world. As the amount of information to be processed by computers has recently been increased there has been cluster computing systems developed by connecting workstations server using high speed networks for high availability. As a result, this study on a cluster based DBMS and common solution of DBMS venders has been studying with a wide range, as well as It is not good study a management skill for the cluster-based DBMS efficiently and optimization. accordingly, This study find out optimization managements skill and theory of he High availability solution on cluster-based DBMS.

Broadband Power Line Communications (BPL) is a technology that has proved to be a very suitable option for the deployment of Smart Grid solutions. It provides a low cost, proprietary, high performance future-proof backhaul between Secondary Substations. This paper will focus on the description of the different "Fault Cases" that might occur in medium voltage BPL communication architecture and their consequent High Availability solution, taking advantage of Iberdrola's experience in the use and maintenance of this technology along its large scale Smart Grid deployment. The description of the High Availability functionality and the results of the tests developed so far are presented in this paper so that utilities might find it useful to provide an added value in their own Smart Grid deployments.

In our increasingly wired world, there is a stringent need for the IT community to provide uninterrupted services of networks, servers and databases. Considerable efforts, both by the industrial and academic community have been directed to this end. In this paper, we examine the requirements for high availability, measures used to express it, and approaches used to implement this for databases. We present a high availability solution, using off the shelf hardware and software components, for transactions based applications and give our experience with this system.

High availability is a critical feature for service clusters and cloud computing, and is often considered more valuable than performance. One commonly used technique to enhance the availability is live migration, which replicates services based on virtualization technology. However, continuous live migration with checkpointing will introduce significant overhead. In this paper, we present a lightweight live migration (LLM) mechanism to integrate whole-system migration and input replay efforts, which aims at reducing the overhead while providing comparable availability. LLM migrates service requests from network clients at high frequency during the interval of checkpointing system updates. Once a failure happens to the primary machine, the backup machine will continue the service based on the virtual machine image and network inputs at their respective last migration rounds. We implemented LLM based on Xen and compared it with Remus—a state-of-the-art effort that enhances the availability by checkpointing system status updates. Our experimental evaluations show that LLM clearly outperforms Remus in terms of network delay and overhead. For certain types of applications, LLM may also be a better alternative in terms of downtime than Remus. In addition, LLM achieves transaction level consistency like Remus.KeywordsCloud ComputingVirtual MachineService RequestClient SideNetwork DelayThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

It is important for any organization to handle increase in data; normally this is the job of the DBA in organization to take care of this data growth, along with its protection and its availability. High availability of data is also most important for organizations, for that purpose, shared storage is usually the solution, for example, SAN or NAS storage as Microsoft Cluster Database instances. Mostly Organization does not have shared storage in their infrastructure, which was required for Microsoft cluster SQL database instance; due to that they used other native methods to implement like log shipping or database mirroring, which was not efficient method for high-availability and disaster-recovery solution. After that, Microsoft introduced native method called SQL AlwaysOn method that could be implemented without using SAN and NAS storage method to implement high availability and disaster recovery without using shared storage. SQL AlwaysOn option is using only Microsoft cluster service and shared folder between the nodes. This paper written for DBA and System Administrators; and is implementation of Microsoft SQL Database tier step by step.

Museums play an important role in shaping social discourses, not only offering economic benefits but also making significant contributions in the development of social and cultural enrichment. In the current dynamic environment, museums face the challenges of innovating and adopting technologies and combining art education with market trends, and this often conflicts with their social mission. This research focuses on the perceptions of a museum’s key stakeholders of the growing trend of virtual technology, using a qualitative case study on a modern and contemporary art museum in Indonesia. The findings reveal that, despite the positive responses of using digital technologies, the museum’s key stakeholders believed that physical-human interaction is still critical in achieving the museum mission as well as in responding to market trends.

Chapter 11 - High Availability: Reset to Good

Purpose – The physical server transition to virtualized infrastructure server have encountered crucial problems such as server consolidation, virtual machine (VM) performance, workload density, total cost of ownership (TCO), and return on investments (ROIs). In order to solve the problems mentioned above, the purpose of this paper is to perform the analysis of virtualized cloud server together with shared storage as well as the estimation of consolidation ratio and TCO/ROI in server virtualization. Design/methodology/approach – This paper introduces five distinct virtualized cloud computing servers (VCCSs), and provides the appropriate assessment to five well-known hypervisors built in VCCSs. The methodology the authors proposed in this paper will gives people an insight into the problem of physical server transition to virtualized infrastructure server. Findings – As a matter of fact, VM performance seems almost to achieve the same level, but the estimation of VM density and TCO/ROI are totally different among hypervisors. As a result, the authors have the recommendation to choose the hypervisor ESX server if you need a scheme with higher ROI and lower TCO. Alternatively, Proxmox VE would be the second choice if you like to save the initial investment at first and own a pretty well management interface at console. Research limitations/implications – In the performance analysis, instead of ESX 5.0, the authors adopted ESXi 5.0 that is free software, its function is limited, and does not have the full functionality of ESX server, such as: distributed resource scheduling, high availability, consolidated backup, fault tolerance, and disaster recovery. Moreover, this paper do not discuss the security problem on VCCS which is related to access control and cryptograph in VMs to be explored in the further work. Practical implications – In the process of virtualizing the network, ESX/ESXi has restrictions on the brand of the physical network card, only certain network cards can be detected by the VM. For instance: Intel and Broadcom network cards. The newer versions of ESXi 5.0.0 and above now support parts of Realtek series (Realtek 8186, Realtek 8169, and Realtek 8111E). Originality/value – How to precisely assess the hypervisor for server/desktop virtualization is also of hard question needed to deal with it crisply before deploying new IT with VCCS on site. The authors have utilized the VMware calculator and developed an approach to server/desktop consolidation, virtualization performance, VM density, TCO, and ROIs. As a result, in this paper the authors conducted a comprehensive approach to analyze five well-known hypervisors and will give the recommendation for IT manager to choose a right solution for server virtualization.