High Availability Cluster Research Articles

Management and Operator Control System based on Microservice Architecture and Application on the HIPr Accelerator

The paper describes the basic principles of developing a distributed control system (DCS) and a GARNET operator control system based on a microservice architecture as part of a high-availability cluster. The application of the operator’s control system as a DCS component is described. The main elements of software components of operator control and DCS are presented and described. The process of conveyor assembly and publication of software tools into a working product environment, which implements the principle of continuous integration, is described. The mechanism of interaction of key components among themselves is presented. The mechanism for hosting management services using the Docker containerization system and Kubernetes container orchestration is demonstrated. Examples of services for interaction with users in the environment of the GARNET operator control system being developed, separation of users by roles and access rights, integration of the data visualization service using Grafana are shown. The vector of further development of DCS and operator control tools is described, in particular, the possibility of using the practice of developing user web interfaces using the micro frontend approach. The components and results of the operation of a prototype system designed to interact with the measurement infrastructure of the linear heavy ion accelerator HIPR are presented.

High Availability’s Implementation on the Fortigate Firewall Using SD-WAN Zone and HA Cluster Active-Passive

Networks that contain sensitive data or have high-security requirements require reliable and dependable network security solutions. FortiGate Firewall, as one of the popular network security solutions, provides High Availability (HA) features that ensure network availability and reliability. This study aims to analyze the implementation of HA on FortiGate Firewall in specific scenarios, such as networks with sensitive data or networks with high-security requirements. A real-world case study is applied to evaluate the effectiveness of HA implementation on FortiGate Firewall in enhancing network reliability and security. In this research, the implementation of HA on FortiGate Firewall at PT ABC was successfully built using the PPDIOO method and deploying SD-WAN load balancing and failover configurations, along with the utilization of a high-availability cluster mechanism. The HA implementation on FortiGate proves to be an effective solution, as demonstrated in the SD-WAN Zone testing of the Source-destination SD-WAN load balancing mode, which showed effectiveness in evenly and optimally distributing traffic among multiple available links, resulting in a 93.3% reduction in downtime. Furthermore, the testing of HA cluster mode in active-passive configuration achieved a 91.8% reduction in downtime compared to the pre-HA implementation state.

High availability of kernel-based virtual machine using nested virtualization

- KVM (Kernel-based Virtual Machine) is one of the popular, free and open-source virtual machine managers for Linux distributions. Many people or companies use plain KVM virtualization, but in many cases, they have no measures in place for ensuring availability if a host fails. The existing method to set up a high availability cluster using basic KVM virtualization is a difficult procedure for someone unfamiliar with the process. A growing number of powerful strategies are furnished with network interconnection and are related to the Internet of Things (IoT). In this research work proposes a simple method for ensuring the high availability of KVM hypervisor with the help of the nested virtualization technique. In the proposed work, the KVM hypervisor will run on another high availability enabled hypervisor. For the performance evaluation, the parameters like CPU performance, I/O performance and memory performance were evaluated. That got the better results in the proposed system than others. The proposed evaluation demonstrates that the overhead in relations of network throughput and CPU accomplishment is low so it related that the proposed concept is a evocative step in the direction of additional resilient forthcoming IoT devices.

A computationally efficient method for assessing the impact of an active viral cyber threat on a high-availability cluster

The field of computer science, like its sub-field of cyber threat modelling, is rapidly evolving. The prerequisites for key changes can be summarized as follows: cyber threats are evolving; there are leaks of special services tools; agile development methodology is being introduced everywhere; the boundaries of the object of protection are blurred; the scope of application of artificial intelligence is expanding; potentially vulnerable API integrations are increasingly being used. These factors lead to the fact that the processes of analysis of cyber threats, analysis of protective measures, generalization of data, and development of protective tools should now be considered continuous, not discrete. At the same time, the cost of cybersecurity increases like an avalanche in an attempt to avoid reputational and information losses. The only way to avoid this tendency is to apply a rational, scientific, accurate method of cognition to these processes. Thus, the creation of mathematical models of processes in the field of cybersecurity is now more relevant than ever. The article is devoted to the investigation of the process of the influence of an active viral cyber threat on a high-availability cluster in the paradigm of the provisions of the theory of Markov processes, graph theory and the theory of mathematical analysis. The main contribution of the research is a formalized computationally efficient method of approximate estimation of the average number of affected elements of the target high-availability cluster under the influence of an active viral cyber threat. Also, a criterion that allows estimating the trend of the quantitative parameter of the metric of the model of the studied process at medium and long time intervals is proposed. To obtain the declared scientific result, the authors: - formulated a Markov model of the process of the influence of an active viral cyber threat on a high availability cluster; - substantiated a compact metric for accurate assessment of the average number of cluster elements affected by an active viral cyber threat at any time; - formulated a computationally efficient method of approximate estimation of the parameter of the mentioned metric for the model of the target studied process; - proposed a criterion that allows researchers to evaluate the trend of the parameter of the mentioned metric for the model of the target researched process at medium and long intervals of time. The adequacy of the formulated method has been proven empirically.

Predicting locally manageable resource failures of high availability clusters

AbstractCritical services from domains as diverse as finance, manufacturing and healthcare are often delivered by complex enterprise applications (EAs). High‐availability clusters (HACs) are software‐managed IT infrastructures that enable these EAs to operate with minimum downtime. This article presents a novel Bayesian decision network model to improve the failure detection capabilities of the HACs components using a comprehensive set of characteristics for the analyzed component. The model then combines these characteristics to predict whether the failure of this component can be managed locally at the failed component level without propagating the failure to upper‐level components and causing a complete system failure. By improving the detection capabilities and predicting locally manageable failures, the model improves the decision‐making process of HACs, and has the potential to reduce the downtime and improve availability for the applications protected by HACs. The model uses the capabilities of the Bayesian decision networks, which combines Bayesian networks with the utility theory, to assign weights to different characteristics and consolidate the related variables to output the result. The model evaluation in a realistic testbed environment with three servers, an established HAC and a well‐known EA shows that the model can improve the area under the receiver operating characteristic curve for prediction of locally manageable failures by up to 9.05% compared to the baseline HAC results.

Edge Workloads Monitoring and Failover: a StarlingX-Based Testbed Implementation and Measurement Study

With the ever-growing amount of time-critical, compute-intensive, and private IoT applications, the need for High Availability (HA) Edge Clouds becomes indispensable. Realizing HA Edge Clouds is inherently challenging due to the geographically-dispersed hierarchy of the Distributed Cloud Infrastructure (DCI). For example, frequent isolation between the central Cloud and Edge Clouds due to networking instability necessitates some autonomous operations at the Edge Clouds. Furthermore, because Edge Clouds have fewer resources than central Clouds, configuring the Edge functions (i.e., control, compute, and storage) in HA clusters will undoubtedly reduce downtime. However, it will limit the Edge scalability. To that end, StarlingX is developing an HA-protected and scalable DCI virtualization platform based on the open-source ecosystem, focusing on low-touch management of Edge Clouds. StarlingX provides a fault management service that realizes DCI-wide alarming and logging capabilities, allowing for rapid response to virtualized infrastructure events. Recently, the IETF Network Working Group proposed that monitoring both the DCI and the Edge workloads (software containers) is critical for an Edge Computing Platform to maintain HA IoT application deployment. Indeed, the possibility of the infrastructure remaining stable and healthy while the workloads suffer a fatal failure simultaneously necessitates failover functionality that monitors both the infrastructure and the Edge workloads. In this paper, we first propose a dynamic failover functionality that centrally monitors Edge workloads to recover from deployment or Edge node failures, motivated by the IETF direction. Second, we experimentally optimize the failover functionality for monitoring a microservice-architected IoT application deployed on a StarlingX-based DCI testbed to collect temperature sensor readings from Raspberry Pis. Regardless of how quickly the Edge workload health checks are collected, the recorded failover measurements reveal that the recovery time will not drop below a predetermined level controlled by Edge resources and network speed. Furthermore, reducing the statistics collection timeout reduces the recovery time of an Edge node failure. When the timeout value is less than the minimum achievable recovery time, false-positive failures (FPFs) can occur. Third, to supplement the StarlingX fault management service, we provide a modular implementation of the proposed failover functionality. Finally, we present the first-ever introduction of the StarlingX platform’s software stack to promote its use in academic research.

High-availability clusters: A taxonomy, survey, and future directions

The delivery of key services in domains ranging from finance and manufacturing to healthcare and transportation is underpinned by a rapidly growing number of mission-critical enterprise applications. Ensuring the continuity of these complex applications requires the use of software-managed infrastructures called high-availability clusters (HACs). HACs employ sophisticated techniques to monitor the health of key enterprise application layers and of the resources they use, and to seamlessly restart or relocate application components after failures. In this paper, we first describe the manifold uses of HACs to protect essential layers of a critical application and present the architecture of high availability clusters. We then propose a taxonomy that covers all key aspects of HACs—deployment patterns, application areas, types of cluster, topology, cluster management, failure detection and recovery, consistency and integrity, and data synchronisation; and we use this taxonomy to provide a comprehensive survey of the end-to-end software solutions available for the HAC deployment of enterprise applications. Finally, we discuss the limitations and challenges of existing HAC solutions, and we identify opportunities for future research in the area.

Evolution of the CERNBox platform to support the Malt project

CERNBox is the CERN cloud storage hub for more than 25,000 users at CERN. It allows synchronising and sharing files on all major desktop and mobile platforms (Linux, Windows, MacOSX, Android, iOS) providing universal, ubiquitous, online- and offline access to any data stored in the CERN EOS infrastructure. CERNBox also provides integration with other CERN services for big science: visualisation tools, interactive data analysis and real-time collaborative editing.Over the last two years, CERNBox has evolved from a pure cloud sync and share platform into a collaborative service, to support new applications such as DrawIO for diagrams and organigrams sketching, OnlyOffice and Collabora Online for documents editing, and DXHTML Gantt for project management, as alternatives to traditional desktop applications. Moving to open source applications has the advantage to reduce licensing costs and enables easier integration within the CERN infrastructure. This move from commercial software to open source solutions is part of the MALT project, led by the IT department at CERN to reduce the dependencies on commercial solutions.As part of the MALT project, CERNBox is the chosen solution to replace Home directories of the Windows DFS file system. Access to storage from Windows managed devices for end-users is largely covered by synchronization clients. However, online access using standard CIFS/SMB protocol is required for shared use-cases, such as central login services (Terminal Services) and visitor desktop computers. We present recent work to introduce a set of Samba gateways running in High Availability cluster mode to enable direct access to the CERNBox backend storage (EOS).

PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources

BackgroundBiological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data.ResultsIn this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTful web service API offered by CellBase. This package offers a fast and user-friendly access to biological information without the need of installing any local database. In addition, a series of command-line tools are provided to perform common bioinformatic tasks, such as variant annotation. CellBase data is always available by a high-availability cluster and queries have been tuned to ensure a real-time performance.ConclusionPyCellBase is an open-source Python package that provides an efficient access to heterogeneous biological information. It allows to perform tasks that require a comprehensive set of knowledge resources, as for example variant annotation. Queries can be easily fine-tuned to retrieve the desired information of particular biological features. PyCellBase offers the convenience of an object-oriented scripting language and provides the ability to integrate the obtained results into other Python applications and pipelines.

Topology-Aware Resource-Efficient Placement for High Availability Clusters Over Geo-Distributed Cloud Infrastructure

A management and orchestration framework (MANO) in network function virtualization (NFV) enables the agile deployment and operation of virtual network functions over a geographically distributed cloud infrastructure. This facilitates the deployment of redundancy models (i.e., high availability clusters) over different cloud centers, to guarantee the high availability of network services. In particular, in the telecommunications field, availability and resiliency are always required at a high level. Existing placement algorithms only consider one type of redundancy model at a given time. However, in reality, different redundancy configurations can be utilized to ensure the availability of virtual functions. In this article, we present an optimization model and topology-aware resource-efficient placement algorithm (TARE), which can be employed to optimally deploy high availability clusters with different redundancy configurations over geo-distributed cloud infrastructures. This model takes into account the different requirements of various high availability clusters in terms of bandwidth and computing resource demands. By simulation, the TARE has better performance than other baseline solutions in terms of the bandwidth usage, while maintaining an acceptable level of availability.

High-availability cluster on the basis of applications servers “GlassFish”

High-availability cluster on the basis of applications servers “GlassFish”

High availability cluster for environmental management tasks

High availability cluster for environmental management tasks

Implementation And Analysis High Availability Network File System Based Server Cluster

Server is a computer system that provides the kind of service in a computer network. One of the functions of the server is as data storage. Computers servers with high availability values are generally referred to as High Availability (HA) Server. HA enables a server can be operational in a sustainable manner for long periods of time. Now, HA has been combined with a cluster technique known as High Availability Clusters or failover cluster. In this research the author intends to apply, analyze, and implement a network file server that has a high availability of service. Researchers used a pacemaker as cluster resource management, Corosync as cluster messaging service and DRBD for the synchronization of data if a failover occurs and measured network performer cluster file system that does have a high availability service. The result is a network file system or the availability of the cluster has a value of 99.998% availability, which means it has a High Availability. The server network file system failover cluster meets the conditions, which, if the primary server (master) dies it will be replaced by a slave server.

Biodiversity Data Curation: South Africa Goes Online

The South African Institute for Aquatic Biodiversity (SAIAB) operates several research platforms, which may be used by the broader South African research community (e.g. a marine research vessel and a remotely operated underwater vehicle). SAIAB’s Enterprise-grade data centre, along with expertise in systems administration and biodiversity information management, allow the institute to offer a Biodiversity Information Management Platform. Data hosted by SAIAB is replicated across three data centres, with each centre being at least 250m apart and operating independently. Infrastructure at two data centres replicates in real time, forming a high availability cluster. The third datacentre is dedicated to storing backups. High-capacity tape backup will be added in the near future. As an additional measure, cloud storage is used to store daily extracts of Specify databases, which are retained for one year. In the first instance, the Platform aims to provide SAIAB researchers and associates with biodiversity data curation services. This begins with support for the SAIAB Collections Division, to ensure that voucher specimens, tissue samples and associated media are accurately catalogued and can be easily retrieved. Biodiversity data curation is broader than this. It also means that any biodiversity data/metadata (records of species, events, occurrences/observations and traits) can potentially be curated using Specify Software, and standardised and published (subject to relevant policies) to the GBIF Data Portal using the GBIF Integrated Publishing Toolkit. The use of Specify Software to curate biodiveristy data that do not represent voucher specimens (e.g. underwater images and video) is a new research project within SAIAB, which has the potential to be extended beyond SAIAB. A new national initiative, the Natural Science Collections Facility (NSCF), was launched in 2017 to reinvigorate natural science museums across the country, to halt deterioration of specimens and improve capacity for specimen and data curation. In support of the NSCF, the SAIAB platform is offered to natural science museums in South Africa (excluding herbaria, which are all part of or affiliated with SANBI, and therefore accommodated by a different system). Each museum will be provided with a webserver, Specify 7 database, Specify web portal and IPT server. In offering this platform to the broader South African Biodiversity Science community, SAIAB is primarily motivated by the potential for collaborative research in capacity development for biodiversity data curation / information management, using Specify Software. The first research project will examine participating museums’ capacity to use the Specify Workbench sustainably, to import new voucher/occurrence records generated by fieldwork. The requisite training to enhance this potential will be provided. The Natural Science Collections Facility (NSCF) is an important collaborator in the context of enhancing the general state of South Africa’s specimen collections, and the Specify Collections Consortium is an important collaborator, specifically for support.

Fast and Reliable Restoration Method of Virtual Resources on OpenStack

We propose a fast and reliable restoration method of virtual resources on OpenStack when physical servers or virtual machines are down. Many providers have recently started cloud services, and the use of OpenStack, which is open source IaaS software, is increasing. When physical servers are down, there is a fail-over method using the high-availability cluster software such as Pacemaker to restore virtual resources. However, it takes a long time to restore all virtual resources. There is also a method for monitoring each virtual machine by using Ping or other methods and restoring a virtual machine when it is down. However, data may be destroyed due to the double mounts of virtual machines depending on the timing of failures because restoration methods of failed physical servers and virtual machines are independent. Therefore, we propose a fast and reliable restoration method with a uniform way for plural types virtual resources. In our method, Pacemaker only detects a physical server failure and notifies a failure to a virtual resource arrangement scheduler, then a virtual resource arrangement scheduler determines multiple physical servers to restore virtual resources and calls OpenStack APIs to rebuild. The virtual resource arrangement scheduler also detects virtual machine failures by using a Libvirt monitoring module and restores virtual machines without data loss by handling Pacemaker and Libvirt notifications uniformly. We implemented the proposed method and showed its effectiveness regarding fast restoration through performance measurements.

An Achievement of High Availability and Low Cost on Data Center Infrastructure

This study is to provide a design of low-cost and high-availability data center infrastructure for small/medium-scale businesses. The basic concept is to establish an infrastructure consisting of primary and backup sides through the clustering technology. By default, the primary side is active and responsible for data switching while the backup side is standby for the failure of the primary side. The design achieves the features of 1) providing full-level high availability (HA) at network, server, application, and management levels, 2) controlling the routing among network-level clusters to solve the “PPPOE connection racing” and “winding path” problems, 3) monitoring and recovering the objects in each level with an economic and effective way, and 4) handling events resulting from changing of object states in an event center. Finally, the experiment results are exhibited with five testing scenarios for verification and elaboration of the effectiveness of the HA design. The system can recover the failed objects and solve the routing problems of PPPOE connection racing and winding path among HA clusters automatically.

SOFTWARE FOR CONTROL OF HIGH-AVAILABILITY CLUSTER FOR RTOS QNX NEUTRINO

Herein are presented aspects of development of control software for high-availability cluster, which is a specialized on-board computational facility based on QNX Neutrino real-time operating system, which has a high reliability and the required set of functions. Debugging and testing of the developed software in Qt Creator developer environment have been reviewed, and inter alia, on the prototype of a high-availability cluster.

Zastosowanie klastra wysokiej dostępności w bezpieczeństwie relacyjnych baz danych

Zastosowanie klastra wysokiej dostępności w bezpieczeństwie relacyjnych baz danych

Performance Measurement and Analysis of High-Availability Clusters

High-availability clusters are groups of servers that provide a reliable framework for applications to achieve a minimum downtime and quick recovery time without any human intervention and yet are completely opaque to the users. Almost all industries are continuously pursuing the goal to minimize their critical application downtimes by using various techniques such as fault tolerance, redundancy, mirroring and clustering. During downtime, applications become unavailable to end users, which can lead to financial, reputation and regulatory business impacts. High-availability clusters provide a mechanism to migrate complete applications or services from one server to another seamlessly without any human intervention at the time of failure of any critical component or the complete server. Hence, an application would start on a healthy server, without end users realizing this failover. In this work, key features and aspects of two cluster products, 'Symantec Veritas Cluster Suite' and 'Red Hat Cluster' were compared against each other based on various parameters. A simulated environment was created to perform a comprehensive analysis of performances of both products. In this work, measurement of average failover time was taken and compared as the key reliability and serviceability attribute. Thus, based on this experimental work, it is concluded that in a controlled test environment running a simple web-server application, Red Hat cluster gives a better failover performance as compared to Veritas Cluster Suite. However, in a large-scale environment, if we consider factors like operating system compatibility, supported applications, compatibility with volume managers, hardware compatibility, reliability, fault tolerance, predictive failure, self-healing etc., then the Veritas Cluster Suite comes out as the winner.

A High Availability Clusters Model Combined with Load Balancing and Shared Storage Technologies for Web Servers

This paper designs and implements a high availability clusters and incorporated with load balance infrastructure of web servers. The paper described system can provide full facilities to the website hosting provider and large business organizations. This system can provide continuous service though any system components fail uncertainly with the help of Linux Virtual Server (LVS) load-balancing cluster technology and combined with virtualization as well as shared storage technology to achieve the three-tier architecture of Web server clusters. This technology not only improves availability, but also affects the security and performance of the application services being requested. Benefits of the system include node failover overcome; network failover overcome; storage limitation overcome and load distribution.