Alternatives to Corosync Cluster Engine

Amazon Elastic Container Service (ECS) is a comprehensive container orchestration platform that is fully managed. Notable clients like Duolingo, Samsung, GE, and Cook Pad rely on ECS to operate their critical applications due to its robust security, dependability, and ability to scale. There are multiple advantages to utilizing ECS for container management. For one, users can deploy their ECS clusters using AWS Fargate, which provides serverless computing specifically designed for containerized applications. By leveraging Fargate, customers eliminate the need for server provisioning and management, allowing them to allocate costs based on their application's resource needs while enhancing security through inherent application isolation. Additionally, ECS plays a vital role in Amazon’s own infrastructure, powering essential services such as Amazon SageMaker, AWS Batch, Amazon Lex, and the recommendation system for Amazon.com, which demonstrates ECS’s extensive testing and reliability in terms of security and availability. This makes ECS not only a practical option but a proven choice for organizations looking to optimize their container operations efficiently.

CIQ empowers people to do amazing things by providing innovative and stable software infrastructure solutions for all computing needs. From the base operating system, through containers, orchestration, provisioning, computing, and cloud applications, CIQ works with every part of the technology stack to drive solutions for customers and communities with stable, scalable, secure production environments. CIQ is the founding support and services partner of Rocky Linux, and the creator of the next generation federated computing stack.

Tungsten Clustering is the only fully-integrated, fully-tested, fully-tested MySQL HA/DR and geo-clustering system that can be used on-premises or in the cloud. It also offers industry-leading, fastest, 24/7 support for Percona Server, MariaDB and MySQL applications that are business-critical. It allows businesses that use business-critical MySQL databases to achieve cost-effective global operations with commercial-grade high availabilty (HA), geographically redundant disaster relief (DR), and geographically distributed multimaster. Tungsten Clustering consists of four core components: data replication, cluster management, and cluster monitoring. Together, they handle all of the messaging and control of your Tungsten MySQL clusters in a seamlessly-orchestrated fashion.

Evidian SafeKit is a robust software solution aimed at achieving high availability for crucial applications across both Windows and Linux systems. This comprehensive tool combines several features, including load balancing, real-time synchronous file replication, automatic failover for applications, and seamless failback after server outages, all packaged within one product. By doing so, it removes the requirement for additional hardware like network load balancers or shared disks, and it also eliminates the need for costly enterprise versions of operating systems and databases. SafeKit's innovative software clustering allows users to establish mirror clusters that ensure real-time data replication and failover, as well as farm clusters that facilitate both load balancing and failover capabilities. Furthermore, it supports advanced configurations like farm plus mirror clusters and active-active clusters, enhancing flexibility and performance. Its unique shared-nothing architecture greatly simplifies the deployment process, making it particularly advantageous for use in remote locations by circumventing the challenges typically associated with shared disk clusters. In summary, SafeKit provides an effective and streamlined solution for maintaining application availability and data integrity across diverse environments.

Failover Clustering in Windows Server (and Azure Local) allows a collection of independent servers to collaborate, enhancing both availability and scalability for clustered roles, which were previously referred to as clustered applications and services. These interconnected nodes utilize a combination of hardware and software solutions, ensuring that if one node encounters a failure, another node seamlessly takes over its responsibilities through an automated failover mechanism. Continuous monitoring of clustered roles ensures that if they cease to function properly, they can be restarted or migrated to uphold uninterrupted service. Additionally, this feature includes support for Cluster Shared Volumes (CSVs), which create a cohesive, distributed namespace and enable reliable shared storage access across all nodes, thereby minimizing potential service interruptions. Common applications of Failover Clustering encompass high‑availability file shares, SQL Server instances, and Hyper‑V virtual machines. This functionality is available on Windows Server versions 2016, 2019, 2022, and 2025, as well as within Azure Local environments, making it a versatile choice for organizations looking to enhance their system resilience. By leveraging Failover Clustering, organizations can ensure their critical applications remain available even in the event of hardware failures.

ConsenSys Quorum empowers businesses to harness the capabilities of Ethereum for their sophisticated blockchain applications. Companies can utilize the Quorum open-source protocol as a foundation and enhance it with product modules from ConsenSys, external providers, or their internal development teams to create high-performance, tailored applications. Our goal is to facilitate the smooth integration of blockchain technology into business operations. Additionally, ConsenSys Quorum allows for the integration of various product modules from ConsenSys, third-party developers, or your own team to develop highly efficient, customizable applications. The framework comprises two open-source initiatives: one developed from Hyperledger Besu and the other from GoQuorum. Furthermore, ConsenSys Quorum Blockchain Service Support offers a subscription model that provides on-demand assistance for developers and businesses, delivering support for the Quorum open-source protocol projects, along with extra tools and updates to ensure the effective operation of your production systems. This comprehensive support is designed to enhance user experience while maximizing the potential of blockchain technology in diverse applications.

AWS ParallelCluster is a free, open-source tool designed for efficient management and deployment of High-Performance Computing (HPC) clusters within the AWS environment. It streamlines the configuration of essential components such as compute nodes, shared filesystems, and job schedulers, while accommodating various instance types and job submission queues. Users have the flexibility to engage with ParallelCluster using a graphical user interface, command-line interface, or API, which allows for customizable cluster setups and oversight. The tool also works seamlessly with job schedulers like AWS Batch and Slurm, making it easier to transition existing HPC workloads to the cloud with minimal adjustments. Users incur no additional costs for the tool itself, only paying for the AWS resources their applications utilize. With AWS ParallelCluster, users can effectively manage their computing needs through a straightforward text file that allows for the modeling, provisioning, and dynamic scaling of necessary resources in a secure and automated fashion. This ease of use significantly enhances productivity and optimizes resource allocation for various computational tasks.

ClusterVisor serves as an advanced system for managing HPC clusters, equipping users with a full suite of tools designed for deployment, provisioning, oversight, and maintenance throughout the cluster's entire life cycle. The system boasts versatile installation methods, including an appliance-based deployment that separates cluster management from the head node, thereby improving overall system reliability. Featuring LogVisor AI, it incorporates a smart log file analysis mechanism that leverages artificial intelligence to categorize logs based on their severity, which is essential for generating actionable alerts. Additionally, ClusterVisor streamlines node configuration and management through a collection of specialized tools, supports the management of user and group accounts, and includes customizable dashboards that visualize information across the cluster and facilitate comparisons between various nodes or devices. Furthermore, the platform ensures disaster recovery by maintaining system images for the reinstallation of nodes, offers an easy-to-use web-based tool for rack diagramming, and provides extensive statistics and monitoring capabilities, making it an invaluable asset for HPC cluster administrators. Overall, ClusterVisor stands as a comprehensive solution for those tasked with overseeing high-performance computing environments.

Displaying only an RTF-Editor in a pop-up does not align with our vision of WYSIWYG; authors require precise control over aspects such as paragraph lengths, line breaks, table dimensions, and image sizes to produce visually appealing content. The system should utilize tags and server-side JavaScript, devoid of any Java within template code. OpenWGA Developer Studio enhances the software development journey by providing all essential tools for the creation, development, deployment, and sharing of OpenWGA web applications. With a suite of advanced technologies—including secure cluster architecture, JMX monitoring, SSO via SPNEGO, CMIS, and an integrated REST-API—OpenWGA Java CMS stands out as the ideal platform for executing business-critical enterprise applications. Additionally, the OpenWGA CMS cluster management framework facilitates not only secure inter-cluster communication and distributed task execution but also incorporates its own session replication system, optimizing resource management for better performance. This comprehensive approach ensures that developers can focus on delivering high-quality applications without the overhead of managing complex backend processes.

Azure Red Hat OpenShift delivers fully managed, highly available OpenShift clusters on demand, with oversight and operation shared between Microsoft and Red Hat. At its foundation lies Kubernetes, which Red Hat OpenShift enhances with premium features, transforming it into a comprehensive platform as a service (PaaS) that significantly enriches the experiences of developers and operators alike. Users can benefit from resilient, fully managed public and private clusters, along with automated operations and seamless over-the-air updates for the platform. The web console also offers an improved user interface, enabling easier building, deploying, configuring, and visualizing of containerized applications and the associated cluster resources. This combination of features makes Azure Red Hat OpenShift an appealing choice for organizations looking to streamline their container management processes.

NVIDIA Base Command Manager provides rapid deployment and comprehensive management for diverse AI and high-performance computing clusters, whether at the edge, within data centers, or across multi- and hybrid-cloud settings. This platform automates the setup and management of clusters, accommodating sizes from a few nodes to potentially hundreds of thousands, and is compatible with NVIDIA GPU-accelerated systems as well as other architectures. It facilitates orchestration through Kubernetes, enhancing the efficiency of workload management and resource distribution. With additional tools for monitoring infrastructure and managing workloads, Base Command Manager is tailored for environments that require accelerated computing, making it ideal for a variety of HPC and AI applications. Available alongside NVIDIA DGX systems and within the NVIDIA AI Enterprise software suite, this solution enables the swift construction and administration of high-performance Linux clusters, thereby supporting a range of applications including machine learning and analytics. Through its robust features, Base Command Manager stands out as a key asset for organizations aiming to optimize their computational resources effectively.

Simplifying Multi-Cloud and Multi-Cluster Kubernetes application deployment and migration is now easier than ever with CAPE. Unlock the full potential of your Kubernetes capabilities with its key features, including Disaster Recovery that allows seamless backup and restore for stateful applications. With robust Data Mobility and Migration, you can securely manage and transfer applications and data across on-premises, private, and public cloud environments. CAPE also facilitates Multi-cluster Application Deployment, enabling stateful applications to be deployed efficiently across various clusters and clouds. Its intuitive Drag & Drop CI/CD Workflow Manager simplifies the configuration and deployment of complex CI/CD pipelines, making it accessible for users at all levels. The versatility of CAPE™ enhances Kubernetes operations by streamlining Disaster Recovery processes, facilitating Cluster Migration and Upgrades, ensuring Data Protection, enabling Data Cloning, and expediting Application Deployment. Moreover, CAPE provides a comprehensive control plane for federating clusters and managing applications and services seamlessly across diverse environments. This innovative tool brings clarity and efficiency to Kubernetes management, ensuring your applications thrive in a multi-cloud landscape.

DxEnterprise is a versatile Smart Availability software that operates across multiple platforms, leveraging its patented technology to support Windows Server, Linux, and Docker environments. This software effectively manages various workloads at the instance level and extends its capabilities to Docker containers as well. DxEnterprise (DxE) is specifically tuned for handling native or containerized Microsoft SQL Server deployments across all platforms, making it a valuable tool for database administrators. Additionally, it excels in managing Oracle databases on Windows systems. Beyond its compatibility with Windows file shares and services, DxE offers support for a wide range of Docker containers on both Windows and Linux, including popular relational database management systems such as Oracle, MySQL, PostgreSQL, MariaDB, and MongoDB. Furthermore, it accommodates cloud-native SQL Server availability groups (AGs) within containers, ensuring compatibility with Kubernetes clusters and diverse infrastructure setups. DxE's seamless integration with Azure shared disks enhances high availability for clustered SQL Server instances in cloud environments, making it an ideal solution for businesses seeking reliability in their database operations. Its robust features position it as an essential asset for organizations aiming to maintain uninterrupted service and optimal performance.

IBM PowerHA SystemMirror is an advanced high availability solution designed to keep critical applications running smoothly by minimizing downtime through intelligent failure detection, automatic failover, and disaster recovery capabilities. This integrated technology supports both IBM AIX and IBM i platforms and offers flexible deployment options including multisite configurations for robust disaster recovery assurance. Users benefit from a simplified management interface that centralizes cluster operations and leverages smart assists to streamline setup and maintenance. PowerHA supports host-based replication techniques such as geographic mirroring and GLVM, enabling failover to private or public cloud environments. The solution tightly integrates IBM SAN storage systems, including DS8000 and Flash Systems, ensuring data integrity and performance. Licensing is based on processor cores with a one-time fee plus a first-year maintenance package, providing cost efficiency. Its highly autonomous design reduces administrative overhead, while continuous monitoring tools keep system health and performance transparent. IBM’s investment in PowerHA reflects its commitment to delivering resilient and scalable IT infrastructure solutions.

Red Hat Advanced Cluster Management for Kubernetes allows users to oversee clusters and applications through a centralized interface, complete with integrated security policies. By enhancing the capabilities of Red Hat OpenShift, it facilitates the deployment of applications, the management of multiple clusters, and the implementation of policies across numerous clusters at scale. This solution guarantees compliance, tracks usage, and maintains uniformity across deployments. Included with Red Hat OpenShift Platform Plus, it provides an extensive array of powerful tools designed to secure, protect, and manage applications effectively. Users can operate from any environment where Red Hat OpenShift is available and can manage any Kubernetes cluster within their ecosystem. The self-service provisioning feature accelerates application development pipelines, enabling swift deployment of both legacy and cloud-native applications across various distributed clusters. Additionally, self-service cluster deployment empowers IT departments by automating the application delivery process, allowing them to focus on higher-level strategic initiatives. As a result, organizations can achieve greater efficiency and agility in their IT operations.

Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).

Rocks is an open-source Linux distribution designed for building computational clusters, grid endpoints, and visualization tiled-display walls with ease for end users. Since its inception in May 2000, the Rocks team has worked to simplify the deployment and management of clusters, focusing on making them easy to deploy, manage, upgrade, and scale effectively. The most recent version, Rocks 7.0, also known as Manzanita, is exclusively a 64-bit release based on CentOS 7.4, incorporating all updates as of December 1, 2017. This distribution comes with a variety of tools, including the Message Passing Interface (MPI), which are essential for converting a collection of computers into a functional cluster. Users can customize their installations by incorporating additional software packages during the installation process using specially provided CDs. Moreover, recent security vulnerabilities known as Spectre and Meltdown impact nearly all hardware, and appropriate mitigations are implemented through operating system updates to enhance security. As a result, Rocks not only facilitates the creation of clusters but also ensures that they remain secure and up-to-date with the latest patches and enhancements.

Efficiently manage multicluster environments for Azure Kubernetes Service (AKS) that involve tasks such as workload distribution, north-south traffic load balancing for incoming requests to various clusters, and coordinated upgrades across different clusters. The fleet cluster offers a centralized management system for overseeing all your clusters on a large scale. A dedicated hub cluster manages the upgrades and the configuration of your Kubernetes clusters seamlessly. Through Kubernetes configuration propagation, you can apply policies and overrides to distribute resources across the fleet's member clusters effectively. The north-south load balancer regulates the movement of traffic among workloads situated in multiple member clusters within the fleet. You can group various Azure Kubernetes Service (AKS) clusters to streamline workflows involving Kubernetes configuration propagation and networking across multiple clusters. Furthermore, the fleet system necessitates a hub Kubernetes cluster to maintain configurations related to placement policies and multicluster networking, thereby enhancing operational efficiency and simplifying management tasks. This approach not only optimizes resource usage but also helps in maintaining consistency and reliability across all clusters involved.

TKE seamlessly integrates with the full spectrum of Kubernetes features and has been optimized for Tencent Cloud's core IaaS offerings, including CVM and CBS. Moreover, Tencent Cloud's Kubernetes-driven products like CBS and CLB facilitate one-click deployments to container clusters for numerous open-source applications, significantly enhancing the efficiency of deployments. With the implementation of TKE, the complexities associated with managing large clusters and the operations of distributed applications are greatly reduced, eliminating the need for specialized cluster management tools or the intricate design of fault-tolerant cluster systems. You simply initiate TKE, outline the tasks you wish to execute, and TKE will handle all cluster management responsibilities, enabling you to concentrate on creating Dockerized applications. This streamlined process allows developers to maximize their productivity and innovate without being bogged down by infrastructure concerns.

Redis for Windows alternative, In Memory Datastore Ready for the most challenging production workloads. Free for testing and development. Redis-compatibility. Memurai's core is based on Redis source code and port to Windows natively. Memurai supports all features that make Redis one of the most popular NoSQL databases, including persistence, replication, transactions and LRU eviction. Redis has many libraries and tools that have been carefully tested to ensure compatibility. You can even replicate data between Memurai or Redis, or both within the same cluster. Integration with Windows infrastructure and workflows is seamless. Memurai seamlessly integrates into Windows best practices, tools, and workflows, regardless of whether it's being used for production or development. Teams of engineers with existing investments in Windows infrastructure will be eligible for this program.

Concentrate on creating applications for processing data streams instead of spending time on infrastructure upkeep. The Managed Service for Apache Kafka takes care of Zookeeper brokers and clusters, handling tasks such as configuring the clusters and performing version updates. To achieve the desired level of fault tolerance, distribute your cluster brokers across multiple availability zones and set an appropriate replication factor. This service continuously monitors the metrics and health of the cluster, automatically replacing any node that fails to ensure uninterrupted service. You can customize various settings for each topic, including the replication factor, log cleanup policy, compression type, and maximum message count, optimizing the use of computing, network, and disk resources. Additionally, enhancing your cluster's performance is as simple as clicking a button to add more brokers, and you can adjust the high-availability hosts without downtime or data loss, allowing for seamless scalability. By utilizing this service, you can ensure that your applications remain efficient and resilient amidst any unforeseen challenges.

Apache Helix serves as a versatile framework for managing clusters, ensuring the automatic oversight of partitioned, replicated, and distributed resources across a network of nodes. This tool simplifies the process of reallocating resources during instances of node failure, system recovery, cluster growth, and configuration changes. To fully appreciate Helix, it is essential to grasp the principles of cluster management. Distributed systems typically operate on multiple nodes to achieve scalability, enhance fault tolerance, and enable effective load balancing. Each node typically carries out key functions within the cluster, such as data storage and retrieval, as well as the generation and consumption of data streams. Once set up for a particular system, Helix functions as the central decision-making authority for that environment. Its design ensures that critical decisions are made with a holistic view, rather than in isolation. Although integrating these management functions directly into the distributed system is feasible, doing so adds unnecessary complexity to the overall codebase, which can hinder maintainability and efficiency. Therefore, utilizing Helix can lead to a more streamlined and manageable system architecture.

Qlustar presents an all-encompassing full-stack solution that simplifies the setup, management, and scaling of clusters while maintaining control and performance. It enhances your HPC, AI, and storage infrastructures with exceptional ease and powerful features. The journey begins with a bare-metal installation using the Qlustar installer, followed by effortless cluster operations that encompass every aspect of management. Experience unparalleled simplicity and efficiency in both establishing and overseeing your clusters. Designed with scalability in mind, it adeptly handles even the most intricate workloads with ease. Its optimization for speed, reliability, and resource efficiency makes it ideal for demanding environments. You can upgrade your operating system or handle security patches without requiring reinstallations, ensuring minimal disruption. Regular and dependable updates safeguard your clusters against potential vulnerabilities, contributing to their overall security. Qlustar maximizes your computing capabilities, ensuring peak efficiency for high-performance computing settings. Additionally, its robust workload management, built-in high availability features, and user-friendly interface provide a streamlined experience, making operations smoother than ever before. This comprehensive approach ensures that your computing infrastructure remains resilient and adaptable to changing needs.

EKS is a community-focused platform that offers support for the latest version of Kubernetes and facilitates native cluster management. It serves as a ready-to-use plugin designed for Tencent Cloud products, enhancing capabilities in areas such as storage, networking, and load balancing. Built upon Tencent Cloud's advanced virtualization technology and robust network architecture, EKS guarantees an impressive 99.95% availability of services. In addition, Tencent Cloud prioritizes the virtual and network isolation of EKS clusters for each user, ensuring enhanced security. Users can define network policies tailored to their needs using tools like security groups and network ACLs. The serverless architecture of EKS promotes optimal resource utilization while minimizing operational costs. With its flexible and efficient auto-scaling features, EKS dynamically adjusts resource consumption based on the current demand. Moreover, EKS offers a variety of solutions tailored to diverse business requirements and seamlessly integrates with numerous Tencent Cloud services, including CBS, CFS, COS, TencentDB products, VPC, and many others, making it a versatile choice for users. This comprehensive approach allows organizations to leverage the full potential of cloud computing while maintaining control over their resources.

Mesos operates on principles similar to those of the Linux kernel, yet it functions at a different abstraction level. This Mesos kernel is deployed on each machine and offers APIs for managing resources and scheduling tasks for applications like Hadoop, Spark, Kafka, and Elasticsearch across entire cloud infrastructures and data centers. It includes native capabilities for launching containers using Docker and AppC images. Additionally, it allows both cloud-native and legacy applications to coexist within the same cluster through customizable scheduling policies. Developers can utilize HTTP APIs to create new distributed applications, manage the cluster, and carry out monitoring tasks. Furthermore, Mesos features an integrated Web UI that allows users to observe the cluster's status and navigate through container sandboxes efficiently. Overall, Mesos provides a versatile and powerful framework for managing diverse workloads in modern computing environments.

Design, oversee, operate, and enhance high-performance computing (HPC) and large-scale compute clusters seamlessly. Implement comprehensive clusters and additional resources, encompassing task schedulers, computational virtual machines, storage solutions, networking capabilities, and caching systems. Tailor and refine clusters with sophisticated policy and governance tools, which include cost management, integration with Active Directory, as well as monitoring and reporting functionalities. Utilize your existing job scheduler and applications without any necessary changes. Empower administrators with complete authority over job execution permissions for users, in addition to determining the locations and associated costs for running jobs. Benefit from integrated autoscaling and proven reference architectures suitable for diverse HPC workloads across various sectors. CycleCloud accommodates any job scheduler or software environment, whether it's proprietary, in-house solutions or open-source, third-party, and commercial software. As your requirements for resources shift and grow, your cluster must adapt accordingly. With scheduler-aware autoscaling, you can ensure that your resources align perfectly with your workload needs while remaining flexible to future changes. This adaptability is crucial for maintaining efficiency and performance in a rapidly evolving technological landscape.

Manage and orchestrate applications seamlessly on a Kubernetes platform that is fully managed, utilizing a centralized SaaS approach for overseeing distributed applications through a unified interface and advanced observability features. Streamline operations by handling deployments uniformly across on-premises, cloud, and edge environments. Experience effortless management and scaling of applications across various Kubernetes clusters, whether at customer locations or within the F5 Distributed Cloud Regional Edge, all through a single Kubernetes-compatible API that simplifies multi-cluster oversight. You can deploy, deliver, and secure applications across different sites as if they were all part of one cohesive "virtual" location. Furthermore, ensure that distributed applications operate with consistent, production-grade Kubernetes, regardless of their deployment sites, which can range from private and public clouds to edge environments. Enhance security with a zero trust approach at the Kubernetes Gateway, extending ingress services backed by WAAP, service policy management, and comprehensive network and application firewall protections. This approach not only secures your applications but also fosters a more resilient and adaptable infrastructure.

Red Hat® Data Grid is a robust, in-memory distributed NoSQL database solution designed for high-performance applications. By enabling your applications to access, process, and analyze data at lightning-fast in-memory speeds, it ensures an exceptional user experience. With its elastic scalability and constant availability, users can quickly retrieve information through efficient, low-latency data processing that leverages RAM and parallel execution across distributed nodes. The system achieves linear scalability by partitioning and distributing data among cluster nodes, while also providing high availability through data replication. Fault tolerance is ensured via cross-datacenter geo-replication and clustering, making recovery from disasters seamless. Furthermore, the platform offers development flexibility and boosts productivity with its versatile and functionally rich NoSQL capabilities. Comprehensive data security features, including encryption and role-based access, are also included. Notably, the release of Data Grid 7.3.10 brings important security enhancements to address a known CVE. It is crucial for users to upgrade any existing Data Grid 7.3 installations to version 7.3.10 promptly to maintain security and performance standards. Regular updates ensure that the system remains resilient and up-to-date with the latest technological advancements.

Slurm Workload Manager, which was previously referred to as Simple Linux Utility for Resource Management (SLURM), is an open-source and cost-free job scheduling and cluster management system tailored for Linux and Unix-like operating systems. Its primary function is to oversee computing tasks within high-performance computing (HPC) clusters and high-throughput computing (HTC) settings, making it a popular choice among numerous supercomputers and computing clusters globally. As technology continues to evolve, Slurm remains a critical tool for researchers and organizations requiring efficient resource management.

Dataproc enhances the speed, simplicity, and security of open source data and analytics processing in the cloud. You can swiftly create tailored OSS clusters on custom machines to meet specific needs. Whether your project requires additional memory for Presto or GPUs for machine learning in Apache Spark, Dataproc facilitates the rapid deployment of specialized clusters in just 90 seconds. The platform offers straightforward and cost-effective cluster management options. Features such as autoscaling, automatic deletion of idle clusters, and per-second billing contribute to minimizing the overall ownership costs of OSS, allowing you to allocate your time and resources more effectively. Built-in security measures, including default encryption, guarantee that all data remains protected. With the JobsAPI and Component Gateway, you can easily manage permissions for Cloud IAM clusters without the need to configure networking or gateway nodes, ensuring a streamlined experience. Moreover, the platform's user-friendly interface simplifies the management process, making it accessible for users at all experience levels.

Oracle's Container Engine for Kubernetes (OKE) serves as a managed container orchestration solution that significantly minimizes both the time and expenses associated with developing contemporary cloud-native applications. In a departure from many competitors, Oracle Cloud Infrastructure offers OKE as a complimentary service that operates on high-performance and cost-efficient compute shapes. DevOps teams benefit from the ability to utilize unaltered, open-source Kubernetes, enhancing application workload portability while streamlining operations through automated updates and patch management. Users can initiate the deployment of Kubernetes clusters along with essential components like virtual cloud networks, internet gateways, and NAT gateways with just a single click. Furthermore, the platform allows for the automation of Kubernetes tasks via a web-based REST API and a command-line interface (CLI), covering all aspects from cluster creation to scaling and maintenance. Notably, Oracle does not impose any fees for managing clusters, making it an attractive option for developers. Additionally, users can effortlessly and swiftly upgrade their container clusters without experiencing any downtime, ensuring they remain aligned with the latest stable Kubernetes version. This combination of features positions Oracle's offering as a robust solution for organizations looking to optimize their cloud-native development processes.

Proxmox VE serves as a comprehensive open-source solution for enterprise virtualization, seamlessly combining KVM hypervisor and LXC container technology, along with features for software-defined storage and networking, all within one cohesive platform. It also simplifies the management of high availability clusters and disaster recovery tools through its user-friendly web management interface, making it an ideal choice for businesses seeking robust virtualization capabilities. Furthermore, Proxmox VE's integration of these functionalities enhances operational efficiency and flexibility for IT environments.

IBM Tivoli System Automation for Multiplatforms (SA MP) is a powerful cluster management tool that enables seamless transition of users, applications, and data across different database systems within a cluster. It automates the oversight of IT resources, including processes, file systems, and IP addresses, ensuring that these components are managed efficiently. Tivoli SA MP establishes a framework for automated resource availability management, allowing for oversight of any software for which control scripts can be crafted. Moreover, it can manage network interface cards by utilizing floating IP addresses, which are assigned to any NIC with the necessary permissions. This functionality means that Tivoli SA MP can dynamically assign these virtual IP addresses among the accessible network interfaces, enhancing the flexibility of network management. In scenarios involving a single-partition Db2 environment, a solitary Db2 instance operates on the server, with direct access to its own data as well as the databases it oversees, creating a streamlined operational setup. This integration of automation not only increases efficiency but also reduces downtime, ultimately leading to a more reliable IT infrastructure.

HPE Performance Cluster Manager (HPCM) offers a cohesive system management solution tailored for Linux®-based high-performance computing (HPC) clusters. This software facilitates comprehensive provisioning, management, and monitoring capabilities for clusters that can extend to Exascale-sized supercomputers. HPCM streamlines the initial setup from bare-metal, provides extensive hardware monitoring and management options, oversees image management, handles software updates, manages power efficiently, and ensures overall cluster health. Moreover, it simplifies the scaling process for HPC clusters and integrates seamlessly with numerous third-party tools to enhance workload management. By employing HPE Performance Cluster Manager, organizations can significantly reduce the administrative burden associated with HPC systems, ultimately leading to lowered total ownership costs and enhanced productivity, all while maximizing the return on their hardware investments. As a result, HPCM not only fosters operational efficiency but also supports organizations in achieving their computational goals effectively.

Designed for IT professionals, Quorum onQ is a server backup solution that helps automate disaster recovery testing, manage data deduplication, identify and recover from malware/viruses, and more.

Edka streamlines the establishment of a production-ready Platform as a Service (PaaS) using standard cloud virtual machines and Kubernetes, significantly minimizing the manual labor needed to manage applications on Kubernetes by offering preconfigured open-source add-ons that effectively transform a Kubernetes cluster into a comprehensive PaaS solution. To enhance Kubernetes operations, Edka organizes them into distinct layers: Layer 1: Cluster provisioning – A user-friendly interface that allows for the effortless creation of a k3s-based cluster with just one click and default settings. Layer 2: Add-ons – A convenient one-click deployment option for essential components like metrics-server, cert-manager, and various operators, all preconfigured for use with Hetzner, requiring no additional setup. Layer 3: Applications – User interfaces with minimal configurations tailored for applications that utilize the aforementioned add-ons. Layer 4: Deployments – Edka ensures automatic updates to deployments in accordance with semantic versioning rules, offering features such as instant rollbacks, autoscaling capabilities, persistent volume management, secret/environment imports, and quick public accessibility for applications. Furthermore, this structure allows developers to focus on building their applications rather than managing the underlying infrastructure.

Rocket iCluster's high availability and disaster recovery (HA/DR) solutions guarantee seamless operation for your IBM i applications, ensuring consistent access by actively monitoring, detecting, and automatically rectifying replication issues. The iCluster's administration console, which supports both traditional green screen and contemporary web interfaces, provides real-time monitoring of events. By implementing real-time, fault-tolerant, object-level replication, Rocket iCluster minimizes downtime caused by unforeseen IBM i system failures. Should an outage occur, you can quickly activate a “warm” mirror of a clustered IBM i system within minutes. The disaster recovery capabilities of iCluster create a high-availability environment, facilitating simultaneous access to both master and replicated data for business applications. This configuration not only enhances system resilience but also allows for the delegation of essential business operations, such as running reports, executing queries, and managing ETL, EDI, and web tasks, from the secondary system without compromising the primary system's performance. Such flexibility ultimately leads to improved operational efficiency and reliability across your business processes.

Hazelcast Jet offers enhanced application performance at scale, making it easier than ever to develop lightning-fast applications. Our platform provides access to a scalable, shared RAM pool across multiple computers in a cluster. As the industry's most thorough in-memory computing solution, it combines the fastest in-memory data grid with cutting-edge high-speed event processing, all accessible through the cloud. Hazelcast empowers you to create new data-enabled applications that can drive significant business impact, provided they meet the urgent demands of modern enterprises. With Hazelcast, you can utilize the shared RAM pool across a cluster to ensure your applications run at peak speed. The distributed architecture of Hazelcast guarantees redundancy, ensuring continuous cluster uptime and the availability of data for even the most resource-intensive applications. As capacity scales smoothly in response to demand, performance and availability remain uncompromised. Additionally, Hazelcast's in-memory solutions work alongside traditional databases, offering speeds that are exponentially greater. Ultimately, Hazelcast enables organizations to harness the full potential of real-time data processing, positioning them for success in a competitive landscape.

TrinityX is a cluster management solution that is open source and developed by ClusterVision, aimed at ensuring continuous monitoring for environments focused on High-Performance Computing (HPC) and Artificial Intelligence (AI). It delivers a robust support system that adheres to service level agreements (SLAs), enabling researchers to concentrate on their work without the burden of managing intricate technologies such as Linux, SLURM, CUDA, InfiniBand, Lustre, and Open OnDemand. By providing an easy-to-use interface, TrinityX simplifies the process of cluster setup, guiding users through each phase to configure clusters for various applications including container orchestration, conventional HPC, and InfiniBand/RDMA configurations. Utilizing the BitTorrent protocol, it facilitates the swift deployment of AI and HPC nodes, allowing for configurations to be completed in mere minutes. Additionally, the platform boasts a detailed dashboard that presents real-time data on cluster performance metrics, resource usage, and workload distribution, which helps users quickly identify potential issues and optimize resource distribution effectively. This empowers teams to make informed decisions that enhance productivity and operational efficiency within their computational environments.

Welcome to the OpenHPC website, a platform born from a collaborative community effort aimed at unifying various essential components necessary for the deployment and management of High Performance Computing (HPC) Linux clusters. This initiative encompasses tools for provisioning, resource management, I/O clients, development utilities, and a range of scientific libraries, all designed with HPC integration as a priority. The packages offered by OpenHPC are specifically pre-built to serve as reusable building blocks for the HPC community, ensuring efficiency and accessibility. As the community evolves, there are plans to define and create abstraction interfaces among key components to further improve modularity and interchangeability within the ecosystem. Representing a diverse array of stakeholders including software vendors, equipment manufacturers, research institutions, and supercomputing facilities, this community is dedicated to the seamless integration of widely used components that are available for open-source distribution. By working together, they aim to foster innovation and collaboration in the field of High Performance Computing. This collective effort not only enhances existing technologies but also paves the way for future advancements in the HPC landscape.

The latest iterations of Docker feature swarm mode, which allows for the native management of a cluster known as a swarm, composed of multiple Docker Engines. Using the Docker CLI, one can easily create a swarm, deploy various application services within it, and oversee the swarm's operational behaviors. The Docker Engine integrates cluster management seamlessly, enabling users to establish a swarm of Docker Engines for service deployment without needing any external orchestration tools. With a decentralized architecture, the Docker Engine efficiently manages node role differentiation at runtime rather than at deployment, allowing for the simultaneous deployment of both manager and worker nodes from a single disk image. Furthermore, the Docker Engine adopts a declarative service model, empowering users to specify the desired state of their application's service stack comprehensively. This streamlined approach not only simplifies the deployment process but also enhances the overall efficiency of managing complex applications.

In summary, OKD represents a highly opinionated version of Kubernetes. At its core, Kubernetes consists of various software and architectural patterns designed to manage applications on a large scale. While we incorporate some features directly into Kubernetes through modifications, the majority of our enhancements come from "preinstalling" a wide array of software components known as Operators into the deployed cluster. These Operators manage the over 100 essential elements of our platform, including OS upgrades, web consoles, monitoring tools, and image-building functionalities. OKD is versatile and suitable for deployment across various environments, from cloud infrastructures to on-premise hardware and edge computing scenarios. The installation process is automated for certain platforms, like AWS, while also allowing for customization in other environments, such as bare metal or lab settings. OKD embraces best practices in development and technology, making it an excellent platform for technologists and students alike to explore, innovate, and engage with the broader cloud ecosystem. Furthermore, as an open-source project, it encourages community contributions and collaboration, fostering a rich environment for learning and growth.

SUSE Rancher Prime meets the requirements of DevOps teams involved in Kubernetes application deployment as well as IT operations responsible for critical enterprise services. It is compatible with any CNCF-certified Kubernetes distribution, while also providing RKE for on-premises workloads. In addition, it supports various public cloud offerings such as EKS, AKS, and GKE, and offers K3s for edge computing scenarios. The platform ensures straightforward and consistent cluster management, encompassing tasks like provisioning, version oversight, visibility and diagnostics, as well as monitoring and alerting, all backed by centralized audit capabilities. Through SUSE Rancher Prime, automation of processes is achieved, and uniform user access and security policies are enforced across all clusters, regardless of their deployment environment. Furthermore, it features an extensive catalog of services designed for the development, deployment, and scaling of containerized applications, including tools for app packaging, CI/CD, logging, monitoring, and implementing service mesh solutions, thereby streamlining the entire application lifecycle. This comprehensive approach not only enhances operational efficiency but also simplifies the management of complex environments.

IBM Spectrum LSF Suites serves as a comprehensive platform for managing workloads and scheduling jobs within distributed high-performance computing (HPC) environments. Users can leverage Terraform-based automation for the seamless provisioning and configuration of resources tailored to IBM Spectrum LSF clusters on IBM Cloud. This integrated solution enhances overall user productivity and optimizes hardware utilization while effectively lowering system management expenses, making it ideal for mission-critical HPC settings. Featuring a heterogeneous and highly scalable architecture, it accommodates both traditional high-performance computing tasks and high-throughput workloads. Furthermore, it is well-suited for big data applications, cognitive processing, GPU-based machine learning, and containerized workloads. With its dynamic HPC cloud capabilities, IBM Spectrum LSF Suites allows organizations to strategically allocate cloud resources according to workload demands, supporting all leading cloud service providers. By implementing advanced workload management strategies, including policy-driven scheduling that features GPU management and dynamic hybrid cloud capabilities, businesses can expand their capacity as needed. This flexibility ensures that companies can adapt to changing computational requirements while maintaining efficiency.

Batch facilitates the execution of applications across workstations and clusters, making it simple to enable your executable files and scripts for cloud scalability. It operates a queue system designed to handle tasks you wish to run, effectively executing your applications as needed. To leverage Batch effectively, consider the data that must be uploaded to the cloud for processing, how that data should be allocated across various tasks, the necessary parameters for each job, and the commands required to initiate the processes. Visualize this as an assembly line where different applications interact seamlessly. With Batch, you can efficiently share data across different stages and oversee the entire execution process. It operates on a demand-driven basis rather than adhering to a fixed schedule, allowing customers to run their cloud jobs whenever necessary. Additionally, it's vital to manage user access to Batch and regulate resource utilization while ensuring compliance with requirements like data encryption. Comprehensive monitoring features are in place to provide insight into the system's status and to help quickly identify any issues that may arise, ensuring smooth operation and optimal performance. Furthermore, the flexibility in resource scaling allows for efficient handling of varying workloads, making Batch an essential tool for cloud-enabled applications.