4.5 out of 5 stars
(125 Ratings)
Bacula Enterprise provides backup and recovery for enterprise, HPC, defense, government and research environments. Developed by Switzerland-based Bacula Systems, it protects physical, virtual, container, database, SaaS and cloud workloads from one platform.
Support data sovereignty with on-premises deployment without mandatory cloud control planes, call-home licensing or continuous internet access. Retain control over backup location, infrastructure, encryption keys and recovery procedures.
Strengthen ransomware resilience with physically air-gapped tape, offline copies, immutable storage options, encryption, MFA, access controls and file integrity verification.
For petabyte-scale HPC datasets, HPC Accelerator, parallel processing and Lustre, GPFS and ZFS integrations help protect large file populations. Use disk, tape, object storage and cloud targets, with no licensing charges based on protected data volume.
VM coverage includes VMware vSphere/ESXi, Hyper-V, Proxmox, Nutanix AHV, XenServer, XCP-ng, KVM, QEMU, Libvirt, Red Hat Virtualization, OpenStack, Amazon EC2 and Azure VMs. Protect Kubernetes, OpenShift and Docker containers.
Database coverage includes Oracle, SQL Server, PostgreSQL, MySQL, Percona for MySQL, MariaDB, SAP HANA, Sybase ASE, IBM Db2, MongoDB and InterSystems IRIS, plus Amazon RDS integration. Other workloads include Hadoop HDFS, Microsoft 365 and Google Workspace.
BWeb administration, scheduling, monitoring, reporting, deduplication and compression simplify operations. Restore files, application data, VMs and supported bare-metal systems.
Its open-core architecture combines Bacula's open-source foundation with enterprise-only plugins, security features, management tools and commercial support.
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Amazon EC2 UltraClusters
Amazon EC2 UltraClusters allow for the scaling of thousands of GPUs or specialized machine learning accelerators like AWS Trainium, granting users immediate access to supercomputing-level performance. This service opens the door to supercomputing for developers involved in machine learning, generative AI, and high-performance computing, all through a straightforward pay-as-you-go pricing structure that eliminates the need for initial setup or ongoing maintenance expenses. Comprising thousands of accelerated EC2 instances placed within a specific AWS Availability Zone, UltraClusters utilize Elastic Fabric Adapter (EFA) networking within a petabit-scale nonblocking network. Such an architecture not only ensures high-performance networking but also facilitates access to Amazon FSx for Lustre, a fully managed shared storage solution based on a high-performance parallel file system that enables swift processing of large datasets with sub-millisecond latency. Furthermore, EC2 UltraClusters enhance scale-out capabilities for distributed machine learning training and tightly integrated HPC tasks, significantly decreasing training durations while maximizing efficiency. This transformative technology is paving the way for groundbreaking advancements in various computational fields.
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TrinityX
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.
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