AdRem NetCrunch
NetCrunch is a powerful, scalable, all-in-one network monitoring system built for modern IT environments. It supports agentless monitoring of thousands of devices, covering SNMP, servers, virtualization (VMware, Hyper-V), cloud (AWS, Azure, GCP), traffic flows (NetFlow, sFlow), logs, and custom data via REST or scripts.
With 670+ monitoring packs and dynamic views, it automates discovery, configuration, alerting, and automates self-healing actions for efficient remote remediation in response to alerts. Its node-based licensing eliminates sensor sprawl and complexity, providing a clear, cost-effective path to scale.
Real-time dashboards, policy-driven setup, advanced alert tuning and 40+ alert actions including remote script execution, service restart, process kill or device reboot-make NetCrunch ideal for organizations replacing legacy tools like PRTG, SolarWinds, or WhatsUp Gold. Fast to deploy and future-proof.
Can be installed on-prem, self-hosted in the cloud, or mixed.
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PeerGFS
One Solution to Simplify File Management and Orchestration Across Edge, Data Center, and Cloud Storage
PeerGFS is a software-only solution developed to solve file management/file replication challenges in multi-site, multi-platform, and hybrid multi-cloud environments.
With over 25 years of experience in geographically dispersed file replication, we help organizations:
- Improve availability through Active-Active data centers (on-premises and/or in the cloud)
- Protect data at the Edge with Continuous Data Protection to the data center
- Increase productivity for distributed project teams with fast, local access to file data
Today’s always-on world requires real-time data infrastructure with 24x7x365 availability.
PeerGFS works with the storage systems you already have deployed and support:
- High volume data replication between well-connected data centers
- Wide area networks with limited bandwidth and higher latency
PeerGFS is easy to install and manage.
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NVIDIA RAPIDS
The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. Accelerate your Python data science toolchain with minimal code changes and no new tools to learn. Increase machine learning model accuracy by iterating on models faster and deploying them more frequently.
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