VIAVI Solutions announced availability of the Xgig 1000 24 Gbps SAS Analyzer, a solution for validating and ensuring 24G Serial Attached SCSI (SAS) network performance in a fully integrated, stand-alone system.
This versatile storage network testing solution helps equipment manufacturers improve R&D efforts, as well as supporting data center deployment and troubleshooting in the field.
VIAVI’s Xgig 1000 24 Gbps Analyzer enables simultaneous analysis and error injection for SAS protocol traffic at all layers of the stack, delivering one of the most powerful monitoring and analysis systems available for SAS applications. The system not only captures and analyzes live data traffic to verify performance, it also provides traffic jammer capabilities to simulate errors in real time for testing the responsiveness of error recovery processes.
The latest SAS 4.0 protocol standard introduces significant technological changes in response to demands for increased storage capacities and faster data speeds, supporting a number of important optimizations for solid-state drives. This new industry standard doubles the effective bandwidth previously possible, from 12 to 24 Gbps. Network equipment manufacturers need optimized testing capabilities to ensure their next-generation 24 Gbps storage systems do not become a bottleneck.
“The ability to test network storage equipment and identify how and when a system fails is key to developing the most robust, high-performance solutions possible for data-intensive applications, ranging from unified communications and large internet content providers to gaming platforms,” said Tom Fawcett, VP and GM, Lab and Production Business Unit, VIAVI Solutions. “We have refined the Xgig 1000 24 Gbps Analyzer to address the specific characteristics of the SAS 4.0 protocol at high speeds so that every data bit is passed through exactly as it was received, and allowing users to see the same signal that the device under test sees.”
While other test and troubleshooting systems can involve complicated, repetitive processes, the Xgig 1000 24 Gbps Analyzer offers users the option to define automation scripts, from simple commands to complex regression test libraries. Analyzer and jammer functions can be managed easily by toggling software switches in the Maestro user interface.
The Xgig 1000 24 Gbps SAS Analyzer blade chassis supports 24/12/6/3 Gbps SAS with dual mini-SAS HD receptacles, allowing bidirectional analysis of single and wide-port SAS links. A design with front-to-back airflow allows for standing the chassis on end, minimizing the overall footprint in desktop testing.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...