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Savvius Insight 2.0 Introduced

Savvius unveiled Savvius Insight 2.0, incorporating the full ELK (Elasticsearch, Logstash, and Kibana) stack for native reporting features that provide key network information and trends in real-time, browser-based dashboards.

Savvius Insight enables anyone responsible for 1G networks in most small-to-medium sized businesses (SMBs) and remote enterprise offices to visualize, detect, pinpoint, diagnose, and manage network issues with a single low-cost solution that includes Savvius Omnipeek software.

Placed inline to an Internet connection, Savvius Insight 2.0 automatically begins collecting network statistics and trend data for immediate display and long-term reporting. Users can instantly access in-depth analytics on network activity such as:

- Bandwidth Utilization – monitor average and maximum bandwidth consumption rates to make key purchasing and management decisions.

- Application Response Times – examine average, minimum, and maximum response times for critical network applications to identify productivity correlations and ensure SLAs with service providers.

- Flow Volume – review overall network traffic flows as well as specific conversations between connected devices.

- Packet Types – filter and analyze network traffic by network protocols.

- Expert Events – real-time analysis of key network operations including TCP events, IP events, ICMP events, DNS errors, and slow server response times to identify spikes and trends.

- Security Events – identify the presence of authentication failures, dictionary attack events, flooding, and other indicators of potential network security issues.

"Savvius Insight 2.0 is unique because it makes the packet analytics engine that Savvius developed for major data centers and large enterprises available to SMBs, MSPs and distributed enterprises in a small, fanless, all-in-one appliance," said Jay Botelho, Director of Product Management at Savvius. "Users of Savvius Insight want to know exactly what is going on with their network, and now, with ELK, they can do so with beautifully-designed web-based dashboards. In addition, the included Savvius Omnipeek software provides detailed root-cause analysis whenever it’s needed."

Savvius Insight 2.0 also has the ability to forward data to a remote ELK or Splunk server, aggregating the data from multiple Insight appliances into a single database for long-term reporting and centralized data access across multiple locations. Savvius Insight has 128 gigabytes of storage that holds days, weeks or months of network data, depending on network traffic and which analytics are captured and stored. Version 2.0 of Insight also adds Savvius’ popular Compass network data visualization dashboard, and its operating system has been upgraded to Ubuntu 14.04.

Savvius Insight 2.0 is available now on Amazon and through resellers.

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Savvius Insight 2.0 Introduced

Savvius unveiled Savvius Insight 2.0, incorporating the full ELK (Elasticsearch, Logstash, and Kibana) stack for native reporting features that provide key network information and trends in real-time, browser-based dashboards.

Savvius Insight enables anyone responsible for 1G networks in most small-to-medium sized businesses (SMBs) and remote enterprise offices to visualize, detect, pinpoint, diagnose, and manage network issues with a single low-cost solution that includes Savvius Omnipeek software.

Placed inline to an Internet connection, Savvius Insight 2.0 automatically begins collecting network statistics and trend data for immediate display and long-term reporting. Users can instantly access in-depth analytics on network activity such as:

- Bandwidth Utilization – monitor average and maximum bandwidth consumption rates to make key purchasing and management decisions.

- Application Response Times – examine average, minimum, and maximum response times for critical network applications to identify productivity correlations and ensure SLAs with service providers.

- Flow Volume – review overall network traffic flows as well as specific conversations between connected devices.

- Packet Types – filter and analyze network traffic by network protocols.

- Expert Events – real-time analysis of key network operations including TCP events, IP events, ICMP events, DNS errors, and slow server response times to identify spikes and trends.

- Security Events – identify the presence of authentication failures, dictionary attack events, flooding, and other indicators of potential network security issues.

"Savvius Insight 2.0 is unique because it makes the packet analytics engine that Savvius developed for major data centers and large enterprises available to SMBs, MSPs and distributed enterprises in a small, fanless, all-in-one appliance," said Jay Botelho, Director of Product Management at Savvius. "Users of Savvius Insight want to know exactly what is going on with their network, and now, with ELK, they can do so with beautifully-designed web-based dashboards. In addition, the included Savvius Omnipeek software provides detailed root-cause analysis whenever it’s needed."

Savvius Insight 2.0 also has the ability to forward data to a remote ELK or Splunk server, aggregating the data from multiple Insight appliances into a single database for long-term reporting and centralized data access across multiple locations. Savvius Insight has 128 gigabytes of storage that holds days, weeks or months of network data, depending on network traffic and which analytics are captured and stored. Version 2.0 of Insight also adds Savvius’ popular Compass network data visualization dashboard, and its operating system has been upgraded to Ubuntu 14.04.

Savvius Insight 2.0 is available now on Amazon and through resellers.

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.