Gigamon announced its Nutanix Ready validation for Gigamon Hawk.
Gigamon Hawk is an elastic visibility and analytics fabric for all data-in-motion across the hybrid cloud. Hawk delivers continuous visibility across the hybrid cloud, dramatically reduces manual intervention with visibility-as-code automation and provides both on-premises and cloud tools with contextualized network information otherwise not possible.
Infrastructure complexity has grown exponentially in recent years, resulting in a foundational gap in visibility across hybrid cloud environments. Utilizing a simple interface with built-in management and reporting, Gigamon Hawk closes this gap by radically simplifying hybrid cloud adoption, eliminating security and compliance blind spots, and helping ensure a positive customer experience. In addition to being validated as a Nutanix Ready AHV solution, Hawk is integrated with leading cloud platforms and tools, providing a unified view across any hybrid infrastructure.
“Security is at the top of most customers’ minds, especially as enterprises continue to embrace the business and technical value provided by hybrid clouds” said Prasad Athawale, VP, Business Development at Nutanix. “Increasing network visibility through products such as Nutanix Flow and Gigamon Hawk, is essential to customers’ ability to secure their data and maintain application performance and availability in hybrid cloud environments.”
“As cloud adoption becomes business critical, it is more important than ever for our customers to ensure the security, optimization and scalability of their IT investments. Working in lockstep with partners such as Nutanix, we enable end-to-end solutions that deliver an immediate ROI,” said Michael Dickman, Chief Product Officer at Gigamon. “With Hawk, our partners and customers can feel confident in their ability move mission critical workloads to the cloud.”
The Latest
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...