
Gigamon introduced Gigamon Application Metadata Intelligence (AMI), which delivers unprecedented application visibility to an organization’s tools ecosystem.
Gigamon AMI provides over 5,000 applications-related attributes extracted from network packet data, allowing NetOps, SecOps and analytics tools to quickly identify and troubleshoot performance and security trouble spots.
Gigamon AMI includes pre-built connectors with leading analytics tools such as Splunk Enterprise and IBM QRadar, enabling IT to easily leverage the power of metadata. Included are pre-configured templates that simplify integration with common use cases such as video quality monitoring, user/session tracking and International Mobile Equipment Identity (IMEI) devices. Furthermore, out-of-the box integration is available with a growing ecosystem of third-party tools, including FireEye, Plixer, Viavi, Flowmon and WitFoo.
Gigamon AMI centralizes network visibility and extracts the context around applications and protocols. Use cases of Gigamon AMI include:
- Network Performance: Troubleshooting server and file access performance issues using error resource codes
- Application Performance: Monitoring roundtrip SQL query time to and from a Mongo DB instance
- Operational Technology (OT) Communications: Isolating traffic and extracting intelligence for OT-related communications to help tools better focus on machine-to-machine communications for specialized use cases, such as healthcare (HL7), finance (OpenRTB) and Industrial Control Systems (SCADA)
- Security and Threat Detection: More precise identification of Command and Control attacks, identification of weak or old cyphers used for encryption, out of date certificates
“An exceptional application user experience, paired with strong security, is critical for the success of any digital transformation initiative. With Application Metadata Intelligence, organizations now have the contextual data needed to quickly pinpoint potential threats and resolve network or application performance issues that can impact the user experience,” said Ananda Rajagopal, VP of Products, Gigamon. “The unparalleled depth of metadata elements, as well as the ease and convenience of integrations with leading analytics providers, enables our customers worldwide to run fast and stay secure in today’s complex, digital ecosystem.”
Solution providers can take advantage of the Gigamon Metadata Empowered Partner Program for rapid AMI integration, with support ranging from access to a development environment to development support and certification. Partners can then leverage the Gigamon Catalyst Program, which includes joint collateral, demo presence at labs and events, and direct access to Gigamon’s extensive field and channel organizations that cover over 3,300 large businesses and global government agencies.
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 ...