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Gigamon Partners with Splunk

Gigamon announced a strategic partnership with Splunk, a Cisco company, to help enterprises unlock greater value from distributed data. 

By combining the Gigamon Deep Observability Pipeline with Splunk’s Federated Search, a core component of the Cisco Data Fabric powered by the Splunk Cloud Platform, organizations can access and analyze high-value telemetry wherever it resides, eliminating the need to centralize or duplicate data.

Together, Gigamon and Splunk eliminate this tradeoff by enabling a more efficient approach to accessing, managing, and operationalizing distributed data.

The Gigamon Deep Observability Pipeline transforms raw network traffic into high-fidelity, actionable telemetry by extracting and enriching application metadata across North-South and East-West traffic flows. Splunk Federated Search extends this value by enabling teams to query and analyze distributed datasets in place, delivering unified visibility across environments without unnecessary data movement.

“Organizations today need deeper, more connected visibility across increasingly distributed environments,” said Seth Brickman, vice president of Product Management for the Splunk Platform, Cisco. “By combining Splunk’s Federated Search capabilities with network telemetry from Gigamon, we’re helping customers gain richer operational and security insights while reducing the cost and complexity of managing large volumes of data. Together, we’re delivering a more flexible and AI-ready approach to data management.”

“As data volumes continue to grow across hybrid cloud and AI-driven environments, organizations need a smarter way to manage telemetry without increasing cost or complexity,” said Srinivas Chakravarty, vice president, cloud ecosystem, at Gigamon. “Together, the Gigamon Deep Observability Pipeline and Splunk Federated Search help customers transform raw network traffic into high-fidelity, actionable telemetry and access it wherever it resides. This approach reduces unnecessary data movement and ingestion costs while improving visibility and enabling earlier threat detection across security and observability workflows.”

At the core of this partnership is a commitment to customer choice. Organizations can determine where their data is stored, including Splunk Cloud Platform indexes, Amazon S3, or Azure Blob Storage, and other third-party repositories, while maintaining seamless, federated access across all environments. This flexibility allows enterprises to balance performance, cost, compliance, and data sovereignty requirements without sacrificing visibility or analytics capabilities.

How the Combined Gigamon and Splunk Solution Helps Organizations:

  • Gain deeper visibility across encrypted, lateral, and hybrid cloud traffic
  • Access distributed data without centralized movement or duplication
  • Reduce cost and complexity through intelligent telemetry filtering and enrichment
  • Enable earlier threat detection and faster security investigations
  • Strengthen compliance readiness with scalable monitoring and reporting

The Gigamon Federated Search App includes pre-built processing pipelines for Splunk Edge and Ingest Processor, federated search templates, and unified dashboards that simplify how organizations analyze and operationalize distributed telemetry.

By integrating the Gigamon Deep Observability Pipeline with Splunk Edge and Ingest Processors, customers can process, route, filter, and enrich telemetry closer to the source, reducing unnecessary data movement while ensuring that only high-value telemetry is stored, searched, and analyzed.

The solution is available now to joint customers.

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Gigamon Partners with Splunk

Gigamon announced a strategic partnership with Splunk, a Cisco company, to help enterprises unlock greater value from distributed data. 

By combining the Gigamon Deep Observability Pipeline with Splunk’s Federated Search, a core component of the Cisco Data Fabric powered by the Splunk Cloud Platform, organizations can access and analyze high-value telemetry wherever it resides, eliminating the need to centralize or duplicate data.

Together, Gigamon and Splunk eliminate this tradeoff by enabling a more efficient approach to accessing, managing, and operationalizing distributed data.

The Gigamon Deep Observability Pipeline transforms raw network traffic into high-fidelity, actionable telemetry by extracting and enriching application metadata across North-South and East-West traffic flows. Splunk Federated Search extends this value by enabling teams to query and analyze distributed datasets in place, delivering unified visibility across environments without unnecessary data movement.

“Organizations today need deeper, more connected visibility across increasingly distributed environments,” said Seth Brickman, vice president of Product Management for the Splunk Platform, Cisco. “By combining Splunk’s Federated Search capabilities with network telemetry from Gigamon, we’re helping customers gain richer operational and security insights while reducing the cost and complexity of managing large volumes of data. Together, we’re delivering a more flexible and AI-ready approach to data management.”

“As data volumes continue to grow across hybrid cloud and AI-driven environments, organizations need a smarter way to manage telemetry without increasing cost or complexity,” said Srinivas Chakravarty, vice president, cloud ecosystem, at Gigamon. “Together, the Gigamon Deep Observability Pipeline and Splunk Federated Search help customers transform raw network traffic into high-fidelity, actionable telemetry and access it wherever it resides. This approach reduces unnecessary data movement and ingestion costs while improving visibility and enabling earlier threat detection across security and observability workflows.”

At the core of this partnership is a commitment to customer choice. Organizations can determine where their data is stored, including Splunk Cloud Platform indexes, Amazon S3, or Azure Blob Storage, and other third-party repositories, while maintaining seamless, federated access across all environments. This flexibility allows enterprises to balance performance, cost, compliance, and data sovereignty requirements without sacrificing visibility or analytics capabilities.

How the Combined Gigamon and Splunk Solution Helps Organizations:

  • Gain deeper visibility across encrypted, lateral, and hybrid cloud traffic
  • Access distributed data without centralized movement or duplication
  • Reduce cost and complexity through intelligent telemetry filtering and enrichment
  • Enable earlier threat detection and faster security investigations
  • Strengthen compliance readiness with scalable monitoring and reporting

The Gigamon Federated Search App includes pre-built processing pipelines for Splunk Edge and Ingest Processor, federated search templates, and unified dashboards that simplify how organizations analyze and operationalize distributed telemetry.

By integrating the Gigamon Deep Observability Pipeline with Splunk Edge and Ingest Processors, customers can process, route, filter, and enrich telemetry closer to the source, reducing unnecessary data movement while ensuring that only high-value telemetry is stored, searched, and analyzed.

The solution is available now to joint customers.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...