Martyn CrewTL; DR
Logs, metrics, and traces are essential, but they miss what is happening in real time across hybrid and multi-cloud environments. Network-derived telemetry from Gigamon adds application metadata, packets, and flows to the observability tools you already use, so teams can separate application issues from network issues, cut troubleshooting time, and validate fixes with hard evidence. By enriching traffic with application and environmental metadata, the Gigamon Deep Observability Pipeline helps you see the network—and solve the problem—with greater speed and precision.
See the Network. Solve the Problem.
Modern applications rarely fail in one place. A user may experience a slow transaction, an intermittent error, or a complete outage, and blame the network while the underlying cause may well sit somewhere between the application, host, cloud service, container, and the network.
Network telemetry for observability gives teams another source of evidence. It shows what is happening in data in motion and adds context that logs, metrics, and traces may not capture. By delivering application metadata, packets, and flows to the observability and security information and event management (SIEM) tools organizations already use, Gigamon helps teams move from “something is wrong” to “this application is experiencing network latency between these services, with these TCP events, on this path.”
The result is a more complete picture and a faster, more precise path to resolution.
Logs Explain Instrumentation. Traffic Shows Behavior.
Logs can only show what systems are configured to report. They can be partial, delayed, inconsistent, or limited to the systems that have been instrumented. They can also be deleted or tampered with by bad actors or suppressed by internal teams to increase systems performance. By their nature, they describe what has happened, not what is happening in real-time in a live environment. In a hybrid cloud infrastructure, that distinction matters: east-west traffic, encrypted sessions, ephemeral containers, and cloud-to-cloud paths are often not captured in logs and can remain difficult to see from any single application or security tool.
Network-derived telemetry complements—not replaces—logs. It provides an independent view of activity in motion, helping teams understand how applications communicate, where latency is introduced, whether connections are being reset, and which workloads or services are involved. As such, telemetry derived from application metadata, flows, and packets can add context such as application identity, DNS information, TLS posture, and suspicious destinations to enrich log data.
At an operational level, this difference can be very significant. Instead of asking an engineer to manually reconcile several dashboards, network telemetry can make the relevant evidence available inside an organization’s existing observability workflow.
From Network Symptoms to Application Context
Traditional packet and flow data can indicate that traffic exists. Richer telemetry can help explain what that traffic means. Gigamon Application Metadata Intelligence (AMI) adds signals such as round-trip times, TCP resets and aborts, wire-level latency, and application-aware context. When that data is enriched with configuration or other application metadata, observability teams can view and understand network behavior in the broader context of applications, services, workloads, hosts, and business processes.
That context helps separate application latency from network latency—an important distinction when multiple teams share responsibility for the same service. It also helps teams focus on the traffic that matters instead of searching through an undifferentiated stream of events.
One reported use case illustrates the potential. At a large airline, to resolve an application performance issue, engineers had to manually correlate huge volumes of systems data including application identities, IP addresses, and hosts. Using Gigamon AMI, network metadata was enriched with application information, which populated a dashboard that immediately showed relevant latency, TCP resets, and other network metrics.
The reported troubleshooting time fell from more than two weeks to under four minutes. The underlying lesson is clear: observability becomes more actionable when network evidence is mapped to the applications the business cares about.
Solve the Business Problem in Front of You
Network telemetry is most valuable when it is connected to a specific operational problem.
At a large bank customer, finance teams struggled to allocate costs for shared VPC traffic from over 700 VPCs, to the business units and workloads consuming this traffic. Native AWS tools could not provide the required level of attribution.
The team captured traffic through VPC mirroring, processed and enriched it using Gigamon to map IP addresses to AWS account and instance information. The enriched data was then delivered to Elastic dashboards and monthly reports showing traffic consumption by account and workload. Although developed to address this FinOps use-case, the customer quickly realized that this created a foundation for broader AWS observability, workload communication mapping, top-talker analysis, certificate monitoring, TLS visibility, and security investigations.
A Deep Observability Pipeline for the Tools You Already Own
The Gigamon Deep Observability Pipeline is designed to make network telemetry usable across existing operational systems. It accesses network traffic from data centers, private and public clouds, and containerized environments; brokers and transforms that traffic; enriches it with application and environmental context; and delivers packets, flows, and metadata to security, observability, operations, and AI tools.
This approach improves the signal available to platforms such as APM, SIEM, NDR, XDR, and analytics systems without requiring organizations to replace the tools they have already invested in. It also provides defensible evidence to map the environment, baseline east-west (lateral) and cloud traffic, improve encrypted and container visibility, detect suspicious behavior, and operationalize the results in dashboards and runbooks.
Validate, Prioritize, Verify
The most useful network telemetry does more than generate another alert. It helps teams answer three operational questions:
- Validate: Is the issue occurring on a live network path?
- Prioritize: Which application, workload, business flow, or critical asset is involved?
- Verify: Did a fix—such as a patch, segmentation change, or configuration update—change behavior?
That evidence can reduce unnecessary escalation, shorten the search for root cause, and make post-remediation validation more objective. It can also help different teams work from the same facts: operations can investigate performance, security can assess exposure, and application owners can understand the impact on services.
Network telemetry is not a substitute for observability. It is what makes observability more complete. By bringing live network behavior and rich application context into the tools teams already trust, Gigamon helps organizations see what is happening, understand why it matters, and resolve operational problems with greater speed and precision.
If you are looking to make your observability practice more precise, the next step is simple: bring network-derived telemetry into the tools your teams already use and see how much faster you can move from “something is wrong” to “this is the problem, and here is how we fix it.”
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