Access more granular flow records and statistics for network event correlation and attribution

MantisNet CNFlow (Cloud Native Flow) functionality, is a set of software probe and processing functions that allows you to instrument your infrastructure from the kernel, machine/node, process and container, up to the cluster, pod and application. 
The MantisNet CNFLow engine leveraging eBPF operates at speed and scale; the lightweight event-driven, sensor and processing functions are vendor, protocol and speed agnostic- they operate on-demand and deliver new forms of detailed, real-time, flow observability metrics and records (see table below) that can be correlated across the most complex private, public and hybrid cloud infrastructure. 

Why CNFlow Matters

More Detail: Legacy technologies, specifically IPFIX, NetFlow, JFlow and sFlow only provide basic network flow and traffic metrics. VPC mirroring and logs also only provide standard metrics of IP traffic in the cloud.
CNFlow provides far more detailed, contextual, network communications and insights.  
Dynamic, Continuous, Real-Time: Predecessor technologies only provide a snapshot of network traffic performance and deliver status metrics over a predetermined time-frame.
CNFlow includes more detailed and reliable forms fo flow records and statistics of the functions, processes, and resulting events as they occur.
No Changes, No Additional Hardware and Unlimited Scale: MantisNet CNFlow is vendor agnostic and doesn't require separate software and hardware to implement (no collector/exporter). 

Get Standard Flow Metrics in Addition to CNFlow Advanced Metrics

Standard Flow Metrics | CNFlow Advanced Flow Metrics and Statistics



Enhanced Observability with Advanced Flow

Gain deeper insights into the network communications and better correlate events with machines, applications and processes across nodes/clusters and containers/pods.
MantisNet CNFlow is more open, detailed, reliable, flexible, scalable and performant than other flow monitoring technologies. 
CNFlow is built on a foundation of kernel level instrumentation combined with local in-node processing and an event driven architecture to support he next generation of development, operations, and security applications- regardless of protocol or speed. CNFlow is cloud-native and supports streaming analytics using an open pub/sub message bus architecture and standards-based interfaces for deployment across public, private or hybrid cloud environments and third-party integrations.

Leverage Cloud Native Flow Across Your Organization

SRE, Dev and Ops Teams

Use MantisNet CNFlow telemetry and correlate events to identify the cause of congestion, performance, and latency issues across complex environments down to the container, node and process. CNFlow metrics are more efficient and scalable because they are processed in-node and delivered continuously and in real-time.

It operates as a DaemonSet or ReplicaSet so it scales to provide a range of traffic visibility, processing and telemetry generation capabilities, regardless of the speed or volume of flows: under load, without new hardware- supporting better forms of application and network performance monitoring (APM/NPM), complex traffic analysis, anomaly detection, troubleshooting and remediation simple and economical for large, or complex, instances of cloud-native deployments.

Security and Compliance Teams

Get continuous, real-time visibility and the ability to uniquely correlate traffic flows and container-level events- enabling faster, more precise anomaly detection and remediation, providing immutable attribution to all network events. Since, we're instrumented at the kernel level, get unprecedented observability of lateral movements within a containerized environment.

With CNFlow telemetry, teams can now more quickly and effectively allocate resources to focus on reducing the time-to-identify (MTTI) and respond (MTTR) to traffic of interest and ultimately resolve security and policy violations. 

Analysts and Data Scientists

MantisNet CNFlow operation and the resulting metadata is independent of the network protocol, vendor, or speed - meaning it can detect events regardless of scale, across the most complex enterprise, 5G / IoT / telecommunications applications- from the core to the edge. 

CNFlow telemetry includes advanced indexing data structures that allow for better event correlation and anomaly detection at speed and scale, regardless of the protocol. Furthermore, CNFlow metadata (as with all MantisNet CVF telemetry) can be natively streamed into event-driven streaming analytic platforms, or into (data-at-rest) storage for follow-on analytics or forensic evaluation.

Cloud Network Planning, Architecture and Development Teams

MantisNet CNFlow telemetry provides continuous event-driven real-time monitoring and observability to help better understand utilization and improve resource efficiencies by supporting both the latest generation of event-driven, real-time streaming AI and ML-enabled workflows, as well as legacy data-at-rest based provisioning and monitoring solutions to monitor the performance and behavior of the infrastructure for changes, trends or anomalies over longer timeframes and/or as new demands arise.  

Learn more about the containerized visibility fabric.