The human progression, over the years, can be credited to a host of different factors, and yet none would deserve the honor as much as our tendency to improve at a consistent pace. We say this because the stated tendency has already fetched the world some huge milestones, with technology appearing as a rather unique member of the group. The reason why technology’s credentials are so anomalous is purposed around its skill-set, which was unprecedented enough to realize all the possibilities for us that we couldn’t have imagined otherwise. Nevertheless, a closer look should be able to reveal how the whole runner was also very much inspired by the way we applied those skills across a real world environment. The latter component was, in fact, what gave the creation a spectrum-wide presence and made it the ultimate centerpiece of every horizon. Now, having such a powerful tool run the show did expand our experience in many different directions, but even after reaching so far ahead, this prodigious concept called technology will somehow keep on delivering the right goods. The same has grown to become a lot more evident in recent times, and assuming one new GRC-themed development pans out just like we envision, it will only propel that trend towards greater heights over the near future and beyond.
Arista Networks, Inc, an industry leader in data driven client to cloud networking, has officially announced the launch of a new network observability software offering. According to certain reports, the stated offering combines network infrastructure performance with data from compute and server systems-of-record to generate a comprehensive view of application and workload performance across data center, campus, and wide area networks. Named as Arista’s CloudVision® Universal Network Observability™ (CV UNO™), it works by facilitating complete automation in regards to network, systems, and application/workload visibility. Joining the same is a prospect of AI-driven proactive analysis and prescriptive recommendations, both the elements seemingly well-equipped to reduce human error, accelerate issue resolution for unforeseen events, and provide precise root cause analysis of network events along with their impact on application delivery. But how would all this look on a slightly deeper level? Well, we touched on how CV UNO can automatically discover applications, hosts, and workloads across various platforms, IT systems, and inventory management systems so to conceive a composite picture of the entire network and application environment. However, the thing we still haven’t discussed is how it also builds an application-to-network graph which is continuously refreshed and stored in time series. Such a graph, like you can guess, goes a long distance to reveal historical record of the environment’s evolution and state at any point in time. Next up, we must talk about the product’s proactive risk analysis capabilities that bank upon real-time application-to-network graphing to support change management workflow, cross-referencing, and impact analysis of network issues and anomalies. Another way one can use this technology is when trying to gauge the potential impact of a disruptive change before deployment across production and mission-critical networks. Having discussed CV UNO’s real-time facet, we must also acknowledge its knowhow in conducting a network change impact analysis just as it is unfolding. Using deep analysis and machine learning, the feature makes it possible for composite dataset within NetDL to figure out when exactly network provisioning or state changes have affected business and critical applications. In an event where network change has affected an application’s performance, CV UNO identifies, on its own, the change at fault, and the impacted application or workload so to allow the network engineering and operations teams to resolve the issue quickly. Beyond network change impact analysis, the solution in question can also conduct for you a host or application change impact analysis. Despite not mandating the deployment of any host-based agents, CV UNO can seamlessly direct the operator or engineer to accurate root cause of an issue, thus reducing the resolution time and improving cross-functional coordination.
“Bringing together multiple network domains with full application visibility and troubleshooting will streamline network operations and improve uptime and reliability. Disparate operating systems and lack of consistent data models across networks have made delivering systems with this degree of visibility previously impossible,” said Zeus Kerravala, Principal Analyst at ZK Research. “Moreover, in an era characterized by stringent regulatory compliance, cybersecurity and observability throughout the enterprise is no longer optional but rather an essential imperative.”
Rounding up the highlights is the way CV UNO can facilitate topology-aware determination of an issue. Enjoying a rather holistic view across all infrastructure systems, virtualization machines, systems of record, network flow, and state data, the solution taps into the biggest factor influencing any application performance issues.
With its functions duly covered, we can now turn our focus towards some of the practical components that come together to form CV UNO. For instance, there is the CV UNO sensor which collects normalizes, and curates flow/SNMP data from various sources like VMware vCenter, DANZ Monitoring Fabric, and third-party network devices before forwarding them to NetDL. Moving on, the solution further has a CV UNO Recorder Note, something made to install packet capture, query, and packet replay capabilities to support intrusion detection, incident response, and forensic use cases. Hold on, there are still a couple of bits left to unpack, considering we still haven’t mentioned the presence of a service node, a node which basically delivers advanced packet processing functions. This includes DPI-based Application Identification and classification. Finally, the offering packs into the mix an analytics mode. This one, in practice, hands you distributed context-aware traffic analysis. In the same regard, CV UNO also has a machine learning setup for large-scale optimization.
“Our customers have been demanding a composite system that provides seamless observability across network domains, prevents human errors, rapidly identifies root cause issues, and aids network engineers and operators to troubleshoot application performance issues,” said Douglas Gourlay, VP and GM of Cloud Networking Software. “Arista’s Universal Network Observability, built upon Arista EOS® and CloudVision platforms, fulfills this critical client need.”