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An Interview with Xangati

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Over the past few weeks we’ve been sitting down to chat with some of the great minds of the cloud industry. This week I had some time with Atchison Frazer of Xangati. Atchison stressed there is still a sense of wariness among the enterprise market when it comes to the cloud and virtualisation, read more below about his thoughts on cloud and Xangati, who he joined a year ago.

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Atchison Frazer, CMO, Xangati

Atchison Frazer brings over 20 years of IT strategic marketing expertise to Xangati, most recently as CMO of KEMP Technologies, an emerging growth software developer competing in the enterprise Application Delivery Controller segment, and prior to that, CMO of Gnodal Ltd (now part of Cray), an innovator of High Performance Computing data-fabric technology and High Frequency Trading fintech infrastructure.  

Atchison, can you give me an overview of Xangati? 

AF: Xangati analyses IT infrastructures in a 360-degree, holistic, live and continuous manner. It not only generates visibility both to the metrics that are emanating from desktop services, network, compute and storage, but also connection brokers and other IT services in the network. Xangati exclusively leverages an in-memory analytics platform that ingests data at very high speeds and scales to large environments, without the need to deploy agents or probes. The company also correlates network data to cross-reference the interdependencies of flows and metrics processed by our analytics engine, enabling superior offerings to our customers. The notion of service assurance involves collecting data, monitoring, trending and performance analytics to provide actionable insights. This includes, for example, real-time analytics as issues materialise, such as post-mortem analytics of historic metrics, gathered when a customer pushes a button to record what’s happening in their environment, and predictive analytics to prevent performance contention storms in the future.

What do you think of the Cloud Industry at present?

AF: We still see caution among the large, global enterprise market, the segment Xangati mostly serves; many of these organisations have only recently in the last 2-3 years deployed large virtualisation environments, whether that be VMware vSphere or Citrix XenServer, and are just now beginning to optimise those virtualised infrastructure investments to extend to application virtualisation, such as for virtual desktop services. However, almost all of these organisations, have hybrid-cloud infrastructure extensibility in their build-out plans, in addition to more transformational events such as software-defined networking, network functions virtualisation and container-based platforms.

What are Xangati’s main strengths?

AF: Because Xangati essentially taps into existing flow-based technologies such as NetFlow for the Cisco estate or AppFlow when Citrix NetScaler is load-balancing web servers, for example, and the fact that the Xangati Virtual Appliance (XVA) can run natively within the customer’s hypervisor, cloud or container platform of choice, we’re the most flexible infrastructure performance management tool available, whereas many other competitors must rely on cumbersome provisioning of agents or probes to achieve the same level of data granularity delivery by XVA. Also, Xangati uniquely generates a cross-reference mesh to all functional components and objects in the virtual infrastructure, then overlays that grid with a storm-tracker utility that provides root-case analysis and triage-style troubleshooting for code-red performance degradation issues.

[easy-tweet tweet=”Xangati uniquely generates a cross-reference mesh to all functional components and objects in the virtual infrastructure” user=”atchisonfrazer” usehashtags=”no”]

What do you think sets Xangati apart in a competitive cloud marketplace?

AF: Given Xangati’s DNA in the virtualisation layer, we’re well-poised to take advantage of cloud service assurance analytics required to ensure that enterprise systems administrators have an independent source of truth, essentially one single pane of glass, to hold accountable internal and external service providers, and conventional silo counterparts, for meeting service-level targets.

Could you describe Xangati’s ideal client for me?

AF: The ideal client for Xangati is an enterprise systems administrator (or a large public sector entity sysadmin) who is the licensee for virtualisation services from VMware, Citrix or Microsoft, and the managed/cloud/hosting services provider system admin is also running hypervisor-based virtual infrastructures and/or offering VDaaS (virtual desktop-as-a-service), as a good example. The other main buying centre for Xangati is app administrators who are responsible for virtualised desktop services leveraging VMware Horizon or Citrix XenApp/XenDesktop.

Could you tell us a bit about some of your current clients?

AF: XVA has been deployed in more than 400 customer organisations, ranging from mid-market to large enterprise, large public sector, and managed service providers. In the UK, we work with the National Health Service, British Gas, Sky, Colt and many others in concert with our go-to-market partners, such as Triangulate IT.

Where you see your company heading in the future?

[easy-tweet tweet=”The future of @Xangati is very much tied to the hybrid-cloud market as well as the development of third-wave platforms” via=”no” usehashtags=”no”]

AF: The future of Xangati is very much tied to the hybrid-cloud market transition as well as the development of third-wave platforms that transcend the hypervisor orthodoxy, such as containerisation and hyper-converged infrastructures. As these multiple tiers are layered over the on-premise physical and virtual infrastructure environments, visibility to performance degradation or v-storm contention issues becomes even more complex, especially for storage IOPS latency or anomalous network traffic patterns, and so with our in-memory architecture and auto-ingest capability of protocol/API metrics, we’re able to deliver pinpoint-accurate intelligence about how to optimise faster (live, second-by-second, continuous high fidelity stream) and with greater scale.