Interop Las Vegas 2016

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  • A New Approach to Fixing Internet Application Performance

    Elad Rave  |  CEO, Teridion
    Location:  Breakers L
    Session Type: Conference Session
    Track: Applications
    Pass type: 3-Day Pass, 5-Day Pass - Get your pass now!
    Vault Recording: TBD

    Over the last decades, the Internet has gotten faster, but has it gotten any better? Routers and connections are faster, but depending upon where you are and the time of day, your overall quality of Internet user experience, even with content delivery networks and the like, may still be frustrating.

    Applications and the data they deliver are shifting from static to dynamic. Consider a social network delivering a customized home page, or an ad serving network building recommendations based on personal preferences. File sharing and synchronization services are mainstream, and protocols including WebRTC and WebSockets are now broadly deployed. Applications have evolved, but content delivery architectures have not, impacting performance and the overall user experience. Here we describe a solution leveraging big data analytics spanning multiple cloud operators.

    The first step is understanding the state of the global Internet. This is a big data problem, accomplished through distributed probes that measure parameters such as throughput and latency. We describe some tools that may be deployed for this task, including Neo4j, a graphing database, Elasticsearch for analytics, Kibana for visualization, and ElasticHQ for cluster monitoring and management.

    But this capability isn't new. The critical next step is leveraging the cloud for networking, just as we've been using it for compute and storage. Under the control of a management system that has generated a 'heat map' of the Internet via probes, we may now leverage compute resources in the cloud for routing. This requires optimizing throughput at the VM level. In addition, a global footprint, especially critical in addressing performance issues distance from origin servers, requires the ability to utilize one or more cloud operators based on performance, geography, and even cost. This is accomplished via the development of APIs, an abstraction layer between the management system and each cloud operator's unique provisioning system.

    Combining the analytics and the virtual routers, we can now establish managed overlay paths connecting one 'cloud router' to another, and user traffic follows these paths to the origin server for dynamic content or applications. One can optimize for throughput, for latency and jitter, or even to avoid certain geographies. For those that know Waze, optimizing navigation in the physical world, this approach accomplishes the same for Internet traffic.