Kentik - Network Flow Analytics

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by Avi Freedman
by Avi Freedman
by Avi Freedman
by Avi Freedman
by Avi Freedman
by Avi Freedman
by Aaron Kagawa, Crystal Li
by Ken Osowski
by Crystal Li, Jim Meehan
by Ken Osowski
by Jim Meehan, Greg Villain
by Crystal Li

Maximizing Network Metadata Value

March 21, 2016

The plummeting cost of storage and CPU allows us to apply distributed computing technology to network visibility, enabling long-term retention and fast ad hoc querying of metadata. In this post we look at what network metadata actually is and how its applications for everyday network operations — and its benefits for business — are distinct from the national security uses that make the news.

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Evolution of BGP NetFlow Analysis, Part 2

March 14, 2016

In part 2 of this series, we look at how Big Data in the cloud enables network visibility solutions to finally take full advantage of NetFlow and BGP. Without the constraints of legacy architectures, network data (flow, path, and geo) can be unified and queries covering billions of records can return results in seconds. Meanwhile the centrality of networks to nearly all operations makes state-of-the-art visibility essential for businesses to thrive.

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BGP Routing Tutorial Series: Part 1

February 08, 2016

Border Gateway Protocol (BGP) is a policy-based routing protocol that has long been an established part of the Internet infrastructure. Understanding BGP helps explain Internet interconnectivity and is key to controlling your own destiny on the Internet. With this post we kick off an occasional series explaining who can benefit from using BGP, how it’s used, and the ins and outs of BGP configuration.

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Exploring for Insights on Anomalous Network Traffic

January 11, 2016

By actively exploring network traffic with Kentik Detect you can reveal attacks and exploits that you haven’t already anticipated in your alerts. In previous posts we showed a range of techniques that help determine whether anomalous traffic indicates that a DDoS attack is underway. This time we dig deeper, gathering the actionable intelligence required to mitigate an attack without disrupting legitimate traffic.

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Designing for Database Fairness

December 21, 2015

Kentik Detect is powered by Kentik Data Engine (KDE), a massively-scalable distributed HA database. One of the challenges of optimizing a multitenant datastore like KDE is to ensure fairness, meaning that queries by one customer don’t impact performance for other customers. In this post we look at the algorithms used in KDE to keep everyone happy and allocate a fair share of resources to every customer’s queries.

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