In the second post in this series, we considered the use of IGP-Prefix segments to carry a flow along a specific path in a data center fabric. Specifically, we looked at pulling the green flow in this diagram—
—along the path [A,F,G,D,E]. Let’s assume this single flow is an elephant flow that we’re trying to separate out from the rest of the traffic crossing the fabric. So—we’ve pulled the elephant flow onto its own path, but this still leaves other flows to simple ECMP forwarding through the fabric. This means some number of other flows are still going to follow the [A,F,G,D,E] path. The flows that are randomly selected (or selected by the ECMP has) to follow the same path as the elephant flow are still going to contend with the elephant flow for queue space, etc.
So we need more than just a way to pull an elephant flow onto a specific path. In fact, we also need a way to pull a specific set of flows off a particular path in the ECMP set. Returning to our diagram, assume we want all the traffic other than the elephant flow to be load shared between H and B, and Continue reading
New paper says machine learning will extend the life cycle of flash memory, which experiences "cell wear" with repeated use.
Networking Field Day 12 starts today. There are a lot of great presenters lined up. As I talk to more and more networking companies, it’s becoming obvious that simply moving packets is not the way to go now. Instead, the real sizzle is in telling you all about those packets instead. Not packet inspection but analytics.
Ask any networking professional and they’ll tell you that the systems they manage have a wealth of information. SNMP can give you monitoring data for a set of points defined in database files. Other protocols like NetFlow or sFlow can give you more granular data about a particular packet group of data flow in your network. Even more advanced projects like Intel’s Snap are building on the idea of using telemetry to collect disparate data sources and build collection methodologies to do something with them.
The concern that becomes quickly apparent is the overwhelming amount of data being received from all these sources. It reminds me a bit of this scene:
How can you drink from this firehose? Maybe you should be asking if you should instead?
Data is useless. We need to perform analysis Continue reading