For many years, when I worked out in the center of the triangle of runways and taxiways, I would get up at around 4, swim a mile in the indoor poor (36 laps), shower, grab breakfast, run by base weather just to check the bigger pieces of equipment out (mostly the RADAR system), and then I’d head out to the shop. We could mostly only get downtime on the airfield equipment (particularly the VOR, TACAN, and glideslopes) in the early morning hours — unless, of course, there was a war on. Then we couldn’t get downtime at all. By 2:30 I was done with my work day, and I headed home to get whatever else done.
When I left the USAF, after being trapped in some 9–5 jobs, I joined the cisco TAC. Our shift started at 8 or 8:30, when we took over the 1–800 number from Brussels, and our shift lasted until around 2 in the afternoon (it varied over time, as the caseloads and TACs were moved around). Freed from 9–5, I started getting to work at around 5:30 again. I could spend the first two or three hours following up on cases (did you know that Continue reading
I’m sure some of you are scratching your head right about now wondering why I would join an Internet security and optimization company. But, Ben, this is not even close to your passion: operating systems.
I had the same reaction when I first saw the CloudFlare website. I wasn’t even sure it made sense for me to go interview here. After taking a closer look, however, I realized that it would be the perfect new home for me. Take a look at this page for a brief introduction to what CloudFlare does and how we do it.
If you know me, you know that I'm a sucker for distributed systems. I fall for a hard computer science problem every time. So, it shouldn’t be a surprise to you that CloudFlare’s John Graham-Cumming, had me at “hello” when he nonchalantly described one of the company's projects: a globally distributed key value store with sub-second consistency guarantees! Ho hum! No big deal.
As the interview process progressed, the team graciously spent several hours walking me through the architecture as well as future plans and product roadmaps. These discussions and email exchanges were frequently interrupted by my cries of protest: Continue reading
I had fun times participating in a discussion focused on whether it makes sense to deploy OTV+LISP in a new data center deployment. Someone quickly pointed out the elephant in the room:
How many LISP VM mobility installs has anyone on this list been involved with or heard of being successfully deployed? How many VM mobility installs in general, where the VMs go at least 1,000 miles? I'm curious as to what the success rate for that stuff is.
I think we got one semi-qualifying response, so I made it even simpler ;)
Read more ...Introduction
This post will describe different load balancer designs, the pros and cons of the designs and how they affect the forwarding of packets.
Load Sharing Vs Load Balancing
The terms load sharing and load balancing often get intermixed. An algorithm such as Cisco Express Forwarding (CEF) does load sharing of packets meaning that packets get sent on a link based on parameters such as source and destination MAC address or source and destination IP address or in some cases also the layer 4 ports in the IP packet. The CEF algorithm does not take into consideration the utilization of the link or how many flows have been assigned to each link. Load balancing on the other hand tries to utilize the links more evenly by tracking the bandwidth of the flows and assigning flows based on this information to the different links. The goal is to distribute the traffic across the links as evenly as possible. However load balancing is mostly used to distribute traffic to different servers to share the load among them.
Why Load Balancing?
What warrants the use of a load balancer? Think of a web site such as facebook.com. Imagine the number of users Continue reading
I loathe MRTG graphs. They were cool in 2000, but now they’re showing their age. We have much better visualisation tools available, and we don’t need to be so aggressive with aggregating old data. I’ve been working with InfluxDB + Grafana recently. Much cooler, much more flexible. Here’s a walk-through on setting up InfluxDB + Grafana, collecting network throughput data, and displaying it.
There’s three parts to this:
A show recorded in a bar. What could go right?
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A show recorded in a bar. What could go right ?
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