I want to know how to characterize my workloads in the cloud. With that, I should be able to find systems both over-provisioned and resource starved to aid in right-sizing and capacity planning. CloudForms by Red Hat can do these at the system level, which is where you would most likely take any actions, but I want to see if there’s any additional value in understanding at the aggregate level. We’ll work backwards for the impatient. I found 7 unique workload types by creating clusters of cpu, mem, disk, and network use through k-means of the short-term data from CloudForms (see the RGB/Gray graph nearby). The cluster numbers are arbitrary, but ordered by median cpu usage from least to most.
From left to right, rough characterizations of the clusters are:
Lots of cleanup left to do in the code parsing/cleaning up the emails, but here’s a first pass. Seems like at least two connected networks, and surprisingly both the yahoo and the Gov’t email addresses are both in the larger one. I wonder what the smaller one comprises of?
What it look like if you took all of the Mathematics articles from JSTOR, the digital journal archive, and mapped co-authorship of the papers? It would look something like this. Interesting to note, that while the distribution does hold to the small world network distribution exponent, there’s some “peakiness” about it that may suggest it’s not really one network, but the merging of several. Given the role of mathematics on so many other subjects, that would not be a surprise.
…for the first time digitized one year’s worth of FARA records, making them accessible in a searchable database that allows users to easily follow the money and connect the dots. With the Foreign Lobbying Influence Tracker, anyone can quickly learn what governments are lobbying whom, how often and about what. [source @ ProPublica]
Here are the firms the Congressmen and -women from my home state have been meeting with:
and the countries of the governmental department or foreign firm paying the lobbyists:
Thanks everyone for showing the strong interest in the Lobbyist map. I got a couple nice mentions at Mother Jones and LittleSis.org, but more importantly, I’ve added in all of the other names in the map.
Circles are people, squares are organizations, and white circles are the lobbyists in question.
If you’d rather the image than the flash bits, here you go, all 2.5MB of it.
A zoomable version of the earlier map is here:
[Thanks to Drew Conway for the Sea Dragon zoomable suggestion]
The Huffington Post, along with public contributors, has been collecting a list of former Congressional staffers turned healthcare lobbyists. LittleSis.org has been keeping track of these former staffers, and thanks to their API, we now have a social graph of their relationships.
Former staffers in white (with names), and the rest of the visual field to show that some are MUCH better networked than others.
If there’s interest, I can add the names of the people they are networked with and start some analysis of the group.
As always, click for a larger image.
Update: network map with all names, and in a zoomable widgethere.
I wanted to put out what’s been done so far on making yesterday’s post more interactive. There’s an awful lot that could be better about this map. Particularly legibility of labels in the core (it’s just too dense). If you want to see names, I suggest looking at the edges of the map.