General Meeting on Wednesday - 8 November 2017
The St. Louis Unix Users Group (SLUUG) general meetings are usually on the second Wednesday of each month.
We start the general meeting with a basic session (usually focused on personal commputing); which may include either
amazing graphical packages,
command line wonders,
demonstrations of useful applications,
displays of newly discovered web sites,
major resolution of long standing anomalies,
shifts in both time and space. Then we will have our usual quick welcome, introduction,
administrative announcements, and a Questions and Answers Period.
After all that, we take a break before our main event (usually focused on enterprise commputing).
The BASIC portion for November will be a tutorial showing how Linux users can
Split Out Home with gparted
by Stan Reichardt
For a number of years Stan has been using the Gparted "partition editor"
on new and reconfigured computers, to divide up the hard drive disks.
This process is known as repartitioning the disk partitions.
We will demonstrate using gparted to repartition a disk
by splitting out the "/home" directory to a separate disk partition.
This is one of those things a System Administrator (SysAdmin) might do.
From Wikipedia, the free encyclopedia:
GParted (acronym of GNOME Partition Editor) is a GTK+ front-end to GNU Parted and an official GNOME partition-editing application
(alongside Disks). GParted is used for creating, deleting, resizing, moving, checking, and copying disk partitions and their file
systems. This is useful for creating space for new operating systems, reorganizing disk usage, copying data residing on hard disks,
and mirroring one partition with another (disk imaging).
The ultimate purposes of partitioning range from improving file system performance, recovery for OSes, multiple-boot
This tutorial might show factors common with both personal and enterprise computing.
Stan Reichardt is one of those Linux bigots.
The MAIN presentation for November will cover
Big Data in The Cloud
by Chris Gore
Do you need to process petabytes of satellite imagery, but you don't have any servers
laying around? No big deal, you can have big data in the cloud.
This can all be done in the Amazon AWS cloud infrastructure, using EC2, ECS, DynamoDB, and
S3 as the most primary components, and much of the rest of the AWS tech stack as well.
This is done in Clojure, Python, and Ruby.
Chris Gore works on the Geospatial Engineering Team at The Climate
Corporation, where he helps process petabytes of satellite imagery into
useful information and imagery for farmers and their advisors.
Before thinking so much about corn and soybeans, Chris mostly worked at various
defense contractors and avionics firms. He has more than ten years of industry
experience, an MS in Computer Science from Missouri S&T and a BS in
Mathematics and Computer Science from EIU.
++ Posted 6 November 2017