Tech Smorgasbord #6

An on-going reference series for interesting technology or projects which deserve further investigation, or for technical documentation (of one media format or another) that looks to be especially good reference material.


There’s been so much good material coming out of late that I’m going to need to put together several of these smorgasbords just to catch up. Here’s the first batch of things I think you’ll find interesting:


Automatic for the People

If you’re into network automation, you might be following the work of Kirk Byers (@kirkbyers). Kirk has been focusing on various tools and methods for automating network devices, such as Ansible, Paramiko, and Python, for awhile now – particularly with Python. His Python for Network Engineers is a good reference, and he routinely teaches classes on that subject – including free-by-email classes, the next of which starts in April. He recently blogged about NAPALM – Network Automation and Programmability Abstraction Layer – in conjunction with Ansible to automate IOS:

NAPALM, Ansible, and Cisco IOS

Another automation project, also utilizing Python and Ansible but originating from VMware, is Chaperone. The new toolkit is targeted at VMware’s SDDC products including vSphere, vCenter, vRealize Automation, vRealize Orchestrator, vRealize Operations, NSX, etc.


Virtually Anything

DoubleCloud Inc., founded by Steve Jin (@sjin2008),  has announced a new “Super vCenter” product called DoubleCloud vSearch that looks pretty interesting: Google search and big data analytics for VMware environments delivered as a single OVA and leveraging a simple HTML5 web UI.

You may also recall his DoubleCloud Interactive Cloud Environment (ICE) product that was launched last year to provide a single console for both CLI & GUI management of vCenter/ESXi environments (and the guests that run in those environments). Both vSearch and ICE are available as 60 day demo downloads, and ICE has a permanently free edition as well.

Keith Tenzer (@keithtenzer) has a really good blog covering Red Hat’s virtualization related technologies such as Red Hat Enterprise Virtualization and OpenStack. His most recent post is a nice write-up on Red Hat Enterprise Virtualization (RHEV) – Management Options.


NetApp News

Stefan Renner (@rennerstefan) has been publishing a number of interesting blog posts of late, with these two covering SnapMirror and Storage Virtual Machine (SVM) DR being of particular note.

How to create mirror-vault and version flexible SnapMirror relationship in CDOT 8.3

How to setup a SVM DR in CDOT 8.3.1 including all configuration and data

NetApp’s very own Andrew Sullivan (@andrew_ntap), co-host of the Tech ONTAP Podcast, has been very productive. He’s churned out a number of great scripting or automation focused blogs (including the first two below and more on Docker in the section), as well as co-writing this recent technical report on SDS from a NetApp/VMware perspective.

cDOT Environment Monitoring Using PowerShell

NetApp PowerShell Toolkit – Templates

TR-4308: Software-Defined Storage with NetApp and VMware

Ed Morgan (@mo6020) has written a handy little post on automating the NetApp simulator using Vagrant:

Using Vagrant to provision the Clustered Data ONTAP vSim


Docker Delights

Mr. Sullivan at work again – this time wearing his Containers Cap with a couple excellent posts on running some NetApp tools inside of Docker:

Putting the NetApp Manageability SDK Into Docker Containers

Perfstat in a Docker Container

Another NetAppian, Jacint Juhaz (@jac1nt), has a nice compendium post around using Docker Swarm on AWS with Cloud ONTAP for persistent data.


Miscellania

Microsoft acquires SwiftKey

SwiftKey has been a must-have on all of my Android devices for years now. It’ll be interesting to see what happens after this acquisition  – trepidation abounds.

Udacity is now offering an Advanced level Deep Learning course developed by Google that’s free for anyone to take so long as they’re willing to put in some time: participants are expected to take approximately 3 months when working about 6hrs/week . It’s part of Udacity’s Machine Learning Engineer Nanodegree program, which is not free overall but  – at $199/month for an expected 10-12 months worth of work – is still pretty affordable, particularly since they promise a 50% refund if you complete & graduate within 12 months. 


 

 

 

 

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