I get a “how do I get started with network automation” question every other week, and when I wrote a lengthy reply to one about configuration templating of existing snowflake network on networktocode Slack channel I decided it’s time to turn my replies into a blog post.
Read more ...I started coveting IP encapsulated network virtualization back in 2005 when I was working to build a huge IP fabric. However, we needed to have layer 2 (L2) adjacencies to some servers for classic DSR load balancing. The ideal solution was to have something that looked like a bridge as far as the load balancers and servers were concerned, yet would tunnel unmodified L2 frames through the IP fabric. Alas, we were way ahead of our time.
Thank the IT gods that things have changed quite a bit in the last 12 years. Today, we as an IT community have VXLAN, which is embodied in most modern networking silicon and (a bit more importantly) realized as part of the Linux networking model so that it’s really straightforward to deploy and scale. IT geeks have a bunch of ways to build L2 domains that are extended across IP fabrics using VXLAN. There are dedicated SDN controllers, such as Contrail, Nuage, Midonet and VMware NSX; there are orchestration-hosted controllers in OpenStack Neutron and Docker Swarm; and there are simple tools like the lightweight network virtualization that we built at Cumulus Networks.
This all leads me to EVPN. We recently made EVPN available Continue reading
The CloudMunch acquisition is the third significant purchase this year by JFrog.
Few companies have provided better insight into how they think about new hardware for large-scale deep learning than Chinese search giant, Baidu.
As we have detailed in the past, the company’s Silicon Valley Research Lab (SVAIL) in particular has been at the cutting edge of model development and hardware experimentation, some of which is evidenced in their publicly available (and open source) DeepBench deep learning benchmarking effort, which allowed users to test different kernels across various hardware devices for training.
Today, Baidu SVAIL extended DeepBench to include support for inference as well as expanded training kernels. Also of …
A Deep Learning Performance Lens for Low Precision Inference was written by Nicole Hemsoth at The Next Platform.
ForeScout now improves visibility into VMware environments.
For #AskAnsible posts, we interview Ansible experts on IT automation topics and ask them to share their direct experiences building automation solutions.
In this post, I’ve asked Matt Davis five questions about Ansible for Windows automation.
Matt Davis is a Senior Principal Software Engineer for Ansible, focused on Ansible's Windows support. He has over 20 years experience in software engineering, architecture and operations at companies large and small. An avid musician, maker and home hacker, Matt lives with his wife and daughter in Beaverton, Oregon. You can follow him on Twitter at @mattdavispdx.
1. How is Ansible for Windows different than System Center Configuration Manager (SCCM) or Powershell Desired State Configuration (DSC)?
Matt: SCCM is generally considered a legacy workstation-flavored management technology, dating from the mid 1990s (though many places use it for server management, too). It requires agents on the managed hosts, which must be installed, configured and kept up-to-date. SCCM executes many operations locally and asynchronously from the server, so it's often difficult to orchestrate interdependent changes across hosts, and to reason about the overall system state at any point in time as part of larger deployments.
DSC is a much more modern management technology, supporting both an Continue reading
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