Architecture Development How To Load Balancer 
Scott Lowe
JANUARY 21, 2022
Aidan Steele examines how VPC sharing could potentially improve security and reduce cost. Nick Schmidt talks about using GitOps with the NSX Advanced Load Balancer. Time will tell how successful they are. Chris Evans revisits the discussion regarding Arm processor architectures in the public cloud.
Scott Lowe
OCTOBER 14, 2017
Romain Decker has an “under the hood” look at the VMware NSX load balancer. Jason Brooks has a write-up discussing how to run Kubernetes on Fedora Atomic Host. This graphical summary of the AWS Application Load Balancer (ALB) is pretty handy. Joel Knight shares how he’s tried to blog more in 2017.
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Scott Lowe
JULY 13, 2018
Bernd Malmqvist talks about Avi Networks’ software-defined load balancing solution, including providing an overview of how to use Vagrant to test it yourself. Chris Hein shows how to use the Heptio Authenticator with kops to link Kubernetes cluster authentication to AWS IAM. Cloud Computing/Cloud Management.
Linux Academy
FEBRUARY 26, 2019
By adding free cloud training to our Community Membership, students have the opportunity to develop their Linux and cloud skills further. You will walk through a local installation as well as how to use our Cloud Servers in order to follow along with our demos.
Scott Lowe
DECEMBER 17, 2015
He describes how to set it up (on both VirtualBox and Digital Ocean) and provides some high-level performance information as well. Rackspace and VMware have a pair of articles discussing their interoperable OpenStack cloud architecture ( here’s the post from Rackspace , and here’s the post from VMware ). Virtualization. Good write-up.
Scott Lowe
JUNE 23, 2015
Porting it back to development wasn’t the right approach. This led BI to Fig (now Docker Compose), which led to a decrease in the time it took to get a development environment up and running. Before Docker, the workflow was developers to GitHub to Jenkins, which then pushed to AWS in production.
Dataconomy
APRIL 28, 2023
With the increasing demand for machine learning deployment, various tools and platforms have emerged to help data scientists and developers deploy their models quickly and efficiently. Dedicated Model API architecture, where a separate API is created specifically for the model and serves as an interface for model interaction.
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