Google Open Sources Data Center Load Balancing Software
Data Center Knowledge
FEBRUARY 2, 2016
Company developed Seesaw internally because no adequate solution was available Read More.
Data Center Knowledge
FEBRUARY 2, 2016
Company developed Seesaw internally because no adequate solution was available Read More.
Galido
APRIL 27, 2020
Most users of containers on Google and Azure are using Kubernetes. Google was the company that originally created and owned Kubernetes. This container management system obviously had a lot of potential since it comes from Google’s engineers. Traffic routing and load balancing. But what is Kubernetes really?
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SPF13
JULY 13, 2011
Those words were written in 2004 by Adam Bosworth , a veteren of Microsoft, Google and BEA. Open source products came to maturity (if you can call it that), but none improved on any of the challenges Bosworth outlines. the system dynamically load balances their data across the machines. by Steve Francia.
Linux Academy
MAY 15, 2019
Implementing an Auto Scaling Group and Application Load Balancer in AWS. And a brand new lab for Google Labs: Crafting a Google Kubernetes Engine Blue/Green Deployment. Plus, Jason goes down yet another awesome rabbit hole with a new project on GitHub aimed at giving back to the Linux and open source community.
Linux Academy
JUNE 17, 2019
Ansible is an open source tool that has been backed by Red Hat since 2015. Google Labs. Applying Google Cloud Identity-Aware Proxy To Restrict Application Access. Load Balancing Google Compute Engine Instances. Initiating Google Cloud VPC Network Peering. That’s where Ansible comes into play.
Scott Lowe
JUNE 18, 2021
The first is a post on Cilium and F5 load balancer integration , while the second discusses implementing Kubernetes network policies with Cilium and Linkerd. Michael Gasch has a nice post on git and using it to collaborate on an open source project. I read a couple of Cilium-related blog posts recently that may be useful.
Linux Academy
MARCH 28, 2019
High speed low latency networks now allow us to add these nodes anywhere in a cloud infrastructure and configure them under existing load balancers. These metrics makeup a great data source for further analytics. Most of them are proprietary and few open source solutions exist. Machine Learning.
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