F5 CEO to Retire (Again) as New ADCs Emerge
The Shuttle series points to the future as John McAdam points toward the exit.
Worth Reading: Navigating EU safe harbor
The post Worth Reading: Navigating EU safe harbor appeared first on 'net work.
Stacking Up Oracle S7 Against Intel Xeon
Even though the Xeon processor has become the default engine for most kinds of compute in the datacenter, it is by no means to only option that is available to large enterprises that can afford to indulge in different kinds of systems because they do not have to homogenize their systems as hyperscalers must if they are to keep their IT costs in check.
Sometimes, there are benefits to being smaller, and the ability to pick point solutions that are good for a specific job is one of them. This has been the hallmark of the high-end of computing since …
Stacking Up Oracle S7 Against Intel Xeon was written by Timothy Prickett Morgan at The Next Platform.
It all started with Dockerizing an old version of Confluence with Docker Datacenter
This is a guest post by Shawn Bower
In my role as Cloud Architect I often hear, “Docker sounds great but it won’t work for my application.” In my experience Docker can improve the state of many applications including legacy and vendor solutions. The first production workload at Cornell on Docker was the University’s wiki which is run on Atlassian’s Confluence in April 2015.
Our installation of Confluence is an interesting intersection of legacy and vendor solution. We have customized the code, to work with our single sign on solution, as well as a custom synchronization with LDAP for group management. When we started the project to move Confluence to the cloud the infrastructure, the software was old, compiled from the source and was being hand maintained.
Our installation of Confluence is an interesting intersection of legacy and vendor solution. We have customized the code, to work with our single sign on solution, as well as a custom synchronization with LDAP for group management. When we started the project to move Confluence to the cloud the infrastructure, the software was old, compiled from the source and was being hand maintained.
The stack looked like this:
- Apache 2. Continue reading
HPE, Intel & 6WIND DemoFriday Q&A: High Performance vADCs & OpenStack Virtual Infrastructure
Further explore the HPE, Intel & 6WIND's high performance vADC demo. Read the Q&A
Microservices Gone Wild – Tech Dive Part 2
In this post, I’ll outline the program I’ll be using to demonstrate how microservices work. It’s written in go but it’s pretty straightforward. At the end of the series of posts I will upload all of these examples to github as well, in case anybody wants to poke at them.
The Program – Squariply
For demonstration purposes, I’ll be discussing a very simple program that is currently implemented in a monolithic fashion. I’ve called it squariply
for reasons that will momentarily become obvious.
Purpose
Squariply accepts two integers on the command line, calculates the product (i.e. multiplies the two numbers), then squares the resulting number before printing the final result out. Mathematically speaking, if the integers provided on the command line are a and b, the output will be equivalent to (a * b) ^ 2.
Monolithic Code
My extremely amateur go code looks like this:
package main
import (
"fmt"
"os"
"strconv"
)
func main() {
str_a := os.Args[1]
str_b := os.Args[2]
int_a, _ := strconv.Atoi(str_a)
int_b, _ := strconv.Atoi(str_b)
multiplyResult := int_a * int_b
squareResult := multiplyResult * multiplyResult
fmt.Printf("Result is %d\n", squareResult)
}For the purposes of clarity, Continue reading