bmeck

About

This is the most basic example of vertical scaling by transferring connections to workers, rather than sharing server sockets. It was presented at JSConf US 2012. With this you can create some interesting balancing algorithms that cluster would defer to internal/OS logic.

Exercises

A good first project when working with this is to implement sticky sessions based upon connection.remoteAddress and/or connection.remotePort.

A good advanced project is to change from a TCP based balancer to a HTTP(S) one and balance based upon not just connection.remoteAddress etc. but also on the protocol and/or Host header.

markhibberd

Installation

FreeBSD

portmaster irc/irssi
portmaster irc/irssi-xmpp

OS X

brew install irssi

GABeech

# This is an example of the Stack Exchange Tier 1 HAProxy config
# The only things that have been changed from what we are running are: 
# 1. User names have been removed
# 2. All Passwords have been remove
# 3. IPs have been changed to use the example/documentation ranges
# 4. Rate limit numbers have been changed to randome numbers, don't read into them

userlist stats-auth
        group admin users $admin_user
        user $admin_user insecure-password $some_password

kgorskowski

{
  "AWSTemplateFormatVersion": "2010-09-09",
  "Description": "CoreOS on EC2: http://coreos.com/docs/running-coreos/cloud-providers/ec2/",
  "Mappings" : {
      "RegionMap" : {

          "eu-central-1" : {
              "AMI" : "ami-487d4d55"
          },

lornajane

Keyboard-only Mac Cheatsheet

Hi, I'm Lorna and I don't use a mouse. I have had RSI issues since a bad workstation setup at work in 2006. I've tried a number of extra hardware modifications but what works best for me is to use the keyboard and only the keyboard, so I'm in a good position and never reaching for anything else (except my coffee cup!). I rather unwisely took a job which required me to use a mac (I've been a linux user until now and also had the ability to choose my tools carefully) so here is my cheatsheet of the apps, tricks and keyboard shortcuts I'm using, mostly for my own reference. Since keyboard-only use is also great for productivity, you may also find some of these ideas useful, in which case at least something good has come of this :)

Apps List

There's more detail on a few of these apps but here is a quick overview of the tools I've installed and found helpful

Tool	Link	Comments

codefromthecrypt

I've had many people ask me questions about OpenTracing, often in relation to OpenZipkin. I've seen assertions about how it is vendor neutral and is the lock-in cure. This post is not a sanctioned, polished or otherwise muted view, rather what I personally think about what it is and is not, and what it helps and does not help with. Scroll to the very end if this is too long. Feel free to add a comment if I made any factual mistakes or you just want to add a comment.

So, what is OpenTracing?

OpenTracing is documentation and library interfaces for distributed tracing instrumentation. To be "OpenTracing" requires bundling its interfaces in your work, so that others can use it to time distributed operations with the same library.

So, who is it for?

OpenTracing interfaces are targeted to authors of instrumentation libraries, and those who want to collaborate with traces created by them. Ex something started a trace somewhere and I add a notable event to that trace. Structure logging was recently added to O

StevenACoffman

MicroService Proxy Gateway Solutions

Kong, Traefik, Caddy, Linkerd, Fabio, Vulcand, and Netflix Zuul seem to be the most common in microservice proxy/gateway solutions. Kubernetes Ingress is often a simple Ngnix, which is difficult to separate the popularity from other things.

Github Star Trend:

This is just a picture of this link from March 2, 2019

Originally, I had included some other solution

mstemm

# Split all objects and pass them to each filter below

# Create/Delete Namespace
(select(.verb == "create" and .objectRef.resource=="namespaces") |
    "[" + .stageTimestamp + "] " + "Namespace Created: name=" + .objectRef.name),

(select(.verb == "delete" and .objectRef.resource=="namespaces") |
    "[" + .stageTimestamp + "] " + "Namespace Deleted: name=" + .objectRef.name),

# Create/Delete Deployment

kislayverma

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't really have SREs and they make engineers pretty much do everything,

max-rocket-internet

CPU: percentage of limit

A lot of people land when trying to find out how to calculate CPU usage metric correctly in prometheus, myself included! So I'll post what I eventually ended up using as I think it's still a little difficult trying to tie together all the snippets of info here and elsewhere.

This is specific to k8s and containers that have CPU limits set.

To show CPU usage as a percentage of the limit given to the container, this is the Prometheus query we used to create nice graphs in Grafana:

sum(rate(container_cpu_usage_seconds_total{name!~".*prometheus.*", image!="", container_name!="POD"}[5m])) by (pod_name, container_name) /