Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

this is a rough draft and may be updated with more examples
GitHub was kind enough to grant me swift access to the Copilot test phase despite me @'ing them several hundred times about ICE. I would like to examine it not in terms of productivity, but security. How risky is it to allow an AI to write some or all of your code?
Ultimately, a human being must take responsibility for every line of code that is committed. AI should not be used for "responsibility washing." However, Copilot is a tool, and workers need their tools to be reliable. A carpenter doesn't have to
#Spin up Kubernetes control plane as part of before_script, and destroys it using after_script | |
#Some custom logic to get to the right ip address | |
#Requres the gitlab docker runner, with "pass-thru" to the host docker socket. | |
stages: | |
- test | |
image: python:3.6.6 #the docker image you run in needs Docker installed, and access to the host docker socket. | |
test_integration_k8s: | |
tags: |
Ramp up your Kubernetes development, CI-tooling or testing workflow by running multiple Kubernetes clusters on Ubuntu Linux with KVM and minikube.
In this tutorial we will combine the popular minikube
tool with Linux's Kernel-based Virtual Machine (KVM) support. It is a great way to re-purpose an old machine that you found on eBay or have gathering gust under your desk. An Intel NUC would also make a great host for this tutorial if you want to buy some new hardware. Another popular angle is to use a bare metal host in the cloud and I've provided some details on that below.
We'll set up all the tooling so that you can build one or many single-node Kubernetes clusters and then deploy applications to them such as OpenFaaS using familiar tooling like helm. I'll then show you how to access the Kubernetes clusters from a remote machine such as your laptop.
Kubernetes is great! It helps many engineering teams to realize the dream of SOA (Service Oriented Architecture). For the longest time, we build our applications around the concept of monolith mindset, which is essentially having a large computational instance running all services provided in an application. Things like account management, billing, report generation are all running from a shared resource. This worked pretty well until SOA came along and promised us a much brighter future. By breaking down applications to smaller components, and having them to talk to each other using REST or gRPC. We hope expect things will only get better from there but only to realize a new set of challenges awaits. How about cross services communication? How about observability between microservices such as logging or tracing? This post demonstrates how to set up OpenTracing inside a Kubernetes cluster that enables end-to-end tracing between serv
#!/bin/bash | |
# if we are testing a PR, merge it with the latest master branch before testing | |
# this ensures that all tests pass with the latest changes in master. | |
set -eu -o pipefail | |
PR_NUMBER=${CI_PULL_REQUEST//*pull\//} | |
err=0 | |
if [ -z "$PR_NUMBER" ]; then |