gane5h

"""
Custom parser for nginx log suitable for use by Datadog 'dogstreams'.
To use, add to datadog.conf as follows:
    dogstreams: [path to ngnix log (e.g: "/var/log/nginx/access.log"]:[path to this python script (e.g "/usr/share/datadog/agent/dogstream/nginx.py")]:[name of parsing method of this file ("parse")]
so, an example line would be:
    dogstreams: /var/log/nginx/access.log:/usr/share/datadog/agent/dogstream/nginx.py:parse
Log of nginx should be defined like that:
    log_format time_log '$time_local "$request" S=$status $bytes_sent T=$request_time R=$http_x_forwarded_for';
when starting dd-agent, you can find the collector.log and check if the dogstream initialized successfully
    """

fnichol

SUITE_NAME=default

# create a bats subdirectory under your desired suite
mkdir -p test/integration/$SUITE_NAME/bats

# create an initial "canary" bats test file
# more examples at:
# * https://github.com/fnichol/chef-rvm/tree/master/test/integration/rubies/bats
# * https://github.com/fnichol/chef-ruby_build/tree/master/test/integration/alltherubies/bats
# * https://github.com/sstephenson/bats

alekstorm

Installation

To install, place datadog.py in your callback plugins directory. If you don't yet have one, run:

mkdir -p plugins/callback

Then place the following in your ansible.cfg file:

[defaults]

callback_plugins = ./plugins/callback

mitchellh

Vagrant::Config.run do |config|
  # ...

  config.vm.customize ["modifyvm", :id, "--natdnshostresolver1", "on"]
end

timlo

// https://github.com/settings/replies
// Settings > Saved Replies
// Execute in JS console.
(async function generateReplies(document) {
  // https://conventionalcomments.org/#labels
  const LABEL = {
    praise: "praise",
    nitpick: "nitpick",
    suggestion: "suggestion",
    issue: "issue",

schacon

$ git branch -r --merged | 
  grep origin | 
  grep -v '>' | 
  grep -v master | 
  xargs -L1 | 
  awk '{split($0,a,"/"); print a[2]}' | 
  xargs git push origin --delete

jayjanssen

net.core.somaxconn = 32768
net.ipv4.conf.all.send_redirects = 1
net.ipv4.ip_nonlocal_bind = 1
net.ipv4.tcp_abort_on_overflow = 0
net.ipv4.tcp_fin_timeout = 10
net.ipv4.tcp_keepalive_time = 300
net.ipv4.tcp_max_orphans = 262144
net.ipv4.tcp_max_syn_backlog = 16384
net.ipv4.tcp_max_tw_buckets = 262144
net.ipv4.tcp_mem = 200000    280000    300000

D2theR

Why?

I got sick of writing the same Serializer & ModelViewSet classes over and over so I found and wrote some code to do it for me, and somehow it works! Please note that there are a lot of caveats to running an API like this and while this may work, I know there's A LOT of room for improvement, feel free to fork and help!

USAGE

Import the router module to your main sites urls.py file as the injection point like so... Make sure to remove any other imports from other viewsets that you don't need that may conflict!

Daenyth

import requests
import logging
import httplib

# Debug logging
httplib.HTTPConnection.debuglevel = 1
logging.basicConfig()
logging.getLogger().setLevel(logging.DEBUG)
req_log = logging.getLogger('requests.packages.urllib3')
req_log.setLevel(logging.DEBUG)

nzakas

I'm doing some research on how companies use GitHub Enterprise (or public GitHub) internally. If you can help out by answering a few questions, I'd greatly appreciate it.

1. What is the primary setup? Is there an organization and each official repo is owned by that organization?
2. Does every engineer have a fork of each repo they're working on?
3. Are engineers allowed to push directly to the official repo? Or must all commits go through a pull request?
4. Do engineers work on feature branches on the main repo or on their own forks?
5. Do you require engineers to squash commits and rebase before merging?
6. Overall, what is the workflow for getting a new commit into the main repository?
7. What sort of hooks do you make use of?
8. Are there any ops issues you encountered? (Scaling, unforeseen downtime, etc.)