Packs (plugins, dashboards and rules) you can import into Dataloop
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apache2 [apache] process name Nov 7, 2016
autoscaling add autoscaling pack template and update icons Nov 2, 2016
base fix base plugin for windows boxes without perf stats enabled Nov 11, 2016
couchbase fix up couchbase plugin for lists that contain strings May 23, 2016
dataloop-usage Fixed Dataloop usage script to ignore containers and non-EC2 agents Nov 4, 2016
docker update docker dashboard Feb 8, 2017
dynamodb fix dynamodb dashboard template Jan 17, 2017
ebs update ebs dashboard template period to one hour Jan 17, 2017
ec2 update aws dashboards and rules period/threshold Dec 21, 2016
elasticache update aws dashboards and rules period/threshold Dec 21, 2016
elasticsearch [es] missed a couple of wrong capitalisations Jun 22, 2016
elb update aws dashboards and rules period/threshold Dec 21, 2016
firehose icons Dec 13, 2016
googleanalytics Updated GA Pack to support wildcard queries Jun 10, 2016
haproxy Added HAProxy Pack Nov 29, 2016
iis add iis service May 24, 2016
java [java] some more paths Nov 10, 2016
kafka update kafka readme Nov 11, 2016
kinesis add autoscaling pack template and update icons Nov 2, 2016
lambda add lambda dashboard template Jan 17, 2017
memcache tighten up regex on memcache May 23, 2016
mongodb more mongo and redis processes for auto discovery prod test Apr 20, 2016
mssql Update package.yaml May 26, 2016
mysql fix mysql dashboard widgets Oct 12, 2016
nginx ignore value errors too May 27, 2016
ntp adds an ntp pack Nov 6, 2016
opsworks add opsworks and route53 dashboard template Jan 18, 2017
php-fpm add a description to php-fpm Dec 18, 2015
postfix add postfix processes May 23, 2016
postgres add postgres, rabbitmq, riak and varnish processes May 23, 2016
rabbitmq [rabbitmq] version increase Jul 25, 2016
rds update aws dashboards and rules period/threshold Dec 21, 2016
redis more mongo and redis processes for auto discovery prod test Apr 20, 2016
redshift update aws dashboards and rules period/threshold Dec 21, 2016
riak add postgres, rabbitmq, riak and varnish processes May 23, 2016
route53 add opsworks and route53 dashboard template Jan 18, 2017
s3 add autoscaling pack template and update icons Nov 2, 2016
sns icons Dec 13, 2016
sqs icons Dec 13, 2016
varnish display zeros in varnish May 24, 2016
wordpress Updated wordpress dashboard with pages Apr 11, 2016
.gitignore Added Google Anayltics Pack Apr 12, 2016
README.md Update README.md Jan 28, 2016
create.py also create package.yaml and readme.md Nov 27, 2015

README.md

Dataloop Packs

Each pack is comprised of a plugin (Nagios check script), exported dashboard yaml file, exported rules yaml file, a package description and some help. Each directory in this repo appears as a separate pack in the Dataloop 'Packs Store' under the Setup page.

To create a new pack fork this repo and then run:

./create.py <pack name>

Where <pack name> is whatever you want your pack to be called. For now just single words please.

This will create a directory structure like this:

example
├── README.md
├── dashboards
│   └── example.yaml
├── package.yaml
├── plugins
│   └── example.py
└── rules
    └── example.yaml

When the install button is clicked on each pack in Dataloop it will automatically create a Tag based on the <pack name>. In the example above it would create a Tag called 'example'. It then automatically creates a link between that tag and all of the plugins in the plugins directory.

The README.md is the help file. Use markdown to describe any configuration changes that need to be in place to get your pack working. You may also want to describe what the metrics mean on the dashboards and rules.

Paste your exported dashboard yaml content into dashboards/<pack name>.yaml but ensure that the scope for every widget is set to a tag that matches the <pack name>.

Update the package.yaml with the following information:

title: example
author: steven
version: 1.0.0
description: this is just an example pack
instructions_required: false
icon:
    name: linux
    background: white
    foreground: crimson

For the icon you can specify any of the icons in our repo:

http://dataloop.github.io/icons/

Just ignore the .di- in the name.

Paste your plugin content into the plugins/<pack name>.py. For now every plugin needs to be written in Python as they get executed by the Dataloop agent's built Python 2.7 interpreter.

Paste your exported rules yaml content into rules/<pack name>.yaml but ensure that the scope for every criteria is set to a tag that matches the <pack name>.

You can add multiple plugins, dashboards and rules to a pack if you'd like to split stuff out a bit. Every plugin will get linked to the Tag that matches the <pack name>.

Once you've done all of the above submit a pull request and earn your place in the halls of monitoring fame.