Deploying ElasticSearch Clusters With Juju and Ansible
One thing we’d like to see is to bring these capabilities to our users. So I’ve been working on bundling together some of our ElasticSearch resources in Ubuntu so we can bring them to the cloud, it looks like this:
This is a standalone ElasticSearch cluster. I’ve added a few things:
- A preconfigured Kibana dashboard
- A script that preloads the cluster with the works of Shakespeare, so you can start the 10 minute introduction right away and get to work.
- Paramedic and Bigdesk so you can monitor your cluster.
A Production-ready Stack
One of the nice things about this bundle is it uses our ElasticSearch charm. Right off the bat you’re getting a charm that we’re using in production today. That means it’s tested (see the included tests, and it also uses many of the modern techniques for writing a charm. In this case, Michael Nelson leveraged Ansible to do most of the heavy lifting. Our ability to consume multiple tools to get the job done is one of the nice things that we can support in charms, so if you prefer a certain tool, then by all means use it! It also just consumes upstream packages, so you’ll always have a fresh version.
The major use of ElasticSearch is within Ubuntu’s Software Store for Unity 8. On Ubuntu Touch anytime a user is searching for and navigating the store they’re using ElasticSearch. ElasticSearch was chosen for a few reasons.
- It allowed us to design the store where every category is basically a search term. This allows the team to dynamically generate categories based on certain criteria. For example a list of “Top 10 apps” might be different depending whether you are in the US or in China.
- Since everything is designed around search, it lets the team “future proof” the Software Store for future categories and queries.
- ElasticSearch was designed to scale much more than other solutions we looked at. ElasticSearch can be horizontally scaled by just
juju add-unitwith no extra configuration.
- Since the team didn’t have to worry about learning how to make search it let them concentrate on the store itself and let ElasticSearch do the heavy lifting.
- Since ElasticSearch is driving the backend, this will enable Ubuntu Phone partners to offer customized views on top of the existing store without having to do major engineering work around building a branded store.
- Our team found the ElasticSearch documentation to be excellent.
The quick way to get up and running
Ok so let’s deploy this badboy. Assuming you’re brand new:
sudo apt-get install juju juju-quickstart juju quickstart bundle:elasticsearch/cluster
At this point follow the ncurses menus to pick which cloud you want to deploy to and add your credentials and then Juju will bootstrap and start deploying ES.
Total deployment time will depend on where you’re deploying to, but on AWS US East 1 I can go from zero to cluster in about 10 minutes. By default I give you one Kibana node and one ElasticSearch node. For ElasticSearch we ensure you’re node has at least 4 CPU cores and 16GB of RAM. You can follow the instructions to load up the sample data and the other sample plugins I’ve included. Just go to the ip address of the Kibana unit in your browser and start searching:
Now you’re ready to horizontally scale:
juju add-unit elasticsearch
To add a new node.
And that’s it
You now have an ElasticSearch cluster. Using the same best practices that we’re doing in production. Amir Sanjar and I are prototyping bundling the ElasticSearch Hadoop plugin in a bundle as well, though that’s not quite ready (testing and help wanted!).
As you can see, we’ve barely scratched the surface. Chuck Butler’s been reworking the Logstash charm for Trusty, we expect that to land soon. We plan to make the charm a subordinate, you can just plop it onto any unit. The idea is to enable people to put logstash’s indexer on every unit they can shove all they care about into ElasticSearch.