You can see the sample code for this post on GitHub.

PostgreSQL is still my favorite database, and if a project I’m working on makes sense as a relational database model, it’s always what I reach for.

You can see the sample code associated with this post on Github.

In two previous posts, we looked at how to provision a reverse proxy using nginx and then how to add caching to the nginx reverse proxy. The implementation we ended up with at the end of the last post was a “dumb” cache, meaning that it doesn’t know when or if any data gets updated–it just times out after 60 seconds and then asks for a new payload from the application it’s acting as proxy for.

The source code for this post can be found on Github.

In my last post, I provided an example for how to set up an Nginx Reverse Proxy for a Spring MVC application. One such reason to set up a reverse proxy is to utilize caching of resources. If you have dynamically generated content that doesn’t change very often, then adding caching at the site entry point can dramatically improve site responsiveness and reduce load on critical resources.

Nginx is a popular webserver, excellent at serving up static content, and commonly used as a load balancer or reverse proxy. This post will set up a basic Spring Boot MVC web application, and use Nginx as a reverse proxy. The source code can be found on GitHub.

You can view the sample code associated with this post on GitHub.

In a previous post on Provisioning a Server with Kibana, we saw that it’s very straightforward to get kibana on a box.

You can see the source code for this post on GitHub.

In a previous post on How to Provision Multiple Logstash Hosts Using Ansible, we saw that provisioning logstash is pretty straightforward. However, what do we do with it after it’s been out there transforming messages this entire time? Given that elastic comes out with a new version of Logstash every fifteen or twenty minutes, a wise person would look to automate the upgrade process as soon as possible.

You can see the source code for this blog post on GitHub.

In a previous post, we saw how to provision a multi-node elasticsearch cluster using ansible. The problem with that post is that, by the time I was done writing it, Elastic had already come out with a new version of elasticsearch. I’m being mildly facetious, but not really. They release new versions very quickly, even by the standards of modern software engineering.

The corresponding source code for this post is available on GitHub.

Kibana is a fancy pants web application that tries to make data in Elasticsearch user-friendly. Rounding out the previous two posts on how to install an elasticsearch cluster and how to install multiple logstash hosts, I will now show you how to stack kibana on top of them.

The source code for this post can be found on GitHub.

Logstash primarily exists to extract useful information out of plain-text logs. Most applications have custom logs which are in whatever format the person writing them thought would look reasonable…usually to a human, and not to a machine. While countless future developer hours would be preserved if everything were just in JSON, that is sadly not even remotely the case, and in particular it’s not the case for log files. Logstash aims to be the intermediary between the various log formats and Elasticsearch, which is the document database provided by Elastic as well.

You can see the sample code for this tutorial on GitHub.

Elasticsearch is a distributed, NoSQL, document database, built on top of Lucene. There are so many things I could say about Elasticsearch, but instead I’ll focus on how to install a simple 3-node cluster with an Ansible role. The following example will not have any security baked into it, so it’s really just a starting point to get you up and running.

You can see the sample code for this tutorial on GitHub.

 Molecule is primarily a way to manage the testing of infrastructure automation code. At its core, it wraps around various providers like Vagrant, Docker, or VMWare, and provides relatively simple integration with testing providers, notably TestInfra. Molecule is a great tool, but in my opinion there are not enough resources, by way of examples, to provide an adequate getting started guide. This post is meant to help fill that void.

Lombok manipulates the output java bytecode .class files, and inserts boilerplate code that java developers are very familiar with repeating themselves on.