Automating Server Deployments in AWS with Terraform

Previously I discussed deploying Enterprise Linux in AWS which I demonstrated by using the AWS console. This is a common way to deploy servers to the cloud, however doing server deployments manually can create a situation where you’re stuck with static images that are difficult to replicate when your infrastructure grows. One of the benefits of Cloud Computing is that the infrastructure is programmable, meaning we can write code that can automate tasks for us. [Read More]

Deploying Enterprise Linux in AWS

In a previous post I discussed installing Enterprise Linux in VMWare, this time I wanted to write about deploying a server to the cloud. Cloud Computing platforms like Amazon’s AWS allow you to build and run all kinds of Infrastructure and services on-demand without having to purchase and maintain expensive physical computing hardware. You can deploy a server in minutes and have the capability to scale your workload as much as you need. [Read More]

Rebuilt AWS Infrastructure

I was hired as a contractor in early 2017 for some web development work. At the time, the company I was contracted to were experiencing extreme performance issues with their AWS environment. They were having to reboot their primary RDS every Monday morning to prevent it collapsing under load. Websites were very slow, often into the minute or more load times. Content managers were unable to access the CMS, website visitors couldn’t access the front end, and any increase in traffic could crash the entire server(s). [Read More]

Using ElasticSearch with WordPress

I’m a big fan of stuff that’s cool. And ElasticSearch is really cool… I’m not going to explain ElasticSearch in any detail, that’s not my job, other better people have already done that. But I am going to discuss my experience working with ElasticSearch and WordPress on a couple of recent projects. Earlier this year I started working on an analytics platform. It’s still in very experimental stages (meaning I have no idea what I’m building), but we have lots of data in multiple locations and we needed a central way to process and understand it. [Read More]