Juan Tamariz

• Set up the infrastructure for four different environments, including production. CI/CD, monitoring, backups, and security tools.
• Established the automation to continuously introduce security patches from lower environments to production.
• Set up AWS Inspector to validate possible new vulnerabilities in the code.
• Setup a CI/CD pipeline including code testing, security assessment, and a no-downtime deployment strategy that covers database upgrades. This resulted in minimizing the downtime of the application in production and improving production release frequency.
• Implemented core component upgrades to reduces costs and maximize performance for the client.

I built a framework to automate the bootstrapping of several tools for a CI/CD pipeline which included the build, code promotion, static code testing, performance baselines, and continuous deployment.

The impact of my work was a significant reduction of implementation time for new pipelines from 30 days to seven days.

Making use of KubeSpawner, I developed an implementation of JupyterHub Notebooks. It provides a long-term solution for on-demand autoscaling of users instances, together with Kubernetes' allocated resources.

At a glance, for every user logged in, a new Kubernetes pod is created on-demand. When more resources are needed, the Kubernetes cluster will also auto-scale.

A full project that involved an analysis of requirements and definition of dependencies and stakeholders.

I created an Agile project to track the creation of every Terraform module. We ended up on a set of authorized scripts that were instanced on several projects on Google Cloud.

The result is that before the project setup took a month and with the scripts, a new project could be set up every three days.

The framework considered the usage of the latest available Terraform version, together with a shared backend/state to make collaboration easier.