Yonny Vizcaya

Equifax Perú

At Equifax, my main responsibility was to maintain the availability and stability of multiple key applications running on-premise RedHat servers and on AWS cloud instances. So to fulfill my main responsibility I had to manage incident response procedures with PagerDuty and implement DevOps practices to integrate, test and deploy Java applications.

Key Achievements:

• Reduced time and complexity of code integration by migrating from SVN version control to Git and training team members on the adoption of Github and Gitflow as a branching management workflow.

• Reduced 90% of technical debt by implementing SonarQube to analyze code quality and code security.

• Fixed and improved the bash deployment scripts since it only supported Docker Compose deployments. Now a single Docker Service can be deployed without compromising other application's services.

Stack used for this Job:

• Jenkins for automating continuous integration process compilating with maven, test with Junit, build Docker Image, and upload the image to AWS ECR.

• Infrastructure as a code with Hashicorp Terraform for AWS cloud resources.

• AWS Cloudwatch logs for monitoring application services.

• Docker Swarm management and troubleshooting for four working environments.

• Incident response with PagerDuty, incident management with ServiceNow.

DevOps Developer

Waki is a peer-to-peer lending platform where my main responsibility was to maintain the availability and stability of multiple microservices running on AWS EC2 instances as well as fix and implement new functionalities on the front end and back end of the project.

Key Achievements:

• Built a fintech platform from the ground up under a DevOps mindset and methodology with a small team of great people.

• Improved code integration by implementing Gitflow Workflow with two main branches (Master and Develop) and three auxiliary branches (Feature, Release, and Hotfix).

• Improved service log monitoring by implementing a microservice in Python3, AWS SDK and AWS CloudWatch.

Stack used for this Job:

• Angular as main front end framework implementing reusable components module, lazy loaded modules, authguard, Routing Modules, RxJS library to handle asynchronous API requests.

• Bootstrap and Sass pre-processor, for handling UI components and Theaming.

• Expressjs for creating REST APIS on Nodejs.

• Bitbucket for managing source code versioning.

• GoCD automation Pipelines for building, testing and deploying microservices on three different environments (DEV, QA and PROD).

• Python 3 and Unix Bash Scripting for automating system administration and configuration tasks using.

• Docker for building container images, deploying Docker services to Docker Swarm.

• Amazon ECR as Docker images repository.

• EC2 instances and EC2 auto scaling groups for automating server provisioning.

• AWS CloudWatch and microservices logs with AWS CloudWatch for monitoring EC2 instance performance and Docker Logs.

DevOps Developer

Horses Dev is a small software development agency. At this point, I started to get involved with DevOps practices and cloud computing, specifically with the AWS platform. My responsibilities were to handle FrontEnd development, continuous integration, deployments, and administrate the AWS cloud resources.

Key Achievements:

• During this experience, I improved my technical skillsets by learning Docker, AWS and DevOps practices.

• Improved code integration by implementing Gitflow Workflow with two main branches (Master and Develop) and three auxiliary branches (Feature, Release, and Hotfix).

• Improved service log monitoring by implementing a microservice in Python3, AWS SDK and AWS CloudWatch.

Stack used for this Job:

• Angular as main front end framework implementing reusable components module, lazy loaded modules, authguard, Routing Modules, RxJS library to handle asynchronous API requests.

• Bootstrap and Sass pre-processor, for handling UI components and Theaming.

• Bitbucket for managing source code versioning.

• GoCD automation Pipelines for building, testing and deploying microservices on three different environments (DEV, QA and PROD).

• Docker for building container images, deploying Docker services to Docker Swarm.

• Amazon ECR as Docker images repository.

• EC2 instances and EC2 auto scaling groups for automating server provisioning.

• AWS CloudWatch and microservices logs with AWS CloudWatch for monitoring EC2 instance performance and Docker Logs.

Vancouver Film School