I did an internship at Mcafee as devops junior and then become a full time employee where I was in charge of most of the CI/CD, the configuration management and the infrastructure and orchestration of my team.
This includes Dev to Prod, RCA, logging and monitoring, performance testing, etc. 

Devops & Cloud Engineer

I've maintained every cluster for my team during 4 years. That includes DEV where we use both docker-compose, migrated to Minikube later on, and EKS to test on AWS. 
INT, PREPROD, QA  were not managed by me, I only provided maintenance & do testing. 
I've used HPA, servicemonitors, Ingress, pvcs, configmaps, Jobs, networkpolicies, PDB, serviceaccounts, CDR, etc. 
For production environments I exported all the metrics using prometheus, did all the dashboards for both grafana and Kibana and did all the RCAs.  
I did all the Docker images on my team and the path to production. 
On the security side, I had to harden these images for FEDRamp certification. 
Helm was used to deploy some tools (Prometheus/Grafana, Kong, ELK) and also did a chart for the service. 

I have nearly 4 years of experience using AWS. 
I used most of the services of EC2 and also a lot the services of networking (VPC). S3 and Route53 are worth metion and of course EKS and ECR since we deploy every environment using these.
I've also used both the aws cli and python library Boto, but most of our infrastructure was done on Terraform which decreased a lot when we switched to the EKS module. 

I've used teamcity for 4 years and did some side projects on jenkins on my free time to get used to the differences between them. 
I introduced to the team the Gitflow schema because at the time they weren't using anything and seemed a logical thing to do. 
I managed the entire cycle from the builing of the images using Maven/Gradle, the Dockerfiles for those app, the packaging, deploy into kuberenetes/AWS, testing, release and shipping. 

We were a Streaming team and we primarily focused on Kafka. The whole application was based around Kafka so I learned how to configure it for running at large scale (10TB/day),  the good things and bad things about it, how to debug it and keep it running, etc. 

Personal details

martin C.

Summary

Technical skills

Work Experience