Alejandro F.

At Infinitas Learning, I help build the cloud infrastructure and automation that power digital learning platforms across Europe. My focus is on cloud infrastructure, observability, reliability and DevOps practices that enable our teams to deliver great educational experiences at scale.

✅ Infrastructure & Automation

- Develop and extend Terraform modules to provision and manage scalable infrastructure

- Migrated Elastic Stack config to Terraform for version control and reproducibility

- Build internal Python automation tools to eliminate repetitive tasks and improve productivity

- Maintain and provide the internal CI/CD platform using self-hosted GitHub Actions

- Develop GitHub Actions CI/CD pipelines to streamline deployments

✅ Observability & Reliability

- Build and maintain the observability platform based on the Elastic stack

- Configure and optimize OpenTelemetry Collectors and their pipelines to ensure reliable and efficient data ingestion into Elastic

- Collect and analyze profiling data to gain deep insights into application performance

- Create dashboards to provide visibility into application and system performance

- Develop alerting to detect anomalies and reduce incident response time

- Optimize and administer Elasticsearch clusters for scalability and cost efficiency

✅ Cost Optimization & Efficiency

- Reduce operational costs by identifying underutilized resources, optimizing infrastructure usage and implementing effective autoscaling

✅ Risk Management & Compliance

- Identify security risks across infrastructure and observability systems

- Partnering with teams to enforce data governance and prevent the ingestion of PII

✅ Innovation & Developer Experience

- Developing and maintaining Python-based Slack ChatOps bots that automate provisioning tasks, cutting context switching and boosting team productivity

- Integrating AI tools by creating agents to assist in diagnosing issues in Kubernetes, OpenTelemetry and Elasticsearch

Worked on building and maintaining observability platforms to strengthen monitoring and analytics, enabling developers to troubleshoot live issues more effectively. Applied DevOps and SRE practices to deliver scalable, reliable, and cost-efficient solutions.

✅ Platform Engineering & Automation

- Designed and built a Kubernetes-based ELK platform on Azure, with Elastic clusters automatically deployed and configured using GitOps practices, using Helm and Terraform

- Provisioned and managed infrastructure on Azure using Terraform

- Developed CI/CD pipelines in Azure DevOps to automate deployments

- Migrated ELK configurations to Infrastructure as Code with Terraform

✅ Observability & Reliability

- Built a Kubernetes-based observability stack with Grafana, Loki, Tempo, and Mimir

- Integrated data ingestion into Elasticsearch from Cribl, Kafka, Logstash and OpenTelemetry Collectors.

- Architected, managed, and tuned high-throughput Elasticsearch clusters for stability and performance

- Implemented Elastic APM with OpenTelemetry for application performance monitoring

- Participated in on-call rotations to support observability infrastructure and resolve incidents

✅ Migration & Modernization

- Participated in the migration of the legacy on-premises Elastic platform to the new Kubernetes platform, preparing Elastic to handle higher data volumes as APM workloads were moved from Azure Application Insights and security workloads from Splunk into Elastic

- Helped transition from traditional system administration to modern, code-first reliability engineering

✅ Cost Optimization

- Monitored deployed resources to identify underutilization and apply cost-saving measures

✅ Collaboration & Mentorship

- Helped developers and data engineers adopt Elastic effectively through support with Kibana alerting and dashboards

- Helped teammates upskill in Kubernetes and Helm through mentoring and knowledge sharing

I worked as a Cloud / DevOps Engineer under Agile methodologies, focusing on deploying applications from the HPE catalog on Kubernetes/OpenShift in private clouds and major cloud providers.

- Developed and maintained several complex Helm charts following best practices

- Kubernetes and Openshift cluster creation and administration

- Gained experience running stateful services in Kubernetes

- Implemented end-to-end testing for HPE applications running on Kubernetes using Ansible

- CI/CD using tools such as Jenkins, ArgoCD, FluxCD and Spinnaker

- Implemented policies to the govern Kubernetes clusters using Kyverno

- Troubleshooted and debugged application running on Kubernetes

- Dockerfile optimization

- Participated in the development of various Kubernetes operators using Python, Java and Ansible

- Implemented logging and monitoring solutions for Kubernetes clusters: ELK (Elasticsearch, Logstash, Kibana), FluentD, Prometheus and Grafana

- Perform ETL processes with Logstash