$ cat ~/about.md

Gideon

DevOps & SRE engineer building observable, resilient infrastructure. I specialize in monitoring pipelines, synthetic checks, and alert engineering using Prometheus, Grafana, Splunk, and PagerDuty.

systems nominal · currently @ CAREER BREAK
// Active Workstreams
[1] MFT/SFTP synthetic monitoring via Python lifecycle checks writing to node_exporter's textfile collector.
$ cat contact.txt
$ git activity @GideonIsBuilding
Less
More
$ ls ~/projects/
sftp-synthetic-monitor observability

End-to-end SFTP lifecycle check: connect → authenticate → upload → download → SHA-256 verify → cleanup. Writes Prometheus metrics to node_exporter's textfile collector. Covers services endpoints across stacks.

python prometheus grafana SHA-256 monitoring
automated-integration-and-deployment-pipelines deployment

Comprehensive CI/CD pipelines integrating Terraform for infrastructure automation and Ansible for configuration management. Designed GitOps workflows to streamline deployments for a three-tier application stack and monitoring solutions (Prometheus, Grafana, Loki). Implemented branching strategies to automate infrastructure validation, planning, and application deployment, and delivered modular and reusable workflows for validation, planning, applying, and monitoring, ensuring efficient and scalable operations.

ci/cd monitoring infra gitops client-server
flask-k8s-cicd-pipeline infrastructure

Containerized a Flask service using Docker (Python 3.10 Alpine), served via Gunicorn, and built a full CI/CD pipeline around it. GitHub Actions builds and pushes versioned images to Docker Hub on every push to main, with the image tag tied to github.run_number. Kubernetes deployment is fully automated via Terraform using the Kubernetes provider — provisioning a configurable-replica Deployment and a NodePort Service. The workflow closes the CI/IaC loop by automatically updating the Terraform image variable to reference the latest build, ensuring no manual tag bumping between pipeline and infrastructure.

docker python github-actions k8s terraform ci/cd
$ cat ~/.toolbox
// Observability
Prometheus Grafana Splunk PromQL
// Incident & Alerting
PagerDuty Alert Engineering SLO / SLA On-call
// Synthetic Monitoring
k6 k6 Browser Python Scripts
// Infrastructure
Kubernetes Docker Ansible Terraform Jenkins GitHub Actions
// Languages
Python Bash PowerShell
// Environments
AWS GCP Digital Ocean Linux Windows Server F5
$ cat ~/experience.log
Monitoring & Observability Engineer
TechPeak Lab | London
Sept 2024 - Mar 2026
  • Migrated 1,200+ SCOM alerts to Splunk, automated NOC forwarding, and diagnosed high-severity Windows Server incidents, reducing response latency by 45%
  • Developed Python and PowerShell remediation scripts integrated into operational playbooks, automating recovery for 70% of repetitive alerts and cutting intervention time by 60%
  • Implemented multi-layer validity checks (Layers 1–6) for critical services, improving MTTD by 35% and MTTR by 42% across high-priority incidents
  • Designed and deployed Grafana dashboards for 4XX and 5XX error monitoring, giving leadership real-time reliability insights and reducing undetected service degradations by 50%
  • Developed SFTP synthetic monitoring via Python lifecycle checks (connect → auth → upload → download → verify → cleanup) writing to node_exporter textfile collector
  • Participated in ORCA (Operational Root Cause Analysis) reviews for core production systems, preventing recurrence of repeat error patterns and reducing post-incident
Technical Content Writer
Turing | Palo Alto, California
May 2025 - Oct 2025
  • Engineered complex, real-world application scenarios to demonstrate the functional depth of Gemini AI agents across workplace automation, business operations, and enterprise systems integration
  • Translated multifaceted business workflows into executable AI logic, designing modular, testable structures that mirrored real-world processes such as sales enablement, lead generation, and automated contact intelligence
  • Developed structured, code-like datasets for AI scenario modeling—simulating key automation tasks including business data extraction, contact enrichment, personalized outreach generation, and intelligent follow-up prioritization
  • Applied software-engineering principles such as iterative refinement, logic debugging, and functional validation to enhance the precision and adaptability of synthetic datasets across multiple industry verticals
  • Collaborated with AI models and human reviewers to identify logic gaps, improve output consistency, and establish scalable frameworks for reproducible testing and agent training
  • Contributed to the development of a reusable AI scenario library, enabling accelerated deployment, benchmarking, and product QA for enterprise-grade automation tools
DevOps Engineer
HNG Tech | Lagos
Jun 2024 - Aug 2024
  • Automated user and group creation, home directory setup, and password management using Bash scripts with error handling and logging for system administration tasks
  • Containerized full-stack web applications (React, FastAPI, PostgreSQL) using Docker and Nginx, ensuring proper proxy configurations and cloud deployment on AWS EC2 with domain setup and HTTPS redirection
  • Developed and deployed an email queue management and logging system using Python behind NGINX with RabbitMQ/Celery to automate email tasks and logging activities
  • Developed and wrote the documentation of a GitHub bot used to automate pull requests and deployments, and provide real-time status updates and resource cleanup
  • Automated deployment of full-stack applications using Ansible, managing PostgreSQL databases, messaging queues, and application configuration on cloud servers
$ ls ~/blog/