# Javier Jiménez Molina > DevOps Engineer DevOps Engineer with more than four years of technical experience and a strong software development background. I work with CI/CD, Kubernetes, containers, Linux and automation to improve how applications are delivered and operated. **Role:** DevOps Engineer **Career direction:** Growing toward Platform & Cloud Engineering **Location:** Murcia, Spain **Language:** English [Website](https://javierjimenez.dev/en) [Complete Markdown profile](https://javierjimenez.dev/en/index.md) [Versión en español](https://javierjimenez.dev/es/index.md) **My focus:** Kubernetes, CI/CD, Docker, Linux, Automation I build and maintain delivery pipelines with Jenkins. I work with Kubernetes and troubleshoot production issues. I develop tools to audit and optimize resources. ## About me I'm Javier, a DevOps Engineer based in Murcia. I started out building applications and became interested in everything that makes them reliable to deliver and operate: pipelines, containers, observability and automation. I like understanding the whole system, investigating difficult problems and turning repetitive tasks into clearer processes. Outside work I build personal products and explore how AI can support engineering work. ### Curiosity beyond the screen I enjoy learning, collaborating and trying new things. Sport and travel help me change perspective. **In my spare time:** CrossFit, Climbing, Padel, Travel ## Professional experience My path connects software development with automation, continuous delivery and platform operations. ### Krimda — DevOps Engineer 2025 — present Current CI/CD and Kubernetes operations, focused on automation, deployment standardization and production troubleshooting. - Designed and maintained modular Jenkins pipelines with Groovy Shared Libraries to standardize deployments and reduce duplication. - Administered and troubleshot Kubernetes; handled Docker and Helm deployments and production incidents. - Developed scripts to audit resources by microservice and inform optimization proposals. - Managed binaries and dependencies with JFrog Artifactory integrated into the Bitbucket workflow. - Used Grafana, Prometheus and Graylog dashboards, metrics and logs to improve operational visibility. ### Capgemini — Software / DevOps Engineer 2021 — 2025 I started in Full-Stack development and gradually moved toward automation, CI/CD and DevOps. **Role progression:** Development → Automation → CI/CD → DevOps - Developed Java and Spring Boot microservices, plus React and Node.js applications and REST APIs. - Built Jenkins and GitHub Actions pipelines while moving toward automation and CI/CD. - Worked with Docker, Kubernetes and Helm; monitored environments with Rancher and Lens. - Deployed applications and managed resources on OVHCloud. - CI/CD improvements reduced deployment times by more than 80%. ## Concrete problems, practical solutions Real cases from CI/CD, automation and platform operations: the problem, how I approached it and what it brings to the team. ### A shared workflow for Python projects CI/CD · Standardization **Status:** Pipeline and Shared Library development A complete Python build and deployment workflow, reusable across projects through Jenkins Shared Libraries. **The challenge:** Bringing Python into the shared delivery flow without creating and maintaining a separate pipeline for every project. **What I did:** I developed a complete workflow for this new technology using Jenkins Shared Libraries, keeping reusable build and deployment logic in a common foundation. **What it brings:** One maintenance point for Python projects and a delivery flow consistent with the team's other technologies. **Case technologies:** Jenkins, Shared Libraries, Groovy, Python ### Configuration changes without rebuilding the application CI/CD · Developer Experience **Status:** Development and validation Validation of changes to values.yaml, application.properties and other configuration files to avoid unnecessary Jenkins builds. **The challenge:** A change to values.yaml or application.properties triggered a full build even when the application code had not changed. **What I did:** I developed pre-validation in the Shared Library to classify files in the exact commit and skip unnecessary builds. Classification fails closed on errors. I tested it across several technology generators and in one Jenkins run. **What it brings:** Less waiting for developers when adjusting configuration and less repeated work on Jenkins agents. **Estimate:** 13–25 h / day — Potential aggregate savings · 67–125 h / week Estimate for around 100 microservices (10 projects × 10): 4–5 weekly changes per microservice × 10–15 min per build, spread across 5 working days. This adds up CI agent execution time across projects, excluding deployments. **Case technologies:** Jenkins, Shared Libraries, Git, Helm ### Pull Requests that reach the team automatically Automation · Collaboration **Status:** Integration developed Bitbucket webhooks connected to Jenkins to notify reviewers through Slack, email and Microsoft Teams. **The challenge:** The team needed to hear about Pull Requests without manually checking Bitbucket or sending a separate message to every channel. **What I did:** I automated the Bitbucket → webhook → Jenkins flow and the subsequent notifications to the Slack channel, email and Microsoft Teams. **What it brings:** Review requests reach the team's working channels, reducing the need to chase manual notifications. **Case technologies:** Bitbucket, Webhooks, Jenkins, Slack, Email, Microsoft Teams ### From a Jenkins failure to a container in Kubernetes Operations · Troubleshooting **Status:** Incident resolution Troubleshooting build, deployment and Docker container execution issues in Kubernetes. **The challenge:** Delivery could stall during the build, deployment or container execution: each stage needed a different diagnosis. **What I did:** I resolved build and deployment failures in Jenkins pipelines and Docker container issues in Kubernetes, following the failure from the pipeline run to the application's behavior. **What it brings:** Restoring the delivery flow and helping the team identify whether a blockage comes from CI/CD or container execution. **Case technologies:** Jenkins, Docker, Kubernetes, Linux ### HTTP 500 errors with direct Slack notifications Observability · Alerting **Status:** Alerts configured Grafana alerts backed by Prometheus metrics to bring server errors into the team's working channel. **The challenge:** Server errors needed a visible signal for the team without relying on someone watching a dashboard. **What I did:** I configured Grafana alerts for HTTP 500 errors using Prometheus metrics and notifications to Slack channels. **What it brings:** Errors become operational notifications that the team can investigate from its usual working channel. **Case technologies:** Grafana, Prometheus, HTTP, Slack ### Resource auditing by microservice Kubernetes · Automation **Status:** Audit tooling developed Scripts to review Kubernetes resources and inform optimization proposals for each microservice. **The challenge:** Manual Kubernetes resource reviews made it harder to compare microservices and identify where to investigate adjustments. **What I did:** I developed scripts to audit resource usage by microservice and support configuration analysis in Kubernetes environments. **What it brings:** A repeatable basis for resource optimization proposals grounded in data from the cluster. **Case technologies:** Kubernetes, Bash, Linux ### Faster delivery at Capgemini CI/CD · Continuous improvement **Status:** Documented result CI/CD improvements that reduced deployment times by more than 80% during my transition toward DevOps. **The challenge:** The delivery process needed to shorten the time between development changes and deployment. **What I did:** I contributed to CI/CD improvements while moving from software development toward automation and DevOps at Capgemini. **What it brings:** The improvements reduced deployment times by more than 80%, making application delivery faster. **Documented result:** \>80% — Reduction in deployment time Documented result from my time at Capgemini. **Case technologies:** CI/CD, Automation ### Validating a Helm chart and its telemetry Kubernetes · Helm **Status:** Preparation and dry-run Finding an invalid HPA configuration during a dry-run and preparing the chart fix and telemetry integration. **The challenge:** A Helm OCI chart contained an invalid HPA specification that surfaced during pre-deployment validation. **What I did:** I found the issue during a dry-run and prepared the chart fix alongside a telemetry integration for local validation. **What it brings:** Identifying a configuration problem before deployment and preparing its fix. This case reached preparation and local validation. **Case technologies:** Helm, Kubernetes, OCI, HPA ### Diagnosing memory-related restarts in Kubernetes Kubernetes · Reliability **Status:** Analysis and proposal Analysis of out-of-memory restarts and proposed requests and limits adjustments based on observed behavior. **The challenge:** Containers were restarting due to insufficient memory, requiring an understanding of observed usage relative to configured resources. **What I did:** I analyzed restarts by relating requests and limits to application behavior and documented a proposed adjustment. **What it brings:** An evidence-based diagnosis to guide memory adjustments. No measured post-change improvement is recorded for this case. **Case technologies:** Kubernetes, Docker, Requests / Limits ## Projects A gallery of the personal products, platforms and tools I have built or continue to develop. ### MoneyFlow Web and mobile product A personal finance app with web and React Native clients. They share logic in a monorepo and use Supabase as the backend. The web and mobile clients share logic in a core package within a monorepo, so product rules do not have to be duplicated across interfaces. Supabase provides authentication, PostgreSQL and Edge Functions. The product includes accounts, transactions, transfers, recurring entries and analytics dashboards; Gemini assists natural-language entry. **Category:** Product #### What it includes - React web app and React Native mobile app - Shared core package in a monorepo - Supabase, PostgreSQL and Edge Functions - AI-assisted natural-language transaction entry **Technologies:** React, React Native, TypeScript, Supabase, PostgreSQL, Gemini API ### Self-hosted Knowledge Platform Self-hosted platform An Outline-based documentation platform with custom extensions, operated on Linux and container infrastructure. An Outline-based self-hosted project: reverse proxy, application, PostgreSQL and Redis run in containers on Linux. Alongside the deployment, I work on custom extensions and their change and CI/CD workflow. Print Studio belongs to the same ecosystem. **Category:** Platform #### What it includes - Docker deployment and reverse proxy - PostgreSQL and Redis - Custom extensions and CI/CD workflow **Technologies:** Linux, Docker, PostgreSQL, Redis, CI/CD ### Print Studio Product extension An extension integrated with the knowledge platform to format documents and prepare them for printing or export. An extension integrated into the knowledge platform to prepare and format documents for printing or export. It is developed alongside the self-hosted application and shares its workflow: code changes, container deployment and CI/CD. **Category:** Product #### What it includes - Application customization - Containerized deployment - CI/CD integration **Technologies:** Web development, Docker, CI/CD ### Hermes Agent Personal automation · evolving A personal environment for working with AI agents: persistent profiles, skills, task memory and tool integrations. A personal lab for experimenting with agents: profiles, persistent context, skills and task journals. I am exploring API and MCP tool integrations, local validation and explicit boundaries before external actions. It is still developing, not a production platform. **Category:** Automation #### What it includes - Context organization and task journaling - Integrations through APIs and MCP tools - Local validation and explicit boundaries for external actions **Technologies:** LLMs, MCP, APIs, Automation ### Personal Portfolio Personal website This bilingual site presents my career, projects and skills using Astro for the page architecture and React for interactive elements. This site organizes bilingual content and reusable components. Astro generates the pages, while React is reserved for interactions that need it. It includes accessible navigation, a command menu and per-language metadata; the project gallery and blog have dedicated routes. **Category:** Web #### What it includes - Spanish and English routes with dedicated metadata - Accessible navigation and command menu - Static content with interaction only where useful **Technologies:** Astro, React, TypeScript, Tailwind CSS, i18n ### Services Site Services website A bilingual technology-services landing page built around reusable structure, internationalization and SEO fundamentals. A Spanish/English landing page for technology services, built on a shared structure across both languages. Its technical SEO foundation includes OpenGraph, canonical URLs, hreflang, a sitemap and robots.txt, along with reusable components and environment configuration. **Category:** Web #### What it includes - Spanish and English content - OpenGraph, canonical, hreflang and sitemap - Reusable components and environment configuration **Technologies:** Astro, TypeScript, CSS, i18n, SEO ## Technical skills Technologies I use, with applied experience distinguished from areas I am still developing. ### DevOps & CI/CD Continuous delivery and deployment standardization. - Jenkins / Shared Libraries — Applied experience - Git / Bitbucket — Strong - GitHub Actions — Applied experience - Artifactory — Applied experience ### Containers & platform Containerized applications and cluster operations. - Docker — Strong - Kubernetes — Applied experience - Helm — Applied experience - Rancher — Applied experience ### Observability Metrics, logs and production troubleshooting. - Prometheus — Applied experience - Grafana — Applied experience - Graylog — Applied experience ### Development Software engineering background across the delivery cycle. - Java / Spring Boot — Applied experience - React — Applied experience - Node.js — Applied experience - TypeScript — Applied experience ### Cloud & infrastructure Growth path toward Platform and Cloud Engineering. - Linux — Strong - AWS — Developing - Terraform — Developing ### Automation Scripts, integrations and reducing manual work. - Bash / Shell — Strong - Groovy — Applied experience - REST APIs / Webhooks — Applied experience - Python — Developing ### Applied AI & harness engineering Personal exploration of agents: persistent context, tools and validation. - LLMs and tool workflows — Developing - MCP tools — Developing - Harness engineering — Developing - Context design — Developing - Hermes Agent — Developing - Codex — Developing - Gemini — Developing - OpenCode — Developing ## Education ### Bachelor's Degree in Telematics Engineering Polytechnic University of Cartagena · 2017 — 2021 ### Additional training - Continuous Delivery & DevOps · University of Minnesota - Docker Advanced · Pluralsight - Linux Advanced · Pluralsight ## Blog Notes on DevOps, engineering and personal projects. ### From software development to DevOps: seeing the whole system **Category:** Career path [Original article](https://javierjimenez.dev/en/blog/del-desarrollo-a-devops) How a software development background led me toward delivery, operations and automation. I started by building applications. Working on their delivery showed me that writing code was only part of the system: pipelines, environments, deployment and understanding what happened afterwards mattered too. That interest gradually brought me toward automation, CI/CD and DevOps. Today I work with Jenkins, containers and Kubernetes, while keeping the perspective of the people developing the applications being operated. I care about reducing manual work and making delivery processes understandable and repeatable. Platform Engineering is the direction in which I want to keep growing. ### Building a self-hosted knowledge platform **Category:** Personal project [Original article](https://javierjimenez.dev/en/blog/plataforma-de-conocimiento-autoalojada) A look at Outline, containers, data services and custom extensions in a personal project. My personal knowledge platform is based on Outline. I run it on Linux and containers, with a reverse proxy, PostgreSQL and Redis. Alongside deployment, I have worked on custom extensions and their CI/CD workflow. Print Studio grew out of an extension that prepares documents for printing or export. The project lets me practise an end-to-end view: application, infrastructure, changes and operations. ## Contact If you’re looking for someone to work on CI/CD, Kubernetes, infrastructure, AI, integration, and automation, I’d love to connect. Let’s make delivery clearer, more automated and more reliable. - [contact@javierjimenez.dev](mailto:contact@javierjimenez.dev) - [LinkedIn](https://www.linkedin.com/in/javierjimenezmolina) - [GitHub](https://github.com/javij98)