🌱 Welcome to Dev Pollinate#
Dev Pollinate is where I document my DevOps journey, share lessons learned, and explore innovative ideas in DevOps engineering, Continuos Integration and Continuous Delivery and Ways of working.
I created Dev Pollinate to document my personal growth in the world of DevOps, as well as to contribute to the broader community by sharing valuable insights. I believe in the power of collaboration and continuous learning, and this blog serves as both a record of my journey and a resource for those looking to enhance their DevOps practices.
🔥 What You’ll Find Here#
🔹 Hands-on Tutorials – Step-by-step guides on automation, CI/CD practices and implementation.
🔹 DevOps Transformation Insights – Real-world challenges and strategies for modernizing engineering workflows.
🔹 Project Case Studies – Deep dives into automation projects, tool integrations, and best practices.
🔹 Ideas & Discussions – Exploring the future of DevOps, infrastructure as code, and site reliability.
🚀 Featured Projects#
- 🔹 Data Warehouse (In Progress) – Building a data warehouse for business analytics utilizing solutions.
- 🔹 Server Cloning Automation (Completed) – Automated the server cloning process and with return value of time.
- 🔹 Continuous Delivery for Puppet (Completed) – Automated deployments with canary approach.
💬 Join the Conversation#
Dev Pollinate is all about collaboration and shared learning. If you’re passionate about DevOps, cloud engineering, or automation, let’s connect!
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🛠 Overview Puppet CD4PE (Continuous Delivery for Puppet Enterprise) was implemented to streamline the Puppet code deployment lifecycle. This project integrated GitLab with Puppet CD4PE to enable:
Automated code validation and testing. Environment promotion pipelines. Integration with approval workflows. ⚡ Key Features GitOps Integration: Seamless connection between GitLab and Puppet CD4PE. Automated Testing: Enforced code quality checks using RSpec and Rubocop. Pipeline Automation: Configured multi-stage pipelines for development, testing, and production.
🛠 Overview The Server Cloning Automation project was developed to streamline the rebuilding and cleaning of hosts in a financial transaction environment. Previously, the team had to manually clean up test environments, which was a time-consuming process that took weeks to complete. This project leverages GitLab, Pipelines, and Runners to automate critical tasks such as:
Registry Host Level Cleanup: Automatically cleaning up registry entries from previous configurations to ensure a clean environment for the next deployment. Microsoft SQL Server Cleanup: Automated cleanup of SQL Server instances, removing old configurations and ensuring the database environment is ready for new deployments. ⚡ Key Features GitLab Integration: GitLab CI/CD pipelines and runners manage the automation tasks, providing seamless integration and version control. Registry Host Cleanup: Uses custom scripts in the pipeline to identify and remove outdated registry entries, ensuring hosts are clean for new configurations. SQL Server Cleanup: Automates the cleanup of Microsoft SQL Server, removing obsolete data and resetting configurations to improve performance and security. Automation of Rebuilds: Fully automated host rebuild process using pipelines for environment consistency and scalability. Test Environment Optimization: Reduces the time spent cleaning test environments from weeks to hours, improving overall efficiency and throughput. 🚀 Benefits Efficiency: Significantly reduced manual intervention by automating the host rebuild and cleanup processes. Consistency: Ensured consistent host environments by automating cleanup tasks, eliminating human error. Scalability: Streamlined the process for scaling the deployment of hosts, allowing the environment to grow efficiently without compromising quality. Time Savings: What previously took weeks to clean up in the test environment is now accomplished in hours, accelerating development and testing cycles. 🎯 Goals Achieved Successfully automated the host rebuild process for Postilion environments. Integrated GitLab Pipelines and Runners to handle complex tasks like registry cleanup and SQL Server reset. Reduced test environment cleanup time from weeks to hours, enabling faster iterations and deployments. Improved overall testing efficiency and reduced downtime for development teams.