Google Cloud Profiler is a continuous profiling tool that helps analyze CPU and memory usage in production environments with minimal overhead. It provides insights into performance bottlenecks, enabling teams to optimize their applications for efficiency and cost savings.
When running workloads in Kubernetes that need to access Google Cloud resources, a common approach has been to use a service account JSON key stored in a secret. However, this method has security vulnerabilities. Recently, I transitioned to using **Workload Identity Federation (WID)**, which eliminates the need for JSON keys while ensuring secure access. Here’s why WID is a game-changer and what I learned during this migration. 🚀
📌 This document outlines my experience implementing a Kubernetes microservice using KEDA (Kubernetes Event-Driven Autoscaling) to scale based on Pub/Sub messages. The focus is on how KEDA enables efficient scaling of workloads in response to event-driven triggers and the key lessons I learned along the way.
Managing logs across multiple projects was challenging, requiring frequent context switching in GCP Logs Explorer. By implementing log scopes, we centralized logging into a single view, improving troubleshooting and monitoring. Using Terraform, we automated log scope creation, efficiently handling project limits and ensuring scalability. 🚀📊
A high CPU usage issue in a VM caused delays in data transfer from Datastore to BigQuery. Switching to a Pub/Sub-based approach improved scalability, efficiency, and reliability. 🚀🔄
I was tasked with setting up a new development environment for testing and development. It lacked the necessary data, so I had to carefully transfer it from one project to another. This document outlines my experience and the steps I took to transfer data between `Google Cloud Projects`, including `Cloud Storage buckets`, `Firestore (Datastore)`, and `BigQuery datasets`. This guide can be helpful when creating a new environment and seeding it with data from an existing project.
A practical guide on using cf-terraforming to automate Cloudflare resource management with Terraform
A project where I built and deployed a serverless API using Google Cloud Functions and Firestore, integrated with Cloud Build as CI/CD to deploy functions on every push to GitHub automatically. An API that can serve resume data in JSON format. I used Terraform to manage and provision cloud infrastructure.
A step-by-step guide to creating a static website on Google Cloud Platform using Terraform, Cloud Storage, Cloud CDN, and HTTPS load balancer
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