How 3 Java Champions are using GitHub Copilot :
https://t.co/sChkxIb2Nc
Learn from my friends @vlad_mihalcea , @patbaumgartner and @FrankDelporte and get advices, tips, and best practices !
Argo CD Architecture Explained 🚀
By the end of this blog,
You will understand how Argo CD actually works under the hood.
It covers,
- Core components and what they really do
- How they communicate and sync changes
- How Argo CD stores data and how to back it up properly
- How to run Argo CD in high availability mode
- Security and monitoring (Prometheus + Grafana)
and more..
𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗚𝘂𝗶𝗱𝗲: https://t.co/eInfslfQ0E
Over to you 👇
How are you using Argo CD today?
What is the key issue you faced in mnaging ArgoCD
Share it in the comments below.
#devops #gitops
The CI/CD Pipeline I Built Helped Me Understand DevOps End-to-End
One of the most valuable projects in my DevOps learning journey was building an end-to-end CI/CD pipeline on AWS.
It wasn't just about deploying an application it was about understanding how every stage contributes to a reliable software delivery process.
Project Workflow:
Developer pushes code to GitHub
⬇️
Jenkins triggers the pipeline
⬇️
Build & Unit Tests
⬇️
SonarQube checks code quality
⬇️
OWASP Dependency Check scans third-party libraries
⬇️
Docker image is built
⬇️
Trivy scans the container image for known vulnerabilities (CVEs)
⬇️
Image is pushed to Amazon ECR
⬇️
Helm values.yaml is updated with the new image tag
⬇️
Argo CD detects the Git change and synchronizes the Kubernetes cluster
⬇️
Application is deployed to Kubernetes
What I Learned:
Building the pipeline taught me that DevOps isn't just about deployment.
It's about automation | security | observability | reliability | repeatability.
Best Practices
✅ Automate every deployment.
✅ Fail the pipeline early when quality or security checks fail.
✅ Store infrastructure and deployment configuration in Git.
Question
Which stage do you think adds the most value in a CI/CD pipeline?
ESTO ES JODIDAMENTE INCREÍBLE
un dev en solitario acaba de abrir el código de un reemplazo 100% GRATIS de ElevenLabs que se ejecuta completamente en tu propia máquina.
el repo de GitHub está en 19.4K estrellas.
te permite:
→ clonar una voz desde un clip de referencia limpio
→ doblar cualquier video a 646 idiomas
→ generar audiolibros, dictado, transcripción
→ elegir entre 14 motores TTS en lugar de uno
ElevenLabs soporta 32 idiomas. esto hace 646.
sin cobro por carácter. sin límites de uso. ningún audio sale nunca de tu computadora.
guarda esto para después.
os dejo el repo abajo
Clean Architecture vs Onion Architecture
𝗖𝗹𝗲𝗮𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 organizes an application around its business rules and use cases, keeping them independent from external technologies.
The architecture typically separates entities, use cases, interface adapters, and frameworks or infrastructure. Dependencies point inward toward the core, helping keep business logic independent from databases, frameworks, UI, and external services. The focus is on separation of concerns, testability, and maintaining a stable application core.
𝗢𝗻𝗶𝗼𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 also places the domain model at the center and pushes infrastructure concerns toward the outside.
The core domain contains the most important business rules, while application services surround it and infrastructure sits in the outer layers. Dependencies point toward the center, allowing the domain to remain independent from databases, frameworks, and external systems.
Clean Architecture emphasizes use cases and a structured separation between business rules, adapters, and infrastructure. Onion Architecture emphasizes the domain model at the center with dependencies flowing inward.
Both aim to protect business logic from infrastructure. The key difference is mainly how the architecture organizes and describes those boundaries.
What else would you add?
📘 Mastering Software Architectures:
https://t.co/rQ5uqOjO5c
➕ Follow me ( @e_opore ) to improve at software architecture.
🐍 Python Data Structures Made Easy! 💻📚
Lists, Tuples, Sets, Dictionaries, Strings, Ranges, Frozensets & more — all explained in one simple visual guide! 🚀
Save this post for quick Python revision and use it whenever you're learning or practicing Python. 🔖