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Week 13 of #100DaysOfCode: Completing Spring Microservices and Starting JUnit 5

Introduction This week was another challenging but rewarding part of my #100DaysOfCode journey. I started the week by learning about Docker and containerized Microservices , exploring how containers differ from Virtual Machines, how Docker images and containers work, and how Docker helps package applications and their dependencies consistently. I then moved into scaling Dockerized Microservices ,…

Week 13 of the #100DaysOfCode journey brought challenging yet rewarding progress in learning about Docker, containerized Microservices, and starting JUnit 5 for software testing. The week began with understanding the basics of Docker, containerized Microservices, and how they differ from Virtual Machines. Key takeaways included Docker's benefits in scaling applications, portability, and reusability, as well as its role in deploying Microservices consistently.

Autoscaling and container orchestration were explored next, with a focus on Apache Mesos, Marathon, resource allocation, and managing Microservices at scale. It became evident that managing Microservices manually becomes challenging as their number grows, and orchestration tools provide automation and abstraction to handle resources, deployments, and failures more efficiently.

As the week concluded, I officially completed the Building Spring with Microservices course, scoring 85% on the exam. The journey, marked by dedication and perseverance, has instilled a stronger sense of accomplishment in becoming a better backend engineer. There's still more learning, building, and improvement ahead, but the progress made thus far highlights the importance of continuous growth and sharing the journey with the supportive community.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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My Extraction Score Was 0.08 and the Model Was Innocent: Rebuilding the Ruler

Update — v0.3.1 released. CauterRule is now live on GitHub and PyPI . It turns repeated agent failures into permanent standing rules — extract, replay-test, promote.

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