Author: Sergio Lema

  • Layered Architecture in Java: A Practical Guide to Keeping Your Code Clean

    Layered Architecture in Java: A Practical Guide to Keeping Your Code Clean

    The post emphasizes the importance of structured programming to avoid spaghetti code, advocating for a layered architecture. It delineates three layers: Presentation, Business, and Data layers, each with distinct responsibilities. Defining a clear structure early in project development facilitates effective teamwork and ensures scalable, maintainable applications by keeping concerns separate.

  • 3 JVM Parameters You Must Know

    3 JVM Parameters You Must Know

    Proper configuration of JVM parameters significantly enhances the performance and stability of Java applications in production. Key areas include setting appropriate heap sizes, effectively managing out-of-memory scenarios, and selecting the right garbage collector based on workload needs. Implementing these optimizations ensures consistent performance during high-demand periods.

  • The CEO’s Guide to Choosing the Right Tech Stack

    The CEO’s Guide to Choosing the Right Tech Stack

    Choosing the right tech stack is crucial for product development. Prioritize team familiarity, market availability of talent, and suitability for the product. Avoid trendy but unfamiliar technologies and focus on what accelerates shipping and aligns with team capabilities. Aim for effective solutions rather than the best, ensuring quick market delivery.

  • Publish a Python Wheel to GCP Artifact Registry with Poetry

    Publish a Python Wheel to GCP Artifact Registry with Poetry

    In this article, I’m building a Python project that outputs a runnable file instead of a Docker image, as I need to directly communicate with GPU drivers. Using Poetry and GCP’s artifact registry, I must create and publish a wheel file, configuring dependencies, and deploying the project on a virtual machine, resolving issues with versioning…

  • Mastering Data Validation in Java Applications

    Mastering Data Validation in Java Applications

    The article emphasizes the importance of validating data before it enters the database to prevent issues like NullPointerExceptions and inconsistent data. It advocates for early validation at both the controller and domain model levels, using annotations and custom validators for cleaner, simpler code, ultimately leading to enhanced application reliability.

  • 3 Signs Your Website Is Slowing Down Your Company’s Growth

    3 Signs Your Website Is Slowing Down Your Company’s Growth

    In the early 2000s, I’ve learned that cluttered websites hinder user engagement. Key takeaways include integrating analytics to understand user behavior, ensuring fast loading times to avoid high bounce rates, and maintaining a modern, clean design to reflect professionalism. Impressions made through a website are crucial for business success.

  • Architecture, DevOps and Security: The 3 Pillars to Grow A Product

    Architecture, DevOps and Security: The 3 Pillars to Grow A Product

    A company’s success hinges on its product, which requires strong architecture, DevOps, and security from the start. Neglecting these areas leads to chaos and difficult scaling. Automating processes and maintaining security standards are essential for efficient growth. Investing in these pillars prevents costly issues, ensuring a healthier product lifecycle and company sustainability.

  • Python Unittest Mocking Constructors

    Python Unittest Mocking Constructors

    Writing effective unit tests can be challenging, especially with mocks. The post discusses issues with mocking constructors in Python’s unittest framework, suggesting that imports be structured differently to enable successful mocking. By importing the module instead of the class directly, the @patch decorator can function correctly, allowing for effective testing.

  • Debug Server Performance

    Debug Server Performance

    In this article, I compare the performance of an application hosted on AWS and Scaleway, revealing that AWS was significantly slower despite higher resources. Through testing various instance types and configurations, they determine that the issue lies in CPU performance and instance age impacting response times. Ultimately, a better instance type was found on AWS,…

  • Architecture for my Generative AI Application

    Architecture for my Generative AI Application

    In this article, I explore using AI image generation models accessed via platforms like Hugging Face but faces challenges with high GPU costs and inefficient resource management. The solution involves a web application and a backend service that auto-scales GPU usage via asynchronous messaging, ensuring resources are only used when necessary.