Decodable’s Post

Good article for beginners. Scala is used by companies like Google, Twitter, LinkedIn, and others for applications in finance, content management, and more. It’s also the language of choice for Apache Spark. https://lnkd.in/gahC3rUV

That’s huge and part of what Scala always has had missing: business centricity. There is another impactful problem in that space: http Servers (http4s is hard to use without very specific and deep knowledge, play is not continued iirc). what python gets right: it’s damn easy to use and get started. https://lnkd.in/ecitr4wZ

Simple solutions do exist for complex problems! Today, one of the critical Python lambda code in AWS was timing out suddenly. It is a fairly complex process that tests certain functionality and spits out metrics with test results to a spreadsheet. Couple of us took a look at it, analyzed it and tinkered with it. With multiple changes (complex over-thinking), performance tuning certain parts of code, it was as stubborn as a rock and timed out. Revisited the issue after taking some time off from it. Light bulb moment arrived !!! To account for the data growth, we increased memory & storage on the Lambda, after which it ran smooth to completion. Lessons 're-learnt': Take a break, break down the problem fully, think straight and simple for solutions.

Stream processing shines when flexibility meets complexity. In many large organizations, where legacy infrastructure or custom systems are still in play, off-the-shelf tools may not be enough. That’s when teams turn to custom code in languages like Python or Java. With stream processing, these custom jobs act like microservices, continuously processing events in real-time and applying business-specific logic. This allows for dynamic responses—such as triggering API calls or making real-time decisions. In this landscape, stream processing becomes the engine that turns raw data into actionable insights. Decodable’s CEO and Founder, Eric Sammer takes a deeper look at real-time ETL and stream processing in this on demand tech talk. Watch it here 📺 https://dcdbl.co/4846upp

This month, Java dives deeper into AI, and Google finds itself in a game of corporate Jenga: https://lnkd.in/dAYJ8nDR. In this edition of our digest: ☕ Oracle’s ambitious AI plans: discover how they’re shaping the future of Java; 🤖 Microsoft’s AI-powered coding companion: a game-changer for developers; 📉 Google’s potential tech breakup drama: what it could mean for the industry. Buckle up for a thrilling journey through the ever-evolving landscape of Java technology—more exciting than your average debugging session! 👉 Read it now and subscribe to the monthly updates. #AvengaInsights #JavaDigest #Java

Join this webinar with Oracle experts as they guide you through the process of leveraging #Java, Spring Boot, and the innovative Spring AI APIs to create next-generation applications. https://lnkd.in/dWzMfTPF

Join this webinar with Oracle experts as they guide you through the process of leveraging #Java, Spring Boot, and the innovative Spring AI APIs to create next-generation applications. https://lnkd.in/dGKdW3tS

Join this webinar with Oracle experts as they guide you through the process of leveraging #Java, Spring Boot, and the innovative Spring AI APIs to create next-generation applications. https://lnkd.in/gaQCAGX9

How do teams approach Scala in practice? - Purely functional Scala leads with 38% of projects. - Regular stdlib + utils Scala follows closely at 35%. - Generic-heavy, type-level Scala accounts for 20%. - Pythonish/Java-like Scala rounds it out at 7%. #ScalaSurvey

Join this webinar with Oracle experts as they guide you through the process of leveraging #Java, Spring Boot, and the innovative Spring AI APIs to create next-generation applications. https://lnkd.in/gxcPgA_9