CircuitWall Consultancy

Transforming a Website with Cursor AI: A Success Story As a software engineer and tech enthusiast, I’m always excited to try new tools that promise to improve development workflows. Recently, I had the opportunity to use Cursor AI to upgrade this website, and the results were nothing short of impressive. In this post, I’ll share how Cursor AI helped transform this site from a basic portfolio into a modern, feature-rich platform.

At the NDSML Summit 2023, the premier annual event for the Nordic Data Science and Machine Learning community, I had the privilege of presenting “Elevating Your Existing Models to Vertex AI” alongside my colleague Lef Filippakis. Together, we shared our expertise in AI and cloud computing with an engaged audience. Vertex AI is Google Cloud’s unified platform for building and managing machine learning solutions throughout the entire ML lifecycle. It seamlessly integrates Google Cloud’s AI tools and services, providing comprehensive support for training, deployment, monitoring, and optimization of machine learning models.

I recently had the honor of presenting at the Data Innovation Summit 2022, the premier annual Data and AI event in the Nordic region. My presentation, titled “Scaling ML in One of Europe’s Hottest Fintech Companies,” resonated strongly with the audience and generated engaging discussions about the challenges and opportunities in scaling machine learning operations. Recognition in Nordic 100 I am deeply honored to be named to the Nordic 100 in Data, Analytics & AI list.

As a consultant, admitting “I don’t know” can be challenging. A few months ago, I began working as a DevSecOps engineer on a large Kafka (Confluent) installation for a bank, despite having only limited knowledge of Kafka at the time. I’m writing this article to share key insights gained from working on and tuning this multi-datacenter setup. While I may not cover every important topic, I welcome feedback to help improve this guide.

Organizations typically consider multi-datacenter setups for two main reasons: Business expansion into different geographical regions Enhanced reliability requirements that take precedence over pure performance When implementing a multi-datacenter setup, there are three critical aspects to consider during both normal operations and disaster scenarios: Consistency: Will data be lost if a datacenter fails and operations switch to another datacenter? Availability: Will a datacenter failure cause partitions to go offline? This can happen due to: No in-sync replicas being available Zookeeper cluster failing to form a quorum and elect new leaders Broker unavailability Performance: What are the expected latency and throughput characteristics?