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The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!

Diving into JTAG - Debugging (Part 2)

As noted in my previous article Diving into JTAG protocol. Part 1 — Overview, JTAG was initially developed for testing integrated circuits and printed circuit boards. However, its potential for debugging was realized over time, and now JTAG has become the standard protocol for microcontroller debugging. Many Firmware and Embedded engineers first encountered it in this particular context.

Telco-grade Sylva-compliant Canonical platforms

In December 2023, Canonical joined the Sylva project of Linux Foundation Europe to provide fully open-source and upstream telco platform solutions to the project. Sylva aims to tackle the fragmentation in telco cloud technologies and the vendor lock-in caused by proprietary platform solutions, by defining a common validation software framework for telco core and edge clouds.

Improving mobile performance, from slow screens to app start time

Based on our experience working with thousands of mobile developer teams, we developed a mobile monitoring maturity curve here at Sentry. We hypothesized that once teams achieved stability and were no longer firefighting and fixing crashes, they’d shift to streamlining workflows and eventually focus more on optimizing mobile app performance. In a recent workshop, we asked mobile devs where they fell on the curve. The results were surprising.

Optimal Parking Solutions for Smooth Operations

The integration of cutting-edge technology and modern mobility trends is reshaping the landscape of parking solutions, introducing groundbreaking enhancements to the parking experience for all involved. This evolution in parking solutions not only serves the customer's growing needs but also offers significant benefits to facility operators and owners. Addressing the complexities of parking operations requires a well-thought-out strategy that ensures smooth traffic flow, sustainability, and adherence to regulations. This article delves into the latest solutions that are revolutionizing optimal parking solutions.

FOSDEM - Costa Tsaousis: Netdata Open Source Distributed Observability Pipeline Journey & Challenges

FOSDEM - Costa Tsaousis: Netdata Open Source Distributed Observability Pipeline Journey & Challenges ABSTRACT: Netdata is a powerful open-source, distributed observability pipeline designed to provide higher fidelity, easier scalability, and a lower cost of ownership compared to traditional monitoring solutions. This presentation will offer an in-depth overview of the journey we've undertaken in building Netdata, highlighting the challenges we've faced and the innovative solutions we've developed to address them.

Top 5 Outcomes CIOs Need to Accomplish by 2025: Driving Business Value Through Technology

In January 2024, I published findings from some of my recent research as, “Top 5 Outcomes CIOs Need to Achieve by 2025: Driving Business Value Through Technology.” By focusing on these five key outcomes, CIOs can ensure that their technology investments directly contribute to business growth, resilience, and competitive advantage in the years leading up to 2025.

Aiven workshop: Build a movie recommendation app with TensorFlow and pgvector

Learn how to create a movie recommendation web app, using PostgreSQL® and pgvector. We'll work together to build a movie recommendation system from start to finish, utilizing NodeJS, TensorFlow, and PostgreSQL’s extension pgvector. We'll guide you through the process of creating the vector embeddings using TensorFlow right on your laptop. Additionally, we'll leverage pg-promise to efficiently handle bulk row inserts, and we'll explore the usage of Next.js for a full-stack project. By the end of the workshop, you'll have a fully functional project that generates movie recommendations.

Advancing MLOps with JFrog and Qwak

Modern AI applications are having a dramatic impact on our industry, but there are still certain hurdles when it comes to bringing ML models to production. The process of building ML models is so complex and time-intensive that many data scientists still struggle to turn concepts into production-ready models. Bridging the gap between MLOps and DevSecOps workflows is key to streamlining this process.