Systems | Development | Analytics | API | Testing

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Navigating the Skies of Entrepreneurship: How Building a Software Startup Mirrors Flying a Small Plane

Exploring the parallels between piloting a small plane and building a software startup, emphasizing preparation, adaptability, teamwork, and data-driven decision-making for success.

Benchmarking llama.cpp on Arm Neoverse-based AWS Graviton instances with ClearML

By Erez Schnaider, Technical Product Marketing Manager, ClearML In a previous blog post, we demonstrated how easy it is to leverage Arm Neoverse-based Graviton instances on AWS to run training workloads. In this post, we’ll explore how ClearML simplifies the management and deployment of LLM inference using llama.cpp on Arm-based instances and helps deliver up to 4x performance compared to x86 alternatives on AWS. (Want to run llama.cpp directly?

Demo | Snowflake Data Clean Rooms

Snowflake Data Clean Rooms empower organizations to collaborate on data in a privacy-conscious way directly within Snowflake. With an intuitive interface and a focus on simplifying secure data sharing, Snowflake Data Clean Rooms enables businesses to build and use clean rooms seamlessly, leveraging Snowflake’s powerful data platform. This solution eliminates unnecessary complexity and additional access fees, ensuring organizations can focus on deriving insights while maintaining data privacy. Learn more about how Snowflake Data Clean Rooms support privacy-preserving collaboration in this blog.

Optimizing Supply Chains with Data Streaming and Generative AI

It’s a truism that global supply chains are complex. The process of sourcing raw materials, transforming them into finished products, and distributing them to customers encompasses numerous systems (e.g., ERPs, WMSs, and TMSs). All systems within “the supply chain” are trending in the same direction; they’re aiming to be more efficient, resilient, and agile. Various technological developments have facilitated this directional trend.

Why shift-right testing brings real results

Shift-left testing gets all the attention, but it’s shift-right that reveals what truly works. At @BlaBlaCar, Quality Assurance Manager @Rémy Gronencheld explains why testing in production is critical for real-world success: Shift-left: Build with confidence but rely on assumptions. Shift-right: Test against the unpredictable—low connections, real devices, and user behavior. The reality? Combining both approaches lets teams take calculated risks without sacrificing quality.

How to Improve Release Quality Throughput

Automation is like slicing through butter—smooth and time-saving. But how can you maximize your results without driving your developers up the wall? @Lori Henderson shares how they’ve boosted first-time releases and decreased hot fixes by blending automation with peer testing. Trust us, less manual work + quality throughput = happy developers.