Datadog’s Post

What impact could it have on entrepreneurs if they requested less funding than their ideal target? How would this decision affect their businesses at various stages of growth when seeking investment? Balancing expectations between investors and business owners is crucial in managing the funding process effectively. We appreciate Arnaud Bonzom for his valuable insights shared with regional entrepreneurs, guiding us in supporting our clients and facilitating successful outcomes by ensuring alignment between investor expectations and the needs of business owners. #investors #entreprenurs #funding #fundraising XasaSERVICE Holdings

This is what happens when a bunch of senior engineers discuss deep tech for 4 hours straight ⚡ So many practical nuggets we cover throughout the cohort ⚡ no random boxes, but literally how systems are built in the real world. arpitbhayani.me/course #AsliEngineering #SystemDesign

Businesses are struggling with getting value faster with #ai . Getting access to compute resources without ringing up huge cloud bills and picking a core AI platform that helps navigate across the #mlops lifecycle are two pieces of advice that Alex Corvin, Engineering Manager in Red Hat’s AI business unit, provides.

a short 370-word blob (2 min read) i wrote for Datadog after attending GopherCon 2023 #go #golang #gophercon

Red Hat’s latest GenAI updates tell the story of a firm still staunchly focused on the needs of software engineers, systems architects and operations team staff. Let’s now ask what’s new, why does it matter and how much of what Red Hat does today still draws on its heritage? https://lnkd.in/eicSPd3H

I'm happy to formally introduce my publication "Performance engineering for the ordinary Barbie." You might have already seen a few blog posts in the past months published on there! My goal is to make complex and “hardcore” topics in performance engineering, like profiling, accessible and understandable to any holder of a technical role. One thing that inspired me to start writing and to create this publication is precisely because I faced a huge activation energy in order to get into the swing of things when I joined the profiling team at Datadog. This publication is for anyone interested in delving into the field of performance optimization who are not already domain experts. And please note: just because we are ordinary Barbies in the space of observability and performance, it does not mean we are ordinary people 🙂 If you like my work, please give this publication a follow! https://lnkd.in/e5hVxRrk #profiling #performanceoptimization #observability #datadog #datadoglife

I am reading site reliability engineering written by Google engineers. The principles defined are a great starting off point. However, your industry use case is fraught with security restraints, compliance reqs etc… Before we even talk about infrastructure how available are we suppose to be? Google has an interesting take on it which I won't go into detail. Many of the tools they used are baked into some modern orchestration systems in some fashion. The integration of testing includes maintaining coding standards so our performance does not degrade when our system grows linearly. This can come down to service system calls depending on latency reqs. Reliability through chaos engineering and other schools of thought. Still reading will share interesting tidbits. #softwareengineering #reliability

DYI work is very grounding and educational experience that can inform more intangible areas like software engineering and data science. For example, Dave Snowden’s Entangled Trios is applicable in both. With single person or entity, making progress is a very much uphill battle. Not impossible but the effort of each also would be more than twice than what they would need to contribute to the pair. And ideally, the pair should be of one quite experienced and confident person and another less experienced but compensating with energy and enthusiasm. A third person in not as beneficial if this they are simply trying to add in a similar direct contributions. But if they go solve ahead and “unblock” the pair, they can server as a turbo for the engine pair. Then, the nextnet-beneficial scaling would be adding another pair that shares the “unblocking” one across the pairs if possible or going for a parallel Entangled Trio. What do you think about this? What is your experience in forming software engineering or data science / ML engineering / data engineers teams?

The most robust, reliable, and productive uses of AI are when many models are used in coordination with each other, with "regular" programming mixed in. This leads to more capable, more reliable, and more interpretable AI systems. Most people building with AI already know this. But (unless you work for Google) the main barrier to realizing multi-step AI workloads is an infrastructure one. For the rest of us, we’re left creating an unwieldy mess of chained API calls to multiple providers, with many roundtrips in between. This state of affairs is stifling progress. Nobody wants to deal with more tooling and infrastructure… but everyone would benefit from simple, intuitive interfaces that abstract away a powerful system underneath. Substrate is the first inference API optimized for multi-step AI workloads. With Substrate, you can write less code, run more inference, and build high performance AI applications with zero infrastructure to manage. No tooling, no infrastructure – just elegant abstractions. Excited to support Ben Guo, Rob Cheung and the amazing Substrate team on their mission to democratize how AI applications are built.

On September 9, 1947, the concept of a 'computer bug' took on a whole new meaning when Grace Hopper and her team found a moth causing trouble in the Harvard Mark II. This incident was carefully logged, and the term 'bug' was forever immortalised in the world of computing. It's a reminder that sometimes, the smallest things can disrupt complex systems. As someone passionate about the history and future of technology, I love diving into these fascinating stories that highlight our journey as developers. If you've encountered any 'real-life bugs' in your code or have a favorite piece of tech trivia, I’d love to hear about it in the comments! #SoftwareEngineering #TechHistory #GraceHopper #Debugging"