February 21, 2024

[ad_1] Building an effective machine learning pipeline is an essential part of the end-to-end MLOps lifecycle, which follows up the concept of building reliable data pipelines by applying DataOps, as explained in our previous blog post. A pipeline for machine learning is a set of instructions that manages the data flow into and out of […]

[ad_1] With more than 20 years of field experience and working with the leading IT partners, Digital Architects Zurich developed a blueprint to support digital transformation. In this blog post, we will present this blueprint for the Digital Highway for reliable and continuous software delivery and operations. The challenge of successful Digital Transformation In order

[ad_1] According to Reuters, ChatGPT, the popular chatbot from OpenAI, is estimated to have reached 100 million monthly active users in January, just two months after launch, making it the fastest-growing consumer application in history. While this is phenomenal news, ChatGPT also crashed repeatedly, struggling with the usage load. OpenAI then announced a $20 monthly

[ad_1] If you let a software engineer come up with an ideal set-up for application operations, you will most likely hear about a concept that is very similar to that of Site Reliability Engineering (SRE) as Ben Treynor, VP of engineering at Google and founder of Google’s SRE team, describes.  The motivation to introduce and define such a role is based on conflicting goals in modern operating models. Two examples of such conflicts

[ad_1] We have already touched on multiple points of the Machine Learning lifecycles in previous blog posts and our Next Generation Data & AI Journey powered by MLOps. In the last post, we talked about effective Data Science & Machine Learning pipelines. In this blog post, we will dive a little deeper into the quality

[ad_1] You certainly have heard of a company named Google. The IT giant was among the first pioneers of Site Reliability Engineering (SRE) . After making its proofs within Google’s production systems, the concept gained a lot of attraction around the Software Engineering community. At Digital Architects Zurich, we understand Site Reliability Engineering as a fundamental concept, as we explained in a previous

[ad_1] In the ever-evolving field of life sciences, the emergence of Large Language Models (LLMs) has brought about a revolutionary shift in how data can be processed, analyzed, and harnessed. LLMs, powered by state-of-the-art natural language processing (NLP) techniques, are able to generate and manipulate vast amounts of scientific text and data. By leveraging their

[ad_1] An open Observability-based instrumentation & AI-able streaming architecture to pilot the Digital Highway We introduced, in a previous blogpost, the high-level pattern of the digital highway suggested by Digital Architects Zurich to tackle the following challenge: “Ensuring SLOs in the age of digital transformation, Cloud & DevOps while keeping budget under control and leveraging

[ad_1] Are you fascinated by the recent hype around data and artificial intelligence (AI)? Apart from leveraging external tools like Chat GPT, are you wondering how to implement your own machine learning (ML) projects in your organization? And how do you take projects from the PoC and experimentation stage into production, including deploying and continuously

[ad_1] Digital Transformation advocates, initiators and suitors (DevOps and Agile to name the most prominent) are all insisting on the importance of the culture transformation to assure the success of such a demanding and transversal process. However, the way to attack this culture transformation remains a very volatile field of experimentation. In this note we try to shed some light on how Socrates