The GitLab Duo Agentic Platform (DAP) workshop/bootcamp took place on 24-25 June 2026. GitLab Duo Agentic Platform (DAP) was a workshop/bootcamp where GitLab DAP technical architects and engineers wanted to exhibit/train us on their new DAP feature in GitLab. The event was focused on DevOps engineers and developers in general. The event took place at Codecentric Tech Base in Solingen, a small industrial town next to Düsseldorf.
Xopero Software is officially expanding into Germany, bringing its cyber resilience solutions directly to the DACH market. With the launch of its new Berlin branch, the company has established its local presence and introduced its growing regional partner network.
The automotive industry is moving toward software-defined vehicles (SDVs), which makes software central to how vehicles are designed, function, and are maintained over their lifecycle. But the industry's hardware-centric roots mean software's real challenges are still often underestimated. This shows up in how companies are organized, how they develop products, and how they allocate resources; hindering SDVs from reaching their full potential.
Recently I got a sneak preview about the future of software development in an interesting show – the world according to tool vendors ... The new mantra is all around orchestrated agents, working 24x7, conducted by a single human developer, with access to all knowledge being used to train the AI model, fixing security flaws faster than ever and generate new applications quicker and more reliable than ever.
Recently, we reached an important milestone: we became ISO 27001 certified. To be completely honest, we did not start this process from scratch. Information security had already been an important topic for us for quite some time. Over the years, we had established many processes, policies, and ways of working that were already aligned with ISO 27001 principles. Due to the expectations of our customers and the nature of our business, structured processes, risk awareness, and clear responsibilities were not new concepts to us.
The automotive industry has long embraced model-driven development (MDD) as a foundational methodology for designing and implementing vehicle software systems, particularly in the context of embedded control systems. While MDD has proven effective in developing traditional embedded systems, its limitations become pronounced in the shift toward SDVs, where software complexity rivals or exceeds that of hardware.
The transition to Software-Defined Vehicles (SDVs) mirrors many principles found in the Internet of Things (IoT), particularly in how both domains shift from dedicated hardware to flexible, software-driven architectures. A key parallel lies in the use of generic CPUs for processing, where software transforms raw inputs into intelligent sensor-like functionality. This approach decouples physical hardware from specific behaviors, enabling greater adaptability and scalability. In SDVs, this convergence allows centralized compute platforms to handle sensor data through software algorithms, much like IoT edge devices turn basic sensors into programmable, context-aware components.
The transition to software-defined vehicles (SDVs) elevates software as a pivotal asset in automotive innovation, yet many organizations cling to a cost-controlling paradigm inherited from hardware-dominated eras, potentially undermining long-term competitiveness. This approach impedes with the need for strategic investments in scalable software architectures, ecosystems, and talent. In this blog, we delve into the entrenched cost-focused mindset, its detrimental impacts on SDV advancement, and the essential transformations to foster sustainable growth in a software-centric industry.
A customer was struggling with a DevSecOps environment built on a patchwork of custom scripts. Over time, this setup became increasingly difficult to maintain, less efficient and harder to scale. Through focused consultation and a strategic redesign, we delivered a modern, stable and future-proof DevSecOps solution designed for long-term performance.
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