Architecting SAP for resilience: A business continuity guide for IT leaders
Key takeaways: Achieving SAP resilience requires moving beyond basic hardware failovers to address patching, upgrades and regional outages. IT leaders must balance Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) with operational complexity. A robust architecture covers local High Availability (HA) and regional Disaster Recovery (DR) to ensure core business continuity. When an…
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The path to a sovereign autonomous enterprise: Why open source is your clean core advantage
Key Takeaways Building an autonomous SAP environment requires balancing rapid AI innovation with strict data control and compliance. Keeping your SAP core clean relies on hybrid integration, private AI deployment, and open virtualization strategies. Open-source architecture provides true technological sovereignty, preventing lock-in and eliminating rising hypervisor costs. Managing…
Managing multiple EKS clusters: why cluster #3 is the wall
Do the arithmetic before you read the rest of this. Count the people on your team who need access to a cluster. Multiply by the number of clusters you run. That result is how many access decisions somebody is maintaining by hand today. Now add one cluster and run it again. The jump between those […] The post Managing multiple EKS clusters: why cluster #3 is the wall appeared first on SUSE…
From SAP data to operational insight: Modernizing Day-Two SAP operations with SUSE Trento
Key takeaways: Day-Two Operations are critical for maintaining SAP environment health, security and configuration consistency. SUSE Trento automates discovery, prevents configuration drift and standardizes high-risk administrative workflows. Integrating AI safely through the Model Context Protocol (MCP) exposes hidden or multi-view Trento data through direct, unified querying. Getting an SAP…
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Bringing enterprise Linux to the robotics frontier: ROS2 adds Red Hat Enterprise Linux as a tier-1 supported platform
The convergence of enterprise IT and physical computing is accelerating. As artificial intelligence transitions from purely digital environments into autonomous systems, industrial automation, and smart edge devices, the software foundation behind these systems must be as resilient as the physical machines themselves.To power this next generation of intelligent systems, we’re pleased that Red Hat…
Best practices guide for customizing Gemini models via Reinforcement Learning (RL)
Reinforcement learning (RL) has been a keystone of modern LLM post-training, but it demands large training clusters and access to model internals that external customers can't have with proprietary models like Gemini. So here at Google Cloud, we packaged it into a managed RL fine-tuning service (RLFT service) — you bring prompts and a reward function; we handle the infrastructure and the…
Breaking the AI productivity paradox: an intelligent migration factory to modernize infrastructure and applications
The rise of generative AI promised a silver bullet, but for most enterprises, especially banks, digital transformation remains a slow, complex, and costly endeavor. Early reports suggested massive developer productivity gains. But when AI is applied to complex enterprise systems, organizations often collide with what we call the AI productivity paradox.According to a Stanford software engineering…
AI Reliability Engineering for Dependable Humans | Solo.io
Learn AI reliability engineering (AIRE): how AI agents help SRE and platform teams triage incidents faster and stay dependable.