#tpc-ds

#tpc-ds

When civilian banks, logistics platforms, and payment processors share physical data center infrastructure with military AI systems, those facilities become legitimate military targets under international humanitarian law - and the civilian services housed inside lose their legal protection.

DataBahn's AI-driven connectors automatically normalize, enrich, and route telemetry from more than 500 sources to Microsoft Sentinel. DataBahn's Cruz AI engine determines which data to send to the analytics tier and which to the Sentinel data lake for long-term storage. Customers report cost savings of up to 60 percent on Sentinel ingestion thanks to this intelligent tiering mechanism.

Imagine you're selecting an influencer to work with on your new campaign. You've narrowed it down to two, both in the right area, both creating the right sort of content. One has 24.6 million subscribers, the other 1.4 million. Which do you choose? Now imagine you could find out the first had 8.7 million unique viewers last month, while the second had 9.9 million. Do you want to change your mind?

Developers have spent the past decade trying to forget databases exist. Not literally, of course. We still store petabytes. But for the average developer, the database became an implementation detail; an essential but staid utility layer we worked hard not to think about. We abstracted it behind object-relational mappers (ORM). We wrapped it in APIs. We stuffed semi-structured objects into columns and told ourselves it was flexible.

CloudBolt's survey also examined how respondents are migrating workloads off of VMware. Currently, 36 percent of participants said they migrated 1-24 percent of their environment off of VMware. Another 32 percent said that they have migrated 25-49 percent; 10 percent said that they've migrated 50-74 percent of workloads; and 2 percent have migrated 75 percent or more of workloads. Five percent of respondents said that they have not migrated from VMware at all.

A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?

Databricks today announced the general availability of Lakebase on AWS, a new database architecture that separates compute and storage. The managed serverless Postgres service is designed to help organizations build faster without worrying about infrastructure management. When databases link compute and storage, every query must use the same CPU and memory resources. This can cause a single heavy query to affect all other operations. By separating compute and storage, resources automatically scale with the actual load.

Organizations are drowning in dashboards, KPIs, performance metrics, behavioral traces, biometric indicators, predictive scores, engagement rates, and AI-generated forecasts. We have more data than we know what to do with. We pretend that the mere presence of data guarantees clarity. It does not. That's data hubris—the arrogant belief that because something can be measured, it can be mastered.

The more attributes you add to your metrics, the more complex and valuable questions you can answer. Every additional attribute provides a new dimension for analysis and troubleshooting. For instance, adding an infrastructure attribute, such as region can help you determine if a performance issue is isolated to a specific geographic area or is widespread. Similarly, adding business context, like a store location attribute for an e-commerce platform, allows you to understand if an issue is specific to a particular set of stores

The rise of generative AI is often seen as an existential threat to the SaaS model. Interfaces would disappear, software would fade away, and existing players would become irrelevant. However, new figures from Databricks paint a different picture. Rather than undermining SaaS, AI appears to be increasing its use. This week, Databricks reported a revenue run rate of $5.4 billion, a 65 percent year-on-year increase. More than a quarter of that now comes from AI-related products.

The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.

Many organizations, Gans suggests, resemble public airports - full of people waiting for phones to ring, managing buffers, absorbing uncertainty.

When ChatGPT launched in late 2022, I watched something remarkable happen. Within two months, it hit 100 million users, a growth rate that sent shockwaves through Silicon Valley. Today, it has over 800 million weekly active users. That launch sparked an explosion in AI development that has fundamentally changed how we build and operate the infrastructure powering our digital world.