DevOps
fromInfoQ
17 hours agoReplacing Database Sequences at Scale Without Breaking 100+ Services
Validating requirements can simplify complex problems, and embedding sequence generation reduces network calls, enhancing performance and reliability.
Neocloud providers, which include the likes of Nscale, CoreWeave and Carbon3.ai, are having a somewhat disruptive impact on the market by making huge commitments to build out hyperscale datacentres in support of the UK government's AI growth agenda. These providers are also taking up capacity in colocation datacentres that some of the hyperscale cloud giants previously committed to renting space in, before pulling out.
Azure Governance is the set of policies, processes, and technical controls that ensure your Azure environment is secure, compliant, and well-managed. It provides a structured approach to organizing subscriptions, resources, and management groups, while defining standards for naming, tagging, security, and operational practices.
As businesses contend with ever-increasing data volumes and performance-intensive applications such as AI model training, AI inferencing and high-performance computing, they need infrastructure that delivers speed, scalability and efficiency without added complexity.
There is a growing emphasis on database compliance today due to the stricter enforcement of compliance rules and regulations to safeguard user privacy. For example, GDPR fines can reach £17.5 million or 4% of annual global turnover (the higher of the two applies). Besides the direct monetary implications, companies also need to prioritize compliance to protect their brand reputation and achieve growth.
An observability control plane isn't just a dashboard. It's the operational authority system. It defines alert rules, routing, ownership, escalation policy, and notification endpoints. When that layer is wrong, the impact is immediate. The wrong team gets paged. The right team never hears about the incident. Your service level indicators look clean while production burns.
The new version combines lower costs with improved cybersecurity and offers up to 2 petabytes of storage in a 2U rack space. Companies are struggling with explosive data growth, increasing cyber threats, and limited budgets. Dell Technologies is responding to this with PowerStore 4.3, a platform that addresses storage challenges without compromising performance or security. The latest version brings innovations that double storage density and reduce energy costs.
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.
A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."
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?
In 2024, Oracle launched its Database 23ai, dropping the "c" suffix it established for cloud in 2013. But the release never arrived as a general on-premises option beyond Oracle's own engineered systems, and the company later pushed back the Premier Support cutoff for 19c to December 31, 2029, with Extended Support running through December 31, 2032. Premier support was originally slated to end in 2024.
This new reality is forcing organizations to undertake careful assessments before making platform decisions for AI. The days when IT leaders could simply sign off on wholesale cloud migrations, confident it was always the most strategic choice, are over. In the age of AI, the optimal approach is usually hybrid. Having openly championed this hybrid path even when it was unpopular, I welcome the growing acceptance of these ideas among decision-makers and industry analysts.
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.
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.