Operations | Monitoring | ITSM | DevOps | Cloud

Trends in tech come and go, but certain underlying primitives stick around forever. In software, two such primitives are virtual machines and containers. Virtualization paved the way for the cloud to become massive. Data centers would likely never have been commercially viable without it. While still relatively new, containerization has already made a serious mark on the software engineering world.

We’ve been steadily building something powerful into GitKraken: AI that understands your code and your context. In recent releases, GitKraken AI has already helped you: Now, in version 11.2, it’s tackling one of the most frustrating parts of your day: merge conflicts.

Sometimes your API call takes a few seconds longer than expected. Or users start reporting slow page loads. One of the most common reasons? Network latency.

If your users are spread across the globe but your servers are sitting in Virginia, you’ll probably hear complaints about slow load times, especially from places like Australia. CDNs fix this by caching static assets closer to where your users are. Azure CDN does exactly that, and it fits well if you're already using Azure services. You can hook it up to Blob Storage, App Services, or your origin. This guide covers how to set it up, what to expect, and how to know it’s working.

In a traditional IT environment, the service catalog has long functioned as a directory—an online menu of things users can ask IT for. Need a new laptop? Submit a ticket. Need Salesforce access? File a request. Every need, every problem, every question gets funneled into a form, queued up for manual processing, and eventually (and hopefully) resolved. But this static, ticket-heavy model can’t keep up with the pace of business today. Employees expect seamless, self-service experiences.

Hyperview stands out with its transparent and flexible subscription-based pricing. Being a cloud-based solution, it eliminates hefty upfront costs often associated with traditional DCIM software. Updates and upgrades are rolled out seamlessly with zero downtime, and there are no hidden fees, making it highly budget-friendly for businesses looking to control long-term costs.

AI agents are undoubtedly exciting. What company would turn down the opportunity to use an intelligent bot that can make decisions, perform complex tasks, and take on the tedious work employees would normally have to deal with? On paper, AI agents sound like tremendous time and money-savers. The reality, however, is a bit different from the fantasy.

Researchers at Trend Micro have uncovered a critical unauthenticated remote code execution (RCE) vulnerability affecting Langflow versions prior to 1.3.0. Langflow is a Python-based visual framework for building AI applications and boasts over 70,000 stars on GitHub and over 21,000 global weekly downloads from the public PyPI upstream. Source: Cloudsmith Navigator Versions released before 1.3.0 contain a serious flaw in the code validation logic, which allows arbitrary code execution.

We are in mid-2025, and teams across industries are rolling out large language models, or LLMs, to power everything from conversational agents to document understanding. However, getting them to run smoothly in production… That’s still a challenge. A working model isn’t just about putting it in a container and tossing it into a Kubernetes cluster.