Operations | Monitoring | ITSM | DevOps | Cloud

Cost Optimization for AI Workloads: From Visibility to Control

ITOps teams can achieve cost management of AI workloads with an observability platform that connects AI usage and performance with cloud spend for clear visibility and predictability. Behind the buzz around artificial intelligence, or AI, many companies are discovering the hidden and compounding costs of AI adoption.

Platform Engineering 101: What It Is, How It Differs from SRE and DevOps, & Why It Matters for Incident Response

Platform engineering has emerged as a response to the growing complexity of modern software delivery. As organizations adopt Kubernetes, microservices, CI/CD pipelines, and infrastructure as code, they are creating dedicated teams responsible for building and operating the internal platforms that power developer workflows.

Identify untested code across every level of your codebase

As organizations scale their services and adopt AI-assisted coding, code changes are landing faster and in greater volume than ever before. While this powerful new practice is accelerating the pace of development, it is also increasing the likelihood that untested code may slip into repositories without detection. What makes this problem even worse is that most teams have no reliable way to know which code is covered by tests.

Kubernetes Namespaces: What They Are, How They Work, And What They Don't Solve

Using Kubernetes to manage containerized applications has its fair share of challenges. One of those challenges is managing complexity. Using namespaces can help minimize that complexity. Yet, a common misconception is that using multiple namespaces in a single Kubernetes cluster can degrade performance. Another issue: Kubernetes namespaces can reduce visibility into costs. There’s more to it than that.

6 Insights About Marketing Software That Improve Campaign Effectiveness

Modern marketing relies on a complex stack of tools to reach the right people at the right time. Finding the perfect balance between automation and human creativity remains a primary challenge for growth-minded brands. Effective campaigns require more than just flashy graphics or catchy slogans. Data-driven decisions powered by reliable software ensure every dollar spent contributes to the bottom line of the business.

A Guide to Implementing Business Technology Solutions

Technology has become the backbone of modern business. Whether you are running a small local shop or building a larger company, the right technology solutions can improve efficiency, streamline operations, enhance customer experience, and support long-term growth. But implementing business technology is more than buying software or hardware. It is a strategic process that requires planning, alignment, and thoughtful execution.

Is Generative AI Eroding Our Ability to Think?

In aviation, there's a well-documented issue known as "automation addiction." As cockpit systems became more advanced, pilots gradually shifted from actively flying aircraft to supervising automated controls. Everything worked smoothly-until a system malfunctioned. Investigations revealed a troubling pattern: even experienced pilots sometimes struggled with basic manual maneuvers. Their hands remembered less because their brains had practiced less.

AI-Driven Automated Testing for Oracle Applications

As enterprises continue to change rapidly, businesses depend on Oracle-based ecosystems to track their finances, supply chains, HR, and customer operations. With the increase of digital transformation in companies, these environments continue to become more complex. As a result, manual testing is no longer enough for maintaining pace with ongoing updates, integrations and customizations that occur within an organization's systems. This is where AI-powered automated testing for Oracle applications revolutionizes how quality assurance is approached.

Software Audit as a Risk Management Tool: What Teams Often Miss

Modern software systems rarely collapse because of one dramatic mistake. More often, problems build up quietly: undocumented logic, outdated libraries, brittle integrations, or security assumptions that stopped being true years ago. None of these issues look urgent on their own. Together, they create fragility. That's where a software audit becomes useful - not as a bureaucratic exercise, but as a practical way to see what's really going on inside a codebase.