Operations | Monitoring | ITSM | DevOps | Cloud

The evolution of generative AI is beginning to rapidly transform the way that we work and communicate. This is only set to increase as generative AI excels in providing business value by driving innovation and making intelligent decisions at unprecedented speeds. However, to fully harness its potential, organisations must ensure that they deploy this revolutionary technology safely, securely and responsibly with the right network connectivity.

Widespread adoption of containerized infrastructure has been closely followed by an explosion of container-native tools for each layer of the stack, including new solutions for managing CI/CD pipelines in container-based environments, such as the Argo suite, FluxCD, and Tekton. This is because these lightweight solutions make it easier to automate builds, testing, deployments, and more on Kubernetes, as well as other platforms that manage containerized workloads and services.

Most organizations migrate to the Amazon Web Services (AWS) public cloud from on-premises data centers. However, others have switched from another Infrastructure-as-a-Service (IaaS) platform to AWS. The most common reason we hear for choosing AWS is cost savings. As the largest public cloud provider, AWS leverages economies of scale, making its cloud services more affordable than those a company would have to build itself. Yet, not every organization can claim that AWS has saved it money.

Arguably the most important part of an on-call product is knowing that you will be notified when things break, wherever you are. When it comes to SMS and phone call notifications, we have to leave the familiar realm of the internet and JSON responses, and deal with systems that provide limited observability and insight into what’s gone wrong.

When working with ML models, it’s fair to say that a model is only as good as the data it was trained on. Training and testing models on quality datasets of an appropriate size is essential for model performance. Because of the intricate link between a model and the data it was trained on, it’s also important to be able to store datasets and versioned models together.

There’s no shortage of new developer tools promising to reduce toil and improve productivity. But investing in the latest technology can require a leap of faith organizations can no longer afford to make. Leaders need assurance that the investment they’re making will pay off, quickly.

In the ITSM world, automation is no longer just a luxury—it’s essential. Automation empowers organizations to enhance operational efficiency, reduce expenses, and boost service reliability. That said, achieving true, sustainable results with automation can be challenging and often comes at a significant cost. Successful delivery of automation requires a clear vision and the strategic adaptation to align with evolving goals and incorporate agility.

API testing is a vital part of the development lifecycle. In this comparison piece, you’ll compare Speedscale and Hypertest and show where they stand in terms of API testing.

Squadcast shines bright this summer, securing an impressive 38 badges across 95 reports, showcasing our IT Alerting and Incident Management leadership.