Operations | Monitoring | ITSM | DevOps | Cloud

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.

Cloud storage solutions can provide public sector organisations with a high degree of flexibility when it comes to their storage needs, either public cloud based, or in their own private clouds. In our previous blog post we looked at the economic differences between these two approaches. In this blog we will explore some of the security best practices when using cloud storage, so that you can ensure that sensitive data remains securely stored and compliance objectives are met.

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.