Operations | Monitoring | ITSM | DevOps | Cloud

Analyzing Cardinality in Grafana Cloud and Grafana Enterprise Metrics

Cardinality Analysis of metrics is an enabler to reducing costs and focusing observability on the necessary metrics to identify and investigate where issues are occurring in your services. Grafana has added cardinality management dashboards to Grafana Cloud and Grafana Enterprise Metrics to make this an easy and fast process. In this introductory session, we will provide an overview of the Grafana Cardinality features and offer a set of discovery questions to help you with the process.

The key principles that doubled eBay's software delivery productivity ft. Randy Shoup

Rob is joined by Randy Shoup, VP of Engineering at eBay to discuss how to deliver fast, without losing quality. Learn about the value of consistent teams, having a long-term vision, and diligently measuring against key success metrics. Tune in today to find out how your team can increase productivity and move even faster.

SAST vs DAST: what they are and when to use them

As digital transformation accelerates and more organizations use software solutions to facilitate work operations, security threats have become more commonplace. Cybercriminals tirelessly develop ways to exploit software application vulnerabilities to target organizational networks. A notable example is the 2017 Equifax data breach, which exposed the personal details of 145 million Americans.

Expert Tips For Hiring IT Professionals

When looking to fill an IT vacancy, it can be difficult to know where to start. Finding the right people for your IT department can be difficult, and if you don't have the right team in place, your business can suffer. By following expert tips, you can make the process much easier and increase your chances of finding the perfect candidate for the job. Here are a few tips to help you find the best IT professionals for your business.

Machine Learning For Biology Is Starting To Move Towards Retail

There has been a lot of coverage of machine learning (ML) for biological research, for radiology, and for other uses where the direct users are academics, researchers, and medical professionals. However, there is an opportunity for some biological information to be useful in the retail industry. One area is in skincare.