Operations | Monitoring | ITSM | DevOps | Cloud

Originally posted on Forbes Technology Council As organizations increasingly embark on their digital transformation journey, IT is turning into a profit center, rather than a cost center. CIOs (chief information officers) are more than often referred to as chief innovation officers. New roles like chief data officer and chief analytics officer are rising to prominence. AI and data are at the center of this transformation, as CxOs are faced with daunting challenges in.

Many of us have heard single-page applications (SPAs) hailed as the future of web applications. Proponents of SPAs point to increased code reusability and development velocity, and the advantage SPAs can give when it comes to delivering a fast and seamless user experience. Massive sites like Facebook, AirBnB and Trello are all built as SPAs. On the flipside, monitoring SPAs for performance is pretty challenging.

Node.js logging, like any form of software instrumentation, isn’t an easy thing to get right. It takes time, effort, and a willingness to continue to iterate until a proper balance is struck. There are so many points to consider, including: Previously, here on the Loggly blog, I began exploring these questions in the context of three of the most popular web development languages: PHP, Python, and Ruby. But these aren’t the only popular languages in use today.

Let us consider a scenario where a Logic App is used to communicate with SharePoint through API connections, known as connectors. When configuring the connector, it communicates with Azure AD, retrieving a username and password and continuously refreshing the authentication token. When the Logic App calls the connector, it performs operations like uploading files to SharePoint.

One of the most talked about topics in observability today is centered around the question of how to get more value out of the ever-increasing amount of data collected by agents, collectors, scrapers, and the like. Back in May, we announced Adaptive Metrics, a new feature in Grafana Cloud that allows you to reduce the cardinality of Prometheus metrics and the overall volume and costs of your metrics.