Operations | Monitoring | ITSM | DevOps | Cloud

A significant part of being on-call is the ability to respond to pages and handle escalations on the go. In the early stages of developing incident.io On-call, we considered whether a Minimum Viable Product (MVP) could rely solely on SMS and phone calls. However, we quickly realized that a fully featured mobile app was going to be essential to the on-call experience. This led us to the question: how should we build this mobile app?

The differences between a help desk and a service desk might have once seemed clear. But over the years, plenty of things have changed – especially with the arrival of new technologies that have impacted how users and customers receive support. Let's compare help desk vs. service desk models and examine how this ongoing evolution has played out. One area where the distinctions between a help desk and a service desk are apparent comes when discussing IT Service Management (ITSM) solutions.

Transitioning from a monolithic system to a cloud-native microservices environment, Ritchie Bros. sought to modernize their observability infrastructure to support the transition and fuel future growth. Ritchie Bros. has been a pioneering force in the auctioneering market for nearly 70 years, charting remarkable growth through a strategic mix of organic expansion and acquisitions.

In the ever-evolving IT landscape, the Observability Dilemma casts a strategic shadow: To SaaS or not to SaaS, a question being dealt with by many IT professionals today. As organizations grapple with the complexities of maintaining system health and performance, navigating change while staying secure, choosing between the allure of cloud-based services and the on-premises sanctuary becomes pivotal.

Logging in a Python application is straightforward. When you have good logs, you have better visibility into application health. You can monitor performance and track user activity. You’re better equipped to debug errors. Life is good. The challenges come when your application grows more complex. Perhaps your Python code is part of a broader application, or you have services distributed across multiple machines or clouds.