Operations | Monitoring | ITSM | DevOps | Cloud

Few areas of development have seen as much recent change as mobile. Mobile phone and app usage spiked during the pandemic as we adapted to life with social distancing procedures. And even post-Covid, many mobile habits have stuck, whether it’s using apps for connecting with friends, shopping, getting healthcare, or staying fit. In the first half of 2022, daily time spent on mobile devices in the US was up 39% from three years ago and up 9% from late 2021.

If anything’s going to decide what the future of IT automation holds, it’ll be artificial intelligence (AI) and generative AI. And if this past half-year hype has proven anything, it’s that we could see some serious, game-changing surprises. Did anyone see generative AI including tools like ChatGPT coming?

Note: This post is co-authored by Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack. AI/ML is moving beyond the experimentation phase. This involves a shift in the way of operating because productising AI involves many sophisticated processes. Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable?

In recent years, the field of Information Technology Operations (ITOPS) has witnessed a revolutionary transformation with the advent of Generative Artificial Intelligence (AI). This cutting-edge technology has brought about significant changes in how IT operations are managed and has proven to be a game-changer for businesses worldwide. In this blog post, we will explore the revolution of Generative AI in ITOPS, its impact, benefits, and the prospects it holds.

Artificial Intelligence (AI) is revolutionizing the business landscape, offering immense potential to transform organizations into exponential enterprises. ServiceNow, recognized as the "engine of the enterprise," envisions a future of work where AI-powered solutions automate processes, enhance decision-making, and extract valuable insights from data.

Grafana Mimir is an open source distributed time series database. Publicly launched in March 2022, Mimir has been designed for storing and querying metrics at any scale. Highly available, highly performant, and cost-effective, Mimir is the underlying system powering Grafana Cloud Metrics, and it’s used by a growing open source community that includes individual users, small start-up companies, and large enterprises like OVHcloud.

The popularity of open-source log management tools has been on a steady rise in recent years. As businesses become increasingly reliant on software applications and cloud-based services, logging has become an essential part of operations. Log management is a crucial process for organizations to collect, store, and analyze log data. Businesses can troubleshoot problems, identify security threats, and optimize system performance by effectively managing log data.

As part of my work as a Head Nerd, I have the pleasure of meeting with MSPs from all over the world. About a month ago, I was speaking with four technicians from a global MSP based out of California. They were very technically savvy, had a deep understanding of PowerShell, and had a huge emphasis on automation in their business.