Operations | Monitoring | ITSM | DevOps | Cloud

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?

Observability is essential for maintaining the performance and reliability of modern software systems. However, the cost associated with attaining and extending observability can quickly escalate in ways that may not even seem apparent at first. We hear from many organizations struggling to tamp down the costs of observability at a time when every dollar spent on technology is scrutinized.

If you’re still unpacking the latest terminology from Gartner’s 2023 AIOps market update, you aren’t alone. Subject matter experts from Moogsoft recently joined thought leaders from TIAA and Windward Consulting for a debrief on the panel interview Accelerating Your AIOps Journey Webinar. Almost half of technology leaders looking to improve productivity and fuel greater collaboration are struggling to explain AIOps use cases, benefits, and value to other business leaders.

“Why can’t you just use the MDM we’ve been using in corporate IT?” Sounds familiar? If you’ve been in operations IT for the last decade or more, you’ve likely heard this question from your corporate colleagues at least once. It may be a bit ironic that mobile device management may have been part of your operational tech stack for twice as many years as it’s been in the corporate conversation.

The world of FinOps can be pretty complex. Don’t get us wrong, it’s a fantastic way to align IT and finance teams for maximum efficiency in cloud operations. But for newcomers, it may feel a bit overwhelming at first. That’s why following influential leaders in the FinOps space is a must. The tips, insights, and guidance from these top FinOps performers can give you the confidence and motivation to lead FinOps at your company.

CloudOps (or Cloud Operations) is a combination of network, security, performance, device management, help desk and other tasks that keep cloud-native applications and underlying infrastructure up and running.

Event-Driven Architecture (EDA) is a modern approach to designing distributed systems with loosely coupled components. EDA has gained popularity in many industrial applications due to its flexibility, performance and scalability. This article offers a comprehensive overview of Event-Driven Architecture (EDA), explaining its key components and the patterns used. I’ll also cover the use cases of EDA and the benefits and challenges of implementing it.

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?

Today I will cover monitoring and troubleshooting AVD (Azure Virtual Desktop) connection issues and problems. Microsoft Azure Virtual Desktop (AVD) is a powerful cloud-based service that enables organizations to deploy and manage virtual desktops and applications. It provides users with a seamless remote desktop experience, allowing them to access their resources from anywhere. However, like any technology, AVD can encounter connection failures, causing frustration and disruption for users.

This article explores the rise of micro apps and microservices, driving faster and lighter software experiences. It discusses monitoring challenges in distributed systems and provides an introduction to monitoring Kubernetes. Learn about the basics, benefits, and differences of micro apps and microservices, along with insights into effective monitoring strategies. Discover MetricFire's monitoring solutions through a free trial.