Operations | Monitoring | ITSM | DevOps | Cloud

In API testing, speed, accuracy, and confidence in test results are everything. Regardless of whether you’re validating functionality, testing performance under load, or ensuring compliance with your security posture and standards, the ultimate goal is the same: catching problems before they reach production. But what if your tests are lying to you? Lurking beneath even the most sophisticated test suites is a subtle, pervasive threat: data coupling.

When Uptrends became part of ITRS, we knew we were joining a team deeply committed to innovation, precision, and people — whether those people were troubleshooting transaction journeys from their laptops at 8am or keeping enterprise-scale operations online 24x7. We’ve come far since then.

Container image layers provide valuable insight into what goes into a container, including which packages were installed, what commands were run, and where vulnerabilities might live. The metadata associated with these image layers is essential for debugging, optimizing image size, and managing security risks. However, key container-layer metadata fields such as digest, size, and created_by are sometimes missing, which can disrupt important tasks.

As enterprises scale in complexity, the infrastructure landscape is no longer just cloud or on-premises, it’s both. Hybrid is the new normal and it’s here to stay. And with that shift comes a new demand: a unified, scalable observability solution that works across the entire tech stack, from legacy hardware to cloud-native workloads. That’s where LogicMonitor comes in.

We are pleased to announce the general availability of SystemEDGE 6.5. For customers using DX NetOps, SystemEDGE is a key component for gaining a comprehensive view of server infrastructure health. It functions as an agent that resides on systems like physical servers or virtual machines. SystemEDGE collects fundamental performance and status information and delivers reports via SNMP.

There’s a certain comfort in the glow of your network operations center (NOC) dashboards. For some time, the sign of a well-run NOC was that sprawling bank of screens, each dedicated to a different domain. One for the WAN, showing link status. Another for the data center, tracking backbone health. A third for cloud consumption, pulling metrics from your provider. Each screen is a neatly bordered kingdom, diligently monitored by its own set of tools. As long as the lights are green, all is well.

In 2020, we introduced the Snowflake Enterprise data source for Grafana, allowing users to seamlessly pull data from the Snowflake cloud-based data storage and analytics service into Grafana dashboards. Available for Grafana Enterprise and Grafana Cloud users, it’s a powerful way to not only query and visualize Snowlake data, but to do so alongside other data sources, so you can discover correlations and other meaningful insights within minutes.

‍In this final part, the Scout team continues our talk with Freedom Dumalo, former CTO at Flexcar and current CTO at Vestmark. We discuss some essential questions about architecture, touch on Rails, Turbo, and Stimulus, and the key considerations for those starting off before they lock in an architecture or tech decision. ‍ By the way, before we jump in, Scout Error Monitoring is coming!

Agentic AI is making waves across various industries, and its potential to transform ITSM is undeniable. With all the talk about agentic AI capabilities, you are probably daydreaming about streamlining ITSM processes through automated incident management, automated change risk analysis, improved efficiency through service desk automation, or enhanced service quality with predictive maintenance. But you also may start to wonder: How real is all of this? Is my organization truly ready for agentic AI?