The original premise of observability was to ensure system health, identify issues, and resolve those issues efficiently. As I recently outlined, the legacy approach (sometimes called Observability 1.0 now) relied heavily on metrics and tracing because logs were seen as too noisy or challenging. But, as most forward thinkers have identified now, logs are exactly the telemetry type that we need the most.

2024 has been a year of record-breaking growth and innovation at NinjaOne. In fact, we were named to the Deloitte Technology Fast 500 for 2024. Being represented among the fastest-growing tech companies isn’t just an honor—it’s a testament to NinjaOne’s pivotal role in automating the hardest parts of IT through bold creativity and relentless customer focus. Let’s look at some of this year’s highlights.

.NET + DevOps Developer, Evidi Evidi – an IT consultancy and managed service provider based in Norway – are on a mission to help businesses harness the power of the Microsoft stack and realise their ambitions. With a large portfolio of services and a growing network of customers to manage, Evidi faced a challenge relatable to any MSP: They needed better visibility, and the solution had to be cost-effective and scalable.

Learn how to extract and analyze account-level CDN metrics from Akamai logs using Last9 for real-time insights and better customer tracking.

The COVID-19 pandemic disrupted the supply chain industry and exposed its vulnerabilities. Adding to the pressure, even more complicated challenges have emerged, including extreme weather events, complicated geopolitical climates and the complex evolution of AI. A survey by Ivanti reveals the state of the industry, key insights from insiders and trends to watch. The survey collected insights from management and employees across a range of supply chain roles.

We are excited to collaborate with Dell on the white paper,Agentic RAG on Dell AI Factory with NVIDIA. The white paper is a design reference document for developers outlining strategies and solution components to implement agentic retrieval augmented generation (RAG) applications. It’s a design point for organizations across industries, specifically healthcare, for the agentic RAG framework decision-making with AI-driven data retrieval.