Operations | Monitoring | ITSM | DevOps | Cloud

All eyes are on generative AI. Enterprise IT teams are looking to Gen AI to translate the high volume of data from their services architecture into actionable insights. The goal: Improve operational efficiency and quality of work. But it’s challenging to sort through the hype (and confusion) to identify which vendors have GenAI capabilities that can provide true impact and value to their IT and service operations. One capability in particular is AI-powered copilots.

That’s the assessment of Senior DevOps Engineer and Logz.io user Armin Morattab when discussing the impact of AI on his day-to-day job. He dives deep on AI, observability, and strategies for improving workflows with Logz.io Co-founder Asaf Yigal in our webinar, AI in Observability: Real Engineers Talk Real Uses Cases.

Monitoring used to be so easy. Servers had names and lived down the hall, or across the street. If things weren’t working, you could turn them on and off again. Database filling up? Just throw another hard drive in there. Too many simultaneous requests? Rack another server and install a cache. Fast forward a couple decades, and things have gotten much more complicated.

When managing IT infrastructure, one crucial aspect is ensuring that your incident alert management system remains operational during critical failures or outages. Relying on a single cloud provider for both your primary services and incident management can create a significant vulnerability. If that cloud provider experiences an outage, your alert management system could become inaccessible precisely when it’s needed most, leading to delayed responses and extended downtime.

Late last year, Datadog announced something called Flex Logs, a “more affordable” warm storage tier for log data. Designed for high-volume datasets that are infrequently queried and don't require real-time analysis, the Flex Tier offers Datadog Log Management customers a third option for data storage.