Operations | Monitoring | ITSM | DevOps | Cloud

At Sentry, we’re obsessed with things not breaking. It’s kind of our whole deal. But for a while, our own marketing site was testing that obsession. Much of what you see on sentry.io (the marketing site, blog, open source microsite, etc.) were running on a fleet of legacy Gatsby sites powered by a traditional headless CMS. On paper, it worked.

Visibility without control is just expensive awareness. Most IT teams can see when something’s wrong, but can’t easily tell who’s affected, why, or what to do next. In other words, they lack real control. In this in‑depth session, LogicMonitor’s Callum Brown and Brandon Delap showed how to move past that.

Autonomous IT shifts enterprises from reactive to proactive operations“By combining AIOps, agentic AI, predictive analytics, and self-healing automation, Autonomous IT helps organizations detect issues early, automate remediation, and prevent downtime before it impacts customers or revenue.

Most network teams monitor uptime. A lot of them track CPU. Almost none of them consistently monitor memory utilization on routers, firewalls, and switches, and that gap causes more unexplained outages and intermittent issues than most people realize.

A new attack technique called Underminr was disclosed this week. It slips past protective DNS by abusing shared CDN edge IPs. The DNS query looks clean. The connection lands on malware. This post walks through what Underminr is, why protective DNS misses it, what actually stops it, and the OTHER DNS layer most teams forget to watch.

Alibaba Cloud is a major cloud provider in APAC, offering industry-leading foundational AI models in addition to compute, managed databases, object storage, and Kubernetes through its Container Service for Kubernetes (ACK). Teams choose Alibaba Cloud for its infrastructure availability across Asia Pacific and its managed services. For SREs and platform engineers, that often means running Alibaba Cloud alongside AWS, Google Cloud, or Microsoft Azure.

Every Kubernetes environment accumulates waste over time. Teams overprovision CPU and memory requests to avoid performance risk, run idle replicas to preserve headroom, and leave Horizontal Pod Autoscalers (HPAs) untouched long after workload behavior has changed. Some of this waste can be addressed at the node level, where Datadog Cluster Autoscaling helps teams rightsize capacity.

Azure Managed Redis is Microsoft’s fully managed, enterprise-tier in-memory data store. It is designed for the low-latency caching, session storage, and real-time data needs of modern applications, including AI workloads that depend on fast vector and embedding lookups. Because user-facing applications often query Redis directly, even small regressions in latency, hit rate, or memory pressure can degrade the user experience.

Modern web applications rely on frameworks like Next.js, Vue, and Angular to handle routing and rendering. In these architectures, navigation happens within the application rather than through full page loads, which makes it difficult for traditional browser instrumentation to capture what users actually experience. As a result, teams often see misleading view names, missing navigations, and errors that are either misattributed or not captured at all, especially during hydration or lazy loading.

AI agents tend to function as black boxes, and it can be difficult to trace and understand agent workflows end-to-end in order to characterize performance. Particularly, you need visibility into the following: By tracing full agent runs with LLM Observability, Datadog AI Agent Monitoring enables you to visualize workflows with flame graphs and quickly spot sources of failures and latency.