Operations | Monitoring | ITSM | DevOps | Cloud

Why DevOps and SRE Teams are replacing 3-4 monitoring tools with Atatus?

Your on-call engineer gets paged. A critical service is down. Error rates are spiking. They open Sentry for errors. Flip to Grafana for metrics. Pivot to Kibana to search logs. Then jump to Lumigo, but that only covers the Lambda functions, not the Node.js backend throwing the actual errors. Three tabs become five. Five become eight. Half the incident is gone and your team is still piecing together what happened instead of fixing it. Sound familiar?

Log Correlation for Security and Performance Monitoring

International travel comes with amazing sights, cultural experiences, and local delicacies. However, most travelers know that it comes with differing economies that impact a money’s value and various currencies. When people need cash, they have to translate the money in their wallets to the local currency, which means different coins and bills. Depending on the exchange rate, the currency’s value can change as the person moves from one country to another.

Observability Where You Work: Introducing the Honeycomb Slackbot in Beta

Engineers are constantly context switching between tools, adding cognitive overhead on top of already complex work. You're deep in an investigation, you need to analyze some data, pull up a runbook somewhere else, and share findings back in Slack. Context gets lost in the shuffle, correlating across data sources becomes painful, and everything just takes longer. In high-pressure situations like incidents, that friction has a real cost to the business.

Update Management, Content Hub Expansion, and KQL Support

The latest VirtualMetric DataStream release introduces several important capabilities across platform security, data management, and operational workflows. This update strengthens access protection, simplifies infrastructure management, and expands the ways security teams can work with live telemetry. It also extends platform connectivity and improves the user experience across many areas of the interface. Let’s take a closer look.

DNS Monitoring

You can now monitor DNS records directly from Hyperping. DNS issues are often invisible until your users start complaining. With DNS monitoring, Hyperping checks that your records resolve correctly from multiple locations and alerts you the moment something goes wrong. Head to your monitors dashboard to create a DNS monitor. You can also manage DNS monitors via the API. Questions? Reach out via in-app chat or email us at hello@hyperping.io.

Why Your NOC Will Ignore AI

Imagine you are driving to work and a yellow check engine light flickers on your dashboard. The car feels fine. It accelerates normally, there is no strange noise, and the temperature gauge is steady. What do you do? If you are like most people, you keep driving. You might make a mental note to look at it later, but you don't pull over on the highway and call a tow truck.

The bare metal problem in AI Factories

As AI platforms grow in scale, many of the limiting factors are no longer related to model design or algorithmic performance, but to the operation of the underlying infrastructure. GPU accelerators are key components and are responsible for a large part of the total system cost, which makes their continuous availability and stable operation critical to the output and efficiency of the entire AI platform.

What is Ambient AI in Healthcare? Revolutionizing Clinical Care, Efficiency, and Outcomes

You probably use ambient AI every day without even knowing it. When your Apple Watch is telling you to stand up after sitting too long, your CGM recommends you eat a snack, or even when your smart home lights dim around the time you go to bed, every night…that’s ambient AI. Among other things, ambient AI is there to help you stay healthy, tracking what you do in the background and making decisions based on your previous actions and preferences.

MCP vs. CLI for AI-native development

Summary: The CLI vs. MCP question is really a question about where you are in the development loop. CLIs fit the inner loop: fast, local, zero overhead. MCP servers fit the outer loop: external systems, shared infrastructure, structured access. Most teams need both. AI has put a new kind of scrutiny on developer tooling. When a developer works alongside an AI coding assistant, the tools that assistant can reach, and how it reaches them, directly affect the quality and speed of the work.