Operations | Monitoring | ITSM | DevOps | Cloud

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.

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.

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.

Honeycomb Metrics Is Now Generally Available

It’s Black Friday. Checkout latency is spiking. Your on-call engineer pulls up the dashboard and starts working through the list. Is it a regional issue? No, all regions look fine. A payment provider? Stripe, PayPal, Apple Pay all nominal. A bad deployment? Nothing shipped in the last six hours. All your infrastructure dashboards are showing green. But customers are complaining. Checkout is slow, carts are being abandoned and revenue is draining away.

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.

The future of Search is here: Faster, simpler, AI-driven

Do more with less. That’s the mandate we’re all hearing. AI has fundamentally changed how we work. Modern AI workloads generate 10-100x more queries than humans ever could, pushing legacy architectures past performance limits. And the audacity of it all? Legacy logging vendors continue to raise costs without delivering meaningful innovation. IT and security teams are still forced to choose between speed and retention. Investigations are still slow. Data onboarding is still painful.

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.

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?

When Faster Code Starts to Break the Delivery System | Harness Blog

Speed is exposing the cracks. Our research shows that 69% of heavy AI users now face frequent deployment issues. To capture the ROI of AI, leaders must shift focus from code generation to delivery modernization. standardizing foundations and automating the "manual middle" that leads to developer burnout. Over the last few years, something fundamental has changed in software development.