Operations | Monitoring | ITSM | DevOps | Cloud

You can't fix what you can't see, especially when the problem isn't in your infrastructure. #ipm

Most teams monitor from the inside, tracking internal metrics, logs, and uptime. But internal health doesn’t always reflect what your users experience. The internet is made up of many parts you don’t own (ISPs, CDNs, DNS, cloud providers), and any one of them can introduce friction. That’s why monitoring from the outside in matters. By testing from real user vantage points, you get a clearer picture of network reachability and performance as it’s actually experienced.

Top Kubernetes Monitoring Tools in 2025, And Why Alerting Is Critical for DevOps and SRE Teams

What are the best Kubernetes monitoring tools in 2025? And how can you ensure alerts actually drive action when something goes wrong? Kubernetes monitoring is critical for keeping your containerized applications healthy, but alerting is often overlooked. This blog compares popular tools like Prometheus and Datadog and explains why intelligent alerting solutions like OnPage are essential for effective incident response.

What is a Jitter Buffer and How It Works

If you've ever been on a choppy VoIP call or sat through a video meeting where people sounded like robots from the ‘90s, you’ve likely run into a little thing called jitter. It’s one of those sneaky network issues that doesn’t always get the attention it deserves, until it ruins your real-time traffic. As IT pros and network admins, you're probably used to dealing with packet loss and latency. But jitter? That one's a bit trickier.

A Detailed Look at Calico Cloud Free Tier

As Kubernetes environments grow in scale and complexity, platform teams face increasing pressure to secure workloads without slowing down application delivery. But managing and enforcing network policies in Kubernetes is notoriously difficult—especially when visibility into pod-to-pod communication is limited or nonexistent. Teams are often forced to rely on manual traffic inspection, standalone logs, or trial-and-error policy changes, increasing the risk of misconfiguration and service disruption.

Is AI About to Create Its Own Language? Here's What You Need to Know!

This panel brings together experts Josh Mesout (Civo), Nobel Chowdary Mandepudi (Arm), Jimil Patel (Intuit), Numa Dhamani (iVerify), and James Gress (Accenture) to discuss the cutting edge of AI and machine learning. They explore when AI might develop its own language beyond human syntax, the evolving landscape of ML frameworks such as MLIR, Mojo, and JAX, and the challenges involved in bridging the gap from AI research to production while optimizing models for deployment.

Robust Time Series Monitoring: Anomaly Detection Using Matrix Profile and Prophet

Monitoring production systems often feels like searching for a moving needle in a constantly shifting haystack. At Sentry, our goal was to empower customers to move beyond traditional threshold and percentage-based alerting. We aimed to help them detect subtle and complex anomalies in their systems in near real-time. This post will detail how our AI/ML team developed a time series anomaly detection system using Matrix Profile and Meta’s Prophet.