Operations | Monitoring | ITSM | DevOps | Cloud

Kentik transforms real-time network telemetry into actionable alerts for AI-optimized data centers. By converting database queries into custom alerts, engineers can detect issues like elephant flows, idle links, and packet loss before performance suffers and triggers alerts in systems like ServiceNow or PagerDuty.

Production AI needs a network that can keep up. Learn why private, scalable connectivity is the key in our webinar recap with Vultr. AI is no longer a proof-of-concept hiding in a developer lab. It’s a full-fledged production workload, and it’s hungry for data. But as enterprises move their AI strategies from theory to reality, they’re hitting a wall that isn’t about algorithms or processing power – it’s about the network.

In the cloud, Kafka’s promise of “never lose a byte” quietly morphs into “always pay for two.” Every time the leader syncs followers across zones, you get hit with premium egress charges that can dwarf compute costs. Diskless Kafka turns that upside-down: brokers replicate data straight into S3, so the pricey cross-zone hops vanish. Yes, object storage is slower than a local SSD, but the swap buys you on-demand elasticity and a bill that finally makes sense.

In the past year alone, we’ve seen just how much a single outage can disrupt and how much stronger teams become when they learn from it. From the July 16, 2024 incident to the widespread June 2025 outage, it’s clear that incidents are inevitable. The question is: how do you transform each disruption into an opportunity to improve your processes for the next one?

Arie van den Heuvel is an engineer, a System and Application Management Specialist, and a valued member of our community. Below he has shared his journey using Coroot, and how it has helped improve observability for his team. You can read more of Arie’s writing and support the resource articles he has created for open source on his blog.

Vertical Pod Autoscaling (VPA) is a component within Kubernetes designed to automatically resize the CPU and memory requests of pods based on their observed, historical usage patterns. While Pepperdata Capacity Optimizer and VPA both change the resource requests of pods in response to changing application resource requirements, there are several key differences.

You're monitoring a microservices-based system. Alerts trigger when response times exceed 2 seconds. But when you open Jaeger, you're faced with thousands of traces. Identifying which service or operation is responsible becomes time-consuming. Jaeger metrics help reduce this friction by exposing aggregated telemetry. Instead of scanning individual traces, you get service-level and operation-level performance metrics, latency, throughput, and error rates that highlight where the issue lies.

In today’s hospitals, technology is woven into every touchpoint of patient care. Nurses check vitals through digital monitors. Physicians review test results in the EHR. Medications get ordered, verified, and delivered through a network of connected systems. But when even one link in that chain fails, the impact isn’t just inconvenient—it’s dangerous. Downtime doesn’t just slow operations.

IT leaders know the value of process improvement. Smoother onboarding, faster incident resolution, streamlined change management, etc. It’s not for lack of ideas that IT teams fall short; it’s almost always a lack of bandwidth. Because of that, most process improvement efforts stall before they scale. Great ideas get captured in diagrams, Confluence pages, and strategy decks, but they rarely make it into production. Why?

A DIY project to turn alerts into real-world signals using FireHydrant’s Hacker Mode.