High latency and inflexible bandwidth have a domino effect across your entire business, impacting your productivity and revenue. Here’s how to improve it. When we talk about network latency, we’re referring to more than just the occasional lag or slow loading speed. At scale, the consistency of your network can be the difference between your enterprise making and losing money – and latency is where it all starts.

As Gartner predicts, AI will support up to 70% of performance monitoring and troubleshooting tasks in the next few years. The Logz.io AI Agent helps teams get ahead of this curve today. Too much time spent troubleshooting? You’re not alone. Manual investigation, jumping between dashboards, and piecing together scattered data are time-consuming and frustrating.

Can generative AI help improve IT efficiency? Imagine you’re part of an IT team constantly juggling a growing number of support tickets, system issues, and daily maintenance tasks. It can feel like you’re always playing catch-up. It’s a common challenge: Repetitive tasks and troubleshooting waste valuable time, leaving little room for innovation or strategic improvements. Generative AI (GenAI) for IT provides a solution.

Does your SCOM environment run slow? Do you have too many unwanted alerts? Are you preparing for the upcoming upgrade? Don't worry. These issues are very common and frustrating, but thankfully also solvable.

Since the emergence of the cloud, the DevOps movement, and the rise of microservices, developers have been increasingly responsible for the operation of their software. “You build it, you run it” (YBYR) and “You build it, you operate it” (YBYO) have become common mantras in the software engineering industry. However, there’s a misunderstanding in this statement. Developers should remain focused on building software.

In this blog post, we’ll explore how to build a data pipeline using Kafka, Faust, and InfluxDB to effectively ingest, transform, and store data. We’ll start with an overview of Kafka, a high-performance messaging platform, and Faust, a Python library designed for stream processing, now maintained by the community as Faust-streaming.

In today’s multi-cloud landscape, maintaining smooth and reliable connectivity requires complete visibility into cloud networks. With Kentik, network and cloud engineers gain the tools to monitor, visualize, and optimize Azure traffic flows, from ExpressRoute circuits to application performance, ensuring efficient and proactive operations.

We're excited to announce a significant enhancement to Karpenter, an intelligent Kubernetes autoscaling solution that automatically optimizes your infrastructure costs and performance. Since integrating Karpenter six months ago, it has helped our users automatically provision the right AWS instances for their workloads.

Having previously compared the top 5 Datadog alternatives and the top 5 alternatives to Honeybadger, this time we'll compare Sentry against five competing application performance monitoring (APM) tools, so that you can find the best choice for you. We'll compare Sentry to AppSignal first, then Honeybadger, Datadog, New Relic, and Scout.