Operations | Monitoring | ITSM | DevOps | Cloud

Sometimes your API call takes a few seconds longer than expected. Or users start reporting slow page loads. One of the most common reasons? Network latency.

We’ve been steadily building something powerful into GitKraken: AI that understands your code and your context. In recent releases, GitKraken AI has already helped you: Now, in version 11.2, it’s tackling one of the most frustrating parts of your day: merge conflicts.

What if you were to tell Kubernetes Monitoring what you wanted, and the system configured collectors based on your choices? We wondered that as well—wondered enough to create Alloy Operator and its Helm chart for version 3.0 of the Kubernetes Monitoring Helm chart. We’re excited to share that the new Kubernetes Monitoring Helm chart is now available, and it introduces a dynamic way of setting up your telemetry data collection with Alloy Operator.

Trends in tech come and go, but certain underlying primitives stick around forever. In software, two such primitives are virtual machines and containers. Virtualization paved the way for the cloud to become massive. Data centers would likely never have been commercially viable without it. While still relatively new, containerization has already made a serious mark on the software engineering world.

In Part 1, we explored how aligning network visibility with IT service context empowers faster, smarter incident response. But what does this actually look like? Here in Part 2, we’ll go deeper into the challenges of traditional monitoring approaches, and how teams should look to move from fragmented alerts to unified insights – because when ITOps and NetOps can both see the “what” & “why” of the problem, actions become instinct.

This guide aims to help your team shift testing left, simulate real user behavior, and catch critical issues early as part of CI/CD, prevent regressions from reaching production by automating tests as part of your CI/CD and aborting deployments that contain issues. Synthetic monitoring is a great way to check important flows in production and make sure everything is working the way it’s supposed to.

Tired of trying to guess if that half-baked LLM suggestion is really going to fix the issue with your code? Meet Seer—our new AI agent that taps into all the issue context from Sentry and your codebase to not just guess, but root cause gnarly issues and propose merge-ready fixes specific to your application. Code gen tools are great fun—and useful. But even a recent Microsoft study confirmed what you already know: AI struggles with debugging.

Splunk is the backbone of security analytics for many of the world’s most advanced enterprises. Its ability to unify, correlate, and analyze massive volumes of telemetry data has made it the platform of choice for SOC teams worldwide. But as security data grows exponentially in volume and complexity, many organizations face a different challenge: getting the right data into Splunk, in the right shape, without straining infrastructure resources or missing critical signals.

The latest Pandora FMS version presents key improvements to the SIEM, module, designed to enhance security event detection and management. These new features are available starting with Feature Release 782, allowing for optimized log analysis, report generation, and rule validation in distributed IT environments.