Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Cribl Search Pack for Zscaler: Setup & security dashboard walkthrough

Learn how to install and configure the Cribl Search Pack for Zscaler, then walk through prebuilt dashboards for your Zscaler security logs. This video is for security engineers, Zscaler administrators, and SOC/observability teams using Cribl Search to monitor and investigate Zscaler activity. In this walkthrough, you’ll see: If you need a reminder or want to share feedback on the pack, you can always refer to the README bundled with the pack or reach out to the Cribl team.

The Hidden Cost of Network Blind Spots (and How to Fix It)

Even the smallest gaps in infrastructure visibility can lead to major impacts to an enterprise. And with modern IT environments becoming more complex it creates rising expectations for uptime. Our recent webinar, The Hidden Cost of Network Blind Spots and Alert Noise, covered this exact topic. The Progress WhatsUp Gold product experts explored why traditional monitoring falls short and best practices to moving toward smarter, more proactive network management.

What Enterprise AI Gets Wrong About Usage

AI is moving out of the experimental phase and into the everyday rhythm of work. Teams are no longer using it occasionally for novelty or quick wins, but instead are exploring more robust use cases to investigate issues, answer questions faster, surface context, and help them move through complex workflows with more confidence. That’s the shift that most organizations’ leadership teams have been asking for.

Best APM for Small Teams Without Dedicated DevOps in 2026

You don’t have an SRE. There’s no platform team. Your “monitoring strategy” is someone checking Slack for error alerts. When production breaks, the same two or three senior devs drop everything to debug. Sound familiar? Most APM tools are built for organizations with dedicated operations staff. They assume someone has time to configure dashboards, tune alert thresholds, and learn a complex query language. That person does not exist on your team.

Best Error Monitoring for Rails in 2026

You deploy on Friday. Sidekiq starts failing on a job that worked fine in staging. Your error tool shows you a NoMethodError on line 47. But it doesn’t tell you that the job only fails when processing records created after the migration you ran on Thursday. The stack trace is correct and completely useless at the same time. This is the core problem with general-purpose error monitoring on Rails apps. Rails teams deal with N+1 queries that cascade into timeout errors.

DNS Spy Now Has an MCP Server. Ask Your AI About Any Domain.

DNS monitoring should be simple. You want to know if something changed. You want to know if a record propagated. You want to know if a phishing site just went live with your brand name in the domain. But in practice it takes work. You log in to a dashboard. You click through menus. You run a check, copy the output, paste it somewhere else. You repeat that process every time someone on the team asks a question. AI assistants like Claude and ChatGPT could help.

Your AI App Is Lying to You - Here's How to Fix That #devops #observability #programming

You shipped your AI app. But do you have all the answers? Do you actually know which model ran, how many tokens it consumed, or why it stopped? This is what LLM observability gives you, and most AI engineers are skipping it entirely. I built an SOS detection app and used OpenTelemetry to get full visibility into every single call. Token usage, model version, finish reason, and cost per call all in one place, standardised across any provider. Check out the OpenTelemetry GenAI docs in the link below; there is a lot more you can track than you think.

How to generate real-world load tests using Grafana Cloud k6 and production telemetry

For many development teams, a load test starts with a set of assumptions. You pick 100 virtual users because it sounds reasonable. You ramp for 30 seconds because that's what the tutorial showed. You set a 500ms threshold because it feels like a good target. The test passes, you ship the release, and production falls over at 6 p.m. on a Tuesday because your synthetic load never resembled how real users interact with your application.