Operations | Monitoring | ITSM | DevOps | Cloud

Claude Models Just Landed in Azure: I Opened a Terminal and Tested

Microsoft just added Anthropic’s Claude models to Microsoft Foundry. Instead of reading the press release, I ran a mini-benchmark to see how Claude Opus, Sonnet, and Haiku actually perform with real Python tasks and stdin/stdout workflows. The results will surprise you. Opus was the most complete, Haiku the fastest (and chattiest), and instruction-following was the weak point across the board. If you’re thinking about using Claude in production, read this first.

How to Audit AI-Written Pull Requests Without Burning Out

If it feels like your GitHub notifications are a targeted DDoS attack on your brain, you aren't imagining it. Data from GitHub's Octoverse 2025 report shows an average of 43.2 million pull requests merged every month, a 23% jump from just a year ago. This surge in activity coincides with the widespread adoption of AI tools to write code. The temptation to just click "Approve" on a well-formatted AI-written pull request is higher than ever.

Do you still need wildcard certificates?

You’ve used wildcard certificates for years. It made your life easier. Once a year you’d renew your wildcard certificate, and copy it around to all the servers. It was way too complicated and expensive to get a unique certificate for every system. But now certificate lifetimes are shrinking to 47 days by 2029 and it’s not going to work anymore. You need to automate your certificates. Soon.

What NVIDIA, Okta, and Warner Bros. Discovery Learned About Scaling AI Operations Beyond the Pilot Phase

One key takeaway from AWS re:Invent 2025 was that a clear gap has emerged between teams still experimenting with AI and those seeing measurable value at scale. In two sessions, PagerDuty customers joined us onstage to explain how they’ve scaled pilots into successful AI operations.

Building VC-ready AI companies: sustainability as an advantage

This blog post is based on a panel discussion about AI sustainability and investment trends, featuring insights from industry leaders at an AI conference. We utilized AI tools for transcription and to enhance the structure and clarity of the content. The AI investment is increasingly growing. While major tech companies plan to spend over $300 billion on AI infrastructure in 2025, investors are no longer just asking about powerful models or rapid scalability.

Simplifying Microsoft Sentinel Integration: VirtualMetric DataStream Connectors in Content Hub

Microsoft Sentinel adoption often introduces unexpected complexity. While the platform delivers powerful SIEM and XDR capabilities, organizations frequently struggle with manual DCR configuration, inconsistent data quality, rising ingestion costs, and security risks associated with credential-based integrations. VirtualMetric DataStream is now available in the Microsoft Sentinel Content Hub, reducing the effort required to deploy normalized and cost-optimized data ingestion.

IoT Sensor Data into Graylog: A Lab Guide

Graylog has always been associated with log management, metrics, SIEM and security monitoring—but it’s also a great tool for creative, low-cost experiments in a home lab. I wanted to use it for real-world sensor data, so I built a DIY temperature and humidity monitor using an ESP-WROOM-32 development board and a DHT22 sensor.

Cloud Efficiency Rate: A Clear Way To Measure Cloud Business Value

Cloud and AI spending is exploding, and every dollar counts. As companies race to innovate, they also face growing pressure to prove that their cloud investments are delivering real business value. That’s why CloudZero pioneered the Cloud Efficiency Rate (CER) metric, a unifying metric for quantifying cloud business value.

Why TikTok Views Matter for Viral Success

TikTok is probably the easiest platform to go viral on right now. Seriously. I've seen accounts with 50 followers get millions of views on their third video. That doesn't happen on Instagram. It definitely doesn't happen on Facebook. But on TikTok? It happens every single day. The reason is pretty simple TikTok doesn't care about how many followers you have. It cares about views. Specifically, it cares about how your views perform, how long people watch, and whether they engage.