Operations | Monitoring | ITSM | DevOps | Cloud

Zephyr includes many built-in features like stacks for networking and BLE, Flash storage APIs, and many kernel services. These components allow you to quickly get up and running with a project and maintain less code! Taking advantage of these is a huge win for small firmware teams and was a huge motivation in bringing Zephyr to my teams. This post covers Zephyr’s built-in ring buffer API, a component commonly used in producer-consumer scenarios.

The PagerDuty REST API provides 200+ endpoints for users to programmatically access objects and workflows in the PagerDuty platform. Teams leverage these APIs to streamline creating and managing users, teams, services and other components for their environment. Up until now, access to the REST API has been authorized and authenticated via API Keys.

How does Netdata's machine learning (ML) based anomaly detection actually work? Read on to find out!

Azure OpenAI is a service for deploying AI applications on Azure resources. With its easy-to-use REST APIs, you can leverage the service to access OpenAI’s powerful language models, such as ChatGPT, for your applications while taking advantage of the reliability and security of the Azure platform. Datadog already offers an out-of-the-box integration for OpenAI so you can monitor key performance trends, such as API usage patterns, token consumption, and more.

In this bi-weekly micro webinar series, Catchpoint and ITOps Times have partnered to explore six critical topics that are essential for ensuring Internet Resilience for your business. Explore each of the topics in the series: In this fourth segment, we’ll discuss techniques for enhancing Network and API performance by implementing Internet Performance Monitoring. Now, let’s get into the episode!

Honeycomb recently released our Query Assistant, which uses ChatGPT behind the scenes to build queries based on your natural language question. It's pretty cool. While developing this feature, our team (including Tanya Romankova and Craig Atkinson) built tracing in from the start, and used it to get the feature working smoothly. Here's an example. This trace shows a Query Assistant call that took 14 seconds. Is ChatGPT that slow? Our traces can tell us!