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AI

Contribute to Netdata's machine learning efforts!

Netdata contributors have greatly influenced the growth of our company and are essential to our success. The time and expertise that contributors volunteer are fundamental to our goal of helping you build extraordinary infrastructures. We highly value end-user feedback during product development, which is why we’re looking to involve you in progressing our machine learning (ML) efforts!

AI Meets Kubernetes: Install JupyterHub with Rancher

AI and Machine Learning are becoming critical differentiators in the technology landscape. By their nature, AI and ML are computation hungry workloads. They require best-in-class distributed computing environments to thrive. AI and ML present a perfect use case for Kubernetes, the distributed computing platform engineered at Google to run their massive workloads.

HAProxyConf 2019 - Hyperscaling Self-Service Infrastructure with William Dauchy & Pierre Cheynier

At Criteo, we work at the cutting edge of commerce marketing, using Machine Learning and Artificial Intelligence to help our customers grow their businesses through hyper-relevant advertising. We run tens of thousands of servers, host containers that continuously move across data centers, and scale services through our managed APIs, with HAProxy playing a critical role across our fast-paced, event-driven infrastructure. This presentation will describe our journey to achieve load balancing served via a user-centric API in such a large and complex environment. We will share tricks and design considerations that helped us to go from a user intent expressed through an API to a scalable service running globally.

Using AI to Auto-Detect and Remediate Incidents

Today, the number of possible failure modes in cloud and microservices applications are exploding, making it increasingly difficult to gain true observability and take the right action across IT environments. According to Lightstep’s Global Microservices Trends report, 91% of teams are using or have plans to use microservices, but 73% report it is harder to troubleshoot application performance problems due to greater complexity.

AI-Powered Monitoring for Hybrid IT

This blog originally appeared on HPE. Hewlett-Packard Enterprise (HPE) recently invested in OpsRamp. Consider this: when you drive a car, how would you know whether the car needs maintenance? You might look for status indicators like a check engine or change oil light. Similarly, when a pilot flies an airplane, they rely on a multitude of metrics and data to ensure the plane is running smoothly. Managing IT infrastructure is similar in nature.

Five worthy reads: Why AI-as-a-Service, or AIaaS, is quickly growing in popularity

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. Most companies use some type of “as-a-service” solution to optimize output, and this week, we shed some light on the latest “as-a-service” trend to hit the market, AI-as-a-Service.