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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.

Top 10 predictions for AI in IT operations

This article originally appeared in TechBeacon. Gartner first coined the term "AIOps" a few years ago to describe "artificial intelligence for IT operations," and over the last few years, IT operations monitoring tool vendors have begun incorporating AIOps features into their products. Now AIOps tools are commonplace, but many IT leaders remain cautious about using these relatively new capabilities.

Creating a Custom Container for the Deep Learning Toolkit: Splunk + Rapids.ai

The Deep Learning Toolkit (DLTK) was launched at .conf19 with the intention of helping customers leverage additional Deep Learning frameworks as part of their machine learning workflows. The app ships with four separate containers: Tensorflow 2.0 - CPU, Tensorflow 2.0 GPU, Pytorch and SpaCy. All of the containers provide a base install of Jupyter Lab & Tensorboard to help customers develop and create neural nets or custom algorithms.