Remove model-based-integration
article thumbnail

Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
article thumbnail

How Red Hat and Dynatrace intelligently automate your production environment

Dynatrace

A tight integration between Red Hat Ansible Automation Platform, Dynatrace Davis ® AI, and the Dynatrace observability and security platform enables closed-loop remediation to automate the process from: Detecting a problem. Figure 2: Integration options of Red Hat and Dynatrace to drive automation and remediation with context.

DevOps 282
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges. It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security.

Cache 201
article thumbnail

Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

In this blog post, we present our project on Auto Remediation, which integrates the currently used rule-based classifier with an ML service and aims to automatically remediate failed jobs without human intervention. Its major advantages are below: Integrated intelligence. Fully automated.

Tuning 210
article thumbnail

Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

Nir Gazit, CEO and Co-Founder Traceloop Why AI model observability matters The adoption of LLMs has surged across various industries, particularly since the introduction of OpenAI’s GPT model. While these models yield impressive results, the challenge of maintaining their operation within defined boundaries has increased.

article thumbnail

RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

Moreover, in addition to managing cloud spend and resource utilization, organizations must also now consider the cost and carbon impact of developing and using generative AI models. Therefore, these organizations need an in-depth strategy for handling data that AI models ingest, so teams can build AI platforms with security in mind.

article thumbnail

Generative AI model observability, cloud modernization take center stage with partners at Dynatrace Perform 2024

Dynatrace

At this year’s Perform, we are thrilled to have our three strategic cloud partners, Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), returning as both sponsors and presenters to share their expertise about cloud modernization and observability of generative AI models.

Cloud 208