Managing Infrastructure as Code at Scale With env0
Explore common IaC challenges and learn how env0 simplifies infrastructure automation through a hands-on demonstration of managing Infrastructure as Code at scale.
Performant Node Infrastructure for Enterprise Blockchain Adoption
Explore how performant node infrastructure drives enterprise blockchain adoption, focusing on Hyperledger Besu's role and Validation Cloud's innovative approach in reshaping the landscape.
Managing Machine Learning Projects - From Design to Deployment
Explore ML project management strategies, from setup to production integration. Learn to navigate challenges, assess models, and align with business processes for successful implementation.
Building LLM Applications for Production
Explore key challenges in deploying LLMs to production, covering essential considerations for real-world application development and implementation.
Scalable Evaluation and Serving of Open Source LLMs
Explore challenges and solutions for serving open-source LLMs in production, focusing on scalable evaluation and deployment strategies.
The State of Production Machine Learning in 2024
Explore the challenges and best practices for deploying robust, scalable ML systems in production. Learn about key focus areas, recommended tools, and ecosystem insights for effective MLOps at scale.
Open Standards Make MLOps Easier and Silos Harder - MLOps Podcast Episode 234
Explore open standards in MLOps for easier data system integration, scalability, and collaboration. Learn about Ibis, Apache Arrow, and their impact on data engineering and machine learning workflows.
Google App Engine: Deploy Machine Learning Applications in Google Cloud
Deploy machine learning applications on Google Cloud using App Engine. Learn to leverage cloud infrastructure for scalable ML solutions.
Modernizing Applications to the Cloud with AI, Scalability and Optimizations
Modernize legacy apps with Azure: migrate to cloud, scale with Flex Functions, add AI via Logic Apps, and optimize in real-time using cutting-edge tools.
Exascale Computing Project Applications: Lessons Learned
Explore key insights and lessons learned from Exascale Computing Project applications development with Erik Draeger, deputy director of Application Development.
Powering AI Capabilities with API Management
Explore integrating Apache APISIX API Gateway with OpenAI API for scalable, performant, and secure AI applications. Learn proxy caching and security features.
Best Practices for Effective Multi-Cluster Observability: Lessons Learned
Explore strategies for effective multi-cluster observability in cloud-native environments, covering centralized monitoring, logging, tracing, and analytics based on real-world experiences.
Thinking Like a Site Reliability Engineer to Improve Continuous Integration
Apply SRE principles to optimize continuous integration at scale. Learn to balance risk, measure objectives, and adapt strategies for your team's CI process improvement.
Building a Distributed Search Engine for Logs
Explore efficient architecture for building a distributed search engine to handle terabytes of logs, inspired by Snowflake's compute-storage separation approach.
The Feeling of Fast Code - Strategies for Optimizing Performance
Explore strategies for optimizing code performance, from management to assembly level. Learn to design scalable systems and stay current with efficient coding practices.
Exploring OpenShift on Arm: A Deep Dive
Dive deep into OpenShift on Arm architecture with Red Hat expert Duncan Hardie. Explore deployment strategies, performance optimizations, and best practices for Arm-based infrastructure.
Introduction to Apache Kafka - Core Concepts and Use Cases
Explore Apache Kafka's fundamentals, history, key concepts, and real-world applications. Learn how to deploy and manage Kafka using Canonical's Charmed Kafka solution.
The Magic of Merlin - Shopify's New Machine Learning Platform
Explore Shopify's Merlin ML platform, its open-source stack, architecture, and how it scales ML work using Ray.
Scalable Training of Language Models Using Ray, JAX, and TPUv4
Explore challenges and design decisions for scalable language model training, with quantitative analysis of efficiency improvements using Ray, JAX pjit, and TPUv4.
Scalable Feature Engineering with Hamilton on Ray
Explore scalable feature engineering using Hamilton and Ray at StitchFix. Learn declarative dataflow, team scaling, and efficient computation for thousands of time-series features.
Cruise.data - A New Dataset Processing Pipeline for Cruise ML
Explore Cruise.data, a novel ML data pre-processing framework combining tf.data, PyTorch, and large-scale processing capabilities for efficient and scalable dataset handling in autonomous vehicle development.