The Past, Present, and Future of Kubernetes on Raspberry Pi
Explore Kubernetes on Raspberry Pi: past developments, current state, and future possibilities. Learn about ARM architecture, cluster building, and practical applications through live demos and expert insights.
Zero-Touch Provisioning in Scale Computing Fleet Manager - Live Demo
Discover how Zero-Touch Provisioning streamlines cluster deployment and remote staging, reducing setup time and simplifying Day-0 operations for IT teams managing distributed infrastructure.
Enabling Compute and Data Sovereignty with Infrastructure-Level Data Spaces
Explore infrastructure-level data spaces implementation for secure data exchange between clusters, focusing on sovereignty maintenance and efficient compute offloading patterns in modern data management systems.
Databricks Distributed File System (DBFS) vs Local Files on Spark Cluster Driver Node
Understand the key differences between Databricks File System (DBFS) and local driver node storage, exploring distributed storage capabilities and FUSE mount implementation for cloud data access.
A Haskell Auto-Parallelizer for Distributed Computing
Explore a Haskell auto-parallelizer for distributed computing, leveraging function purity to create scalable and performant applications on large clusters.
Hazelcast 5.2 - What's Next?
Explore the latest features and future developments of Hazelcast 5.2, gaining insights into its enhanced capabilities and potential applications.
Creating and Submitting Scala Jobs to Spark Clusters Using Airflow
Build end-to-end data engineering project using Airflow, Docker, Spark, Scala, Python, and Java. Create and submit jobs to Spark clusters, process data, and view real-time results.
End-to-End Data Engineering with Apache Airflow, Docker, and Spark Clusters - Using Python, Scala, and Java
Build an end-to-end data engineering project using Apache Airflow, Docker, Spark Clusters, Scala, Python, and Java. Create and submit jobs in multiple languages to a Spark cluster for processing and real-time results.
Power-aware Deep Learning Model Serving with μ-Serve
Explores μ-Serve, a power-aware model-serving system optimizing GPU frequency scaling and model multiplexing for energy-efficient deep learning workloads in homogeneous GPU clusters.
Infrastructure Software for Hyperscale AI and GPU Clusters
Explore cutting-edge infrastructure software solutions powering large-scale AI operations and GPU cluster management for hyperscale computing environments.
RPC in WhatsApp - Scaling Erlang Infrastructure
Explore WhatsApp's Erlang infrastructure, covering scaled clusters, RPC workflow, service discovery, request dispatching, and load balancing for high-scale systems.
Scaling Deep Learning Model Training
Learn techniques for scaling deep learning model training across distributed systems, reducing training time from days to hours while maintaining cost efficiency.
Building RAG-based LLM Applications for Production - LLMs III Talk
Develop and deploy scalable RAG-based LLM applications. Learn to handle data loading, preprocessing, embedding, and serving on clusters. Explore Anyscale Endpoints for cost-effective open-source model serving.
Magic Castle - Terraforming the Cloud to Teach High-Performance Computing
Replicate HPC infrastructure experience using cloud resources with Magic Castle. Deploy complete clusters with schedulers, data-transfer nodes, and pre-compiled software in minutes.
Proxmox VE SDN VXLAN Setup Tutorial
Learn to set up Software Defined Networking with VXLAN in Proxmox VE, enabling virtual networks across cluster nodes without physical network changes. Ideal for IT professionals seeking efficient network management.
Apache Airflow with Spark for Data Engineers - Full Course
Build end-to-end data engineering projects using Apache Airflow, Docker, Spark, and multiple programming languages. Learn to create and submit jobs to Spark clusters for processing and view real-time results.
Distributed Cache Empowers AI/ML Workloads on Kubernetes Cluster
Discover how to optimize AI/ML workloads on Kubernetes using distributed cache systems, achieving high-performance data access with 50+ GB/s throughput and sub-2ms latency for large-scale GPU clusters.
Apache Pulsar Cluster Scale Control and Stability Practice
Dive into advanced techniques for managing Apache Pulsar clusters, focusing on scale control mechanisms and proven stability practices for enterprise messaging systems.
MicroCloud 2.1.0 LTS - Deployment and Scaling Tutorial
Discover how to deploy and scale MicroCloud 2.1.0 LTS, from single-node setup to creating a highly available cluster, with enhanced security features and flexible initialization options.