NSG Data Analytic Architecture Service - Adopting Mesos for Large-Scale Processing
Explore how the National Geospatial-Intelligence Agency adopts Mesos for large-scale processing, including metrics, Jenkins integration, and future plans.
State is Hard: An SDK for Building Stateful Applications
Learn to build robust stateful applications using the DC/OS SDK, simplifying development on Apache Mesos and DC/OS platforms while standardizing service interactions and handling common challenges.
Adapting Kubernetes for Machine Learning Workflows
Explore how Bloomberg adapted Kubernetes for machine learning, addressing multi-tenancy, data security, and hardware acceleration in their AI-driven financial services platform.
Using External Persistent Volumes for High Availability on DC/OS
Explore strategies for reducing recovery times and achieving high availability in DC/OS using external persistent volumes, focusing on distributed applications like Cassandra and HDFS.
Real-Time Event Processing and Handling Stateful Applications on Apache Mesos
Explore real-time event processing and stateful applications on Apache Mesos, focusing on industrial use cases, PaaS journey, and stream processing platforms. Learn from GE Digital's experience in handling complex workloads.
Apache Mesos for Hybrid Cloud Management
Learn how Apache Mesos enables flexible, scalable hybrid cloud setups for modern applications across on-premise, private, and public environments, addressing business continuity and disaster recovery challenges.
SMACK in the Enterprise - Keynote Panel Discussion
Panel discussion exploring SMACK (Spark, Mesos, Akka, Cassandra, Kafka) implementation in enterprise environments, featuring insights from industry experts at Audi, Deutsche Telekom, and ASML.
OpenTelemetry Collector - The Swiss Army Knife of Observability
Explore Adobe's journey adopting OpenTelemetry Collector to simplify complex observability architecture, including exporters, processors, and custom extensions for streamlined data management.
How to Eliminate I/O Bottleneck and Continuously Feed GPU While Training in the Cloud
Optimize I/O for GPU-intensive machine learning training in the cloud. Learn a new architecture to maintain data throughput and implement it in Kubernetes for PyTorch workloads.
Data Collector Model in Agent-Based Modeling with Mesa - Session 18
Learn to implement a Data Collector Model in Mesa, enhancing your agent-based modeling skills with Python and improving data analysis capabilities.
Measurement and Operationalization in Humanities Analytics - FAHA Course
Explore measurement and operationalization in humanities analytics. Learn to extract meaning from digital sources, enabling new scholarship in cultural and textual analysis.
Perspective in 3D - Vector Math and Ray Tracing for Financial Data Analysis
Explore vector math, ray tracing, and creative engineering as Perspective's expression language is repurposed for 3D graphics, blending financial analysis with game engine concepts.
Dynamic Data and Infinite Possibilities - Exploring Streaming Data in Generative AI
Explore streaming data's role in generative AI, covering applications, model training, and challenges. Learn about real-time data's impact on AI systems' adaptability and contextual relevance.
Leveraging Compiler Code Instrumentation for Zephyr Tracing and Profiling Tools
Explore a new platform-neutral subsystem for Zephyr using compiler function instrumentation, enabling efficient tracing and profiling across various architectures without proprietary tools.
Accessible Neural Search and Cloud-Nativeness for ML Engineers
Explore neural search for cross-modal data, learn Jina's architecture for building cloud-native AI applications, and understand essential technologies for production-ready systems.
Optimizing Speed and Scale of Real-Time Analytics Using Apache Pulsar and Apache Pinot
Explore Apache Pulsar and Apache Pinot's synergy for high-speed, scalable real-time analytics in Cloud Native environments. Learn how these powerful tools enable efficient event streaming and ad-hoc data analysis.
Training AI to Code Using Project CodeNet - Largest Code Dataset
Explore Project CodeNet's vast code dataset and learn to leverage it for AI-driven code classification, complexity analysis, and language translation using MLX and Kubernetes.
Creating a Custom Serving Runtime in KServe ModelMesh - Hands-On Experience
Learn to create custom serving runtimes in KServe ModelMesh for ML model deployment. Explore key features, build container images, and run predictions using custom runtimes in this hands-on tutorial.
Right-Sizing and Auto-Scaling of MySQL Containers in Kubernetes
Optimizing MySQL container resources in Kubernetes using statistical analysis and algorithms for dynamic sizing and scaling, improving performance and efficiency while reducing costs.
Unified and Pluggable Cluster Management Platform at LinkedIn
Explore LinkedIn's journey in adopting Kubernetes for cluster management, addressing challenges and integrating with existing systems at scale.
HDFS CSI Plugin: Speeding Up Kubernetes in On-Premises Big Data Clusters
Explore HDFS CSI plugin design for Kubernetes in on-premises big data clusters, including architecture, best practices, and performance analysis using Spark and TPC-DS benchmarks.