Enterprise Distributed Query Service powered by Presto & Alluxio across cloud...Alluxio, Inc.
Data Orchestration Summit
www.alluxio.io/data-orchestration-summit-2019
November 7, 2019
Enterprise Distributed Query Service powered by Presto & Alluxio across clouds at WalmartLabs
Speaker:
Ashish Tadose, WalmartLabs
For more Alluxio events: https://www.alluxio.io/events/
Enterprise Distributed Query Service powered by Presto & Alluxio across cloud...Alluxio, Inc.
Data Orchestration Summit
www.alluxio.io/data-orchestration-summit-2019
November 7, 2019
Enterprise Distributed Query Service powered by Presto & Alluxio across clouds at WalmartLabs
Speaker:
Ashish Tadose, WalmartLabs
For more Alluxio events: https://www.alluxio.io/events/
Securely Enhancing Data Access in Hybrid Cloud with AlluxioAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Securely Enhancing Data Access in Hybrid Cloud with Alluxio
Michael Fagan & Prashant Khanolkar, Comcast
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
StorageQuery: federated querying on object stores, powered by Alluxio and PrestoAlluxio, Inc.
Alluxio Global Online Meetup
August 25, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Abner Ferreira, Simbiose Ventures
Caio Pavanelli, Simbiose Ventures
Bin Fan, Alluxio
Over the last few years, organizations have worked towards the separation of storage and compute for a number of benefits in the areas of cost, data duplication and data latency. Cloud resolves most of these issues but comes to the expense of needing a way to query data on remote storages. Alluxio and Presto are a powerful combination to address the compute problem, which is part of the strategy used by Simbiose Ventures to create a product called StorageQuery - A platform to query files in cloud storages with SQL.
This talk will focus on:
- How Alluxio fits StorageQuery's tech stack;
- Advantages of using Alluxio as a cache layer and its unified filesystem;
- Development of new under file system for Backblaze B2 and fine-grained code documentation;
- ShannonDB remote storage mode.
Data Orchestration Summit
www.alluxio.io/data-orchestration-summit-2019
November 7, 2019
Presto on Alluxio Hands-On Lab
Speakers:
Bin Fan, Alluxio
Zac Blanco, Alluxio
Kamil Bajda-Pawlikowski, Starburst, Presto Company
Martin Traverso, Presto Software Foundation
For more Alluxio events: https://www.alluxio.io/events/
Ultra Fast Deep Learning in Hybrid Cloud Using Intel Analytics Zoo & AlluxioAlluxio, Inc.
Alluxio Global Online Meetup
Apr 23, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Jiao (Jennie) Wang, Intel
Tsai Louie, Intel
Bin Fan, Alluxio
Today, many people run deep learning applications with training data from separate storage such as object storage or remote data centers. This presentation will demo the Intel Analytics Zoo + Alluxio stack, an architecture that enables high performance while keeping cost and resource efficiency balanced without network being I/O bottlenecked.
Intel Analytics Zoo is a unified data analytics and AI platform open-sourced by Intel. It seamlessly unites TensorFlow, Keras, PyTorch, Spark, Flink, and Ray programs into an integrated pipeline, which can transparently scale from a laptop to large clusters to process production big data. Alluxio, as an open-source data orchestration layer, accelerates data loading and processing in Analytics Zoo deep learning applications.
This talk, we will go over:
- What is Analytics Zoo and how it works
- How to run Analytics Zoo with Alluxio in deep learning applications
- Initial performance benchmark results using the Analytics Zoo + Alluxio stack
Building Fast SQL Analytics on Anything with Presto, AlluxioAlluxio, Inc.
Alluxio Bay Area Meetup @ Galvanize | SF
Aug 20, 2019
Interactive Analytics in the Cloud with Presto and Alluxio
Speaker:
Bin Fan, Founding Engineer, Alluxio
Introducing the Hub for Data OrchestrationAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Introducing the Hub for Data Orchestration
Adit Madan, Product Manager (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Alluxio 2.0 & Near Real-time Big Data Platform w/ Spark & AlluxioAlluxio, Inc.
Alluxio Bay Area Meetup March 14th
Join the Alluxio Meetup group: https://www.meetup.com/Alluxio
Alluxio Community slack: https://www.alluxio.org/slack
Alluxio Use Cases and Future DirectionsAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Data Orchestration for Analytics and AI in the Cloud Era
Calvin Jia, Founding Engineer (Alluxio)
Bin Fan, Founding Engineer, VP of Open Source (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Hands-on with Alluxio Structured Data ManagementAlluxio, Inc.
Alluxio Online Office Hours
January 14, 2020
We introduce the concepts and components of Alluxio Structured Data Management, and go through a demo with Presto.
ApacheCon 2021
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Lu Qiu
Bin Fan
Alluxio’s capabilities as a Data Orchestration framework have encouraged users to onboard more of their data-driven applications to an Alluxio powered data access layer. Driven by strong interests from our open-source community, the core team of Alluxio started to re-design an efficient and transparent way for users to leverage data orchestration through the POSIX interface. This effort has a lot of progress with the collaboration with engineers from Microsoft, Alibaba and Tencent. Particularly, we have introduced a new JNI-based FUSE implementation to support POSIX data access, created a more efficient way to integrate Alluxio with FUSE service, as well as many improvements in relevant data operations like more efficient distributedLoad, optimizations on listing or calculating directories with a massive amount of files, which are common in model training. We will also share our engineering lessons and roadmap in future releases to support Machine Learning applications.
Accelerate Analytics and ML in the Hybrid Cloud EraAlluxio, Inc.
Alluxio Community Office Hour
February 23, 2021
For more Alluxio events: https://www.alluxio.io/events/
Speaker(s):
Alex Ma, Alluxio
Peter Behrakis, Alluxio
Many companies we talk to have on premises data lakes and use the cloud(s) to burst compute. Many are now establishing new object data lakes as well. As a result, running analytics such as Hive, Spark, Presto and machine learning are experiencing sluggish response times with data and compute in multiple locations. We also know there is an immense and growing data management burden to support these workflows.
In this talk, we will walk through what Alluxio’s Data Orchestration for the hybrid cloud era is and how it solves the performance and data management challenges we see.
In this tech talk, we'll go over:
- What is Alluxio Data Orchestration?
- How does it work?
- Alluxio customer results
The Practice of Presto & Alluxio in E-Commerce Big Data PlatformAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
The Practice of Presto & Alluxio in E-Commerce Big Data Platform
Wenjun Tao, Sr. Software Engineer, JD.com
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Reducing large S3 API costs using Alluxio at Datasapiens Alluxio, Inc.
Alluxio Global Online Meetup
August 4, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Koen Michiels, Datasapiens
Juraj Pohanka, Datasapiens
Bin Fan, Alluxio
Datasapiens is an international data-analytics startup based in Prague. We help our clients to uncover the value of their data and open up new revenue streams for them. We provide an end-to-end service that manages the data pipeline and automates the process of generating data insights.
In this talk, we will describe how we have solved an issue with large S3 API costs incurred by Presto under several usage concurrency levels by implementing Alluxio as a data orchestration layer between S3 and Presto. Also, we will show the results of an experiment with estimating the per-query S3 API costs using the TPC-DS dataset.
This talk will focus on:
- The Hadoop ecosystem at Datasapiens
- Drastic increase of S3 API costs during performance tests with Presto
- S3 API costs tests with TPC-DS
- Implications to the cloud data lake architecture
Presto: Fast SQL-on-Anything Across Data Lakes, DBMS, and NoSQL Data StoresAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Presto: Fast SQL-on-Anything Across Data Lakes, DBMS, and NoSQL Data Stores
Kamil Bajda-Pawlikowski, CTO, Starburst Data
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Spark Pipelines in the Cloud with Alluxio by Bin FanData Con LA
Abstract:- Organizations commonly use Big Data computation frameworks like Apache Hadoop MapReduce or Apache Spark to gain actionable insight from their large amounts of data. Often, these analytics are in the form of data processing pipelines, where there are a series of processing stages, and each stage performs a particular function, and the output of one stage is the input of the next stage. There are several examples of pipelines, such as log processing, IoT pipelines, and machine learning. The common attribute among different pipelines is the sharing of data between stages. It is also common for data pipelines to process data stored in the public cloud, such as Amazon S3, Microsoft Azure Blob Storage, or Google Cloud Storage. The global availability and cost effectiveness of these public cloud storage services make them the preferred storage for data. However, running pipeline jobs while sharing data via cloud storage can be expensive in terms of increased network traffic, and slower data sharing and job completion times. Using Alluxio, a memory speed virtual distributed storage system, enables sharing data between different stages or jobs at memory speed. By reading and writing data in Alluxio, the data can stay in memory for the next stage of the pipeline, and this result in great performance gains. In this talk, we discuss how Alluxio can be deployed and used with a data processing pipeline in the cloud. We show how pipeline stages can share data with Alluxio memory for improved performance benefits, and how Alluxio can improves completion times and reduces performance variability for pipelines in the cloud.
Best Practices for Using Alluxio with Apache Spark with Gene PangSpark Summit
Alluxio, formerly Tachyon, is a memory speed virtual distributed storage system and leverages memory for storing data and accelerating access to data in different storage systems. Many organizations and deployments use Alluxio with Apache Spark, and some of them scale out to over PB’s of data. Alluxio can enable Spark to be even more effective, in both on-premise deployments and public cloud deployments. Alluxio bridges Spark applications with various storage systems and further accelerates data intensive applications. In this talk, we briefly introduce Alluxio, and present different ways how Alluxio can help Spark jobs. We discuss best practices of using Alluxio with Spark, including RDDs and DataFrames, as well as on-premise deployments and public cloud deployments.
Securely Enhancing Data Access in Hybrid Cloud with AlluxioAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Securely Enhancing Data Access in Hybrid Cloud with Alluxio
Michael Fagan & Prashant Khanolkar, Comcast
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
StorageQuery: federated querying on object stores, powered by Alluxio and PrestoAlluxio, Inc.
Alluxio Global Online Meetup
August 25, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Abner Ferreira, Simbiose Ventures
Caio Pavanelli, Simbiose Ventures
Bin Fan, Alluxio
Over the last few years, organizations have worked towards the separation of storage and compute for a number of benefits in the areas of cost, data duplication and data latency. Cloud resolves most of these issues but comes to the expense of needing a way to query data on remote storages. Alluxio and Presto are a powerful combination to address the compute problem, which is part of the strategy used by Simbiose Ventures to create a product called StorageQuery - A platform to query files in cloud storages with SQL.
This talk will focus on:
- How Alluxio fits StorageQuery's tech stack;
- Advantages of using Alluxio as a cache layer and its unified filesystem;
- Development of new under file system for Backblaze B2 and fine-grained code documentation;
- ShannonDB remote storage mode.
Data Orchestration Summit
www.alluxio.io/data-orchestration-summit-2019
November 7, 2019
Presto on Alluxio Hands-On Lab
Speakers:
Bin Fan, Alluxio
Zac Blanco, Alluxio
Kamil Bajda-Pawlikowski, Starburst, Presto Company
Martin Traverso, Presto Software Foundation
For more Alluxio events: https://www.alluxio.io/events/
Ultra Fast Deep Learning in Hybrid Cloud Using Intel Analytics Zoo & AlluxioAlluxio, Inc.
Alluxio Global Online Meetup
Apr 23, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Jiao (Jennie) Wang, Intel
Tsai Louie, Intel
Bin Fan, Alluxio
Today, many people run deep learning applications with training data from separate storage such as object storage or remote data centers. This presentation will demo the Intel Analytics Zoo + Alluxio stack, an architecture that enables high performance while keeping cost and resource efficiency balanced without network being I/O bottlenecked.
Intel Analytics Zoo is a unified data analytics and AI platform open-sourced by Intel. It seamlessly unites TensorFlow, Keras, PyTorch, Spark, Flink, and Ray programs into an integrated pipeline, which can transparently scale from a laptop to large clusters to process production big data. Alluxio, as an open-source data orchestration layer, accelerates data loading and processing in Analytics Zoo deep learning applications.
This talk, we will go over:
- What is Analytics Zoo and how it works
- How to run Analytics Zoo with Alluxio in deep learning applications
- Initial performance benchmark results using the Analytics Zoo + Alluxio stack
Building Fast SQL Analytics on Anything with Presto, AlluxioAlluxio, Inc.
Alluxio Bay Area Meetup @ Galvanize | SF
Aug 20, 2019
Interactive Analytics in the Cloud with Presto and Alluxio
Speaker:
Bin Fan, Founding Engineer, Alluxio
Introducing the Hub for Data OrchestrationAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Introducing the Hub for Data Orchestration
Adit Madan, Product Manager (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Alluxio 2.0 & Near Real-time Big Data Platform w/ Spark & AlluxioAlluxio, Inc.
Alluxio Bay Area Meetup March 14th
Join the Alluxio Meetup group: https://www.meetup.com/Alluxio
Alluxio Community slack: https://www.alluxio.org/slack
Alluxio Use Cases and Future DirectionsAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Data Orchestration for Analytics and AI in the Cloud Era
Calvin Jia, Founding Engineer (Alluxio)
Bin Fan, Founding Engineer, VP of Open Source (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Hands-on with Alluxio Structured Data ManagementAlluxio, Inc.
Alluxio Online Office Hours
January 14, 2020
We introduce the concepts and components of Alluxio Structured Data Management, and go through a demo with Presto.
ApacheCon 2021
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Lu Qiu
Bin Fan
Alluxio’s capabilities as a Data Orchestration framework have encouraged users to onboard more of their data-driven applications to an Alluxio powered data access layer. Driven by strong interests from our open-source community, the core team of Alluxio started to re-design an efficient and transparent way for users to leverage data orchestration through the POSIX interface. This effort has a lot of progress with the collaboration with engineers from Microsoft, Alibaba and Tencent. Particularly, we have introduced a new JNI-based FUSE implementation to support POSIX data access, created a more efficient way to integrate Alluxio with FUSE service, as well as many improvements in relevant data operations like more efficient distributedLoad, optimizations on listing or calculating directories with a massive amount of files, which are common in model training. We will also share our engineering lessons and roadmap in future releases to support Machine Learning applications.
Accelerate Analytics and ML in the Hybrid Cloud EraAlluxio, Inc.
Alluxio Community Office Hour
February 23, 2021
For more Alluxio events: https://www.alluxio.io/events/
Speaker(s):
Alex Ma, Alluxio
Peter Behrakis, Alluxio
Many companies we talk to have on premises data lakes and use the cloud(s) to burst compute. Many are now establishing new object data lakes as well. As a result, running analytics such as Hive, Spark, Presto and machine learning are experiencing sluggish response times with data and compute in multiple locations. We also know there is an immense and growing data management burden to support these workflows.
In this talk, we will walk through what Alluxio’s Data Orchestration for the hybrid cloud era is and how it solves the performance and data management challenges we see.
In this tech talk, we'll go over:
- What is Alluxio Data Orchestration?
- How does it work?
- Alluxio customer results
The Practice of Presto & Alluxio in E-Commerce Big Data PlatformAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
The Practice of Presto & Alluxio in E-Commerce Big Data Platform
Wenjun Tao, Sr. Software Engineer, JD.com
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Reducing large S3 API costs using Alluxio at Datasapiens Alluxio, Inc.
Alluxio Global Online Meetup
August 4, 2020
For more Alluxio events: https://www.alluxio.io/events/
Speakers:
Koen Michiels, Datasapiens
Juraj Pohanka, Datasapiens
Bin Fan, Alluxio
Datasapiens is an international data-analytics startup based in Prague. We help our clients to uncover the value of their data and open up new revenue streams for them. We provide an end-to-end service that manages the data pipeline and automates the process of generating data insights.
In this talk, we will describe how we have solved an issue with large S3 API costs incurred by Presto under several usage concurrency levels by implementing Alluxio as a data orchestration layer between S3 and Presto. Also, we will show the results of an experiment with estimating the per-query S3 API costs using the TPC-DS dataset.
This talk will focus on:
- The Hadoop ecosystem at Datasapiens
- Drastic increase of S3 API costs during performance tests with Presto
- S3 API costs tests with TPC-DS
- Implications to the cloud data lake architecture
Presto: Fast SQL-on-Anything Across Data Lakes, DBMS, and NoSQL Data StoresAlluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Presto: Fast SQL-on-Anything Across Data Lakes, DBMS, and NoSQL Data Stores
Kamil Bajda-Pawlikowski, CTO, Starburst Data
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Spark Pipelines in the Cloud with Alluxio by Bin FanData Con LA
Abstract:- Organizations commonly use Big Data computation frameworks like Apache Hadoop MapReduce or Apache Spark to gain actionable insight from their large amounts of data. Often, these analytics are in the form of data processing pipelines, where there are a series of processing stages, and each stage performs a particular function, and the output of one stage is the input of the next stage. There are several examples of pipelines, such as log processing, IoT pipelines, and machine learning. The common attribute among different pipelines is the sharing of data between stages. It is also common for data pipelines to process data stored in the public cloud, such as Amazon S3, Microsoft Azure Blob Storage, or Google Cloud Storage. The global availability and cost effectiveness of these public cloud storage services make them the preferred storage for data. However, running pipeline jobs while sharing data via cloud storage can be expensive in terms of increased network traffic, and slower data sharing and job completion times. Using Alluxio, a memory speed virtual distributed storage system, enables sharing data between different stages or jobs at memory speed. By reading and writing data in Alluxio, the data can stay in memory for the next stage of the pipeline, and this result in great performance gains. In this talk, we discuss how Alluxio can be deployed and used with a data processing pipeline in the cloud. We show how pipeline stages can share data with Alluxio memory for improved performance benefits, and how Alluxio can improves completion times and reduces performance variability for pipelines in the cloud.
Best Practices for Using Alluxio with Apache Spark with Gene PangSpark Summit
Alluxio, formerly Tachyon, is a memory speed virtual distributed storage system and leverages memory for storing data and accelerating access to data in different storage systems. Many organizations and deployments use Alluxio with Apache Spark, and some of them scale out to over PB’s of data. Alluxio can enable Spark to be even more effective, in both on-premise deployments and public cloud deployments. Alluxio bridges Spark applications with various storage systems and further accelerates data intensive applications. In this talk, we briefly introduce Alluxio, and present different ways how Alluxio can help Spark jobs. We discuss best practices of using Alluxio with Spark, including RDDs and DataFrames, as well as on-premise deployments and public cloud deployments.
Getting Started with Apache Spark and Alluxio for Blazingly Fast AnalyticsAlluxio, Inc.
Alluxio Austin Meetup
Aug 15, 2019
Speaker: Bin Fan
Apache Spark and Alluxio are cousin open source projects that originated from UC Berkeley’s AMPLab. Running Spark with Alluxio is a popular stack particularly for hybrid environments. In this session, I will briefly introduce Apache Spark and Alluxio, share the top ten tips for performance tuning for real-world workloads, and demo Alluxio with Spark.
Spark Pipelines in the Cloud with Alluxio with Gene PangSpark Summit
Organizations commonly use Apache Spark to gain actionable insight from their large amounts of data. Often, these analytics are in the form of data processing pipelines, where there are a series of processing stages, and each stage performs a particular function, and the output of one stage is the input of the next stage. There are several examples of pipelines, such as log processing, IoT pipelines, and machine learning. The common attribute among different pipelines is the sharing of data between stages. It is also common for Spark pipelines to process data stored in the public cloud, such as Amazon S3, Microsoft Azure Blob Storage, or Google Cloud Storage. The global availability and cost effectiveness of these public cloud storage services make them the preferred storage for data. However, running pipeline jobs while sharing data via cloud storage can be expensive in terms of increased network traffic, and slower data sharing and job completion times. Using Alluxio, a memory speed virtual distributed storage system, enables sharing data between different stages or jobs at memory speed. By reading and writing data in Alluxio, the data can stay in memory for the next stage of the pipeline, and this result in great performance gains. In this talk, we discuss how Alluxio can be deployed and used with a Spark data processing pipeline in the cloud. We show how pipeline stages can share data with Alluxio memory for improved performance benefits, and how Alluxio can improves completion times and reduces performance variability for Spark pipelines in the cloud.
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloadsAlluxio, Inc.
Alluxio Tech Talk
Aug 7, 2019
Speaker:
Dipti Borkar, Alluxio
Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored.
This release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
In this tech talk, we will introduce the key new features and enhancements such as:
- Support for hyper-scale data workloads with tiered metadata storage, distributed cluster services, and adaptive replication for increased data locality
- Machine learning and deep learning workloads on any storage with the improved POSIX API
- Better storage abstraction with support for HDFS clusters across different versions & active sync with Hadoop
Meetup at AI NextCon 2019: In-Stream data process, Data Orchestration & MoreAlluxio, Inc.
Alluxio - Data Orchestration for Analytics and AI in the Cloud
Oct 8, 2019
Speakers:
Haoyuan Li & Bin Fan, Alluxio
Visit https://www.alluxio.io/events/ for more Alluxio events.
Over the past two decades, the Big Data stack has reshaped and evolved quickly with numerous innovations driven by the rise of many different open source projects and communities. In this meetup, speakers from Uber, Alibaba, and Alluxio will share best practices for addressing the challenges and opportunities in the developing data architectures using new and emerging open source building blocks. Topics include data format (ORC) optimization, storage security (HDFS), data format (Parquet) layers, and unified data access (Alluxio) layers.
Similar to Best Practices for Using Alluxio with Spark (20)
AI/ML Infra Meetup | ML explainability in MichelangeloAlluxio, Inc.
AI/ML Infra Meetup
May. 23, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Eric Wang (Software Engineer, @Uber)
Uber has numerous deep learning models, most of which are highly complex with many layers and a vast number of features. Understanding how these models work is challenging and demands significant resources to experiment with various training algorithms and feature sets. With ML explainability, the ML team aims to bring transparency to these models, helping to clarify their predictions and behavior. This transparency also assists the operations and legal teams in explaining the reasons behind specific prediction outcomes.
In this talk, Eric Wang will discuss the methods Uber used for explaining deep learning models and how we integrated these methods into the Uber AI Michelangelo ecosystem to support offline explaining.
AI/ML Infra Meetup | Reducing Prefill for LLM Serving in RAGAlluxio, Inc.
AI/ML Infra Meetup
May. 23, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Junchen Jiang (Assistant Professor of Computer Science, @University of Chicago)
Prefill in LLM inference is known to be resource-intensive, especially for long LLM inputs. While better scheduling can mitigate prefill’s impact, it would be fundamentally better to avoid (most of) prefill. This talk introduces our preliminary effort towards drastically minimizing prefill delay for LLM inputs that naturally reuse text chunks, such as in retrieval-augmented generation. While keeping the KV cache of all text chunks in memory is difficult, we show that it is possible to store them on cheaper yet slower storage. By improving the loading process of the reused KV caches, we can still significantly speed up prefill delay while maintaining the same generation quality.
AI/ML Infra Meetup | Perspective on Deep Learning FrameworkAlluxio, Inc.
AI/ML Infra Meetup
May. 23, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Triston Cao (Senior Deep Learning Software Engineering Manager, @NVIDIA)
From Caffe to MXNet, to PyTorch, and more, Xiande Cao, Senior Deep Learning Software Engineer Manager, will share his perspective on the evolution of deep learning frameworks.
AI/ML Infra Meetup | Improve Speed and GPU Utilization for Model Training & S...Alluxio, Inc.
AI/ML Infra Meetup
May. 23, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Lu Qiu (Data & AI Platform Tech Lead, @Alluxio)
- Siyuan Sheng (Senior Software Engineer, @Alluxio)
Speed and efficiency are two requirements for the underlying infrastructure for machine learning model development. Data access can bottleneck end-to-end machine learning pipelines as training data volume grows and when large model files are more commonly used for serving. For instance, data loading can constitute nearly 80% of the total model training time, resulting in less than 30% GPU utilization. Also, loading large model files for deployment to production can be slow because of slow network or storage read operations. These challenges are prevalent when using popular frameworks like PyTorch, Ray, or HuggingFace, paired with cloud object storage solutions like S3 or GCS, or downloading models from the HuggingFace model hub.
In this presentation, Lu and Siyuan will offer comprehensive insights into improving speed and GPU utilization for model training and serving. You will learn:
- The data loading challenges hindering GPU utilization
- The reference architecture for running PyTorch and Ray jobs while reading data from S3, with benchmark results of training ResNet50 and BERT
- Real-world examples of boosting model performance and GPU utilization through optimized data access
Alluxio Monthly Webinar | Simplify Data Access for AI in Multi-CloudAlluxio, Inc.
Alluxio Monthly Webinar
May. 14, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- ChanChan Mao (Developer Advocate, Alluxio)
- Bin Fan (VP of Technology, Alluxio)
Running AI/ML workloads in different clouds present unique challenges. The key to a manageable multi-cloud architecture is the ability to seamlessly access data across environments with high performance and low cost.
This webinar is designed for data platform engineers, data infra engineers, data engineers, and ML engineers who work with multiple data sources in hybrid or multi-cloud environments. Chanchan and Bin will guide the audience through using Alluxio to greatly simplify data access and make model training and serving more efficient in these environments.
You will learn:
- How to access data in multi-region, hybrid, and multi-cloud like accessing a local file system
- How to run PyTorch to read datasets and write checkpoints to remote storage with Alluxio as the distributed data access layer
- Real-world examples and insights from tech giants like Uber, AliPay and more
Alluxio Monthly Webinar | Cloud-Native Model Training on Distributed DataAlluxio, Inc.
Alluxio Monthly Webinar
Apr. 23, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- ChanChan Mao (Developer Advocate, Alluxio)
- Shawn Sun (Tech Lead of Cloud Native, Alluxio)
Cloud-native model training jobs require fast data access to achieve shorter training cycles. Accessing data can be challenging when your datasets are distributed across different regions and clouds. Additionally, as GPUs remain scarce and expensive resources, it becomes more common to set up remote training clusters from where data resides. This multi-region/cloud scenario introduces the challenges of losing data locality, resulting in operational overhead, latency and expensive cloud costs.
In the third webinar of the multi-cloud webinar series, Chanchan and Shawn dive deep into:
- The data locality challenges in the multi-region/cloud ML pipeline
- Using a cloud-native distributed caching system to overcome these challenges
- The architecture and integration of PyTorch/Ray+Alluxio+S3 using POSIX or RESTful APIs
- Live demo with ResNet and BERT benchmark results showing performance gains and cost savings analysis
Optimizing Data Access for Analytics And AI with AlluxioAlluxio, Inc.
Alluxio x Tobiko - ETL Happy Hour
April 16, 2024
For more Alluxio events: https://alluxio.io/events/
Speaker:
Lucy Ge (Staff Software Engineer @ Alluxio)
In this presentation, Lucy Ge will discuss the data access challenges in the data pipeline and how to optimize the speed and costs of analytics and AI workloads.
Speed Up Presto at Uber with Alluxio CachingAlluxio, Inc.
Alluxio x Tobiko - ETL Happy Hour
April 16, 2024
For more Alluxio events: https://alluxio.io/events/
Speaker:
Chen Liang (Staff Software Engineer @ Uber)
In this presentation, Chen Liang will share the design and implementation of the Alluxio-Presto local cache to reduce query latency.
Correctly Loading Incremental Data at ScaleAlluxio, Inc.
Alluxio x Tobiko - ETL Happy Hour
April 16, 2024
For more Alluxio events: https://alluxio.io/events/
Speaker:
Toby Mao (CTO @ Tobiko Data)
Writing efficient and correct incremental pipelines is challenging. Data practitioners who take on this challenge are viewed as performing an "advanced" function, which discourages broader teams from adopting incremental loads. In this lightning talk, CTO of Tobiko Data, Toby Mao, will demystify incremental loading data at scale.
Big Data Bellevue Meetup | Enhancing Python Data Loading in the Cloud for AI/MLAlluxio, Inc.
Big Data Bellevue Meetup
March 21, 2024
For more Alluxio events: https://alluxio.io/events/
Speakers:
Bin Fan (VP of Open Source, Alluxio)
In this presentation, Bin Fan (VP of Open Source @ Alluxio) will address a critical challenge of optimizing data loading for distributed Python applications within AI/ML workloads in the cloud, focusing on popular frameworks like Ray and Hugging Face. Integration of Alluxio’s distributed caching for Python applications is accomplished using the fsspec interface, thus greatly improving data access speeds. This is particularly useful in machine learning workflows, where repeated data reloading across slow, unstable or congested networks can severely affect GPU efficiency and escalate operational costs.
Attendees can look forward to practical, hands-on demonstrations showcasing the tangible benefits of Alluxio’s caching mechanism across various real-world scenarios. These demos will highlight the enhancements in data efficiency and overall performance of data-intensive Python applications. This presentation is tailored for developers and data scientists eager to optimize their AI/ML workloads. Discover strategies to accelerate your data processing tasks, making them not only faster but also more cost-efficient.
Alluxio Monthly Webinar | Why a Multi-Cloud Strategy Matters for Your AI Plat...Alluxio, Inc.
Alluxio Monthly Webinar
Feb. 27, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Tarik Bennett (Senior Solutions Engineer, Alluxio)
As GenAI and AI continue to transform businesses, scaling these workloads requires optimized underlying infrastructure. A multi-cloud architecture allows organizations to leverage different cloud services to meet diverse workload demands while maximizing efficiency, reducing costs, and avoiding vendor lock-in. However, achieving a multi-cloud vision can be challenging.
In this webinar, Tarik will share how an agonistic data layer, like Alluxio, allows you to embrace the separation of storage from compute and simplify the adoption of multi-cloud for AI.
- Learn why leveraging multiple cloud providers is critical for balancing performance, scalability, and cost of your AI platform
- Discover how an agnostic data layer like Alluxio provides seamless data access in multi-cloud that bridges storage and compute without data replication
- Gain insights into real-world examples and best practices for deploying AI across on-prem, hybrid, and multi-cloud environments
Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader...Alluxio, Inc.
Alluxio Monthly Webinar
Jan. 30, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Kevin Petrie (VP of Research, Eckerson Group)
- Omid Razavi (SVP of Customer Success, Alluxio)
2024 is gearing up to be an impactful year for AI and analytics. Join us on January 30, as Kevin Petrie (VP of Research at Eckerson Group) and Omid Razavi (SVP of Customer Success at Alluxio) share key trends that data and AI leaders should know. This event will efficiently guide you with market data and expert insights to drive successful business outcomes.
- Assess current and future trends in data and AI with industry experts
- Discover valuable insights and practical recommendations
- Learn best practices to make your enterprise data more accessible for both analytics and AI applications
Data Infra Meetup | FIFO Queues are All You Need for Cache EvictionAlluxio, Inc.
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Juncheng Yang(Ph.D Candidate, @CMU)
As a cache eviction algorithm, FIFO has a lot of attractive properties, such as simplicity, speed, scalability, and flash-friendliness. The most prominent criticism of FIFO is its low efficiency (high miss ratio). In this talk, I will describe a simple, scalable FIFO-based algorithm with three static queues (S3-FIFO). Evaluated on 6594 cache traces from 14 datasets, we show that S3- FIFO has lower miss ratios than state-of-the-art algorithms across traces. Moreover, S3-FIFO’s efficiency is robust — it has the lowest mean miss ratio on 10 of the 14 datasets. FIFO queues enable S3-FIFO to achieve good scalability with 6× higher throughput compared to optimized LRU at 16 threads. Our insight is that most objects in skewed workloads will only be accessed once in a short window, so it is critical to evict them early (also called quick demotion). The key of S3-FIFO is a small FIFO queue that filters out most objects from entering the main cache, which provides a guaranteed demotion speed and high demotion precision.
Data Infra Meetup | Accelerate Your Trino/Presto Queries - Gain the Alluxio EdgeAlluxio, Inc.
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jingwen Ouyang (Product Manager, @Alluxio)
In this session, Jingwen presents an overview of using Alluxio Edge caching to accelerate Trino or Presto queries. She offers practical best practices for using distributed caching with compute engines. In addition, this session also features insights from real-world examples.
Data Infra Meetup | Accelerate Distributed PyTorch/Ray Workloads in the CloudAlluxio, Inc.
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Siyuan Sheng (Senior Software Engineer, @Alluxio)
- Chunxu Tang (Research Scientist, @Alluxio)
In this session, cloud optimization specialists Chunxu and Siyuan break down the challenges and present a fresh architecture designed to optimize I/O across the data pipeline, ensuring GPUs function at peak performance. The integrated solution of PyTorch/Ray + Alluxio + S3 offers a promising way forward, and the speakers delve deep into its practical applications. Attendees will not only gain theoretical insights but will also be treated to hands-on instructions and demonstrations of deploying this cutting-edge architecture in Kubernetes, specifically tailored for Tensorflow/PyTorch/Ray workloads in the public cloud.
Data Infra Meetup | ByteDance's Native Parquet ReaderAlluxio, Inc.
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Shengxuan Liu (Software Engineer, @ByteDance)
Shengxuan Liu from ByteDance presents the new ByteDance’s native Parquet Reader. The talk covers the architecture and key features of the Reader, and how the new Reader is able to facilitate data processing efficiency.
Data Infra Meetup | Uber's Data Storage EvolutionAlluxio, Inc.
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jing Zhao (Principal Engineer, @Uber)
Uber builds one of the biggest data lakes in the industry, which stores exabytes of data. In this talk, we will introduce the evolution of our data storage architecture, and delve into multiple key initiatives during the past several years.
Specifically, we will introduce:
- Our on-prem HDFS cluster scalability challenges and how we solved them
- Our efficiency optimizations that significantly reduced the storage overhead and unit cost without compromising reliability and performance
- The challenges we are facing during the ongoing Cloud migration and our solutions
Alluxio Monthly Webinar | Why NFS/NAS on Object Storage May Not Solve Your AI...Alluxio, Inc.
Alluxio Monthly Webinar
Nov. 15, 2023
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Tarik Bennett (Senior Solutions Engineer)
- Beinan Wang (Senior Staff Engineer & Architect)
Many companies are working with development architectures for AI platforms but have concerns about efficiency at scale as data volumes increase. They use centralized cloud data lakes, like S3, to store training data for AI platforms. However, GPU shortages add more complications. Storage and compute can be separate, or even remote, making data loading slow and expensive:
1) Optimizing a developmental setup can include manual copies, which are slow and error-prone
2) Directly transferring data across regions or from cloud to on-premises can incur expensive egress fees
This webinar covers solutions to improve data loading for model training. You will learn:
- The data loading challenges with distributed infrastructure
- Typical solutions, including NFS/NAS on object storage, and why they are not the best options
- Common architectures that can improve data loading and cost efficiency
- Using Alluxio to accelerate model training and reduce costs
AI Infra Day | Accelerate Your Model Training and Serving with Distributed Ca...Alluxio, Inc.
AI Infra Day
Oct. 25, 2023
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Adit Madan (Director of Product Management, @Alluxio)
In this session, Adit Madan, Director of Product Management at Alluxio, presents an overview of using distributed caching to accelerate model training and serving. He explores the requirements of data access patterns in the ML pipeline and offers practical best practices for using distributed caching in the cloud. This session features insights from real-world examples, such as AliPay, Zhihu, and more.
AI Infra Day | The AI Infra in the Generative AI EraAlluxio, Inc.
AI Infra Day
Oct. 25, 2023
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Bin Fan (Cheif Architect, VP of Open Source, @Alluxio)
As the AI landscape rapidly evolves, the advancements in generative AI technologies, such as ChatGPT, are driving a need for a robust AI infra stack. This opening keynote will explore the key trends of the AI infra stack in the generative AI era.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
We implement context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases such as Linux shows that their Graspan implementations scale to millions of lines of code and are much simpler than their original implementations.
These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppGoogle
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-fusion-buddy-review
AI Fusion Buddy Review: Key Features
✅Create Stunning AI App Suite Fully Powered By Google's Latest AI technology, Gemini
✅Use Gemini to Build high-converting Converting Sales Video Scripts, ad copies, Trending Articles, blogs, etc.100% unique!
✅Create Ultra-HD graphics with a single keyword or phrase that commands 10x eyeballs!
✅Fully automated AI articles bulk generation!
✅Auto-post or schedule stunning AI content across all your accounts at once—WordPress, Facebook, LinkedIn, Blogger, and more.
✅With one keyword or URL, generate complete websites, landing pages, and more…
✅Automatically create & sell AI content, graphics, websites, landing pages, & all that gets you paid non-stop 24*7.
✅Pre-built High-Converting 100+ website Templates and 2000+ graphic templates logos, banners, and thumbnail images in Trending Niches.
✅Say goodbye to wasting time logging into multiple Chat GPT & AI Apps once & for all!
✅Save over $5000 per year and kick out dependency on third parties completely!
✅Brand New App: Not available anywhere else!
✅ Beginner-friendly!
✅ZERO upfront cost or any extra expenses
✅Risk-Free: 30-Day Money-Back Guarantee!
✅Commercial License included!
See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!