ºÝºÝߣshows by User: RobertSanders49 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: RobertSanders49 / Wed, 13 Nov 2019 15:49:28 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: RobertSanders49 Migrating Big Data Workloads to the Cloud /slideshow/migrating-big-data-workloads-to-the-cloud/193182375 migratingbigdataworkloadstothecloud-191113154929
Cloud Services have become an integral part of many organizations’ workloads. With the ease of spinning up instances to react to changing or increased business demands, it’s certainly not hard to see why. Many organizations that once relied on internal data centers are even considering migrating to the cloud to take advantage of not just the ability to spin up instances rapidly, but also to leverage all the services that are available with these offerings. Such as Elastic Map Reduce from Amazon and HD Insight from Microsoft. In this talk, we will go over the various methods and strategies you can employ to migrate your data and workloads to the cloud and what all options this opens up for your business and IT. ]]>
Cloud Services have become an integral part of many organizations’ workloads. With the ease of spinning up instances to react to changing or increased business demands, it’s certainly not hard to see why. Many organizations that once relied on internal data centers are even considering migrating to the cloud to take advantage of not just the ability to spin up instances rapidly, but also to leverage all the services that are available with these offerings. Such as Elastic Map Reduce from Amazon and HD Insight from Microsoft. In this talk, we will go over the various methods and strategies you can employ to migrate your data and workloads to the cloud and what all options this opens up for your business and IT. ]]> Wed, 13 Nov 2019 15:49:28 GMT /slideshow/migrating-big-data-workloads-to-the-cloud/193182375 RobertSanders49@slideshare.net(RobertSanders49) Migrating Big Data Workloads to the Cloud RobertSanders49 Cloud Services have become an integral part of many organizations’ workloads. With the ease of spinning up instances to react to changing or increased business demands, it’s certainly not hard to see why. Many organizations that once relied on internal data centers are even considering migrating to the cloud to take advantage of not just the ability to spin up instances rapidly, but also to leverage all the services that are available with these offerings. Such as Elastic Map Reduce from Amazon and HD Insight from Microsoft. In this talk, we will go over the various methods and strategies you can employ to migrate your data and workloads to the cloud and what all options this opens up for your business and IT. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/migratingbigdataworkloadstothecloud-191113154929-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Cloud Services have become an integral part of many organizations’ workloads. With the ease of spinning up instances to react to changing or increased business demands, it’s certainly not hard to see why. Many organizations that once relied on internal data centers are even considering migrating to the cloud to take advantage of not just the ability to spin up instances rapidly, but also to leverage all the services that are available with these offerings. Such as Elastic Map Reduce from Amazon and HD Insight from Microsoft. In this talk, we will go over the various methods and strategies you can employ to migrate your data and workloads to the cloud and what all options this opens up for your business and IT.
Migrating Big Data Workloads to the Cloud from Robert Sanders
]]> 454 0 https://cdn.slidesharecdn.com/ss_thumbnails/migratingbigdataworkloadstothecloud-191113154929-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Delivering digital transformation and business impact with io t, machine learning and a hybrid cloud /slideshow/delivering-digital-transformation-and-business-impact-with-io-t-machine-learning-and-a-hybrid-cloud/145353151 deliveringdigitaltransformationandbusinessimpactwithiotmachinelearningandahybridcloud-190513210057
A world-leading manufacturer was in search of an IoT solution that could ingest, integrate, and manage data being generated from various types of connected machinery located on factory floors around the globe. The company needed to manage the devices generating the data, integrate the flow of data into existing back-end systems, run advanced analytics on that data, and then deliver services to generate real-time decision making at the edge. In this session, learn how Clairvoyant, a leading systems integrator and Red Hat partner, was able to accelerate digital transformation for their customer using Internet of Things (IoT) and machine learning in a hybrid cloud environment. Specifically, Clairvoyant and Eurotech will discuss: • The approach taken to optimize manufacturing processes to cut costs, minimize downtime, and increase efficiency. • How a data processing pipeline for IoT data was built using an open, end-to-end architecture from Cloudera, Eurotech, and Red Hat. • How analytics and machine learning inferencing powered at the IoT edge will allow predictions to be made and decisions to be executed in real time. • The flexible and hybrid cloud environment designed to provide the key foundational elements to quickly and securely roll out IoT use cases.]]>
A world-leading manufacturer was in search of an IoT solution that could ingest, integrate, and manage data being generated from various types of connected machinery located on factory floors around the globe. The company needed to manage the devices generating the data, integrate the flow of data into existing back-end systems, run advanced analytics on that data, and then deliver services to generate real-time decision making at the edge. In this session, learn how Clairvoyant, a leading systems integrator and Red Hat partner, was able to accelerate digital transformation for their customer using Internet of Things (IoT) and machine learning in a hybrid cloud environment. Specifically, Clairvoyant and Eurotech will discuss: • The approach taken to optimize manufacturing processes to cut costs, minimize downtime, and increase efficiency. • How a data processing pipeline for IoT data was built using an open, end-to-end architecture from Cloudera, Eurotech, and Red Hat. • How analytics and machine learning inferencing powered at the IoT edge will allow predictions to be made and decisions to be executed in real time. • The flexible and hybrid cloud environment designed to provide the key foundational elements to quickly and securely roll out IoT use cases.]]> Mon, 13 May 2019 21:00:57 GMT /slideshow/delivering-digital-transformation-and-business-impact-with-io-t-machine-learning-and-a-hybrid-cloud/145353151 RobertSanders49@slideshare.net(RobertSanders49) Delivering digital transformation and business impact with io t, machine learning and a hybrid cloud RobertSanders49 A world-leading manufacturer was in search of an IoT solution that could ingest, integrate, and manage data being generated from various types of connected machinery located on factory floors around the globe. The company needed to manage the devices generating the data, integrate the flow of data into existing back-end systems, run advanced analytics on that data, and then deliver services to generate real-time decision making at the edge. In this session, learn how Clairvoyant, a leading systems integrator and Red Hat partner, was able to accelerate digital transformation for their customer using Internet of Things (IoT) and machine learning in a hybrid cloud environment. Specifically, Clairvoyant and Eurotech will discuss: • The approach taken to optimize manufacturing processes to cut costs, minimize downtime, and increase efficiency. • How a data processing pipeline for IoT data was built using an open, end-to-end architecture from Cloudera, Eurotech, and Red Hat. • How analytics and machine learning inferencing powered at the IoT edge will allow predictions to be made and decisions to be executed in real time. • The flexible and hybrid cloud environment designed to provide the key foundational elements to quickly and securely roll out IoT use cases. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/deliveringdigitaltransformationandbusinessimpactwithiotmachinelearningandahybridcloud-190513210057-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A world-leading manufacturer was in search of an IoT solution that could ingest, integrate, and manage data being generated from various types of connected machinery located on factory floors around the globe. The company needed to manage the devices generating the data, integrate the flow of data into existing back-end systems, run advanced analytics on that data, and then deliver services to generate real-time decision making at the edge. In this session, learn how Clairvoyant, a leading systems integrator and Red Hat partner, was able to accelerate digital transformation for their customer using Internet of Things (IoT) and machine learning in a hybrid cloud environment. Specifically, Clairvoyant and Eurotech will discuss: • The approach taken to optimize manufacturing processes to cut costs, minimize downtime, and increase efficiency. • How a data processing pipeline for IoT data was built using an open, end-to-end architecture from Cloudera, Eurotech, and Red Hat. • How analytics and machine learning inferencing powered at the IoT edge will allow predictions to be made and decisions to be executed in real time. • The flexible and hybrid cloud environment designed to provide the key foundational elements to quickly and securely roll out IoT use cases.
Delivering digital transformation and business impact with io t, machine learning and a hybrid cloud from Robert Sanders
]]> 355 1 https://cdn.slidesharecdn.com/ss_thumbnails/deliveringdigitaltransformationandbusinessimpactwithiotmachinelearningandahybridcloud-190513210057-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Productionalizing spark streaming applications /RobertSanders49/productionalizing-spark-streaming-applications productionalizingsparkstreamingapplications-180823195934
Spark Streaming has quickly established itself as one of the more popular Streaming Engines running on the Hadoop Ecosystem. Not only does it provide integration with many type of message brokers and stream sources, but it also provides the ability to leverage other major modules in Spark like Spark SQL and MLib in conjunction. This allows for businesses and developers to make use out of data in ways they couldn’t hope to do in the past. However, while building a Spark Streaming pipeline, it’s not sufficient to only know how to express your business logic. Operationalizing these pipelines and running the application with high uptime and continuous monitoring has a lot of operational challenges. Fortunately, Spark Streaming makes all that easy as well. In this talk, we’ll go over some of the main steps you’ll need to take to get your Spark Streaming application ready for production, specifically in conjunction with Kafka. This includes steps to gracefully shutdown your application, steps to perform upgrades, monitoring, various useful spark configurations and more.]]>
Spark Streaming has quickly established itself as one of the more popular Streaming Engines running on the Hadoop Ecosystem. Not only does it provide integration with many type of message brokers and stream sources, but it also provides the ability to leverage other major modules in Spark like Spark SQL and MLib in conjunction. This allows for businesses and developers to make use out of data in ways they couldn’t hope to do in the past. However, while building a Spark Streaming pipeline, it’s not sufficient to only know how to express your business logic. Operationalizing these pipelines and running the application with high uptime and continuous monitoring has a lot of operational challenges. Fortunately, Spark Streaming makes all that easy as well. In this talk, we’ll go over some of the main steps you’ll need to take to get your Spark Streaming application ready for production, specifically in conjunction with Kafka. This includes steps to gracefully shutdown your application, steps to perform upgrades, monitoring, various useful spark configurations and more.]]> Thu, 23 Aug 2018 19:59:34 GMT /RobertSanders49/productionalizing-spark-streaming-applications RobertSanders49@slideshare.net(RobertSanders49) Productionalizing spark streaming applications RobertSanders49 Spark Streaming has quickly established itself as one of the more popular Streaming Engines running on the Hadoop Ecosystem. Not only does it provide integration with many type of message brokers and stream sources, but it also provides the ability to leverage other major modules in Spark like Spark SQL and MLib in conjunction. This allows for businesses and developers to make use out of data in ways they couldn’t hope to do in the past. However, while building a Spark Streaming pipeline, it’s not sufficient to only know how to express your business logic. Operationalizing these pipelines and running the application with high uptime and continuous monitoring has a lot of operational challenges. Fortunately, Spark Streaming makes all that easy as well. In this talk, we’ll go over some of the main steps you’ll need to take to get your Spark Streaming application ready for production, specifically in conjunction with Kafka. This includes steps to gracefully shutdown your application, steps to perform upgrades, monitoring, various useful spark configurations and more. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/productionalizingsparkstreamingapplications-180823195934-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Spark Streaming has quickly established itself as one of the more popular Streaming Engines running on the Hadoop Ecosystem. Not only does it provide integration with many type of message brokers and stream sources, but it also provides the ability to leverage other major modules in Spark like Spark SQL and MLib in conjunction. This allows for businesses and developers to make use out of data in ways they couldn’t hope to do in the past. However, while building a Spark Streaming pipeline, it’s not sufficient to only know how to express your business logic. Operationalizing these pipelines and running the application with high uptime and continuous monitoring has a lot of operational challenges. Fortunately, Spark Streaming makes all that easy as well. In this talk, we’ll go over some of the main steps you’ll need to take to get your Spark Streaming application ready for production, specifically in conjunction with Kafka. This includes steps to gracefully shutdown your application, steps to perform upgrades, monitoring, various useful spark configurations and more.
Productionalizing spark streaming applications from Robert Sanders
]]> 669 3 https://cdn.slidesharecdn.com/ss_thumbnails/productionalizingsparkstreamingapplications-180823195934-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Apache Airflow in Production /RobertSanders49/apache-airflow-in-production apacheairflowinproduction1-180604173344
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it. Speakers: Robert Sanders, Shekhar Vemuri]]>
We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it. Speakers: Robert Sanders, Shekhar Vemuri]]> Mon, 04 Jun 2018 17:33:44 GMT /RobertSanders49/apache-airflow-in-production RobertSanders49@slideshare.net(RobertSanders49) Apache Airflow in Production RobertSanders49 We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it. Speakers: Robert Sanders, Shekhar Vemuri <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/apacheairflowinproduction1-180604173344-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We will introduce Airflow, an Apache Project for scheduling and workflow orchestration. We will discuss use cases, applicability and how best to use Airflow, mainly in the context of building data engineering pipelines. We have been running Airflow in production for about 2 years, we will also go over some learnings, best practices and some tools we have built around it. Speakers: Robert Sanders, Shekhar Vemuri
Apache Airflow in Production from Robert Sanders
]]> 6327 9 https://cdn.slidesharecdn.com/ss_thumbnails/apacheairflowinproduction1-180604173344-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Airflow Clustering and High Availability /slideshow/airflow-clustering-and-high-availability/71554108 airflowclusteringandhighavailability-170130183514
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.]]>
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.]]> Mon, 30 Jan 2017 18:35:13 GMT /slideshow/airflow-clustering-and-high-availability/71554108 RobertSanders49@slideshare.net(RobertSanders49) Airflow Clustering and High Availability RobertSanders49 This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/airflowclusteringandhighavailability-170130183514-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.
Airflow Clustering and High Availability from Robert Sanders
]]> 6480 7 https://cdn.slidesharecdn.com/ss_thumbnails/airflowclusteringandhighavailability-170130183514-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Databricks Community Cloud Overview /slideshow/databricks-community-cloud-overview/66927734 databricks-community-cloud-161009203811
An overview on the Databricks Community Cloud platform offered by Databricks at: https://community.cloud.databricks.com/ Provides step by step instructions on how to create a Spark Standalone Cluster and how to use notebooks.]]>
An overview on the Databricks Community Cloud platform offered by Databricks at: https://community.cloud.databricks.com/ Provides step by step instructions on how to create a Spark Standalone Cluster and how to use notebooks.]]> Sun, 09 Oct 2016 20:38:11 GMT /slideshow/databricks-community-cloud-overview/66927734 RobertSanders49@slideshare.net(RobertSanders49) Databricks Community Cloud Overview RobertSanders49 An overview on the Databricks Community Cloud platform offered by Databricks at: https://community.cloud.databricks.com/ Provides step by step instructions on how to create a Spark Standalone Cluster and how to use notebooks. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/databricks-community-cloud-161009203811-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An overview on the Databricks Community Cloud platform offered by Databricks at: https://community.cloud.databricks.com/ Provides step by step instructions on how to create a Spark Standalone Cluster and how to use notebooks.
Databricks Community Cloud Overview from Robert Sanders
]]> 229 2 https://cdn.slidesharecdn.com/ss_thumbnails/databricks-community-cloud-161009203811-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Intro to Apache Spark /slideshow/intro-to-apache-spark-66905105/66905105 introtoapachespark-desertcodecamp-161008212602
Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming. Presented at the Desert Code Camp: http://oct2016.desertcodecamp.com/sessions/all]]>
Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming. Presented at the Desert Code Camp: http://oct2016.desertcodecamp.com/sessions/all]]> Sat, 08 Oct 2016 21:26:02 GMT /slideshow/intro-to-apache-spark-66905105/66905105 RobertSanders49@slideshare.net(RobertSanders49) Intro to Apache Spark RobertSanders49 Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming. Presented at the Desert Code Camp: http://oct2016.desertcodecamp.com/sessions/all <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introtoapachespark-desertcodecamp-161008212602-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Introduction to Apache Spark. With an emphasis on the RDD API, Spark SQL (DataFrame and Dataset API) and Spark Streaming. Presented at the Desert Code Camp: http://oct2016.desertcodecamp.com/sessions/all
Intro to Apache Spark from Robert Sanders
]]> 4601 7 https://cdn.slidesharecdn.com/ss_thumbnails/introtoapachespark-desertcodecamp-161008212602-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/migratingbigdataworkloadstothecloud-191113154929-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/migrating-big-data-workloads-to-the-cloud/193182375 Migrating Big Data Wor... https://cdn.slidesharecdn.com/ss_thumbnails/deliveringdigitaltransformationandbusinessimpactwithiotmachinelearningandahybridcloud-190513210057-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/delivering-digital-transformation-and-business-impact-with-io-t-machine-learning-and-a-hybrid-cloud/145353151 Delivering digital tra... https://cdn.slidesharecdn.com/ss_thumbnails/productionalizingsparkstreamingapplications-180823195934-thumbnail.jpg?width=320&height=320&fit=bounds RobertSanders49/productionalizing-spark-streaming-applications Productionalizing spar...