This session will give you an update on what SUSE is up to in the Big Data arena. We will take a brief look at SUSE Linux Enterprise Server and why it makes the perfect foundation for your Hadoop Deployment.
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
Apache Ignite vs Alluxio: Memory Speed Big Data AnalyticsDataWorks Summit
Apache Ignite vs Alluxio: Memory Speed Big Data Analytics - Apache Spark’s in memory capabilities catapulted it as the premier processing framework for Hadoop. Apache Ignite and Alluxio, both high-performance, integrated and distributed in-memory platform, takes Apache Spark to the next level by providing an even more powerful, faster and scalable platform to the most demanding data processing and analytic environments.
Speaker
Irfan Elahi, Consultant, Deloitte
Accelerating Business Intelligence Solutions with Microsoft Azure passJason Strate
Business Intelligence (BI) solutions need to move at the speed of business. Unfortunately, roadblocks related to availability of resources and deployment often present an issue. What if you could accelerate the deployment of an entire BI infrastructure to just a couple hours and start loading data into it by the end of the day. In this session, we'll demonstrate how to leverage Microsoft tools and the Azure cloud environment to build out a BI solution and begin providing analytics to your team with tools such as Power BI. By end of the session, you'll gain an understanding of the capabilities of Azure and how you can start building an end to end BI proof-of-concept today.
Apache Ignite vs Alluxio: Memory Speed Big Data AnalyticsDataWorks Summit
Apache Ignite vs Alluxio: Memory Speed Big Data Analytics - Apache Spark’s in memory capabilities catapulted it as the premier processing framework for Hadoop. Apache Ignite and Alluxio, both high-performance, integrated and distributed in-memory platform, takes Apache Spark to the next level by providing an even more powerful, faster and scalable platform to the most demanding data processing and analytic environments.
Speaker
Irfan Elahi, Consultant, Deloitte
MOUG17 Keynote: Oracle OpenWorld Major AnnouncementsMonica Li
Midwest Oracle Users Group Training Day 2017 Presentation by Rich Niemiec, Chief Innovation Officer at Viscosity North America.
Catch up on OOW17's top announcements in this 1 hour presentation.
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
HA/DR options with SQL Server in Azure and hybridJames Serra
What are all the high availability (HA) and disaster recovery (DR) options for SQL Server in a Azure VM (IaaS)? Which of these options can be used in a hybrid combination (Azure VM and on-prem)? I will cover features such as AlwaysOn AG, Failover cluster, Azure SQL Data Sync, Log Shipping, SQL Server data files in Azure, Mirroring, Azure Site Recovery, and Azure Backup.
Hadoop has traditionally been an on-premises workload, with very few notable implementations on the cloud. With Organizations either having jumped on the cloud bandwagon or have started planning their expansion into the ecosystem, it is imperative for us to explore how Hadoop conforms to the cloud paradigm. With the coming off age of some very useful cloud paradigms and the nature of Big Data with high seasonality of workloads, this is becoming a very common ask from customers. Robust architectures, elastic scale, open platforms, OSS integrations, and addressing complex pain points will all be part of this lively talk. To be able to implement effective solutions for Big Data in the cloud it is imperative that you understand the core principles and grasp the design principles of how the cloud can enhance the benefits of parallelized analytics. Join this session to understand the nitty-gritties of implementing Big Data in the cloud and the various options therein. Big Data + Cloud is definitely a deadly combination.
Dynamic DDL: Adding structure to streaming IoT data on the flyDataWorks Summit
At the end of day the only thing that data scientists want is one thing. They want tabular data for their analysis.
They do not want to spend hours or days preparing data. How does a data engineer handle the massive amount of data
that is being streamed at them from IoT devices and apps and at the same time add structure to it so that data scientists
can focus on finding insights and not preparing data? By the way, you need to do this within minutes (sometimes seconds).
Oh... and there are a bunch more data sources that you need to ingest and the current providers of data are changing their structure.
At GoPro, we have massive amounts of heterogeneous data being streamed at us from our consumer devices
and applications, and we have developed a concept of "dynamic DDL" to structure our streamed data on the fly using
Spark Streaming, Kafka, HBase, Hive, and S3. The idea is simple. Add structure (schema) to the data as soon as possible.
Allow the providers of the data to dictate the structure. And automatically create event-based and state-based tables (DDL)
for all data sources to allow data scientists to access the data via their lingua franca, SQL, within minutes.
This presentation is for those of you who are interested in moving your on-prem SQL Server databases and servers to Azure virtual machines (VM’s) in the cloud so you can take advantage of all the benefits of being in the cloud. This is commonly referred to as a “lift and shift” as part of an Infrastructure-as-a-service (IaaS) solution. I will discuss the various Azure VM sizes and options, migration strategies, storage options, high availability (HA) and disaster recovery (DR) solutions, and best practices.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
Azure SQL Database (SQL DB) is a database-as-a-service (DBaaS) that provides nearly full T-SQL compatibility so you can gain tons of benefits for new databases or by moving your existing databases to the cloud. Those benefits include provisioning in minutes, built-in high availability and disaster recovery, predictable performance levels, instant scaling, and reduced overhead. And gone will be the days of getting a call at 3am because of a hardware failure. If you want to make your life easier, this is the presentation for you.
Hadoop’s capabilities offer untapped potential for business insights but companies often get weighed down with DIY platforms and fail to keep up with the requirements. Join this Dell EMC session which will address this challenge with ready bundles to quickly deliver solutions for ETL offload, Single View, & IoT.
Get more value from your big data:
• Deploy big data applications faster
• Increase business agility
• Confidently deliver high performance and endless scale
• Improve IT operational efficiency
Speaker
Shawn Smith, Big Data Specialist, Dell EMC
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Treat your enterprise data lake indigestion: Enterprise ready security and go...DataWorks Summit
Most enterprises with large data lakes today are flying blind when it comes to the extent to which they can understand how the data in their data lakes is organized, accessed, and utilized to create real business value. Couple this with the need to democratize data, enterprises often realize they have created a data swamp loaded with all kinds of data assets without any curation and without appropriate security controls hoping that developers and analysts can responsibly collaborate to generate insights. In this talk we will provide a broad overview of how organizations can use open source frameworks such as Apache Ranger and Apache Knox to secure their data lakes and Apache Atlas to effectively provide open metadata and governance services for Hadoop ecosystem. We will provide an overview of the new features that have been added in each of these Apache projects recently and how enterprises can leverage these new features to build a robust security and governance model for their data lakes.
Speaker
Owen O'Malley, Co-Founder & Technical Fellow, Hortonworks
MOUG17 Keynote: Oracle OpenWorld Major AnnouncementsMonica Li
Midwest Oracle Users Group Training Day 2017 Presentation by Rich Niemiec, Chief Innovation Officer at Viscosity North America.
Catch up on OOW17's top announcements in this 1 hour presentation.
Modern Data Warehousing with the Microsoft Analytics Platform SystemJames Serra
The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.
HA/DR options with SQL Server in Azure and hybridJames Serra
What are all the high availability (HA) and disaster recovery (DR) options for SQL Server in a Azure VM (IaaS)? Which of these options can be used in a hybrid combination (Azure VM and on-prem)? I will cover features such as AlwaysOn AG, Failover cluster, Azure SQL Data Sync, Log Shipping, SQL Server data files in Azure, Mirroring, Azure Site Recovery, and Azure Backup.
Hadoop has traditionally been an on-premises workload, with very few notable implementations on the cloud. With Organizations either having jumped on the cloud bandwagon or have started planning their expansion into the ecosystem, it is imperative for us to explore how Hadoop conforms to the cloud paradigm. With the coming off age of some very useful cloud paradigms and the nature of Big Data with high seasonality of workloads, this is becoming a very common ask from customers. Robust architectures, elastic scale, open platforms, OSS integrations, and addressing complex pain points will all be part of this lively talk. To be able to implement effective solutions for Big Data in the cloud it is imperative that you understand the core principles and grasp the design principles of how the cloud can enhance the benefits of parallelized analytics. Join this session to understand the nitty-gritties of implementing Big Data in the cloud and the various options therein. Big Data + Cloud is definitely a deadly combination.
Dynamic DDL: Adding structure to streaming IoT data on the flyDataWorks Summit
At the end of day the only thing that data scientists want is one thing. They want tabular data for their analysis.
They do not want to spend hours or days preparing data. How does a data engineer handle the massive amount of data
that is being streamed at them from IoT devices and apps and at the same time add structure to it so that data scientists
can focus on finding insights and not preparing data? By the way, you need to do this within minutes (sometimes seconds).
Oh... and there are a bunch more data sources that you need to ingest and the current providers of data are changing their structure.
At GoPro, we have massive amounts of heterogeneous data being streamed at us from our consumer devices
and applications, and we have developed a concept of "dynamic DDL" to structure our streamed data on the fly using
Spark Streaming, Kafka, HBase, Hive, and S3. The idea is simple. Add structure (schema) to the data as soon as possible.
Allow the providers of the data to dictate the structure. And automatically create event-based and state-based tables (DDL)
for all data sources to allow data scientists to access the data via their lingua franca, SQL, within minutes.
This presentation is for those of you who are interested in moving your on-prem SQL Server databases and servers to Azure virtual machines (VM’s) in the cloud so you can take advantage of all the benefits of being in the cloud. This is commonly referred to as a “lift and shift” as part of an Infrastructure-as-a-service (IaaS) solution. I will discuss the various Azure VM sizes and options, migration strategies, storage options, high availability (HA) and disaster recovery (DR) solutions, and best practices.
Today enterprises desire to move more and more of their data lakes to the cloud to help them execute faster, increase productivity, drive innovation while leveraging the scale and flexibility of the cloud. However, such gains come with risks and challenges in the areas of data security, privacy, and governance. In this talk we cover how enterprises can overcome governance and security obstacles to leverage these new advances that the cloud can provide to ease the management of their data lakes in the cloud. We will also show how the enterprise can have consistent governance and security controls in the cloud for their ephemeral analytic workloads in a multi-cluster cloud environment without sacrificing any of the data security and privacy/compliance needs that their business context demands. Additionally, we will outline some use cases and patterns as well as best practices to rationally manage such a multi-cluster data lake infrastructure in the cloud.
Speaker:
Jeff Sposetti, Product Management, Hortonworks
Azure SQL Database (SQL DB) is a database-as-a-service (DBaaS) that provides nearly full T-SQL compatibility so you can gain tons of benefits for new databases or by moving your existing databases to the cloud. Those benefits include provisioning in minutes, built-in high availability and disaster recovery, predictable performance levels, instant scaling, and reduced overhead. And gone will be the days of getting a call at 3am because of a hardware failure. If you want to make your life easier, this is the presentation for you.
Hadoop’s capabilities offer untapped potential for business insights but companies often get weighed down with DIY platforms and fail to keep up with the requirements. Join this Dell EMC session which will address this challenge with ready bundles to quickly deliver solutions for ETL offload, Single View, & IoT.
Get more value from your big data:
• Deploy big data applications faster
• Increase business agility
• Confidently deliver high performance and endless scale
• Improve IT operational efficiency
Speaker
Shawn Smith, Big Data Specialist, Dell EMC
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Treat your enterprise data lake indigestion: Enterprise ready security and go...DataWorks Summit
Most enterprises with large data lakes today are flying blind when it comes to the extent to which they can understand how the data in their data lakes is organized, accessed, and utilized to create real business value. Couple this with the need to democratize data, enterprises often realize they have created a data swamp loaded with all kinds of data assets without any curation and without appropriate security controls hoping that developers and analysts can responsibly collaborate to generate insights. In this talk we will provide a broad overview of how organizations can use open source frameworks such as Apache Ranger and Apache Knox to secure their data lakes and Apache Atlas to effectively provide open metadata and governance services for Hadoop ecosystem. We will provide an overview of the new features that have been added in each of these Apache projects recently and how enterprises can leverage these new features to build a robust security and governance model for their data lakes.
Speaker
Owen O'Malley, Co-Founder & Technical Fellow, Hortonworks
Realizing the Promise of Big Data with Hadoop - Cloudera Summer Webinar Serie...Cloudera, Inc.
Apache Hadoop, an open-source platform, is increasingly gaining adoption within organizations trying to draw insight from all the big data being generated. Hadoop, and a handful of open-source tools that complement it, are promising to make gigantic and diverse datasets easily and economically available for quick analysis. A burgeoning partner ecosystem is also essential to helping organizations turn big data into business value.
Big Data Analytics: Reference Architectures and Case Studies by Serhiy Haziye...SoftServe
BI architecture drivers have to change to satisfy new requirements in format, volume, latency, hosting, analysis, reporting, and visualization. In this presentation delivered at the 2014 SATURN conference, SoftServe`s Serhiy and Olha showcased a number of reference architectures that address these challenges and speed up the design and implementation process, making it more predictable and economical:
- Traditional architecture based on an RDMBS data warehouse but modernized with column-based storage to handle a high load and capacity
- NoSQL-based architectures that address Big Data batch and stream-based processing and use popular NoSQL and complex event-processing solutions
- Hybrid architecture that combines traditional and NoSQL approaches to achieve completeness that would not be possible with either alone
The architectures are accompanied by real-life projects and case studies that the presenters have performed for multiple companies, including Fortune 100 and start-ups.
The right architecture is key for any IT project. This is especially the case for big data projects, where there are no standard architectures which have proven their suitability over years. This session discusses the different Big Data Architectures which have evolved over time, including traditional Big Data Architecture, Streaming Analytics architecture as well as Lambda and Kappa architecture and presents the mapping of components from both Open Source as well as the Oracle stack onto these architectures.
SUSE juega un rol importante como proveedor de soluciones de infraestructura basada en software para el mundo de BigData. Dichas soluciones son los cimientos que permiten despliegues de BigData escalables y sencillos de manejar aprovechando los últimos avances en computación, contenedores, almacenamiento y gestión de entornos.
Los acuerdos de SUSE con los principales fabricantes, tanto de soluciones de software como hardware, permiten una aproximación con garantías al complejo ecosistema de la gestión de datos a nivel empresarial.
Bridging IaaS With PaaS To Deliver The Service-Oriented Data CenterChris Haddad
As enterprises deploy private IaaS clouds into production they are reevaluating their future application delivery models. SUSE and WSO2 believe that private PaaS will leverage the automation and scalability of Private IaaS solutions, such as OpenStack-based SUSE Cloud, to deliver the secure, standardized development environments that will make migrating to an agile, service oriented delivery model possible. Come learn how the combination of IaaS and PaaS enables enterprises to more efficiently and flexibly tackle the challenges of the modern connected enterprise.
SUSE Enterprise Storage - a Gentle IntroductionGábor Nyers
SUSE Enterprise Storage is a scalable and resilient software-based storage solution. It lets you build cost-efficient and highly scalable data storage using commodity, off-the-shelf servers and disk drives.
VMworld 2013
Chris Greer, FedEx
Richard McDougall, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
Introduction to the new SUSE Manager for Retail. This is the updated versions of SUSE's Linux Enterprise Point of Service, combining traditional point of service image management and delivery with all top notch features of SUSE Mananger.
3.6.2015 järjestimme Konesali -ja tietoturvatapahtuma Best of Brainsharen asiakkaille ja kumppaneillemme.
Konesalin SUSE esityksistä vastasi SUSE Suomen asiantuntijat. Esittelyssä SUSE OpenStack Cloud 5 - Privaatti, hybridi ja julkinen pilvi ja ratkaisun uudet ominaisuudet.
Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines.
Through the story of a fictional character "Jack", representing a systems administrator, this presentation shows how the rich feature set of Uyuni helps sysadmins in their day to day operations.
Watch the video on YouTube: https://youtu.be/wZxnmruV_Uo
Data Wrangling on Hadoop - Olivier De Garrigues, Trifactahuguk
As Hadoop became mainstream, the need to simplify and speed up analytics processes grew rapidly. Data wrangling emerged as a necessary step in any analytical pipeline, and is often considered to be its crux, taking as much as 80% of an analyst's time. In this presentation we will discuss how data wrangling solutions can be leveraged to streamline, strengthen and improve data analytics initiatives on Hadoop, including use cases from Trifacta customers.
Bio: Olivier is EMEA Solutions Lead at Trifacta. He has 7 years experience in analytics with prior roles as technical lead for business analytics at Splunk and quantitative analyst at Accenture and Aon.
Stephen Taylor is the community manager for Ether Camp. They provide an analysis tool for the Ethereum blockchain, ‘Block Explorer’ and also an ‘Intergrated Development Environment’ (I.D.E) that empowers developers to build, test and deploy applications in a sandbox environment. This November they are launching their second annual hackathon, hack.ether.camp which is aiming to deliver a more sustained approach to the hackathon ideology, by utilising blockchain technology.
Google Cloud Dataproc - Easier, faster, more cost-effective Spark and Hadoophuguk
At Google Cloud Platform, we're combining the Apache Spark and Hadoop ecosystem with our software and hardware innovations. We want to make these awesome tools easier, faster, and more cost-effective, from 3 to 30,000 cores. This presentation will showcase how Google Cloud Platform is innovating with the goal of bringing the Hadoop ecosystem to everyone.
Bio: "I love data because it surrounds us - everything is data. I also love open source software, because it shows what is possible when people come together to solve common problems with technology. While they are awesome on their own, I am passionate about combining the power of open source software with the potential unlimited uses of data. That's why I joined Google. I am a product manager for Google Cloud Platform and manage Cloud Dataproc and Apache Beam (incubating). I've previously spent time hanging out at Disney and Amazon. Beyond Google, love data, amateur radio, Disneyland, photography, running and Legos."
Using Big Data techniques to query and store OpenStreetMap data. Stephen Knox...huguk
This talk will describe his research into using Hadoop to query and manage big geographic datasets, specifically OpenStreetMap(OSM). OSM is an “open-source” map of the world, growing at a large rate, currently around 5TB of data. The talk will introduce OSM, detail some aspects of the research, but also discuss his experiences with using the SpatialHadoop stack on Azure and Google Cloud.
Extracting maximum value from data while protecting consumer privacy. Jason ...huguk
Big organisations have a wealth of rich customer data which opens up huge new opportunities. However, they have the challenge of how to extract value from this data while protecting the privacy of their individual customers. He will talk about the risks organisations face, and what they should do about it. He will survey the techniques which can be used to make data safe for analysis, and talk briefly about how they are solving this problem at Privitar.
Intelligence Augmented vs Artificial Intelligence. Alex Flamant, IBM Watsonhuguk
IBM is developing the Watson Ecosystem to leverage its Developer Cloud, APIs, Content Store and Talent Hub. This is part of IBM's recent announcement of the $1B investment in Watson as a new business unit including Silicon Alley NYC headquarters. For the first time, IBM will open up Watson as a development platform in the Cloud to spur innovation and fuel a new ecosystem of entrepreneurial software app providers who will bring forward a new generation of applications infused with Watson's cognitive computing intelligence.
In this talk about Apache Flink we will touch on three main things, an introductory look at Flink, a look under the hood and a demo.
* In the introduction we will briefly look at the history of Flink and then go on to the API and different use cases. Here we will also see how it can be deployed in practice and what some of the pitfalls in a cluster setting can be.
* In the second section we will look at the streaming execution engine that lies at the heart of Flink. Here we will see what makes it tick and also what distinguishes it from other approaches, such as the mini-batch execution model.
Ufuk Celebi - PMC member at Apache Flink and co-founder and software engineer at data Artisans
* In the final section we will see a live demo of a fault-tolerant streaming job that performs analysis of the wikipedia edit-stream.
Lambda architecture on Spark, Kafka for real-time large scale MLhuguk
Sean Owen – Director of Data Science @Cloudera
Building machine learning models is all well and good, but how do they get productionized into a service? It's a long way from a Python script on a laptop, to a fault-tolerant system that learns continuously, serves thousands of queries per second, and scales to terabytes. The confederation of open source technologies we know as Hadoop now offers data scientists the raw materials from which to assemble an answer: the means to build models but also ingest data and serve queries, at scale.
This short talk will introduce Oryx 2, a blueprint for building this type of service on Hadoop technologies. It will survey the problem and the standard technologies and ideas that Oryx 2 combines: Apache Spark, Kafka, HDFS, the lambda architecture, PMML, REST APIs. The talk will touch on a key use case for this architecture -- recommendation engines.
Today’s reality Hadoop with Spark- How to select the best Data Science approa...huguk
Martin Oberhuber and Eliano Marques, Senior Data Scientists @Think Big International
In this talk Think Big International Lead Data Scientists will discuss the options that exist today for engineering and data science teams aiming to use big data patterns to solve new business problems. With the enterprise adoption of the Hadoop ecosystem and the emerging momentum of open source projects like Spark it is becoming mandatory to have an approach that solves for business results but remains flexible to adapt and change with the open source market.
Signal Media: Real-Time Media & News Monitoringhuguk
Startup pitch presented by CTO Wesley Hall. Signal Media is a real-time media and news monitoring platform that tracks media outlets. News items are analysed for brand & media monitoring as well as market intelligence.
Startup pitch presented by Aeneas Wiener. Cytora is a real-time geopolitical risk analysis platform that extracts events from open-source intelligence and evaluates these events on their geopolitical impact.
Startup pitch presented by co-founder and CEO Jaco Els. Cubitic offers a predictive analytics platform that allows developers to build custom solutions for analytics and visualisation on top of a machine learning engine.
Startup pitch presented by co-founder and CEO Corentin Guillo. Bird.i is building a platform for up-to-date earth observation data that will bring satellite imagery to the mass market. Providing fresh imagery together with analytics around the forecast of localised demand opens up innovative opportunities in sectors like construction, tourism, real-estate and remote facility monitoring.
Startup pitch presented by co-founders Laure Andrieux and Nic Greenway. Aiseedo applies real-time machine learning, where the model of the world is constantly updated, to build adaptive systems which can be applied to robotics, the Internet of Things and healthcare.
Secrets of Spark's success - Deenar Toraskar, Think Reactive huguk
This talk will cover the design and implementation decisions that have been key to the success of Apache Spark over other competing cluster computing frameworks. It will be delving into the whitepaper behind Spark and cover the design of Spark RDDs, the abstraction enables the Spark execution engine to be extended to support a wide variety of use cases: Spark SQL, Spark Streaming, MLib and GraphX. RDDs allow Spark to outperform existing models by up to 100x in multi-pass analytics.
TV Marketing and big data: cat and dog or thick as thieves? Krzysztof Osiewal...huguk
Technical developments in the area of data warehousing have allowed companies to push their analysis a step further and, therefore, allowed data scientists to deliver more value to business areas. In that session, we will focus on the case of performance marketing at King and demonstrate how we use Hadoop capabilities to exploit user-level data efficiently. That approach results in obtaining a more holistic view in a return-on-investment analysis of TV advertisement.
Hadoop - Looking to the Future By Arun Murthyhuguk
Hadoop - Looking to the Future
By Arun Murthy (Founder of Hortonworks, Creator of YARN)
The Apache Hadoop ecosystem began as just HDFS & MapReduce nearly 10 years ago in 2006.
Very much like the Ship of Theseus (http://en.wikipedia.org/wiki/Ship_of_Theseus), Hadoop has undergone incredible amount of transformation from multi-purpose YARN to interactive SQL with Hive/Tez to machine learning with Spark.
Much more lies ahead: whether you want sub-second SQL with Hive or use SSDs/Memory effectively in HDFS or manage Metadata-driven security policies in Ranger, the Hadoop ecosystem in the Apache Software Foundation continues to evolve to meet new challenges and use-cases.
Arun C Murthy has been involved with Apache Hadoop since the beginning of the project - nearly 10 years now. In the beginning he led MapReduce, went on to create YARN and then drove Tez & the Stinger effort to get to interactive & sub-second Hive. Recently he has been very involved in the Metadata and Governance efforts. In between he founded Hortonworks, the first public Hadoop distribution company.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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!
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
5. 5
Big Data Reference Architecture
Operating System OS / Cloud Platform
Source: Hortonworks Modern Data Architecture - http://hortonworks.com/partner/suse/
6. 6
SUSE Big Data Reference Architecture
Source: Hortonworks Modern Data Architecture - http://hortonworks.com/partner/suse/
7. 7
SUSE Big Data Partners
Hadoop Data Systems
Applications Services
8. 8
Certified for Leading Hadoop Platforms
Additional level of testing
and quality assurance to
make sure SUSE Linux
Enterprise Server
integrates with partner
software, saving our
customers time while
providing them with an
assurance of
interoperability.
We hereby declare that
SUSE Linux Enterprise Server
is officially certified for:
Cloudera CDH 5
Hortonworks HDP2
10. 10
SUSE in High Performance
“Teradata's extensive
financial, technical,
and management
resources can
create a unique,
high-performance
Hadoop appliance
that few other
vendors can match.”
– Forrester Feb 2014
High Performance Computing
‒ Half of the world's largest super computer
clusters run SUSE Linux Enterprise Server
Mainframe Computing
‒ Over 80% of all Linux running on mainframe
computers is SUSE Linux
SAP Hana
‒ SUSE Linux Enterprise Server is the
recommended OS for the market leading
analytics appliance, SAP HANA.
Teradata
‒ SUSE Linux Enterprise Server is the OS
foundation for Hadoop in the Aster Big Analytics
Appliance
IBM Watson
‒ Power artificial intelligence computer runs SUSE
Linux and Hadoop
11. 11
What Makes an Optimal Foundation
for Hadoop?
SLAs and
Business Continuity
Resource Utilization
and Efficiency
Security and
Compliance
Affordable, No
Vendor Lock-in
12. 12
Power, Scalability
Reliability, Availability,Serviceability:
Swap-over NFS
Built-in open source multi-path IO
CPU/Memory hot-plugging
Horizontal/Vertical Scalability:
Large capacity and faster system
interconnect (OFED, Infiniband)
A rock-solid, certified
foundation for deploying
Hadoop clusters.
Huge Data, Massive Compute:
4096 logical CPU
64 TiB RAM
Supports latest Intel CPUs:
Ivy Bridge v2
Haswell
SUSE Linux Enterprise Server
13. 13
Flexibility, Agility
Massively Scalable Private
Cloud Implementations
Deploy pre-configured
Hadoop clusters on
KVM, Xen, Hyper-V, ESXi
Spin up fully configured and
optimized Hadoop Cluster in
minutes for dev/test
Scale-out Hadoop cluster
Infrastructure easily
API for Cloud-aware
Applications
SUSE Cloud
Hadoop in the Cloud:
OpenStack based
enterprise ready IaaS Cloud
Platform.
14. 14
Improve Resource Utilization and Efficiency
Batch Command Speeds Up
Cluster Implementation
Centralized Server
Infrastructure Management
Software and Patch
Management for Linux and
Hadoop
Batch-deploy config files to
entire Hadoop cluster
Asset Management
and Reporting
Application and
Infrastructure Monitoring
SUSE Manager
A perfect complement
to the monitoring and
management capabilities
provided in the Hadoop
cluster management
software.
15. 15
Security and Certifications
90% of companies cite data access and data protection as either extremely or very important
security capabilities. - IDG Big Data Survey 2014
Security Features SUSE Linux Enterprise Server
System Hardening YaST2 Security Center
Application Confinement AppArmor
System Confinement SE Linux (stack support)
Intrusion Detection (file system) AIDE
Fine-grained Access Rights File system POSIX capabilities
Encryption Capabilities Three ways: Full disk, Volume, Filesystem
(eCryptFS)
Certifications Carrier Grade Linux (CGL) 4.0 IPv6 (refresh)
Measure and Monitor System Integrity During
Trusted Platform Modules (TPM)—Trusted
Reboot
Computing
System Requirements for Cryptographic Modules FIPS 140-2 Validation for OpenSSL
Common Criteria for IT Security Evaluation Common Criteria Certification for SP2
(x86 64 with KVM; IBM System z)
16. 16
Summary: Key Features and Benefits
Key Features Benefits
Reliability,
Availability,
Serviceability,
Scalability
Swap over NFS Cut cost with less expensive diskless servers
Kernel 3.0 Enhanced RAS capabilities
Intel Ivy-Bridge 2 and Haswell Support Harness the latest CPU technologies and provides
excellent 4096 Logical CPU, 64TiB RAM Support vertical scalability
InfiniBand, iSCSI Target (LIO) and OFED Faster connectivity with networking and storage equipment
Dual Hypervisor Support: Xen and KVM
Cross-platform Maximum choice both as a host and as a guest
Virtualization
Optimized for vSphere, Hyper-V, Open
Source Hypervisors
Linux Containers Light weight OS level virtualization
UEFI Secure Boot Less malicious attach risk in boot
Security and
Compliance
FIPS 140-2 Validation and Common
Criteria Certification Security standard compliance
AppArmor Protects from external/internal threats and zero-day
attacks
Integrated System
Management
Snapper and BTRFS Snapshot and rollback for easy management
YaST, AutoYaST and Zypp Integrated single system management and fast update
tools
Interop with
Other Platforms
SAMBA 3.6 Compatible with Windows
IPv6 Compliance Networking with IPv6 equipment
18. 18
Hadoop on SLES
Best Practices White Paper:
• Deployment scenarios
• Proposed Architecture using SLES
• Infrastructure considerations
• Basic optimization of the Linux OS
• Installation and configuration of Hadoop
on SLES
19. 19
SUSE Manager and Hadoop
Step-by-step guide for using SUSE
Manager to deploy Cloudera on SLES:
• Automate OS provisioning
• Deploy new servers with identical
characteristics
• Auto-deployment of RPM-based applications
• Centralize management of configuration files
• Connect to SUSE Customer Center for
updates
• Create / manage multiple organizations from a
single remote console.
• Create customized repositories
• Maintain the security of enterprise systems
• Leverage the SUSE Manager API to create
custom scripts to manage tasks or integrate
third-party applications and management
tools
20. 20
Hadoop / HP Reference Architecture
HP Reference Architechture:
• Written by SUSE, HP & Hortonworks,
• Proposed Architecture using SLES
• HP Recommends SLES
21. 21
SUSE Big Data Lab
Big Data Cluster in USA for:
• Benchmarking
• Software certification
• Integration / test
• Reference architectures
22. Learn About:
Register:
22
SUSE Linux Expert Days
• SUSE and Big Data
• Towards Zero Uptime with SUSE Tecnology
• SUSE Linux Enterprise Server
https://www.suse.com/events/slef-2014/#Liste
23. 23
Learn More
Visit our web site
www.suse.com/solutions/platform.html#big_data
Read our whitepapers
Deploying Hadoop on SLES
Deploy and Manage Hadoop with SUSE Manager
HP Reference Architecture.
Contact us
bigdata@suse.com
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