After a brief introduction to programmatic ads and RTB we go through the evolution of Jampp's data platform to handle the enormous about of data we need to process.
Processing 19 billion messages in real time and NOT dying in the processJampp
Here is an introduction in the Jampp architecture for data processing. We walk through our journey of migrating to systems that allows us to process more data in real time
High availability, real-time and scalable architecturesJampp
Presented at the Architecture Conference (ArqConf) in Buenos Aires, Argentina. Here is a 10,000ft view of our Real Time Bidding and Stream Processing architecture.
Presented at the AWS Summit in London, here's a deep dive on getting started with Amazon Kinesis and use-case with Jampp, the world's leading mobile app marketing platform.
How to Quantify the Value of Kafka in Your Organization confluent
(Lyndon Hedderly, Confluent) Kafka Summit SF 2018
We all know real-time data has a value. But how do you quantify that value in order to create a business case for becoming more data, or event driven?
The first half of this talk will explore the value of data across a variety of organizations, starting with the five most valuable companies in the world: Apple, Alphabet (Google), Microsoft, Amazon and Facebook (based on stock prices July 2017). We will go on to discuss other digital natives: Uber, Ebay, Netflix and LinkedIn, before exploring more traditional companies across retail, finance and automotive. Next, we’ll look at non-businesses such as governments and lobbyists. Whether organizations are using data to create new business products and services, improve user experiences, increase productivity, manage risk or influencing global power, we’ll see that fast and interconnected data, or “event streaming” is increasingly important.
After showing that data value can be quantified, the second half of this talk will explain the five steps to creating a business case.
Most businesses focus on:
-Making more money or conferring competitive advantage to make more money
-Increasing efficiency to save money and/or
-Mitigating risk to the business to protect money
-We’ll walk through examples of real business cases, discuss how business cases have evolved over the years and show the power of a sound business case. If you’re interested in big money and big business, as well as big data, this talk is for you.
Real-Time Bidding (RTB) is a service offered by advertising networks to agencies. The agencies decide on the value of advertising opportunities in real-time and bid accordingly on behalf of their advertising clients. Typically the window of opportunity for bids to be calculated from provided consumer details (e.g. cookies) and then submitted is 100ms.
Processing 19 billion messages in real time and NOT dying in the processJampp
Here is an introduction in the Jampp architecture for data processing. We walk through our journey of migrating to systems that allows us to process more data in real time
High availability, real-time and scalable architecturesJampp
Presented at the Architecture Conference (ArqConf) in Buenos Aires, Argentina. Here is a 10,000ft view of our Real Time Bidding and Stream Processing architecture.
Presented at the AWS Summit in London, here's a deep dive on getting started with Amazon Kinesis and use-case with Jampp, the world's leading mobile app marketing platform.
How to Quantify the Value of Kafka in Your Organization confluent
(Lyndon Hedderly, Confluent) Kafka Summit SF 2018
We all know real-time data has a value. But how do you quantify that value in order to create a business case for becoming more data, or event driven?
The first half of this talk will explore the value of data across a variety of organizations, starting with the five most valuable companies in the world: Apple, Alphabet (Google), Microsoft, Amazon and Facebook (based on stock prices July 2017). We will go on to discuss other digital natives: Uber, Ebay, Netflix and LinkedIn, before exploring more traditional companies across retail, finance and automotive. Next, we’ll look at non-businesses such as governments and lobbyists. Whether organizations are using data to create new business products and services, improve user experiences, increase productivity, manage risk or influencing global power, we’ll see that fast and interconnected data, or “event streaming” is increasingly important.
After showing that data value can be quantified, the second half of this talk will explain the five steps to creating a business case.
Most businesses focus on:
-Making more money or conferring competitive advantage to make more money
-Increasing efficiency to save money and/or
-Mitigating risk to the business to protect money
-We’ll walk through examples of real business cases, discuss how business cases have evolved over the years and show the power of a sound business case. If you’re interested in big money and big business, as well as big data, this talk is for you.
Real-Time Bidding (RTB) is a service offered by advertising networks to agencies. The agencies decide on the value of advertising opportunities in real-time and bid accordingly on behalf of their advertising clients. Typically the window of opportunity for bids to be calculated from provided consumer details (e.g. cookies) and then submitted is 100ms.
Glynn Bird - Building the "microservices way" involves breaking monolithic IT systems into small, decoupled services that each to one job well. This talk builds a practical microservices architecture during the talk using small Node.js apps that perform storage, analytics and visualisation tasks. Learn how to orchestrate your own microservice architecture using simple, easily-tested building blocks.
Analysing data analytics use cases to understand big data platformdataeaze systems
Get big picture of data platform architecture by knowing its purpose and problem it solves.
These slides take top down approach, starting with basic purpose of data platform ie. to serve analytics use cases. These slides categorise use cases and analyses their expectation from data platform.
Customer Experience at Disney+ Through Data PerspectiveDatabricks
Disney+ has rapidly scaled to provide a personalized and seamless experience to tens of millions of customers. This experience is powered by a robust data platform that ingests, processes and surfaces billions of events per hour using Delta lake, Databricks, and AWS technologies. The data produced by the platform is used by multitude of services including a recommendation engine for personalized experience, optimizing watch experience including group watch, and fraud and abuse prevention.
In this session, you will learn how Disney+ built these capabilities, the architecture, technologies, design principles, and technical details that make it possible.
Streaming data in the cloud with Confluent and MongoDB Atlas | Robert Waters,...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
Use Apache Gradle to Build and Automate KSQL and Kafka Streams (Stewart Bryso...confluent
KSQL is an easy-to-use and easy-to-understand streaming SQL engine for Apache Kafka built on top of Kafka Streams. The ability to write streaming applications using only SQL makes Apache Kafka available to a whole range of new developers and potential use cases, either as a stand-alone solution, or as a single component to a broader Kafka Streams implementation. Inspired by a customer project now in production, experience the lifecycle of a streaming application developed using KSQL and Kafka Streams. With Apache Gradle as our build framework, we’ll explore the open-source Gradle plugin we built during this project to improve developer efficiency and automate the deployment of KSQL pipelines, user-defined functions, and Kafka Streams microservices.
We’ll demonstrate the deployment process live, and discuss design decisions around incorporating SQL-based processes into an overall streaming application.
Key Takeaways
1. KSQL is a natural choice for expressing data-driven applications, but it may not naturally fit into established DevOps processes and automations.
2. We built an open-source Gradle plugin to handle all aspects of deploying a Kafka-based streaming application: KSQL pipelines, KSQL user-defined functions, and Kafka Streams microservices.
3. KSQL pipelines can be deployed using either a server start script, or the KSQL REST API, and our Gradle plugin fully supports both options.
Winning the On-Demand Economy with Spark and Predictive AnalyticsSingleStore
Today’s on-demand economy drives companies to provide fast load times, personalization, and instantaneous service for hungry end-users across all types of applications. Yet most still use dated, legacy systems to process and analyze data. In this session, Ankur Goyal, VP of Engineering at MemSQL will showcase implementing a one-click Lambda Architecture with Apache Spark, Apache Kafka and an operational database, resulting in lightning fast analytics on large, changing datasets.
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...confluent
At Under Armour Connected Fitness, we’ve built an event streaming platform on top of Kafka and the Confluent stack that makes it easy for developers to produce and consume schema-based events without requiring direct knowledge of Kafka. We are constantly trying to improve the developer experience. The platform consists of multiple federated Kafka clusters, a schema registry, a topology service, an archiver and specialized client libraries and Web / CLI tools that assist developers with producer and consumer workflows.
In this talk, we will take a deeper dive into the design and implementation of a Scala/Java implementation of our client library that allows developers to produce or consume events without worrying about the underlying infrastructure and their location while enjoying the benefits of data compatibility through schemas. We’ll also look at an HTTP based client proxy that exposes the same API but for languages without our native support. Finally, we’ll walk through Web and CLI tools we built to make working with the platform easier.
The content of this talk will be primarily aimed at software developers looking for ideas on how to build Kafka client tools that allow producer/consumer interactions protected by schema-based event definitions while hiding details of the underlying infrastructure.
Processing Real-Time Data at Scale: A streaming platform as a central nervous...confluent
(Marcus Urbatschek, Confluent)
Presentation during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Stream Processing with Kafka in Uber, Danny Yuan confluent
The session will discuss how Uber evolved its stream processing system to handle a number of use cases in Uber Marketplace, with a focus on how Apache Kafka and Apache Samza played an important role in building a robust and efficient data pipeline. The use cases include but not limited to realtime aggregation of geospatial time series, computing key metrics as well as forecasting of marketplace dynamics, and extracting patterns from various event streams. The session will present how Kafka and Samza are used to meet the requirements of the use cases, what additional tools are needed, and lessons learned from operating the pipeline.
The evolution of the big data platform @ Netflix (OSCON 2015)Eva Tse
At Netflix, the big data platform is the foundation for analytics that drive all product decisions that directly impact our customer experience. As for scale, it is one of the top three largest services running at Netflix, in terms of compute power and data size.
In this talk, we will take the audience through a journey to understand how we scale the platform to handle the increasing amount of data (over 500 billion events generated daily), the increasing demand of analytics (which translates to compute power), and the increasing number of users dependent on our platform to make business decisions.
"Building Real-Time Data Pipelines with Kafka and MemSQL" by Rick Negrin, Director of Product Management at MemSQL for Orange County Roadshow March 17, 2017.
Glynn Bird - Building the "microservices way" involves breaking monolithic IT systems into small, decoupled services that each to one job well. This talk builds a practical microservices architecture during the talk using small Node.js apps that perform storage, analytics and visualisation tasks. Learn how to orchestrate your own microservice architecture using simple, easily-tested building blocks.
Analysing data analytics use cases to understand big data platformdataeaze systems
Get big picture of data platform architecture by knowing its purpose and problem it solves.
These slides take top down approach, starting with basic purpose of data platform ie. to serve analytics use cases. These slides categorise use cases and analyses their expectation from data platform.
Customer Experience at Disney+ Through Data PerspectiveDatabricks
Disney+ has rapidly scaled to provide a personalized and seamless experience to tens of millions of customers. This experience is powered by a robust data platform that ingests, processes and surfaces billions of events per hour using Delta lake, Databricks, and AWS technologies. The data produced by the platform is used by multitude of services including a recommendation engine for personalized experience, optimizing watch experience including group watch, and fraud and abuse prevention.
In this session, you will learn how Disney+ built these capabilities, the architecture, technologies, design principles, and technical details that make it possible.
Streaming data in the cloud with Confluent and MongoDB Atlas | Robert Waters,...HostedbyConfluent
Are you looking for a cloud-based architecture that includes the best of breed streaming and database technologies? In this session you will learn how to setup and configure the Confluent Cloud with MongoDB Atlas. We'll start the journey learning about the basic connectivity between the two cloud services and end with a brief discovery of what you can do with data once it is in MongoDB Atlas. By the end of this session you will know how to securely setup and configure the MongoDB Atlas connectors in the Confluent Cloud in both a source and sink configuration.
Use Apache Gradle to Build and Automate KSQL and Kafka Streams (Stewart Bryso...confluent
KSQL is an easy-to-use and easy-to-understand streaming SQL engine for Apache Kafka built on top of Kafka Streams. The ability to write streaming applications using only SQL makes Apache Kafka available to a whole range of new developers and potential use cases, either as a stand-alone solution, or as a single component to a broader Kafka Streams implementation. Inspired by a customer project now in production, experience the lifecycle of a streaming application developed using KSQL and Kafka Streams. With Apache Gradle as our build framework, we’ll explore the open-source Gradle plugin we built during this project to improve developer efficiency and automate the deployment of KSQL pipelines, user-defined functions, and Kafka Streams microservices.
We’ll demonstrate the deployment process live, and discuss design decisions around incorporating SQL-based processes into an overall streaming application.
Key Takeaways
1. KSQL is a natural choice for expressing data-driven applications, but it may not naturally fit into established DevOps processes and automations.
2. We built an open-source Gradle plugin to handle all aspects of deploying a Kafka-based streaming application: KSQL pipelines, KSQL user-defined functions, and Kafka Streams microservices.
3. KSQL pipelines can be deployed using either a server start script, or the KSQL REST API, and our Gradle plugin fully supports both options.
Winning the On-Demand Economy with Spark and Predictive AnalyticsSingleStore
Today’s on-demand economy drives companies to provide fast load times, personalization, and instantaneous service for hungry end-users across all types of applications. Yet most still use dated, legacy systems to process and analyze data. In this session, Ankur Goyal, VP of Engineering at MemSQL will showcase implementing a one-click Lambda Architecture with Apache Spark, Apache Kafka and an operational database, resulting in lightning fast analytics on large, changing datasets.
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...confluent
At Under Armour Connected Fitness, we’ve built an event streaming platform on top of Kafka and the Confluent stack that makes it easy for developers to produce and consume schema-based events without requiring direct knowledge of Kafka. We are constantly trying to improve the developer experience. The platform consists of multiple federated Kafka clusters, a schema registry, a topology service, an archiver and specialized client libraries and Web / CLI tools that assist developers with producer and consumer workflows.
In this talk, we will take a deeper dive into the design and implementation of a Scala/Java implementation of our client library that allows developers to produce or consume events without worrying about the underlying infrastructure and their location while enjoying the benefits of data compatibility through schemas. We’ll also look at an HTTP based client proxy that exposes the same API but for languages without our native support. Finally, we’ll walk through Web and CLI tools we built to make working with the platform easier.
The content of this talk will be primarily aimed at software developers looking for ideas on how to build Kafka client tools that allow producer/consumer interactions protected by schema-based event definitions while hiding details of the underlying infrastructure.
Processing Real-Time Data at Scale: A streaming platform as a central nervous...confluent
(Marcus Urbatschek, Confluent)
Presentation during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
Stream Processing with Kafka in Uber, Danny Yuan confluent
The session will discuss how Uber evolved its stream processing system to handle a number of use cases in Uber Marketplace, with a focus on how Apache Kafka and Apache Samza played an important role in building a robust and efficient data pipeline. The use cases include but not limited to realtime aggregation of geospatial time series, computing key metrics as well as forecasting of marketplace dynamics, and extracting patterns from various event streams. The session will present how Kafka and Samza are used to meet the requirements of the use cases, what additional tools are needed, and lessons learned from operating the pipeline.
The evolution of the big data platform @ Netflix (OSCON 2015)Eva Tse
At Netflix, the big data platform is the foundation for analytics that drive all product decisions that directly impact our customer experience. As for scale, it is one of the top three largest services running at Netflix, in terms of compute power and data size.
In this talk, we will take the audience through a journey to understand how we scale the platform to handle the increasing amount of data (over 500 billion events generated daily), the increasing demand of analytics (which translates to compute power), and the increasing number of users dependent on our platform to make business decisions.
"Building Real-Time Data Pipelines with Kafka and MemSQL" by Rick Negrin, Director of Product Management at MemSQL for Orange County Roadshow March 17, 2017.
(BDT403) Best Practices for Building Real-time Streaming Applications with Am...Amazon Web Services
Amazon Kinesis is a fully managed, cloud-based service for real-time data processing over large, distributed data streams. Customers who use Amazon Kinesis can continuously capture and process real-time data such as website clickstreams, financial transactions, social media feeds, IT logs, location-tracking events, and more. In this session, we first focus on building a scalable, durable streaming data ingest workflow, from data producers like mobile devices, servers, or even a web browser, using the right tool for the right job. Then, we cover code design that minimizes duplicates and achieves exactly-once processing semantics in your elastic stream-processing application, built with the Kinesis Client Library. Attend this session to learn best practices for building a real-time streaming data architecture with Amazon Kinesis, and get answers to technical questions frequently asked by those starting to process streaming events.
The role of Big Data and Modern Data Management in Driving a Customer 360 fro...Cloudera, Inc.
Organizations spanning all industries are in pursuit of Customer 360, which aims to integrate and enrich customer information across multiple channels, systems, devices and products in order to improve the interaction experience and maximize the value delivered. To achieve this real-time integration requires a modern approach to working with data and the Cloud is providing a differentiating strategic platform for many organisations. Discover how you can strategically structure your data environment leveraging the Cloud to empower analytical deployment, create next generation customer applications whilst also saving costs and realising greater efficiencies.
The CRM@Oracle series highlights Oracle's internal implementation of Oracle CRM products such as Siebel CRM, Oracle CRM On Demand and Oracle Mobile Sales Assistant. This presentation discusses how Oracle sales reps have a complete view of their customer information within Siebel CRM.
Running Fast, Interactive Queries on Petabyte Datasets using Presto - AWS Jul...Amazon Web Services
Learn how to deploy a managed Presto environment to interactively query log data on AWS
Organizations often need to quickly analyze large amounts of data, such as logs, generated from a wide variety of sources and formats. However, traditional approaches require a lot of time and effort designing complex data transformation and loading processes; and configuring data warehouses. Using AWS, you can start querying your datasets within minutes
In this webinar you will learn how you can deploy a managed Presto environment in minutes to interactively query log data using plain ANSI SQL. Presto is a popular open source SQL engine for running interactive analytic queries against data sources of all sizes. We will talk about common use cases and best practices for running Presto on Amazon EMR.
Learning Objectives:
• Learn how to deploy a managed Presto environment running on Amazon EMR
• Understand best practices for running Presto on Amazon EMR, including use of Amazon EC2 Spot instances
• Learn how other customers are using Presto to analyze large data sets
(BDT314) A Big Data & Analytics App on Amazon EMR & Amazon RedshiftAmazon Web Services
"No matter the industry, leading organizations need to closely integrate, deploy, secure, and scale diverse technologies to support workloads while containing costs. Nasdaq, Inc.—a leading provider of trading, clearing, and exchange technology—is no exception.
After migrating more than 1,100 tables from a legacy data warehouse into Amazon Redshift, Nasdaq, Inc. is now implementing a fully-integrated, big data architecture that also includes Amazon S3, Amazon EMR, and Presto to securely analyze large historical data sets in a highly regulated environment. Drawing from this experience, Nasdaq, Inc. shares lessons learned and best practices for deploying a highly secure, unified, big data architecture on AWS.
Attendees learn:
Architectural recommendations to extend an Amazon Redshift data warehouse with Amazon EMR and Presto.
Tips to migrate historical data from an on-premises solution and Amazon Redshift to Amazon S3, making it consumable.
Best practices for securing critical data and applications leveraging encryption, SELinux, and VPC."
Organizations across diverse industries are in pursuit of Customer 360, by integrating customer information across multiple channels, systems, devices and products. Having a 360-degree view of the customer enables enterprises to improve the interaction experience, drive customer loyalty and improve retention. However delivering a true Customer 360 can be very challenging.
Big data Argentina meetup 2020-09: Intro to presto on dockerFederico Palladoro
We will talk about how we are migrating our Presto clusters from AWS EMR to Docker using production-grade orchestrators
considering cluster management, configuration and monitoring. We will discuss between Hashicorp Nomad and Kubernetes as a base solution
Webinar: Enterprise Trends for Database-as-a-ServiceMongoDB
Two complementary trends are particularly strong in enterprise IT today: MongoDB itself, and the movement of infrastructure, platform, and software to as-a-service models. Being designed from the start to work in cloud deployments, MongoDB is a natural fit.
Learn how your enterprise can create its own MongoDB service offering, combining the advantages of MongoDB and cloud for agile, nearly-instantaneous deployments. Ease your operations workload by centralizing your points for enforcement, standardize best policies, and enable elastic scalability.
We will provide you with an enterprise planning outline which incorporates needs and value for stakeholders across operations, development, and business. We will cover accounting, chargeback integration, and quantification of benefits to the enterprise (such as standardizing best practices, creating elastic architecture, and reducing database maintenance costs).
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Prolifics
Abstract: Recent projects have stressed the "need for speed" while handling large amounts of data, with near zero downtime. An analysis of multiple environments has identified optimizations and architectures that improve both performance and reliability. The session covers data gathering and analysis, discussing everything from the network (multiple NICs, nearby catalogs, high speed Ethernet), to the latest features of extreme scale. Performance analysis helps pinpoint where time is spent (bottlenecks) and we discuss optimization techniques (MQ tuning, IIB performance best practices) as well as helpful IBM support pacs. Log Analysis pinpoints system stress points (e.g. CPU starvation) and steps on the path to near zero downtime.
AWS Partner Webcast - Analyze Big Data for Consumer Applications with Looker ...Amazon Web Services
Analyze Big Data for Consumer Applications with Looker BI and Amazon Redshift Customizing the customer experience based on user behavior is a constant challenge for today’s consumer apps. Business intelligence helps analyze and model large amounts of data. Looker offers a modern approach to BI leveraging AWS that’s fast, agile, and easy to manage. Join this webinar to learn how MessageMe, which provides emotionally engaging messaging apps to consumers, leverages Looker business intelligence software and the Amazon Redshift data warehouse service to analyze billions of rows of customer data in seconds.
Webinar topics include:
• How MessageMe turns billions of rows of customer data stored in Amazon Redshift into actionable insights
• How Looker connects directly to Amazon Redshift in just a few clicks, enabling MessageMe to build a modern, big data analytics in the cloud. Who should attend
• Information or Solution Architects, Data Analysts, BI Directors, DBAs, Development Leads, Developers, or Technical IT Leaders.
Presenters:
• Justin Rosenthal, CTO, MessageMe
• Keenan Rice, VP, Marketing & Alliances, Looker
• Tina Adams, Senior Product Manager, AWS
IBM z/OS Version 2 Release 2 -- Fueling the digital enterpriseAnderson Bassani
Carta de anúncio oficial da IBM sobre o z/OS V2R2 a ser disponibilizado oficialmente para os clientes no dia 30/Setembro/2015. Link: http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?subtype=ca&infotype=an&supplier=899&letternum=ENUSLP15-0369
Serverless Design Patterns for Rethinking Traditional Enterprise Application ...Amazon Web Services
AWS Lambda is a powerful and flexible tool for solving diverse business problems, from traditional grid computing to scheduled batch processing workflows. Cloud native solutions using AWS Lambda enable architectures that depart from traditional enterprise application design. These new design patterns can provide substantially increased performance and reduced costs. In this session, learn how Fannie Mae re-architected one of their mission-critical traditional grid computing applications to a modern serverless solution using AWS Lambda. Learn More: https://aws.amazon.com/government-education/
GigaSpaces - Getting Ready For The Cloudgigaspaces
Mr Nati Shalom, Founder and CTO of GigaSpaces
Nati is responsible for defining the technology roadmap and the direction of GigaSpaces products as they relate to standards adaptations, architecture, and product design.
He has more than 10 years of experience with distributed technology and architecture namely CORBA, Jini, J2EE, Grid and SOA. He has been working for the past ten years with some of the leading Israeli companies, such as ECI, Comverse, BMC, Elisra, Rafael, and Amdocs. He has led the development of the first Reverse BID exchange in the Israeli Yellow Pages. He previously worked with IONA, and was responsible for the penetration of their products and technology, to most of the leading ISV's in Israel.
As the Head of the Israeli Grid consortium, Mr. Shalom is recognized as a software visionary and industry leader, he is a frequent presenter at industry conferences and is actively involved in evangelizing Space Based Architecture, Data Grid patterns, and Cloud Computing.
______________________________________________________________________________________________________________
Topic - Getting Ready for the Cloud – Technology
In this session Nati will describe what is the latest developments in the industry on cloud computing, and where he feels this will be going. He will also share his experience on how to design and deploy enterprise applications in a cloud/grid computing platform, what to take into account while developing or deploying applications on the cloud, and demonstrate how to transition applications to run on the Cloud without needing to completely re-architect them. Standard Application Servers as we've known them only partially address enterprises' needs for scalability. As a result, a new class of application servers has emerged, focused on massive scalability. In this session, we will explore some of the common characteristics of these servers while looking at how to migrate an existing Java EE web app to a scale-out application server, relatively seamlessly.
Included is a 10-minute demo on turning an existing tier-based application into a tierless scaled out application running on the Amazon EC2 Cloud. In this live demo session, we will also use the cloud-based environment to demonstrate how you can add dynamic scaling, self healing and improved performance with almost no changes to your code.
Operational systems manage our finances, shopping, devices and much more. Adding real-time analytics to these systems enables them to instantly respond to changing conditions and provide immediate, targeted feedback. This use of analytics is called "operational intelligence," and the need for it is widespread.
This talk will explain how in-memory computing techniques can be used to implement operational intelligence. It will show how an in-memory data grid integrated with a data-parallel compute engine can track events generated by a live system, analyze them in real time, and create alerts that help steer the system’s behavior. Code samples will demonstrate how an in-memory data grid employs object-oriented techniques to simplify the correlation and analysis of incoming events by maintaining an in-memory model of a live system.
The talk also will examine simplifications offered by this approach over directly analyzing incoming event streams from a live system using complex event processing or Storm. Lastly, it will explain key requirements of the in-memory computing platform for operational intelligence, in particular real-time updating of individual objects and high availability using data replication, and contrast these requirements to the design goals for stream processing in Spark.
Using real time big data analytics for competitive advantageAmazon Web Services
Many organisations find it challenging to successfully perform real-time data analytics using their own on premise IT infrastructure. Building a system that can adapt and scale rapidly to handle dramatic increases in transaction loads can potentially be quite a costly and time consuming exercise.
Most of the time, infrastructure is under-utilised and it’s near impossible for organisations to forecast the amount of computing power they will need in the future to serve their customers and suppliers.
To overcome these challenges, organisations can instead utilise the cloud to support their real-time data analytics activities. Scalable, agile and secure, cloud-based infrastructure enables organisations to quickly spin up infrastructure to support their data analytics projects exactly when it is needed. Importantly, they can ‘switch off’ infrastructure when it is not.
BluePi Consulting and Amazon Web Services (AWS) are giving you the opportunity to discover how organisations are using real time data analytics to gain new insights from their information to improve the customer experience and drive competitive advantage.
How to Succeed in Hadoop: comScore’s Deceptively Simple Secrets to Deploying ...MapR Technologies
Get an insider's view into one of the most talked-about Hadoop deployments in the world!
As more enterprises realize the value of big data, Hadoop is moving from lab curiosity to genuine competitive advantage. But how can you confidently deploy it in a production environment?
In this joint webinar with Syncsort, learn firsthand from industry thought leader, Mike Brown, CTO of comScore, how to offload critical data and optimize your enterprise data architecture with Hadoop to increase performance while lowering costs.
Similar to Building a real-time, scalable and intelligent programmatic ad buying platform (20)
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!
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.
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.
Understanding Nidhi Software Pricing: A Quick Guide 🌟
Choosing the right software is vital for Nidhi companies to streamline operations. Our latest presentation covers Nidhi software pricing, key factors, costs, and negotiation tips.
📊 What You’ll Learn:
Key factors influencing Nidhi software price
Understanding the true cost beyond the initial price
Tips for negotiating the best deal
Affordable and customizable pricing options with Vector Nidhi Software
🔗 Learn more at: www.vectornidhisoftware.com/software-for-nidhi-company/
#NidhiSoftwarePrice #NidhiSoftware #VectorNidhi
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
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
#AIFusionBuddyReview,
#AIFusionBuddyFeatures,
#AIFusionBuddyPricing,
#AIFusionBuddyProsandCons,
#AIFusionBuddyTutorial,
#AIFusionBuddyUserExperience
#AIFusionBuddyforBeginners,
#AIFusionBuddyBenefits,
#AIFusionBuddyComparison,
#AIFusionBuddyInstallation,
#AIFusionBuddyRefundPolicy,
#AIFusionBuddyDemo,
#AIFusionBuddyMaintenanceFees,
#AIFusionBuddyNewbieFriendly,
#WhatIsAIFusionBuddy?,
#HowDoesAIFusionBuddyWorks
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
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.
In the ever-evolving landscape of technology, enterprise software development is undergoing a significant transformation. Traditional coding methods are being challenged by innovative no-code solutions, which promise to streamline and democratize the software development process.
This shift is particularly impactful for enterprises, which require robust, scalable, and efficient software to manage their operations. In this article, we will explore the various facets of enterprise software development with no-code solutions, examining their benefits, challenges, and the future potential they hold.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
AI Genie Review: World’s First Open AI WordPress Website CreatorGoogle
AI Genie Review: World’s First Open AI WordPress Website Creator
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-genie-review
AI Genie Review: Key Features
✅Creates Limitless Real-Time Unique Content, auto-publishing Posts, Pages & Images directly from Chat GPT & Open AI on WordPress in any Niche
✅First & Only Google Bard Approved Software That Publishes 100% Original, SEO Friendly Content using Open AI
✅Publish Automated Posts and Pages using AI Genie directly on Your website
✅50 DFY Websites Included Without Adding Any Images, Content Or Doing Anything Yourself
✅Integrated Chat GPT Bot gives Instant Answers on Your Website to Visitors
✅Just Enter the title, and your Content for Pages and Posts will be ready on your website
✅Automatically insert visually appealing images into posts based on keywords and titles.
✅Choose the temperature of the content and control its randomness.
✅Control the length of the content to be generated.
✅Never Worry About Paying Huge Money Monthly To Top Content Creation Platforms
✅100% Easy-to-Use, Newbie-Friendly Technology
✅30-Days Money-Back Guarantee
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
#AIGenieApp #AIGenieBonus #AIGenieBonuses #AIGenieDemo #AIGenieDownload #AIGenieLegit #AIGenieLiveDemo #AIGenieOTO #AIGeniePreview #AIGenieReview #AIGenieReviewandBonus #AIGenieScamorLegit #AIGenieSoftware #AIGenieUpgrades #AIGenieUpsells #HowDoesAlGenie #HowtoBuyAIGenie #HowtoMakeMoneywithAIGenie #MakeMoneyOnline #MakeMoneywithAIGenie
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.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
4. Jampp is a leading mobile app
marketing and retargeting platform.
Founded in 2013, Jampp has offices in San
Francisco, London, Berlin, Buenos Aires, São
Paulo and Cape Town.
We help companies grow their business by
seamlessly acquiring, engaging & retaining
mobile app users.
5. Jampp’s platform combines machine
learning with big data for programmatic ad
buying which optimizes towards in-app
activity.
Our platform processes +200,000 RTB ad bid
requests per second (17+ billions per day)
which amounts to about 300 MB/s or 25 TB
of data per day.
6. How does programmatic ads work?
DOWNLOAD
APP
Source /
Exchange
Jampp
Tracking
Platform
AppStore /
Google Play
App
Install
Postback
Postback
8. Jampp Events
1. RTB:
a. Auction: the exchange asks if we want to bid for the
impression.
b. Bid/Non-Bid: bid with price or non-bid (less than 80ms).
c. Impression: the ad is displayed to the user.
2. Non-RTB:
a. Click: event that marks when the user clicks on the ad.
b. Install: install of the app on first app open.
c. Event: in app events like purchase, view, favorited.
9. Data @ Jampp
● Our platform started using RDBMSs and a
traditional Data Warehouse architecture on Amazon
Web Services.
● Data grew exponentially and data needs became
more complex.
● In the last year alone, 2500%+ in-app events and
500%+ RTB bids.
● This made us evolve our architecture to be able to
effectively handle Big Data.
12. Jampp Initial Systems: Bidder
● OpenRTB bidding system implementation that runs on
200+ virtual machines with 70GB RAM each.
● Strong latency requirements. Less than 80ms to answer a
request.
● Written in Cython and uses ZMQ for communication.
● Heavy use of coherent caching to comply with latency
requirements.
● Data is continually replicated and enriched from MySQL
by the replicator process.
13. Jampp Initial Systems: Cupper
● Event tracking system written in Node.js.
● Tracks clicks, installs and in-app events. (200+
millions per day)
● Can be scaled horizontally (10 instances) and is
located behind a load balancer (ELB).
● Uses a MySQL database to store attributed events
and Kinesis to store organics.
14. Jampp Initial Systems: API
● PostgreSQL is used as a Data Warehouse database apart
from the use the bidder does.
● An API exposes the data for querying with a caching
layer.
● Fact tables are maintained with hourly, daily and
monthly granularity and high cardinality dimensions are
removed in large fact tables for data older than 15 days.
● Data is continually aggregated through an aggregation
process written in Python.
16. Emerging Needs
● Log forensics capabilities - as our systems and company
scale and we integrate with more outside systems.
● More historical and granular data for advanced analytics
and model training.
● The need to make the data readily available to other
systems outside from the traditional RDBMS arose. Some
of these systems are too demanding for RDBMS to
handle easily.
18. New System Characteristics
● The new system was based on Amazon Elastic Map
Reduce.
● Data imported hourly from RDBMSs with Sqoop.
● Logs are imported every 10 minutes from different
sources to S3 tables.
● Facebook PrestoDB and Apache Spark are used for
interactive log and analytics.
19. New System Characteristics
● Scalable storage and processing capabilities using
HDFS, YARN and Hive for ETLs and data storage.
● Connectors from different languages like Python,
Julia and Java/Scala.
● Data archiving in S3 for long term storage and
enabling other data processing technologies.
20. Aspects that needed improvement
● Data still imported in batch mode. Delay was larger
for MySQL data than with Python replicator.
● EMR not great for long running clusters.
● The EMR cluster is not designed with strong multi-
user capabilities. It is better to have multiple
clusters with few users than a big one with many.
● Data still being accumulated in RDBMSs (clicks,
installs, events).
21. Final stage of the evolution
● Real-time event processing architecture based on
best practices for stream processing in AWS.
● Uses Amazon Kinesis for streaming data storage
and Amazon Lambda for data processing.
● DynamoDB and Redis are used for temporal data
storage for enrichment and analytics.
● S3 gives us a Source of Truth for batch data
applications and Kinesis for stream processing.
23. Still, it isn’t perfect...
● There is no easy way to manage windows and out or
order data with Amazon Lambda.
● Consistency of DynamoDB and S3.
● Price of AWS managed services for events with large
numbers compared to custom maintained solutions.
● ACID guarantees of RDBMs are not an easy thing to part
with.
● SQL and indexes in RDBMs make forensics easier.
24. Benefits of the Evolution
● Enables the use of stream processing frameworks to
keep data as fresh as economically possible.
● Decouples data from processing to enable multiple Big
Data engines running on different clusters/
infrastructure.
● Easy on demand scaling given by AWS managed tools
like AWS Lambda, AWS DynamoDB and AWS EMR.
● Monitoring, logs and alerts managed by AWS
Cloudwatch.
26. Key Take Aways
● Ad tech is a technologically intensive market which
complies with the three Vs from Big Data.
● As the business’ data needs grows in complexity specialized
data systems need to be put in place.
● Using technologies that are meant to scale easily and are
managed by a third party can bring you peace of mind.
● Stream processing is fundamental in new Big Data Projects.
● There is currently no one tool that clearly fulfills all the
needs for scalable and correct stream processing.