Introducing Apache Geode and Spring Data GemFireJohn Blum
This document introduces Apache Geode, an open source distributed in-memory data management platform. It discusses what Geode is, how it is implemented, and some key features like high availability, scalability and low latency. It also introduces Spring Data GemFire, which simplifies using Geode with Spring applications through features like repositories and caching. Finally, it outlines the project roadmap and opportunities to get involved in the Geode community.
An Introduction to Apache Geode (incubating)Anthony Baker
Geode is a data management platform that provides real-time, consistent access to data-intensive applications throughout widely distributed cloud architectures.
Geode pools memory (along with CPU, network and optionally local disk) across multiple processes to manage application objects and behavior. It uses dynamic replication and data partitioning techniques for high availability, improved performance, scalability, and fault tolerance. Geode is both a distributed data container and an in-memory data management system providing reliable asynchronous event notifications and guaranteed message delivery.
Pivotal GemFire has had a long and winding journey, starting in 2002, winding through VMware, Pivotal, and finding it's way to Apache in 2015. Companies using GemFire have deployed it in some of the most mission critical latency sensitive applications in their enterprises, making sure tickets are purchased in a timely fashion, hotel rooms are booked, trades are made, and credit card transactions are cleared. This presentation discusses:
- A brief history of GemFire
- Architecture and use cases
- Why we are taking GemFire Open Source
- Design philosophy and principles
But most importantly: how you can join this exciting community to work on the bleeding edge in-memory platform.
Building Scalable Applications using Pivotal Gemfire/Apache Geodeimcpune
This document discusses using Pivotal GemFire/Apache Geode to build scalable applications. It provides an overview of GemFire concepts like distributed caching and integration with traditional databases. It also presents a case study of how the Indian Railways used GemFire to improve performance and scalability of its online ticket booking system, allowing it to support over 200,000 concurrent purchases. The document concludes by outlining GemFire's roadmap and providing information on how to get involved with the GemFire community.
The document discusses the evolution of Pivotal Gemfire, now known as Apache Geode, from a proprietary product to an open source project. It provides an overview of Gemfire/Geode's capabilities including elastic scalability, high performance, and flexibility for developers. It also outlines Geode's role as a potential in-memory data exchange layer and integration point across modern data infrastructure technologies. Key aspects of Geode like its PDX serialization and asynchronous events are highlighted as building blocks that position it well for this role.
Using the awesome power of Spring Boot with Spring Data Geode to build highly-scalable, distributed Spring/Java applications using Apache Geode or Pivotal GemFire.
Slides for the Apache Geode Hands-on Meetup and Hackathon Announcement VMware Tanzu
This document provides an agenda for a hands-on introduction and hackathon kickoff for Apache Geode. The agenda includes details about the hackathon, an introduction to Apache Geode including its history and key features, a hands-on lab to build, run, and use Geode, and a Q&A session. It also outlines how to contribute to the Geode project through code, documentation, issue tracking, and mailing lists.
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XDVMware Tanzu
Companies across all industries and sizes are investing in strategic custom applications to enhance their competitive advantages. Developing these applications requires continuous improvement, based on insights gleaned from collecting and analyzing the data that they generate.
Big Data for high-performing, scalable and reliable applications requires a new set of tools and technologies. Pivotal GemFire is a distributed in-memory NoSQL data management solution for creating high-scale custom applications. Pivotal GemFire XD supports structured data as part the industry’s first Hadoop-based platform for creating closed loop analytics solutions – enabling businesses to continuously optimize real-time automation in their applications.
This document provides an overview of GemFire, an in-memory data grid that pools memory across processes to manage application data and behavior. Some key points:
- GemFire allows distributed applications to achieve low-latency data access through an in-memory shared cache. It supports features like caching, querying, transactions, and event notifications.
- Data in GemFire is organized into regions, which allow data to be stored across multiple servers without regard to location. Region types include replicated, partitioned, and local.
- The CAP theorem states that only two of three properties - consistency, availability, and partition tolerance - can be achieved in a distributed system. GemFire aims to balance availability and partition tolerance.
YARN Containerized Services: Fading The Lines Between On-Prem And CloudDataWorks Summit
Apache Hadoop YARN is the modern distributed operating system for big data applications. In Apache Hadoop 3.1.0, YARN added a service framework that supports long-running services. This new capability goes hand in hand with the recent improvements in YARN to support Docker containers. Together these features have made it significantly easier to bring new applications and services to YARN.
In this talk you will learn about YARN service framework, its new containerization capabilities and how it lays the foundation for a hybrid and uniform architecture for compute and storage across on-prem and multi-cloud environments. This will include examples highlighting how easy it is to bring applications to the YARN service framework as well as how to containerize applications.
Here's what to expect in this talk:
- Motivation for YARN service framework and containerization
- YARN service framework overview
- YARN service examples
- Containerization overview
- Containerization for Big Data and non Big Data workloads - wait that's everything
SpringCamp 2016 - Apache Geode 와 Spring Data GemfireJay Lee
The document discusses Apache Geode and Spring integration. It provides an overview of Apache Geode, an open source distributed in-memory database. It then covers Spring Data Gemfire, which allows using Geode with Spring's programming model. It also discusses using Spring Session to manage user sessions in a stateless manner by storing them in Geode. The presentation includes demos of integrating Geode with Spring applications.
Build your first Internet of Things app today with Open SourceApache Geode
This document provides an overview of Apache Geode, an in-memory data management platform. It discusses using Geode for high-performance and scalable applications that require fast access to critical datasets. Key concepts explained include regions, caching of data, and the use of functions to enable distributed processing across a Geode cluster. The document also mentions integrations with Spark and Cloud Foundry that allow persisting RDDs in Geode and exposing regions as RDDs.
1. The document discusses Project Geode, an open source distributed in-memory database for big data applications. It provides scale-out performance, consistent operations across nodes, high availability, powerful developer features, and easy administration of distributed nodes.
2. The document outlines Geode's architecture and roadmap. It also discusses why the project is being open sourced under Apache and describes some key use cases and customers of Geode.
3. The presentation includes a demo of Geode's capabilities including partitioning, queries, indexing, colocation, and transactions.
Apache Geode Meetup, Cork, Ireland at CITApache Geode
This document provides an introduction to Apache Geode (incubating), including:
- A brief history of Geode and why it was developed
- An overview of key Geode concepts such as regions, caching, and functions
- Examples of interesting large-scale use cases from companies like Indian Railways
- A demonstration of using Geode with Apache Spark and Spring XD for a stock prediction application
- Information on how to get involved with the Geode open source project community
Apache Geode is a distributed, memory-based data management platform that provides high performance, scalability, resiliency and continuous availability for data-oriented applications. It originated from Pivotal's open sourcing of Gemfire in 2015. Some key features of Geode include fast access to critical datasets, location-aware distributed data processing, and an event-driven data architecture. It has been used in many large-scale production systems and sees adoption rates increasing.
Cloud-Native PostgreSQL is a Kubernetes Operator for Postgres written by EDB entirely from scratch in the Go language and relying exclusively on the Kubernetes API.
This webinar covered:
- About DevOps & Cloud Native
- Overview of Cloud Native Postgres
- Storage for Postgres workloads in Kubernetes
- Start Using Cloud-Native Postgres
- Demo
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...DataWorks Summit
The document discusses Hive LLAP (Live Long and Process) as a high performance and cost-effective alternative to traditional Massively Parallel Processing (MPP) databases for querying large datasets on Hadoop. It describes Walmart's implementation of Hive LLAP on their data lake to improve query performance for business users. A proof-of-concept found Hive LLAP queries were up to 50% faster when using 15 nodes instead of 10, and it performed comparably or better than two MPP databases with similar or larger infrastructures. Walmart plans to further evaluate Hive LLAP on newer Hadoop distributions and technologies to improve availability and workload management.
Building Apps with Distributed In-Memory Computing Using Apache GeodePivotalOpenSourceHub
Slides from the Meetup Monday March 7, 2016 just before the beginning of #GeodeSummit, where we cover an introduction of the technology and community that is Apache Geode, the in-memory data grid.
In April 2015, Apache Geode (incubating) was born from Pivotal’s GemFire, the distributed in-memory database. However, the donation of over 1M LOC was just the beginning of the journey. In this talk we discuss how the GemFire engineering team has adapted their development infrastructure, processes, and culture to embrace the “Apache Way". We present lessons learned and best practices for new and incubating open source projects in areas of initial code submission, IP clearance, governance policies, code review, and community building. We discuss the challenges the team faced and how we changed internal communication and software design processes to a community-driven model. In particular, we highlight effective strategies for growing a project community and embracing new members. Finally, we show how changing to the open source model has increased both productivity and quality.
Hadoop {Submarine} Project: Running Deep Learning Workloads on YARNDataWorks Summit
Deep learning is useful for enterprises tasks in the field of speech recognition, image classification, AI chatbots and machine translation, just to name a few.
In order to train deep learning/machine learning models, applications such as TensorFlow / MXNet / Caffe / XGBoost can be leveraged. And sometimes these applications will be used together to solve different problems.
To make distributed deep learning/machine learning applications easily launched, managed, monitored. Hadoop community has introduced Submarine project along with other improvements such as first-class GPU support, container-DNS support, scheduling improvements, etc. These improvements make distributed deep learning/machine learning applications run on YARN as simple as running it locally, which can let machine-learning engineers focus on algorithms instead of worrying about underlying infrastructure. Also, YARN can better manage a shared cluster which runs deep learning/machine learning and other services/ETL jobs with these improvements.
In this session, we will take a closer look at Submarine project as well as other improvements and show how to run these deep learning workloads on YARN with demos. Audiences can start trying running these workloads on YARN after this talk.
Speakers:
Sunil Govindan, Staff Engineer
Hortonworks
Zhankun Tank, Staff Engineer
Hortonworks
Demand for cloud is through the roof. Cloud is turbo charging the Enterprise IT landscape with agility and flexibility. And now, discussions of cloud architecture dominate Enterprise IT. Cloud is enabling many ephemeral on-demand use cases which is a game changing opportunity for analytic workloads. But all of this comes with the challenges of running enterprise workloads in the cloud securely and with ease.
In this session, we will take you through Cloudbreak as a solution to simplify provisioning and managing enterprise workloads while providing an open and common experience for deploying workloads across clouds. We will discuss the challenges (and opportunities) to run enterprise workloads in the cloud and will go through a live demo of how the latest from Cloudbreak enables enterprises to easily and securely run Apache Hadoop. This includes deep-dive discussion on Ambari Blueprints, recipes, custom images, and enabling Kerberos -- which are all key capabilities for Enterprise deployments.
Speakers
Jeff Sposetti, VP Product Management, Hortonworks
Attila Kanto, Principal Engineer, Hortonworks
In this webinar, we will discuss different open-source models and different ways open source communities are organized. Understanding these key concepts is essential when selecting a strategic open-source platform. We will explore how the PostgreSQL community ensures that it stays independent, remains vibrant, drives innovation, and provides a reliable long-term platform for strategic IT projects.
This document provides an agenda for a hands-on introduction and hackathon kickoff for Apache Geode. The agenda includes details about the hackathon, an introduction to Apache Geode including its history, key features, and roadmap. It also covers hands-on labs for building, running, and clustering Geode as well as creating a first application. The document concludes with information on how to contribute to the Geode project.
Next Generation Scheduling for YARN and K8s: For Hybrid Cloud/On-prem Environ...DataWorks Summit
Scheduler of a container orchestration system, such as YARN and K8s, is a critical component that users rely on to plan resources and manage applications.
And if we assess where we are today, in YARN effectively it had two power schedulers (Fair and Capacity scheduler) and both serve many strong use cases in big data ecosystem. It can scale up to 50k nodes per cluster, and schedule 20k containers per second, and extremely efficient to manage batch workloads.
K8s default scheduler is an industry-proven solution to efficiently manage long-running services. As more big data apps are moving to K8s and cloud world, but many features like hierarchical queues to support multi-tenancy better, fairness resource sharing, and preemption, etc. are either missing or not mature enough at this point of time to support big data apps running on K8s.
At this point, there is no solution that exists to address the needs of having a unified resource scheduling experiences across platforms. That makes it extremely difficult to manage workloads running on different environments, from on-premise to cloud.
Hence evolving a common scheduler powered from YARN and K8s’s legacy capabilities and improving towards cloud use cases will focus more on use cases like:
Better bin-packing scheduling (and gang scheduling)
Autoscale up and shrink policy management
Effectively run batch workloads and services with clear SLA’s
In summary, we are improving core scheduling capabilities to manage both K8s and YARN cluster which is cloud aware as a separate initiative and above-mentioned cases will be the core focus of this initiative. More details of our works will be presented in this talk.
Apache Geode is an open source in-memory data grid that provides data distribution, replication and high availability. It can be used for caching, messaging and interactive queries. The presentation discusses Geode concepts like cache, region and member. It provides examples of how large companies use Geode for applications requiring real-time response, high concurrency and global data visibility. Geode's performance comes from minimizing data copying and contention through flexible consistency and partitioning. The project is now hosted by Apache and the community is encouraged to get involved through mailing lists, code contributions and example applications.
Highly available databases are essential to organizations depending on mission-critical, 24/7 access to data. Postgres is widely recognized as an excellent open-source database, with critical maturity and features that allow organizations to scale and achieve high availability.
This webinar will explore:
- Evolution of replication in Postgres
- Streaming replication
- Logical replication
- Replication for high availability
- Important high availability parameters
- Options to monitor high availability
- HA infrastructure to patch the database with minimal downtime
- EDB Postgres Failover Manager (EFM)
- EDB tools to create a highly available Postgres architecture
Deep Dive - Usage of on premises data gateway for hybrid integration scenariosSajith C P Nair
Presentation delivered by Sajith C P, Integration Architect at the 2017 Global Integration Bootcamp, Bangalore.
https://www.biztalk360.com/gib2017-india/#speakers[inline]/7/
In this session the speaker talked about ‘on-premises data gateway’ as a secure centralized gateway that can be used for accessing on premise data from various Azure Services. He took a deep dive on how it works, how to install and various methods to troubleshoot connectivity. He concluded the session with few demos of its use in Azure Logic App, Microsoft Flow, Power Apps and Power BI.
Using Apache Calcite for Enabling SQL and JDBC Access to Apache Geode and Oth...Christian Tzolov
When working with BigData & IoT systems we often feel the need for a Common Query Language. The system specific languages usually require longer adoption time and are harder to integrate within the existing stacks.
To fill this gap some NoSql vendors are building SQL access to their systems. Building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your NoSql system.
We will walk through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
In this session we review the design of the newly released off heap storage feature in Apache Geode, and discuss use cases and potential direction for additional capabilities of this feature.
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XDVMware Tanzu
Companies across all industries and sizes are investing in strategic custom applications to enhance their competitive advantages. Developing these applications requires continuous improvement, based on insights gleaned from collecting and analyzing the data that they generate.
Big Data for high-performing, scalable and reliable applications requires a new set of tools and technologies. Pivotal GemFire is a distributed in-memory NoSQL data management solution for creating high-scale custom applications. Pivotal GemFire XD supports structured data as part the industry’s first Hadoop-based platform for creating closed loop analytics solutions – enabling businesses to continuously optimize real-time automation in their applications.
This document provides an overview of GemFire, an in-memory data grid that pools memory across processes to manage application data and behavior. Some key points:
- GemFire allows distributed applications to achieve low-latency data access through an in-memory shared cache. It supports features like caching, querying, transactions, and event notifications.
- Data in GemFire is organized into regions, which allow data to be stored across multiple servers without regard to location. Region types include replicated, partitioned, and local.
- The CAP theorem states that only two of three properties - consistency, availability, and partition tolerance - can be achieved in a distributed system. GemFire aims to balance availability and partition tolerance.
YARN Containerized Services: Fading The Lines Between On-Prem And CloudDataWorks Summit
Apache Hadoop YARN is the modern distributed operating system for big data applications. In Apache Hadoop 3.1.0, YARN added a service framework that supports long-running services. This new capability goes hand in hand with the recent improvements in YARN to support Docker containers. Together these features have made it significantly easier to bring new applications and services to YARN.
In this talk you will learn about YARN service framework, its new containerization capabilities and how it lays the foundation for a hybrid and uniform architecture for compute and storage across on-prem and multi-cloud environments. This will include examples highlighting how easy it is to bring applications to the YARN service framework as well as how to containerize applications.
Here's what to expect in this talk:
- Motivation for YARN service framework and containerization
- YARN service framework overview
- YARN service examples
- Containerization overview
- Containerization for Big Data and non Big Data workloads - wait that's everything
SpringCamp 2016 - Apache Geode 와 Spring Data GemfireJay Lee
The document discusses Apache Geode and Spring integration. It provides an overview of Apache Geode, an open source distributed in-memory database. It then covers Spring Data Gemfire, which allows using Geode with Spring's programming model. It also discusses using Spring Session to manage user sessions in a stateless manner by storing them in Geode. The presentation includes demos of integrating Geode with Spring applications.
Build your first Internet of Things app today with Open SourceApache Geode
This document provides an overview of Apache Geode, an in-memory data management platform. It discusses using Geode for high-performance and scalable applications that require fast access to critical datasets. Key concepts explained include regions, caching of data, and the use of functions to enable distributed processing across a Geode cluster. The document also mentions integrations with Spark and Cloud Foundry that allow persisting RDDs in Geode and exposing regions as RDDs.
1. The document discusses Project Geode, an open source distributed in-memory database for big data applications. It provides scale-out performance, consistent operations across nodes, high availability, powerful developer features, and easy administration of distributed nodes.
2. The document outlines Geode's architecture and roadmap. It also discusses why the project is being open sourced under Apache and describes some key use cases and customers of Geode.
3. The presentation includes a demo of Geode's capabilities including partitioning, queries, indexing, colocation, and transactions.
Apache Geode Meetup, Cork, Ireland at CITApache Geode
This document provides an introduction to Apache Geode (incubating), including:
- A brief history of Geode and why it was developed
- An overview of key Geode concepts such as regions, caching, and functions
- Examples of interesting large-scale use cases from companies like Indian Railways
- A demonstration of using Geode with Apache Spark and Spring XD for a stock prediction application
- Information on how to get involved with the Geode open source project community
Apache Geode is a distributed, memory-based data management platform that provides high performance, scalability, resiliency and continuous availability for data-oriented applications. It originated from Pivotal's open sourcing of Gemfire in 2015. Some key features of Geode include fast access to critical datasets, location-aware distributed data processing, and an event-driven data architecture. It has been used in many large-scale production systems and sees adoption rates increasing.
Cloud-Native PostgreSQL is a Kubernetes Operator for Postgres written by EDB entirely from scratch in the Go language and relying exclusively on the Kubernetes API.
This webinar covered:
- About DevOps & Cloud Native
- Overview of Cloud Native Postgres
- Storage for Postgres workloads in Kubernetes
- Start Using Cloud-Native Postgres
- Demo
Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP ...DataWorks Summit
The document discusses Hive LLAP (Live Long and Process) as a high performance and cost-effective alternative to traditional Massively Parallel Processing (MPP) databases for querying large datasets on Hadoop. It describes Walmart's implementation of Hive LLAP on their data lake to improve query performance for business users. A proof-of-concept found Hive LLAP queries were up to 50% faster when using 15 nodes instead of 10, and it performed comparably or better than two MPP databases with similar or larger infrastructures. Walmart plans to further evaluate Hive LLAP on newer Hadoop distributions and technologies to improve availability and workload management.
Building Apps with Distributed In-Memory Computing Using Apache GeodePivotalOpenSourceHub
Slides from the Meetup Monday March 7, 2016 just before the beginning of #GeodeSummit, where we cover an introduction of the technology and community that is Apache Geode, the in-memory data grid.
In April 2015, Apache Geode (incubating) was born from Pivotal’s GemFire, the distributed in-memory database. However, the donation of over 1M LOC was just the beginning of the journey. In this talk we discuss how the GemFire engineering team has adapted their development infrastructure, processes, and culture to embrace the “Apache Way". We present lessons learned and best practices for new and incubating open source projects in areas of initial code submission, IP clearance, governance policies, code review, and community building. We discuss the challenges the team faced and how we changed internal communication and software design processes to a community-driven model. In particular, we highlight effective strategies for growing a project community and embracing new members. Finally, we show how changing to the open source model has increased both productivity and quality.
Hadoop {Submarine} Project: Running Deep Learning Workloads on YARNDataWorks Summit
Deep learning is useful for enterprises tasks in the field of speech recognition, image classification, AI chatbots and machine translation, just to name a few.
In order to train deep learning/machine learning models, applications such as TensorFlow / MXNet / Caffe / XGBoost can be leveraged. And sometimes these applications will be used together to solve different problems.
To make distributed deep learning/machine learning applications easily launched, managed, monitored. Hadoop community has introduced Submarine project along with other improvements such as first-class GPU support, container-DNS support, scheduling improvements, etc. These improvements make distributed deep learning/machine learning applications run on YARN as simple as running it locally, which can let machine-learning engineers focus on algorithms instead of worrying about underlying infrastructure. Also, YARN can better manage a shared cluster which runs deep learning/machine learning and other services/ETL jobs with these improvements.
In this session, we will take a closer look at Submarine project as well as other improvements and show how to run these deep learning workloads on YARN with demos. Audiences can start trying running these workloads on YARN after this talk.
Speakers:
Sunil Govindan, Staff Engineer
Hortonworks
Zhankun Tank, Staff Engineer
Hortonworks
Demand for cloud is through the roof. Cloud is turbo charging the Enterprise IT landscape with agility and flexibility. And now, discussions of cloud architecture dominate Enterprise IT. Cloud is enabling many ephemeral on-demand use cases which is a game changing opportunity for analytic workloads. But all of this comes with the challenges of running enterprise workloads in the cloud securely and with ease.
In this session, we will take you through Cloudbreak as a solution to simplify provisioning and managing enterprise workloads while providing an open and common experience for deploying workloads across clouds. We will discuss the challenges (and opportunities) to run enterprise workloads in the cloud and will go through a live demo of how the latest from Cloudbreak enables enterprises to easily and securely run Apache Hadoop. This includes deep-dive discussion on Ambari Blueprints, recipes, custom images, and enabling Kerberos -- which are all key capabilities for Enterprise deployments.
Speakers
Jeff Sposetti, VP Product Management, Hortonworks
Attila Kanto, Principal Engineer, Hortonworks
In this webinar, we will discuss different open-source models and different ways open source communities are organized. Understanding these key concepts is essential when selecting a strategic open-source platform. We will explore how the PostgreSQL community ensures that it stays independent, remains vibrant, drives innovation, and provides a reliable long-term platform for strategic IT projects.
This document provides an agenda for a hands-on introduction and hackathon kickoff for Apache Geode. The agenda includes details about the hackathon, an introduction to Apache Geode including its history, key features, and roadmap. It also covers hands-on labs for building, running, and clustering Geode as well as creating a first application. The document concludes with information on how to contribute to the Geode project.
Next Generation Scheduling for YARN and K8s: For Hybrid Cloud/On-prem Environ...DataWorks Summit
Scheduler of a container orchestration system, such as YARN and K8s, is a critical component that users rely on to plan resources and manage applications.
And if we assess where we are today, in YARN effectively it had two power schedulers (Fair and Capacity scheduler) and both serve many strong use cases in big data ecosystem. It can scale up to 50k nodes per cluster, and schedule 20k containers per second, and extremely efficient to manage batch workloads.
K8s default scheduler is an industry-proven solution to efficiently manage long-running services. As more big data apps are moving to K8s and cloud world, but many features like hierarchical queues to support multi-tenancy better, fairness resource sharing, and preemption, etc. are either missing or not mature enough at this point of time to support big data apps running on K8s.
At this point, there is no solution that exists to address the needs of having a unified resource scheduling experiences across platforms. That makes it extremely difficult to manage workloads running on different environments, from on-premise to cloud.
Hence evolving a common scheduler powered from YARN and K8s’s legacy capabilities and improving towards cloud use cases will focus more on use cases like:
Better bin-packing scheduling (and gang scheduling)
Autoscale up and shrink policy management
Effectively run batch workloads and services with clear SLA’s
In summary, we are improving core scheduling capabilities to manage both K8s and YARN cluster which is cloud aware as a separate initiative and above-mentioned cases will be the core focus of this initiative. More details of our works will be presented in this talk.
Apache Geode is an open source in-memory data grid that provides data distribution, replication and high availability. It can be used for caching, messaging and interactive queries. The presentation discusses Geode concepts like cache, region and member. It provides examples of how large companies use Geode for applications requiring real-time response, high concurrency and global data visibility. Geode's performance comes from minimizing data copying and contention through flexible consistency and partitioning. The project is now hosted by Apache and the community is encouraged to get involved through mailing lists, code contributions and example applications.
Highly available databases are essential to organizations depending on mission-critical, 24/7 access to data. Postgres is widely recognized as an excellent open-source database, with critical maturity and features that allow organizations to scale and achieve high availability.
This webinar will explore:
- Evolution of replication in Postgres
- Streaming replication
- Logical replication
- Replication for high availability
- Important high availability parameters
- Options to monitor high availability
- HA infrastructure to patch the database with minimal downtime
- EDB Postgres Failover Manager (EFM)
- EDB tools to create a highly available Postgres architecture
Deep Dive - Usage of on premises data gateway for hybrid integration scenariosSajith C P Nair
Presentation delivered by Sajith C P, Integration Architect at the 2017 Global Integration Bootcamp, Bangalore.
https://www.biztalk360.com/gib2017-india/#speakers[inline]/7/
In this session the speaker talked about ‘on-premises data gateway’ as a secure centralized gateway that can be used for accessing on premise data from various Azure Services. He took a deep dive on how it works, how to install and various methods to troubleshoot connectivity. He concluded the session with few demos of its use in Azure Logic App, Microsoft Flow, Power Apps and Power BI.
Using Apache Calcite for Enabling SQL and JDBC Access to Apache Geode and Oth...Christian Tzolov
When working with BigData & IoT systems we often feel the need for a Common Query Language. The system specific languages usually require longer adoption time and are harder to integrate within the existing stacks.
To fill this gap some NoSql vendors are building SQL access to their systems. Building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your NoSql system.
We will walk through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
In this session we review the design of the newly released off heap storage feature in Apache Geode, and discuss use cases and potential direction for additional capabilities of this feature.
This document discusses implementing a Redis adaptor using Apache Geode. It provides an overview of Redis data structures and commands, describes how Geode partitioned regions and indexes can be used to store and access Redis data, outlines advantages like scalability and high availability, and presents a roadmap for further development including supporting additional commands and performance optimization.
#GeodeSummit - Large Scale Fraud Detection using GemFire Integrated with Gree...PivotalOpenSourceHub
In this session we explore a case study of a large-scale government fraud detection program that prevents billions of dollars in fraudulent payments each year leveraging the beta release of the GemFire+Greenplum Connector, which is planned for release in GemFire 9. Topics will include an overview of the system architecture and a review of the new GemFire+Greenplum Connector features that simplify use cases requiring a blend of massively parallel database capabilities and accelerated in-memory data processing.
An Introduction to Apache Geode (incubating) - Geode is a data management platform that provides real-time, consistent access to data-intensive applications throughout widely distributed cloud architectures.
This talk provides an in-depth overview of the key concepts of Apache Calcite. It explores the Calcite catalog, parsing, validation, and optimization with various planners.
IoT Architecture - are traditional architectures good enough?Guido Schmutz
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
This is my Spring 2015 studio project. The 2nd Year Foundation Studio focused on developing an existing parking lot for UVa's sports facilities into a mixed use student housing area. My project focused on creating spaces for interaction between students and fans at the center of game day activity.
Este documento describe la estructura y procesos de la memoria humana. Explica que la memoria está compuesta de tres procesos básicos: codificación, almacenamiento y recuperación. Además, presenta el modelo de Atkinson-Shiffrin, el cual propone que la memoria está formada por tres almacenes: memoria sensorial, memoria de corto plazo y memoria de largo plazo. Finalmente, define la memoria operativa como la habilidad para almacenar y manipular información por períodos cortos de tiempo para apoyar
Muhammad Sufian is a Pakistani national holding a Master's degree from Virtual University of Pakistan seeking a job opportunity in the UAE. He has over 5 years of experience in roles like Assistant Admin/Store Keeper at Farhan Trading Corporation, Verification Officer at Tameer Microfinance Bank Ltd, and Assistant HR at Finca Microfinance Bank Ltd. His key skills include business development, sales, customer service, problem solving, and Microsoft Office.
Matthew Hartman has over 20 years of experience as a technician and workshop manager for various automotive brands such as VW, Honda, Audi, and Mazda. He is currently the manager of a team of 4 fitters at National Tyres Borehamwood. Previously, he managed a team of 10 technicians as manager of Kwik-fit in Bushey. Hartman is reliable, adaptable, and capable of working independently as well as part of a team. He has strong skills in diagnostics, maintenance, inventory systems, and leading others.
In this session we review the design of the current capabilities of the Spring Data GemFire API that supports Geode, and explore additional use cases and future direction that the Spring API and underlying Geode support might evolve.
Part 4: Custom Buildpacks and Data Services (Pivotal Cloud Platform Roadshow)VMware Tanzu
Custom Buildpacks & Data Services
The primary goals of this session are to:
Give an overview of the extension points available to Cloud Foundry users.
Provide a buildpack overview with a deep focus on the Java buildpack (my target audience has been Java conferences)
Provide an overview of service options, from user-provided to managed services, including an overview of the V2 Service Broker API.
Provide two hands-on lab experiences:
Java Buildpack Extension
via customization (add a new framework component)
via configuration (upgrade to Java 8)
Service Broker Development/Management
deploy a service broker for “HashMap as a Service (HaaSh).”
Register the broker, make the plan public.
create an instance of the HaaSh service
deploy a client app, bind to the service, and test it
Pivotal Cloud Platform Roadshow is coming to a city near you!
Join Pivotal technologists and learn how to build and deploy great software on a modern cloud platform. Find your city and register now http://bit.ly/1poA6PG
PHP is the top platform for building and modernizing IBM i applications. In this webinar, Erwin discusses how features of the application server can be leveraged to streamline the development process as well as fast-tracking the management of the PHP environment.
The document discusses different approaches to Platform as a Service (PaaS) and proposes building a PaaS on OpenStack to provide more control without complexity. It describes existing PaaS offerings like Google App Engine, Heroku, and Amazon Elastic Beanstalk that emphasize simplicity over control. The proposed OpenStack-based PaaS would use GigaSpaces technology to offer deployment, management, high availability, scalability, multi-tenancy, and monitoring capabilities while allowing flexibility to choose operating systems, middleware stacks, and other configuration options. It demonstrates deploying and managing a Cassandra service and discusses the current status of integrating GigaSpaces with OpenStack.
Building microservice for api with helidon and cicd pipelineDonghuKIM2
Eclispe Microprofile 기반 프레임워크인 Oracle Helidon에 대한 이해와 이를 활용한 마이크로 서비스 개발을 시연합니다.
• API 문서 검증, 서비스 빌드, 테스트 및 Oracle Kubernetes Engine에 배포하는 과정을 마이크로 서비스 CI/CD 서비스인 Oracle Wercker를 통해 자동화하는 과정을 시연합니다.
o Building microservice with Helidon MP and Helidon SE
o Validating API document against backend microservice with Dredd and Apiary
o Building CI/CD pipeline with Wercker and Oracle Kubernetes Engine
Express is a popular Node.js framework that provides scaffolding for building web applications in an organized manner. It allows adding middleware functions and templating engines like Dust.js to add dynamic content. The document demonstrates how to use the Request module to call an external weather API, parse the JSON response, and render the data in a Dust template to present weather information for different cities. It concludes by discussing deploying the application to production platforms like Bluemix.
The document discusses rapid prototyping of applications using Grails and SAP's HANA Cloud Platform (HCP). It provides an overview of HCP and Grails, then demonstrates building a simple web application for managing tech events using Grails on HCP. Key steps include generating a Grails domain class and controllers, modifying configuration for the HCP deployment, building and deploying the WAR file locally and to HCP, and accessing the application. Resources for further information on HCP, Grails, Groovy and the sample app are also listed.
Spring Data and In-Memory Data Management in ActionJohn Blum
This document provides an overview and agenda for a presentation on Spring Data and in-memory data management using Apache Geode. The presentation will cover Apache Geode functionality, integrating Geode with Spring frameworks, and examples of caching, events, data access and improvements in Geode and related projects. It lists caching, scalability, availability and other capabilities of Geode. The roadmap discusses upcoming versions of Spring Data GemFire and Geode as well as integration with Spring Boot, Session and other projects.
As seen at our meetup on 2017 Feb 21.
https://www.meetup.com/futureofdata-budapest/events/236853376/
Author: Marton Elek, Hortonworks
Oracle Coherence Strategy and Roadmap (OpenWorld, September 2014)jeckels
The Oracle Coherence strategy and roadmap session from OpenWorld 2014. Includes details on the 12.1.3 Cloud Application Foundation release (including WebLogic integration), a road map for the 12.2.1 release, and notable features including JCache (JSR-107) support, Memcached adapters, federated caching, recoverable caching, security enhancements, multitenancy support and more. As usual, all items and statements contained herein are subject to change based on slide 3 of this presentation.
Apigee Deploy Grunt Plugin - API Management Lifecycle Tool that makes your life easier by providing a JavaScript pluggable framework for API development.
Ram Ji Soni has over 11 years of experience developing web applications using Java/J2EE technologies such as Spring, Hibernate, and Hadoop. He currently works as a Technical Architect at AppTad Technologies where he designs applications using technologies like Spring and Hadoop. Previously he has worked as a Technical Lead at companies such as HCL Technologies and CSDC India, developing applications for clients in various domains. He has an MCA from Global Institute of Information Technology and a B.Sc. from B.K.D. Jhansi.
Timings API: Performance Assertion during the functional testingPetrosPlakogiannis
1. The Timings API allows performance metrics collected from the W3C Performance API in browsers to be stored and visualized using Elasticsearch and Kibana. It provides an API and clients for different languages to integrate performance measurements into functional tests.
2. The API works by injecting JavaScript code returned from a POST request into the browser after page loads and user actions. This code collects navigation timing data which is sent back to another POST request to be stored in Elasticsearch and compared to baselines.
3. To use the Timings API, the documentation recommends cloning the repo and running Docker Compose to start the API and Elasticsearch/Kibana services. Example code for the Java client is also provided.
The document provides an overview of Apache Cordova and the SAP Kapsel plugins:
- Apache Cordova allows web-based applications to access hardware features on mobile devices by running the application within a container. SAP Kapsel provides additional plugins for Cordova applications to interact with SAP Mobile Platform services.
- The Kapsel Logon plugin manages the onboarding and authentication process with SAP Mobile Platform/HCPms servers. It handles functions like initializing the login process, logging in users, and providing the application context after successful login.
- Other Kapsel plugins allow offline data access using OData, logging, application updates, push notifications, and encrypted storage. Using Kapsel plugins, a single
The document discusses various topics related to next generation technologies including data warehousing, business intelligence, enterprise applications, and cloud computing. It covers data modeling schemas, reporting dashboards, n-tier application architectures, integration of frameworks like Spring and Hibernate, and the evolution of Java EE technologies over time. Examples of topics are data warehousing that collects and analyzes data from multiple databases, reporting dashboards to extract business insights, and service-oriented architectures that enable cloud computing through web service calls.
David Wible has extensive experience developing Java applications using technologies like Spring, AngularJS, and MongoDB. He has worked on projects involving web applications, REST APIs, and SPA development. His career includes positions at Znalytics, Bridge2Solutions, McKesson, and Bank of America developing applications across various industries.
This document discusses plans for JAX-RS 2.1 (also known as JAX-RS.next), which aims to improve the JAX-RS specification. Some key areas of focus include improving performance through reactive programming and streams, better aligning with Java EE standards like CDI and JSON-B, filling gaps like server-sent events support, and continued evolution of the API. The overview outlines proposed features and the agenda for an upcoming presentation on the topic.
Java 9 New Features | Java Tutorial | What’s New in Java 9 | Java 9 Features ...Edureka!
The document discusses several new features in Java 9 including REPL JShell, collection factory methods that provide immutable collections, a new HTTP/2 client API, modularity with the Jigsaw project, and other minor features like Stream API improvements, multi-release JARs, and improved Javadoc. It provides details on each of these features and their benefits.
This document provides an overview of how to configure and deploy applications on Google App Engine. It discusses using an IDE like Eclipse with the GAE plugin, supported APIs, local testing, project setup, and configuration files for deployment descriptors, datastore indexes, cron jobs, task queues, and more. Other services covered include Google Users, Memcache, URL Fetch, mail, XMPP, Blobstore, and Images APIs. The document emphasizes testing locally first before deployment and references online documentation for additional information.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍
Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Massive Power Outage Hits Spain, Portugal, and France: Causes, Impact, and On...Aqusag Technologies
In late April 2025, a significant portion of Europe, particularly Spain, Portugal, and parts of southern France, experienced widespread, rolling power outages that continue to affect millions of residents, businesses, and infrastructure systems.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
Want to learn practical tips for designing systems that can scale efficiently without compromising speed?
Join us for a workshop where we’ll address these challenges head-on and explore how to architect low-latency systems using Rust. During this free interactive workshop oriented for developers, engineers, and architects, we’ll cover how Rust’s unique language features and the Tokio async runtime enable high-performance application development.
As you explore key principles of designing low-latency systems with Rust, you will learn how to:
- Create and compile a real-world app with Rust
- Connect the application to ScyllaDB (NoSQL data store)
- Negotiate tradeoffs related to data modeling and querying
- Manage and monitor the database for consistently low latencies
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungenpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/
HCL Nomad Web wird als die nächste Generation des HCL Notes-Clients gefeiert und bietet zahlreiche Vorteile, wie die Beseitigung des Bedarfs an Paketierung, Verteilung und Installation. Nomad Web-Client-Updates werden “automatisch” im Hintergrund installiert, was den administrativen Aufwand im Vergleich zu traditionellen HCL Notes-Clients erheblich reduziert. Allerdings stellt die Fehlerbehebung in Nomad Web im Vergleich zum Notes-Client einzigartige Herausforderungen dar.
Begleiten Sie Christoph und Marc, während sie demonstrieren, wie der Fehlerbehebungsprozess in HCL Nomad Web vereinfacht werden kann, um eine reibungslose und effiziente Benutzererfahrung zu gewährleisten.
In diesem Webinar werden wir effektive Strategien zur Diagnose und Lösung häufiger Probleme in HCL Nomad Web untersuchen, einschließlich
- Zugriff auf die Konsole
- Auffinden und Interpretieren von Protokolldateien
- Zugriff auf den Datenordner im Cache des Browsers (unter Verwendung von OPFS)
- Verständnis der Unterschiede zwischen Einzel- und Mehrbenutzerszenarien
- Nutzung der Client Clocking-Funktion
AI EngineHost Review: Revolutionary USA Datacenter-Based Hosting with NVIDIA ...SOFTTECHHUB
I started my online journey with several hosting services before stumbling upon Ai EngineHost. At first, the idea of paying one fee and getting lifetime access seemed too good to pass up. The platform is built on reliable US-based servers, ensuring your projects run at high speeds and remain safe. Let me take you step by step through its benefits and features as I explain why this hosting solution is a perfect fit for digital entrepreneurs.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
How Can I use the AI Hype in my Business Context?Daniel Lehner
𝙄𝙨 𝘼𝙄 𝙟𝙪𝙨𝙩 𝙝𝙮𝙥𝙚? 𝙊𝙧 𝙞𝙨 𝙞𝙩 𝙩𝙝𝙚 𝙜𝙖𝙢𝙚 𝙘𝙝𝙖𝙣𝙜𝙚𝙧 𝙮𝙤𝙪𝙧 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙣𝙚𝙚𝙙𝙨?
Everyone’s talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know 𝗵𝗼𝘄.
✅ What exactly should you ask to find real AI opportunities?
✅ Which AI techniques actually fit your business?
✅ Is your data even ready for AI?
If you’re not sure, you’re not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
#6: Key is to manage large quantities of data under extreme load with accuracy and resilience reliably.
Big Data == data lake (any and all data)
Fast Data == processing streams of events in real-time
All about… Data Access
#7: Scale Out rather than Scale Up
Throughput (or number of operations) increases as more nodes are added to the cluster
Data is stored in distributed, highly-concurrent, in-memory data structures to minimize context switching and contention
Data is replicated & partitioned for fast, predictable read/write throughput
#8: In a nutshell… under-the-hood Apache Geode is implemented…
Stores data in-memory with puts.
Stores data to disk (synchronously (default) or asynchronously) on persistence and overflow
Oplogs are append-only; compaction is necessary
HDFS is new and Geode can feed Apache Spark processing streams.
#12: Misconceptions about Spring…
Spring is a Web Application Framework
Spring’s programming model is unique and Spring uses it’s own conventions
Built on fundamental OO principles (POJO)
Software Design Patterns (IoC/DI, AOP) and…
Open Standards (OSS)
Apache Geode is a complex technology…
Too many configuration options and settings.
Inconsistent behavior between XML configuration (i.e. cache.xml) and API.