Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing.
Using ScyllaDB for Distribution of Game Assets in Unreal EngineScyllaDB
How Epic Games is using ScyllaDB for distribution of large game assets used by Unreal Engine across the world —enabling game developers to more quickly build great games.
Seastore: Next Generation Backing Store for CephScyllaDB
Ceph is an open source distributed file system addressing file, block, and object storage use cases. Next generation storage devices require a change in strategy, so the community has been developing crimson-osd, an eventual replacement for ceph-osd intended to minimize cpu overhead and improve throughput and latency. Seastore is a new backing store for crimson-osd targeted at emerging storage technologies including persistent memory and ZNS devices.
3 Things to Learn About:
-How Kudu is able to fill the analytic gap between HDFS and Apache HBase
-The trade-offs between real-time transactional access and fast analytic performance
-How Kudu provides an option to achieve fast scans and random access from a single API
One of the most important things you can do to improve the performance of your flash/SSDs with Aerospike is to properly prepare them. This Presentation goes through how to select, test, and prepare the drives so that you will get the best performance and lifetime out of them.
Best Practices for a Complete Postgres Enterprise Architecture SetupEDB
This presentation provides the details of a best-practice reference architecture for deploying Postgres into your enterprise for large scale OLTP solutions. It reviews how to put all the key pieces together to build a robust, reliable and cost-effective Postgres infrastructure, providing recommendations for configuration and deployment guidance.
This presentation reviews:
* Standard requirements for robust and reliable OTLP architecture
* How to use open source based Postgres Plus building blocks to meet those requirements
* High availability system design with streaming replication
* Backup with logical and physical backup recommendations and setup for point-in-time recovery
* Replication – single master and multi-master considerations
* Database infrastructure monitoring with alerts
* Managing and tuning your Postgres database configuration
To listen to the recording visit www.enterprisedb.com - Resources - Webcasts - On Demand webcasts
Email sales@enterprisedb.com with your questions about Postgres.
EMR 플랫폼 기반의 Spark 워크로드 실행 최적화 방안 - 정세웅, AWS 솔루션즈 아키텍트:: AWS Summit Online Ko...Amazon Web Services Korea
발표영상 다시보기: https://youtu.be/hPvBst9TPlI
S3 기반의 데이터레이크에서 대량의 데이터 변환과 처리에 사용될 수 있는 가장 대표적인 솔루션이 Apache Spark 입니다. EMR 플랫폼 환경에서 쉽게 적용 가능한 Apache Spark의 성능 향상 팁을 소개합니다. 또한 데이터의 레코드 레벨 업데이트, 리소스 확장, 권한 관리 및 모니터링과 같은 다양한 데이터 워크로드 관리 최적화 방안을 함께 살펴봅니다.
Using ScyllaDB for Distribution of Game Assets in Unreal EngineScyllaDB
How Epic Games is using ScyllaDB for distribution of large game assets used by Unreal Engine across the world —enabling game developers to more quickly build great games.
Seastore: Next Generation Backing Store for CephScyllaDB
Ceph is an open source distributed file system addressing file, block, and object storage use cases. Next generation storage devices require a change in strategy, so the community has been developing crimson-osd, an eventual replacement for ceph-osd intended to minimize cpu overhead and improve throughput and latency. Seastore is a new backing store for crimson-osd targeted at emerging storage technologies including persistent memory and ZNS devices.
3 Things to Learn About:
-How Kudu is able to fill the analytic gap between HDFS and Apache HBase
-The trade-offs between real-time transactional access and fast analytic performance
-How Kudu provides an option to achieve fast scans and random access from a single API
One of the most important things you can do to improve the performance of your flash/SSDs with Aerospike is to properly prepare them. This Presentation goes through how to select, test, and prepare the drives so that you will get the best performance and lifetime out of them.
Best Practices for a Complete Postgres Enterprise Architecture SetupEDB
This presentation provides the details of a best-practice reference architecture for deploying Postgres into your enterprise for large scale OLTP solutions. It reviews how to put all the key pieces together to build a robust, reliable and cost-effective Postgres infrastructure, providing recommendations for configuration and deployment guidance.
This presentation reviews:
* Standard requirements for robust and reliable OTLP architecture
* How to use open source based Postgres Plus building blocks to meet those requirements
* High availability system design with streaming replication
* Backup with logical and physical backup recommendations and setup for point-in-time recovery
* Replication – single master and multi-master considerations
* Database infrastructure monitoring with alerts
* Managing and tuning your Postgres database configuration
To listen to the recording visit www.enterprisedb.com - Resources - Webcasts - On Demand webcasts
Email sales@enterprisedb.com with your questions about Postgres.
EMR 플랫폼 기반의 Spark 워크로드 실행 최적화 방안 - 정세웅, AWS 솔루션즈 아키텍트:: AWS Summit Online Ko...Amazon Web Services Korea
발표영상 다시보기: https://youtu.be/hPvBst9TPlI
S3 기반의 데이터레이크에서 대량의 데이터 변환과 처리에 사용될 수 있는 가장 대표적인 솔루션이 Apache Spark 입니다. EMR 플랫폼 환경에서 쉽게 적용 가능한 Apache Spark의 성능 향상 팁을 소개합니다. 또한 데이터의 레코드 레벨 업데이트, 리소스 확장, 권한 관리 및 모니터링과 같은 다양한 데이터 워크로드 관리 최적화 방안을 함께 살펴봅니다.
NGINX ADC: Basics and Best Practices – EMEANGINX, Inc.
In this webinar we help you get started with NGINX, industry’s most ubiquitous web server and API gateway. We cover best practices for installing, configuring, and troubleshooting both NGINX Open Source and the enterprise-grade NGINX Plus. We provide insights about using NGINX Controller to manage your NGINX Plus instances.
Watch this webinar to learn:
- How to create NGINX configurations for web server, load balancer, etc.
- About improving performance using keepalives and other NGINX directives
- How the NGINX Controller Load Balancing Module can manage NGINX Plus instances at scale
- About augmenting your existing ADC with NGINX
https://www.nginx.com/resources/webinars/nginx-adc-basics-best-practices-emea/
– Elastic stack과 Data pipeline의 개념
– 데이터의 종류와 형태 / Document 데이터 모델링 (mapping, data type)
– 분산 데이터 저장소 관점에서의 Elasticsearch (index, shard & replica, segment)
https://learningspoons.com/course/detail/elastic-stack/
Introducing the Apache Flink Kubernetes OperatorFlink Forward
Flink Forward San Francisco 2022.
The Apache Flink Kubernetes Operator provides a consistent approach to manage Flink applications automatically, without any human interaction, by extending the Kubernetes API. Given the increasing adoption of Kubernetes based Flink deployments the community has been working on a Kubernetes native solution as part of Flink that can benefit from the rich experience of community members and ultimately make Flink easier to adopt. In this talk we give a technical introduction to the Flink Kubernetes Operator and demonstrate the core features and use-cases through in-depth examples."
by
Thomas Weise
Dremio, une architecture simple et performance pour votre data lakehouse.
Dans le monde de la donnée, Dremio, est inclassable ! C’est à la fois une plateforme de diffusion des données, un moteur SQL puissant basé sur Apache Arrow, Apache Calcite, Apache Parquet, un catalogue de données actif et aussi un Data Lakehouse ouvert ! Après avoir fait connaissance avec cette plateforme, il s’agira de préciser comment Dremio aide les organisations à relever les défis qui sont les leurs en matière de gestion et gouvernance des données facilitant l’exécution de leurs analyses dans le cloud (et/ou sur site) sans le coût, la complexité et le verrouillage des entrepôts de données.
HBaseCon2017 Community-Driven Graphs with JanusGraphHBaseCon
Graphs are well-suited for many use cases to express and process complex relationships among entities in enterprise and social contexts. Fueled by the growing interest in graphs, there are various graph databases and processing systems that dot the graph landscape. JanusGraph is a community-driven project that continues the legacy of Titan, a pioneer of open source graph databases. JanusGraph is a scalable graph database optimized for large scale transactional and analytical graph processing. In the session, we will introduce JanusGraph, which features full integration with the Apache TinkerPop graph stack. We will discuss JanusGraph's optimized storage model that relies on HBase for fast graph transversal and processing.
by Jason Plurad and Jing Chen He of IBM
CHERI Capability Hardware Enhanced RISC Instructions - Architecture and Softw...KTN
Presentation from the briefing event for ISCF Digital Security by Design competition: Technology Enabled Business-Led Demonstator Stage 1 Expression of Interest
Amazon EC2 provides a broad selection of instance types to deliver high performance for a diverse mix of applications. In this session, we overview the drivers of system performance and discuss in depth how Amazon EC2 instances deliver system performance while also providing elasticity and complete control over your infrastructure. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
NGINX ADC: Basics and Best Practices – EMEANGINX, Inc.
In this webinar we help you get started with NGINX, industry’s most ubiquitous web server and API gateway. We cover best practices for installing, configuring, and troubleshooting both NGINX Open Source and the enterprise-grade NGINX Plus. We provide insights about using NGINX Controller to manage your NGINX Plus instances.
Watch this webinar to learn:
- How to create NGINX configurations for web server, load balancer, etc.
- About improving performance using keepalives and other NGINX directives
- How the NGINX Controller Load Balancing Module can manage NGINX Plus instances at scale
- About augmenting your existing ADC with NGINX
https://www.nginx.com/resources/webinars/nginx-adc-basics-best-practices-emea/
– Elastic stack과 Data pipeline의 개념
– 데이터의 종류와 형태 / Document 데이터 모델링 (mapping, data type)
– 분산 데이터 저장소 관점에서의 Elasticsearch (index, shard & replica, segment)
https://learningspoons.com/course/detail/elastic-stack/
Introducing the Apache Flink Kubernetes OperatorFlink Forward
Flink Forward San Francisco 2022.
The Apache Flink Kubernetes Operator provides a consistent approach to manage Flink applications automatically, without any human interaction, by extending the Kubernetes API. Given the increasing adoption of Kubernetes based Flink deployments the community has been working on a Kubernetes native solution as part of Flink that can benefit from the rich experience of community members and ultimately make Flink easier to adopt. In this talk we give a technical introduction to the Flink Kubernetes Operator and demonstrate the core features and use-cases through in-depth examples."
by
Thomas Weise
Dremio, une architecture simple et performance pour votre data lakehouse.
Dans le monde de la donnée, Dremio, est inclassable ! C’est à la fois une plateforme de diffusion des données, un moteur SQL puissant basé sur Apache Arrow, Apache Calcite, Apache Parquet, un catalogue de données actif et aussi un Data Lakehouse ouvert ! Après avoir fait connaissance avec cette plateforme, il s’agira de préciser comment Dremio aide les organisations à relever les défis qui sont les leurs en matière de gestion et gouvernance des données facilitant l’exécution de leurs analyses dans le cloud (et/ou sur site) sans le coût, la complexité et le verrouillage des entrepôts de données.
HBaseCon2017 Community-Driven Graphs with JanusGraphHBaseCon
Graphs are well-suited for many use cases to express and process complex relationships among entities in enterprise and social contexts. Fueled by the growing interest in graphs, there are various graph databases and processing systems that dot the graph landscape. JanusGraph is a community-driven project that continues the legacy of Titan, a pioneer of open source graph databases. JanusGraph is a scalable graph database optimized for large scale transactional and analytical graph processing. In the session, we will introduce JanusGraph, which features full integration with the Apache TinkerPop graph stack. We will discuss JanusGraph's optimized storage model that relies on HBase for fast graph transversal and processing.
by Jason Plurad and Jing Chen He of IBM
CHERI Capability Hardware Enhanced RISC Instructions - Architecture and Softw...KTN
Presentation from the briefing event for ISCF Digital Security by Design competition: Technology Enabled Business-Led Demonstator Stage 1 Expression of Interest
Amazon EC2 provides a broad selection of instance types to deliver high performance for a diverse mix of applications. In this session, we overview the drivers of system performance and discuss in depth how Amazon EC2 instances deliver system performance while also providing elasticity and complete control over your infrastructure. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Intro to MongoDB
Get a jumpstart on MongoDB, use cases, and next steps for building your first app with Buzz Moschetti, MongoDB Enterprise Architect.
@BuzzMoschetti
Building Wall St Risk Systems with Apache GeodeAndre Langevin
In this talk from the 2016 Apache Geode Summit, I discuss how Geode forms the core of many Wall Street derivative risk solutions. By externalizing risk from trading systems, Geode-based solutions provide cross-product risk management at speeds suitable for automated hedging, while simultaneously eliminating the back office costs associated with traditional trading system based solutions.
Apache conbigdata2015 christiantzolov-federated sql on hadoop and beyond- lev...Christian Tzolov
Slides from ApacheCon BigData 2015 HAWQ/GEODE talk: http://sched.co/3zut
In the space of Big Data, two powerful data processing tools compliment each other. Namely HAWQ and Geode. HAWQ is a scalable OLAP SQL-on-Hadoop system, while Geode is OLTP like, in-memory data grid and event processing system. This presentation will show different integration approaches that allow integration and data exchange between HAWQ and Geode. Presentation will walking you through the implementation of the different Integration strategies demonstrating the power of combining various OSS technologies for processing bit and fast data. Presentation will touch upon OSS technologies like HAWQ, Geode, SpringXD, Hadoop and Spring Boot.
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.
Infinispan Servers: Beyond peer-to-peer data gridsGalder Zamarreño
In this session, Infinispan developer Galder Zamarreño will:
- Provide a brief introduction to peer-to-peer and client/server architectures.
- Describe the benefits of using Infinispan in a client/server mode, particularly in cloud-style environments.
- Introduce the audience to Infinispan’s selection of server modules that provide varied access methods: REST and WebSocket for HTTP access, Memcached protocol access and Hot Rod, Infinispan’s very own highly efficient binary protocol which supports smart-clients.
- Demonstrate an Infinispan client/server example showing how geographically separated Infinispan data grids could be linked together via Hot Rod client/server modules in order to provide different disaster recovery strategies.
Keeping Infinispan In Shape: Highly-Precise, Scalable Data EvictionGalder Zamarreño
Java Collections Framework represents one of the key building blocks of any Java application. Although the standard JDK devoted a lot of attention to developing a coherent and easy to use collections framework one important aspect remains overlooked – collection element eviction. Collection memory footprint can not grow indefinitely because we would eventually run out of memory; we either have to remove elements from a collection or somehow periodically evict certain elements according to a chosen eviction algorithm. Since day one eviction has been a key feature of Infinispan, and in the latest 4.1 release thanks to event update batching, Infinispan has reduced the eviction overhead to such an extent that it hardly affects application performance. On top of that, Infinispan implements LIRS, a more precise eviction algorithm compared to the traditional LRU, making it the first open source project to implement this revolutionary algorithm in the data grid space. In this session, Galder and Vladimir will present to the details behind these changes, performance measurements and third-party use case testimonies.
How to use the WAN Gateway feature of Apache Geode to implement multi-site and active-active failover, disaster recovery, and global scale applications.
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.
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.
IOT and System Platform From Concepts to CodeAndy Robinson
This presentation was delivered at the Wonderware Software Users Conference in 2015. In this presentation I cover fundamental concepts related to IOT as well as specific applications using Wonderware System Platform.
Flexible and Scalable Domain-Specific ArchitecturesNetronome
This talk introduces the concept of a domain-specific architecture (DSA) using the Netronome Flow Processor (NFP) as an example, it will cover the motivation, design and implementation. It will explore how this architecture’s flexibility has been leveraged in the past to handle unique platforms such as the Facebook Yosemite v2 Platform. Finally approaches for designing flexible chipsets in the future will be explored, including the value of system wide computational modeling.
Capital One Delivers Risk Insights in Real Time with Stream Processingconfluent
Speakers: Ravi Dubey, Senior Manager, Software Engineering, Capital One + Jeff Sharpe, Software Engineer, Capital One
Capital One supports interactions with real-time streaming transactional data using Apache Kafka®. Kafka helps deliver information to internal operation teams and bank tellers to assist with assessing risk and protect customers in a myriad of ways.
Inside the bank, Kafka allows Capital One to build a real-time system that takes advantage of modern data and cloud technologies without exposing customers to unnecessary data breaches, or violating privacy regulations. These examples demonstrate how a streaming platform enables Capital One to act on their visions faster and in a more scalable way through the Kafka solution, helping establish Capital One as an innovator in the banking space.
Join us for this online talk on lessons learned, best practices and technical patterns of Capital One’s deployment of Apache Kafka.
-Find out how Kafka delivers on a 5-second service-level agreement (SLA) for inside branch tellers.
-Learn how to combine and host data in-memory and prevent personally identifiable information (PII) violations of in-flight transactions.
-Understand how Capital One manages Kafka Docker containers using Kubernetes.
Watch the recording: https://videos.confluent.io/watch/6e6ukQNnmASwkf9Gkdhh69?.
We describe an application of CEP using a microservice-based streaming architecture. We use Drools business rule engine to apply rules in real time to an event stream from IoT traffic sensor data.
●Overall introduction of Ichiba
Introduction
●Redis Cluster in Rakuten Ichiba
How we use Redis Cluster in Rakuten Ichiba
●R Framework
The challenge of updating a legacy system sharing code between multiple teams, using an in-house developed library for the Rakuten Ichiba Frontend side.
●Rakuten Catalog Platform- Classification Approach for 280,000,000 Ichiba items -
1. Taxonomy Strategy(Analyze, Adoption)
2. Rakuten Catalog Platform Classification Ichiba Item data -> Taxonomy(Taxonomy(Genre/Tag/Attribute) management/development) -> Catalog(Product Master) -> Data governance system -> Data Processing Unit -> Auto classification(Item information/Image)
●How to reconstruct a million-user app
Describes why we decided to rewrite our app, what difficulties we faced and how we create the new structure to ensure it's flexible, stable and maintainable.
https://tech.rakuten.co.jp/
Rapid Application Design in Financial ServicesAerospike
Applying internet NoSQL design patterns to fraud detection and risk scoring, including when to use SQL and when to use NoSQL. The state of NAND Flash and NVMe is also discussed, as well as storage class memory futures with Intel's 3D Xpoint technology.
This talk was presented in LA at the following meetup:
http://www.meetup.com/scalela/events/233396111/
Druid provides sub-second query latency and Flink provides SQL on streams allowing rich transformation/enrichment of events as it happens. In this talk we will learn how Lyft
uses flink sql and druid together to support real time analytics.
Meetup: https://www.meetup.com/druidio/events/252515792/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
2. • Introduction
• Applications
• Architecture
• Features
• Performance
• Comparison with other products
10/25/2016 Confidential 2
Agenda
3. Introduction
10/25/2016 Confidential 3
• GemStone was the first project for smalltalk.
• First deployed as data engine in financial sector of wall street trading platform.
• Low latency, high concurrency data management system.
• In memory data management platform.
4. 10/25/2016 Confidential 4
Applications
• GIRE[Rapipago] a leading financial company in Argentina
• 19 million transactions per month
• Southwest Airlines
• Southwest.com is the world’s largest airline website by number of visitors.
• SBI, China Citic bank, Philips, BMW, Union bank, AllState,
6. Features
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• Distributed cloud architecture
• Pools memory, CPU, network resources, and optionally local disk
• Uses dynamic replication and data partitioning techniques
• Reliable asynchronous event notifications
• Thousands of concurrent distributed transaction(JTA complaint)
• Shared nothing persistence architecture
7. Features
10/25/2016 Confidential 7
• Asynchronous and synchronous cache update propagation. Delta propagation.
• Horizontally scalable
• Querying and Indexing
• Super fast write-ahead-logging (WAL) persistence
• Compression, eviction and expiration of data
• User functions
8. Features
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• HDFS Store – analytics job
• Rebalancing
• Integrated security : DATA_READ, DATA_WRITE, MONITOR, ADMIN [HTTP/HTTPS Authentication for REST ]
• JVSD – for analyzing the performance issues
• Off heap memory
• REST APIs
9. Internals of Geode
10/25/2016 Confidential 9
• Optimized caching layer, minimum thread and process switches.
• highly concurrent data structures to minimize contention points.
• Servers manage object graphs in serialized form, so less GC.
• Batch operation to the database.
• Uses TCP/IP, UDP UniCast and UDP MultiCast for member communication
• Serialization
10. How to use?
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Bucket 1
Bucket 2
Bucket 3
Bucket 2
Bucket 1
Bucket x
Client
Insert Person(UID, name, age)
Replicate
12. Performance
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• 10 times the read-and-write throughput of traditional disk-based databases.
• 4-40 times better performance of any application.
• 10million concurrent users
• Proven 10-100ms of latency in china railway system
14. Geode and Redis
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• GemFireRedisServer understand the redis protocol
• Keys represents region and namespace is with in OQL boundary.
• Redis is a single-threaded server. It is not designed to benefit from multiple CPU cores.
• Redis cluster you can scale up the number of data structures, not the data structures them selves (Partitioned
regions)
• Replication : slaves loses the data when they startup and sync with master. In Geode, you can have up to 3
redundant copies (for partitioned regions). Rep is async in redis.
• Persistence : AOF with keys and values in same file, on restart need to parse entire file.
• Redis uses Sentinel for managing HA.
• Network Partition
15. 10/25/2016 Confidential 15
Condition No pipelining and 1KB payloads Pipelining 16 requests at a time
Operation Redis GemFireRedis Redis GemFireRedis
SET 100894.94 87627.06 109277.91 109109.55
GET 103504.02 102988.52 113583.70 113523.87
INCR 99662.14 92251.61 1061300.75 575023.25
SADD 99559.35 92254.50 989119.69 644678.81
When to use
Application dev who need extremely fast processing and consistent data usage
Thousands of concurrent transaction
Access to the hundred tera bytes of operational data in memory
Real time analytics
Parallel compute grid
10 million user transactions a day.
VMware Gemfire (Java)
Oracle Coherence (Java)
Huawei Cache SDK over redis (Java)
Alachisoft NCache (.Net)
Gigaspaces XAP Elastic Caching Edition (Java)
Hazelcast (Java)
Scaleout StateServer (.Net)
Jboss (Redhat) Infinispan
deployment includes China National Railways that uses Geode to run railway ticketing for the entire country of China with a 10 node cluster that manages 2 terabytes of "hot data" in memory, and 10 backup nodes for high availability and elastic scale, latencies of 10-100 milliseconds. booked 2.5 million tickets per day on average. 2 terabytes or one month of ticket data in memory.
http://blog.gopivotal.com/case-studies-2/china-railway-corp-for-chinese-new-year-chunyun
Indian Railways system: 500,000 tickets daily, 40,000 concurrent users logged on to purchase tickets during tatkal hours. 200,000 concurrent users without impacting performance, Stable Performance to Book Approximately 150,000 Tickets Per Hour
http://pivotal.io/big-data/case-study/distributed-in-memory-data-management-solution
GIRE : billing, collection, payment and transaction processing via the web, call center, retail service centers
http://pivotal.io/big-data/case-study/enabling-real-time-transactions-and-analysis-gire
South West Airlines : http://pivotal.io/agile/case-study/transforming-it-and-development-for-the-worlds-largest-airline-website-southwest-airlines
Main Concepts and Components
Caches are an abstraction that describe a node in a Geode distributed system. Application architects can arrange these nodes in peer-to-peer or client/server topologies.
Within each cache, you define data regions. Data regions are analogous to tables in a relational database and manage data in a distributed fashion as name/value pairs. A replicated region stores identical copies of the data on each cache member of a distributed system. A partitioned region spreads the data among cache members. After the system is configured, client applications can access the distributed data in regions without knowledge of the underlying system architecture. You can define listeners to create notifications about when data has changed, and you can define expiration criteria to delete obsolete data in a region.
For large production systems, Geode provides locators. Locators provide both discovery and load balancing services. You configure clients with a list of locator services and the locators maintain a dynamic list of member servers. By default, Geode clients and servers use port 40404 and multicast to discover each other.
Functions can be Map Reduce, stored procedures, data parallel – member oriented
Listeners – CacheListener/CacheWriter, AsyncEventListener
Cluster:
Failure detection, dynamically scalable and network partition detection algorithms
Indexing:
RangeIndex - Uses a ConcurrentNavigableMap to store a key to store a RegionEntryToValuesMap. A RegionEntryToValuesMap is a map that uses the entry as the key and a struct as the value An example of the struct (notice the index iter naming associated with the struct and how the struct is a combination of portfolio, position): struct(index_iter1:Portfolio [ID=8 status=active type=type2 pkid=8 XYZ:Position secId=XYZ out=100.0 type=a id=7 mktValue=8.0, AOL:Position secId=AOL out=5000.0 type=a id=5 mktValue=6.0, APPL:Position secId=APPL out=6000.0 type=a id=6 mktValue=7.0, P1:Position secId=MSFT out=4000.0 type=a id=4 mktValue=5.0, P2:null ],index_iter2:Position secId=APPL out=6000.0 type=a id=6 mktValue=7.0)
CompactRangeIndex - A memory efficient but slightly restricted version of RangeIndex. Will be preferred by the engine over range index if possible. Uses a ConcurrentNavigableMap to store a key and value pair, where the value can either be a RegionEntry, an IndexElemArray that contains RegionEntries or a IndexConcurrentHashSet that contains RegionEntries. The ConcurrentNavigableMap also is passed a Comparator that allows Indexes to match across different Numeric types.
MapRangeIndex - This index contains a map where the key is the map key and the value is a range indexes. So for example an portfolio.positions'key' = 'IBM' The map range index would have a map with a key of 'key' and the value would be a range index. The range index would have another map where the key is 'IBM' and the value would be RegionEntryToValuesMap. The RegionEntryToValuesMap would be a map where the key is the entry itself and the value is 'IBM'
CompactMapRangeIndex - Similar to MapRangeIndex but a map of CompactRangeIndexes instead. Similar restrictions to those between CompactRangeIndex and RangeIndex.
HashIndex - Is a memory savings index that does not store key values and instead extracts the key from the object and uses the hash of the key to slot the RegionEntry into an array
PrimaryKeyIndex - The primary key index is a very lightweight index that hints to the query engine that it should do a a region.get(key)
PartitionedIndex - The partition index is a collection of indexes which are the buckets of the region.
Cluster:
Failure detection, dynamically scalable and network partition detection algorithms
Indexing:
RangeIndex - Uses a ConcurrentNavigableMap to store a key to store a RegionEntryToValuesMap. A RegionEntryToValuesMap is a map that uses the entry as the key and a struct as the value An example of the struct (notice the index iter naming associated with the struct and how the struct is a combination of portfolio, position): struct(index_iter1:Portfolio [ID=8 status=active type=type2 pkid=8 XYZ:Position secId=XYZ out=100.0 type=a id=7 mktValue=8.0, AOL:Position secId=AOL out=5000.0 type=a id=5 mktValue=6.0, APPL:Position secId=APPL out=6000.0 type=a id=6 mktValue=7.0, P1:Position secId=MSFT out=4000.0 type=a id=4 mktValue=5.0, P2:null ],index_iter2:Position secId=APPL out=6000.0 type=a id=6 mktValue=7.0)
CompactRangeIndex - A memory efficient but slightly restricted version of RangeIndex. Will be preferred by the engine over range index if possible. Uses a ConcurrentNavigableMap to store a key and value pair, where the value can either be a RegionEntry, an IndexElemArray that contains RegionEntries or a IndexConcurrentHashSet that contains RegionEntries. The ConcurrentNavigableMap also is passed a Comparator that allows Indexes to match across different Numeric types.
MapRangeIndex - This index contains a map where the key is the map key and the value is a range indexes. So for example an portfolio.positions'key' = 'IBM' The map range index would have a map with a key of 'key' and the value would be a range index. The range index would have another map where the key is 'IBM' and the value would be RegionEntryToValuesMap. The RegionEntryToValuesMap would be a map where the key is the entry itself and the value is 'IBM'
CompactMapRangeIndex - Similar to MapRangeIndex but a map of CompactRangeIndexes instead. Similar restrictions to those between CompactRangeIndex and RangeIndex.
HashIndex - Is a memory savings index that does not store key values and instead extracts the key from the object and uses the hash of the key to slot the RegionEntry into an array
PrimaryKeyIndex - The primary key index is a very lightweight index that hints to the query engine that it should do a a region.get(key)
PartitionedIndex - The partition index is a collection of indexes which are the buckets of the region.
HDFS:
Shared nothing architecture impacts full data scan for analytics
Region data persisted on HDFS could be accessed directly from HDFS without impacting cluster performance.
Supports high performance data reads
Supports HDFS data loader
Eviction logic is based on LRU
Secondary indexing is done on the data stored on HDFS store
Replicated HDFS regions
Each write operation will be cached in-memory and HDFS buffers simultaneously.
Offline access : provides tool to parse data in regions which can be done even when geode is offline
Rebalancing:
Currently manual
Decision to rebalance is based on the data distribution and max memory conf of node
As Geode monitors the data size, it can also automatically trigger rebalancing. Auto-balancing will redistribute data-load periodically and prevent conditions leading to failures.
Will be able to configure the threshold to consider it as off balanced
Avoid impact of auto rebalancing by scheduling
Turn off rebalancing
New node addition can be flagged for rebalancing
Geode partitions subscription management (interest registration and continuous queries) across server data stores, ensuring that a subscription is processed only once for all interested clients. The resulting improvements in CPU use and bandwidth utilization improve throughput and reduce latency for client subscriptions.
cause failures with Geode if attempting to create a key using non printable characters such as UTF-8 0x01, 0x02, etc
People are supposed to launch several Redis instances to scale out on several cores if needed. It is not really fair to compare one single Redis instance to a multi-threaded data store.
highly concurrent nature of Geode to make GemFireRedisServer concurrent. Each server instance will start 4 * (number of processor cores) threads for processing client requests, but this can be configured by system property where either one thread per connection can be created or a specific number of client handler threads can be requested.
With the sentinel approach, there is no real protection from network partition. The documentation mentions that write quorum should be used to guard against writing to a primary on the loosing side, however, since the replication is asynchronous, there will still be some amount of data loss. (This will be fixed with redis-cluster, no more need of sentinels for partition detection)
Geode has network partition detection built in. The loosing side servers will shutdown/fence themselves, so that clients cannot connect to them.
https://cwiki.apache.org/confluence/display/GEODE/Geode+Redis+Adapter