Sebastian talks about how they use neo4j to protect data in business critical services running in production. The talk covers both high-level architecture, and detailed technical considerations.
Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor...Sebastian Verheughe
Learn how Telenor uses Neo4j to protect data in business critical services running in production. Sebastian will discuss lessons learned both with technology and our experience after running it in production for half a year, backing many of our mission critical services.
In-Flight Asset Management with Neo4j - Michael Wilmes @ GraphConnect London ...Neo4j
Being part of a flagship project that brings next-generation Inflight-Entertainment systems onto passenger aircrafts, Michael Wilmes tackles the operational aspects of managing IT systems in flight, on ground and anywhere in between. He will give insight on what key factors made Neo4j the database of choice during development of a custom tailored asset management application and how Neo4j was integrated using technologies like Spring, Thymeleaf, Bootstrap and D3.js.
Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor...Sebastian Verheughe
Learn how Telenor uses Neo4j to protect data in business critical services running in production. Sebastian will discuss lessons learned both with technology and our experience after running it in production for half a year, backing many of our mission critical services.
This presentation is an overview of a recent project where we assisted a large client with a complex migration of ECO data to PTC Windchill. We used an agile-like collaboration process to implement more functionality in 75% of the expected time.
Helixa uses serverless machine learning architectures to power an audience intelligence platform. It ingests large datasets and uses machine learning models to provide insights. Helixa's machine learning system is built on AWS serverless services like Lambda, Glue, Athena and S3. It features a data lake for storage, a feature store for preprocessed data, and uses techniques like map-reduce to parallelize tasks. Helixa aims to build scalable and cost-effective machine learning pipelines without having to manage servers.
This document provides a summary of the What's New in Kubernetes 1.22 presentation. The presentation covered 1) updates to the 1.23 release timeline with 3 releases now planned per year, 2) highlights from Kubernetes 1.22 including 56 total enhancements across several major themes, and 3) updates from various Special Interest Groups on new features and changes.
O po r enabling proof of retrievability in cloud computing with resource cons...Pvrtechnologies Nellore
OPoR is a new cloud storage scheme involving a cloud storage server and a cloud audit server. It aims to enable proof of retrievability for cloud storage with resource-constrained devices by outsourcing heavy computation of data tag generation to the cloud audit server. The cloud audit server pre-processes and uploads data on behalf of clients, eliminating their involvement in auditing and preprocessing. OPoR is proven secure against reset attacks while supporting efficient public verifiability and dynamic data operations. Future work may further reduce trust in the audit server and find more efficient solutions.
Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor...Sebastian Verheughe
Learn how Telenor uses Neo4j to protect data in business critical services running in production. Sebastian will discuss lessons learned both with technology and our experience after running it in production for half a year, backing many of our mission critical services.
In-Flight Asset Management with Neo4j - Michael Wilmes @ GraphConnect London ...Neo4j
Being part of a flagship project that brings next-generation Inflight-Entertainment systems onto passenger aircrafts, Michael Wilmes tackles the operational aspects of managing IT systems in flight, on ground and anywhere in between. He will give insight on what key factors made Neo4j the database of choice during development of a custom tailored asset management application and how Neo4j was integrated using technologies like Spring, Thymeleaf, Bootstrap and D3.js.
Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor...Sebastian Verheughe
Learn how Telenor uses Neo4j to protect data in business critical services running in production. Sebastian will discuss lessons learned both with technology and our experience after running it in production for half a year, backing many of our mission critical services.
This presentation is an overview of a recent project where we assisted a large client with a complex migration of ECO data to PTC Windchill. We used an agile-like collaboration process to implement more functionality in 75% of the expected time.
Helixa uses serverless machine learning architectures to power an audience intelligence platform. It ingests large datasets and uses machine learning models to provide insights. Helixa's machine learning system is built on AWS serverless services like Lambda, Glue, Athena and S3. It features a data lake for storage, a feature store for preprocessed data, and uses techniques like map-reduce to parallelize tasks. Helixa aims to build scalable and cost-effective machine learning pipelines without having to manage servers.
This document provides a summary of the What's New in Kubernetes 1.22 presentation. The presentation covered 1) updates to the 1.23 release timeline with 3 releases now planned per year, 2) highlights from Kubernetes 1.22 including 56 total enhancements across several major themes, and 3) updates from various Special Interest Groups on new features and changes.
O po r enabling proof of retrievability in cloud computing with resource cons...Pvrtechnologies Nellore
OPoR is a new cloud storage scheme involving a cloud storage server and a cloud audit server. It aims to enable proof of retrievability for cloud storage with resource-constrained devices by outsourcing heavy computation of data tag generation to the cloud audit server. The cloud audit server pre-processes and uploads data on behalf of clients, eliminating their involvement in auditing and preprocessing. OPoR is proven secure against reset attacks while supporting efficient public verifiability and dynamic data operations. Future work may further reduce trust in the audit server and find more efficient solutions.
Medium Inc. is an enterprise blockchain solution company based in South Korea. Products including MDL1.0 and MDL3.0 offer the industry's finest Hyperledger Fabric solution in terms of transaction speed and scalability.
This document summarizes a research paper that proposes a secure cloud-based mobile health monitoring system called CAM. The system aims to protect patient privacy and the intellectual property of healthcare service providers. It incorporates techniques like anonymous identity-based encryption and outsourced decryption to encrypt health data and shift decryption tasks to the cloud. The system also randomizes diagnostic programs and decision thresholds stored in the cloud to protect provider content. The goal is to allow resource-constrained providers to participate in mobile healthcare via cloud support while preserving security and privacy.
Score based deadline constrained workflow scheduling algorithm for cloud systemsijccsa
Cloud Computing is the latest and emerging trend in information technology domain. It offers utility- based
IT services to user over the Internet. Workflow scheduling is one of the major problems in cloud systems. A
good scheduling algorithm must minimize the execution time and cost of workflow application along with
QoS requirements of the user. In this paper we consider deadline as the major constraint and propose a
score based deadline constrained workflow scheduling algorithm that executes workflow within
manageable cost while meeting user defined deadline constraint. The algorithm uses the concept of score
which represents the capabilities of hardware resources. This score value is used while allocating
resources to various tasks of workflow application. The algorithm allocates those resources to workflow
application which are reliable and reduce the execution cost and complete the workflow application within
user specified deadline. The experimental results show that score based algorithm exhibits less execution
time and also reduces the failure rate of workflow application within manageable cost. All the simulations
have been done using CloudSim toolkit.
Ammar Murtaza is a Network Integration Manager with over 10 years of experience in radio access technologies including GSM, UMTS, LTE, and WiMAX. He has expertise in integration, optimization, and maintenance of these networks. Currently working at Nokia Networks, his previous experience includes roles at Alcatel-Lucent managing integration projects and teams in Pakistan and other countries. He holds an MBA and BSc in Electrical Engineering and several professional certifications in wireless networks.
The eBay Architecture: Striking a Balance between Site Stability, Feature Ve...Randy Shoup
The eBay architecture document discusses how eBay scales its platform to handle massive traffic while maintaining high availability and rapid feature development. Some key points are:
1) eBay uses horizontal scaling techniques like database sharding and separating functions across application servers to scale individual components.
2) The architecture emphasizes statelessness, caching, and minimizing database transactions to improve scalability and availability.
3) eBay evolved its architecture over several major versions to address scaling issues and allow for exponential growth in users and traffic over time.
VMworld 2013: Data In, Data Out and Data Protected VMworld
VMworld 2013
Mike Laverick, VMware
Roshni Pary, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
DEVNET-1140 InterCloud Mapreduce and Spark Workload Migration and Sharing: Fi...Cisco DevNet
Data gravity is a reality when dealing with massive amounts and globally distributed systems. Processing this data requires distributed analytics processing across InterCloud. In this presentation we will share our real world experience with storing, routing, and processing big data workloads on Cisco Cloud Services and Amazon Web Services clouds.
The document discusses Microservices architecture and compares it to monolithic architecture. It covers topics like infrastructure for Microservices including API gateways, service discovery, event buses. It also discusses design principles like domain-driven design, event sourcing and CQRS. Microservices are presented as a better approach as they allow independent deployments, scale independently and use multiple programming languages compared to monolithic applications.
Appraisly is a web-based employee performance review platform launched in October 2013. It aims to make the review process easier and more data-driven for both employees and managers. The founders are seeking £100,000 in seed funding to expand their customer base of 9 businesses and over 1,000 users. Their goal-oriented platform integrates with LinkedIn and provides customizable analytics dashboards and user-friendly reviews.
Neurotransmission, Neuropsychiatry, and Neuropharmacology 2013 dfsmithdfsmith
Neurotransmission, Neuropsychiatry, and Neuropharmacology 2013 Postgraduate Course at Aarhus University includes historical information on Masters of Neuropsychopharmacology
The document discusses computer form factors and cases. It states that form factors specify physical dimensions to ensure interchangeability and proper fit. Cases contain most computer components and come in various sizes depending on the motherboard form factor, such as towers, desktops, and pizza boxes. Cases house components like the power supply, drives, and motherboard according to standard layouts defined by form factors.
The document provides instructions for creating a lino print, including drawing a simple image, tracing it onto tracing paper and securing it to the lino block, placing the traced image onto the lino and transferring the lines with pencil, cutting out the lines while using a woodblock for safety, and then printing the lino block to create the print.
The document analyzes website analytics data from Google Analytics, Google Webmaster Tools, and AW Stats for the website www.advancedheatingwales.com between September and October 2012. The author summarizes that website visits have increased since a new site was launched in June 2012. While more visitors came from England than Wales initially, visitors from Wales viewed more pages and spent more time on the site. The number of unique visitors and visits has grown each month since July. A custom report showed more visitors to the contact page than to pages listing service rates, suggesting rates are not putting visitors off contacting the company.
Este documento define conceptos básicos sobre conjuntos. Explica que un conjunto es una colección de objetos considerados como un todo, cuyos elementos no se repiten. Los conjuntos se representan con letras mayúsculas y pueden contener cualquier tipo de objetos. También introduce conceptos como subconjuntos, operaciones entre conjuntos, el conjunto vacío, cardinalidad y relaciones entre elementos de conjuntos.
Equivalent decimals are decimals that represent the same number or amount. Zeros can be added to the right of a decimal number to create equivalent decimals. The document provides examples of equivalent decimals such as 0.3 and 0.30 as well as examples that are not equivalent like 0.9 and 0.09. It also prompts the reader to write two equivalent decimals for given numbers like 6.03, 0.700, and 8.90.
This document provides instructions for lino cutting in 3 parts:
1. Gather equipment and make a drawing, transferring the design onto tracing paper and then lino.
2. Use a V or U cutter to cut the design quite deep into the lino, keeping your hand behind the tool.
3. Apply ink to the lino with a roller, transfer it evenly to paper by tapping with a wooden spoon, then remove the paper to reveal the printed design.
This document summarizes how Neo4j was adopted by Gamesys, a major online gaming company, to gain insights into player relationships and improve their social games. It describes how Gamesys first used Neo4j in 2011 to build an internal social network and visualize connections between players. Over time, use of Neo4j spread to other teams within Gamesys to optimize the design of their massively multiplayer online role-playing game by analyzing the game's economy graph. This led to increased key performance indicators and reduced time to market.
This document provides an analysis of the website http://azmoon-flow.com/ and recommendations for optimizing it to rank in the top 10 search results for the keyword ""ابزار دقیق on Google USA. The analysis found that the website currently meets 76.5% of requirements for a top 10 ranking. It identifies elements that need improvement in areas like page optimization, link building, social optimization, and more. Implementing the recommended changes could help the website achieve a 95% score and potentially rank in the top 10 search results within 4 weeks.
Using Graph Databases in Real-time to Solve Resource Authorization at Telenor...Neo4j
The document summarizes how Telenor Norway, a subsidiary of Telenor Group generating $2 billion in mobile revenues annually, used a graph database to optimize resource authorization performance. Their previous relational database solution took 20 minutes to calculate user access and lacked scalability. By modeling authorization rules and data as a graph, traversal queries now take milliseconds, improving the user experience. The graph database improved performance 1000x, simplified complex business rules, and allows autonomous scaling to onboard more corporate customers.
The document outlines Neo4j's product strategy and roadmap. It discusses trends like increasing cloud adoption and the blending of transactional and analytical use cases. The roadmap focuses on cloud-first capabilities, ease of use for developers, trusted fundamentals of the database, and enabling AI through graph algorithms and knowledge graphs. Key announcements include new graph algorithms, change data capture for integration, autonomous clustering for scalability, and innovations in graph embeddings and generative AI integration.
Medium Inc. is an enterprise blockchain solution company based in South Korea. Products including MDL1.0 and MDL3.0 offer the industry's finest Hyperledger Fabric solution in terms of transaction speed and scalability.
This document summarizes a research paper that proposes a secure cloud-based mobile health monitoring system called CAM. The system aims to protect patient privacy and the intellectual property of healthcare service providers. It incorporates techniques like anonymous identity-based encryption and outsourced decryption to encrypt health data and shift decryption tasks to the cloud. The system also randomizes diagnostic programs and decision thresholds stored in the cloud to protect provider content. The goal is to allow resource-constrained providers to participate in mobile healthcare via cloud support while preserving security and privacy.
Score based deadline constrained workflow scheduling algorithm for cloud systemsijccsa
Cloud Computing is the latest and emerging trend in information technology domain. It offers utility- based
IT services to user over the Internet. Workflow scheduling is one of the major problems in cloud systems. A
good scheduling algorithm must minimize the execution time and cost of workflow application along with
QoS requirements of the user. In this paper we consider deadline as the major constraint and propose a
score based deadline constrained workflow scheduling algorithm that executes workflow within
manageable cost while meeting user defined deadline constraint. The algorithm uses the concept of score
which represents the capabilities of hardware resources. This score value is used while allocating
resources to various tasks of workflow application. The algorithm allocates those resources to workflow
application which are reliable and reduce the execution cost and complete the workflow application within
user specified deadline. The experimental results show that score based algorithm exhibits less execution
time and also reduces the failure rate of workflow application within manageable cost. All the simulations
have been done using CloudSim toolkit.
Ammar Murtaza is a Network Integration Manager with over 10 years of experience in radio access technologies including GSM, UMTS, LTE, and WiMAX. He has expertise in integration, optimization, and maintenance of these networks. Currently working at Nokia Networks, his previous experience includes roles at Alcatel-Lucent managing integration projects and teams in Pakistan and other countries. He holds an MBA and BSc in Electrical Engineering and several professional certifications in wireless networks.
The eBay Architecture: Striking a Balance between Site Stability, Feature Ve...Randy Shoup
The eBay architecture document discusses how eBay scales its platform to handle massive traffic while maintaining high availability and rapid feature development. Some key points are:
1) eBay uses horizontal scaling techniques like database sharding and separating functions across application servers to scale individual components.
2) The architecture emphasizes statelessness, caching, and minimizing database transactions to improve scalability and availability.
3) eBay evolved its architecture over several major versions to address scaling issues and allow for exponential growth in users and traffic over time.
VMworld 2013: Data In, Data Out and Data Protected VMworld
VMworld 2013
Mike Laverick, VMware
Roshni Pary, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
DEVNET-1140 InterCloud Mapreduce and Spark Workload Migration and Sharing: Fi...Cisco DevNet
Data gravity is a reality when dealing with massive amounts and globally distributed systems. Processing this data requires distributed analytics processing across InterCloud. In this presentation we will share our real world experience with storing, routing, and processing big data workloads on Cisco Cloud Services and Amazon Web Services clouds.
The document discusses Microservices architecture and compares it to monolithic architecture. It covers topics like infrastructure for Microservices including API gateways, service discovery, event buses. It also discusses design principles like domain-driven design, event sourcing and CQRS. Microservices are presented as a better approach as they allow independent deployments, scale independently and use multiple programming languages compared to monolithic applications.
Appraisly is a web-based employee performance review platform launched in October 2013. It aims to make the review process easier and more data-driven for both employees and managers. The founders are seeking £100,000 in seed funding to expand their customer base of 9 businesses and over 1,000 users. Their goal-oriented platform integrates with LinkedIn and provides customizable analytics dashboards and user-friendly reviews.
Neurotransmission, Neuropsychiatry, and Neuropharmacology 2013 dfsmithdfsmith
Neurotransmission, Neuropsychiatry, and Neuropharmacology 2013 Postgraduate Course at Aarhus University includes historical information on Masters of Neuropsychopharmacology
The document discusses computer form factors and cases. It states that form factors specify physical dimensions to ensure interchangeability and proper fit. Cases contain most computer components and come in various sizes depending on the motherboard form factor, such as towers, desktops, and pizza boxes. Cases house components like the power supply, drives, and motherboard according to standard layouts defined by form factors.
The document provides instructions for creating a lino print, including drawing a simple image, tracing it onto tracing paper and securing it to the lino block, placing the traced image onto the lino and transferring the lines with pencil, cutting out the lines while using a woodblock for safety, and then printing the lino block to create the print.
The document analyzes website analytics data from Google Analytics, Google Webmaster Tools, and AW Stats for the website www.advancedheatingwales.com between September and October 2012. The author summarizes that website visits have increased since a new site was launched in June 2012. While more visitors came from England than Wales initially, visitors from Wales viewed more pages and spent more time on the site. The number of unique visitors and visits has grown each month since July. A custom report showed more visitors to the contact page than to pages listing service rates, suggesting rates are not putting visitors off contacting the company.
Este documento define conceptos básicos sobre conjuntos. Explica que un conjunto es una colección de objetos considerados como un todo, cuyos elementos no se repiten. Los conjuntos se representan con letras mayúsculas y pueden contener cualquier tipo de objetos. También introduce conceptos como subconjuntos, operaciones entre conjuntos, el conjunto vacío, cardinalidad y relaciones entre elementos de conjuntos.
Equivalent decimals are decimals that represent the same number or amount. Zeros can be added to the right of a decimal number to create equivalent decimals. The document provides examples of equivalent decimals such as 0.3 and 0.30 as well as examples that are not equivalent like 0.9 and 0.09. It also prompts the reader to write two equivalent decimals for given numbers like 6.03, 0.700, and 8.90.
This document provides instructions for lino cutting in 3 parts:
1. Gather equipment and make a drawing, transferring the design onto tracing paper and then lino.
2. Use a V or U cutter to cut the design quite deep into the lino, keeping your hand behind the tool.
3. Apply ink to the lino with a roller, transfer it evenly to paper by tapping with a wooden spoon, then remove the paper to reveal the printed design.
This document summarizes how Neo4j was adopted by Gamesys, a major online gaming company, to gain insights into player relationships and improve their social games. It describes how Gamesys first used Neo4j in 2011 to build an internal social network and visualize connections between players. Over time, use of Neo4j spread to other teams within Gamesys to optimize the design of their massively multiplayer online role-playing game by analyzing the game's economy graph. This led to increased key performance indicators and reduced time to market.
This document provides an analysis of the website http://azmoon-flow.com/ and recommendations for optimizing it to rank in the top 10 search results for the keyword ""ابزار دقیق on Google USA. The analysis found that the website currently meets 76.5% of requirements for a top 10 ranking. It identifies elements that need improvement in areas like page optimization, link building, social optimization, and more. Implementing the recommended changes could help the website achieve a 95% score and potentially rank in the top 10 search results within 4 weeks.
Using Graph Databases in Real-time to Solve Resource Authorization at Telenor...Neo4j
The document summarizes how Telenor Norway, a subsidiary of Telenor Group generating $2 billion in mobile revenues annually, used a graph database to optimize resource authorization performance. Their previous relational database solution took 20 minutes to calculate user access and lacked scalability. By modeling authorization rules and data as a graph, traversal queries now take milliseconds, improving the user experience. The graph database improved performance 1000x, simplified complex business rules, and allows autonomous scaling to onboard more corporate customers.
The document outlines Neo4j's product strategy and roadmap. It discusses trends like increasing cloud adoption and the blending of transactional and analytical use cases. The roadmap focuses on cloud-first capabilities, ease of use for developers, trusted fundamentals of the database, and enabling AI through graph algorithms and knowledge graphs. Key announcements include new graph algorithms, change data capture for integration, autonomous clustering for scalability, and innovations in graph embeddings and generative AI integration.
Madhulatha has over 7 years of experience in information technology, specializing in data warehousing. She is proficient in ETL tools like Datastage and Talend, databases like Oracle and Teradata, and reporting tools like Qlik View. She seeks a challenging role in software development utilizing her skills in programming languages, data analysis and design, and project experience across various domains.
PLNOG 3: Tomasz Mikołajczyk - Data scalability. Why you should care?PROIDEA
This document discusses data scalability and introduces GridwiseTech, a vendor-independent scalable technology expert. It explains that IT systems are constantly growing due to increased users, applications, and data which can lead to infrastructure bottlenecks. To improve efficiency, GridwiseTech introduces scalability through distributed processing, load balancing, and scaling out data. It then summarizes a case study where GridwiseTech helped an electronic manufacturer scale its infrastructure to ensure scalability on each functional layer and achieve significant performance improvements like 10x faster data processing.
Some interesting case studies of how we helped our clients adopt DevOps. The cases cover various fields within DevOps space: CI/CD, Monitoring, Cloud Migration
This document provides a summary of the experience and skills of an IT professional named M Vamsikrishna from Hyderabad, India. It outlines his 3+ years of experience as an ETL Developer using IBM Infosphere Datastage and working on medium to large projects. It also lists his technical skills including Datastage, Teradata, SQL, and Linux. It provides details on some of the projects he has worked on, including roles and responsibilities, along with the technologies used.
This document contains the resume of Subbarao P, who has 3.5 years of experience working with WebMethods Integration Platform. He has expertise in building and maintaining B2B applications and EAI integrations using WebMethods, and experience with various adapters and protocols. The resume lists three projects he worked on, including maintaining Coca-Cola's global B2B integration infrastructure and developing new interfaces for an upgrade project.
This document contains a resume for Debarpan Mukherjee. It summarizes his professional experience as a System Engineer at Tata Consultancy Services for over 4 years, working on projects for clients like Intel and Deutsche Bank. It also lists his educational qualifications including a B.Tech in Computer Science and Engineering, and technical skills including Oracle PL/SQL, Unix, and data warehousing concepts.
Mayank Aggarwal has over 3.5 years of experience working as a System Administrator for TCS and previously as a Business Analyst for Tech Mahindra LTD and IBM India PVT LTD for clients like Airtel and Vodafone. He has extensive experience with technologies like Java, SQL, Oracle, DB2, UNIX/Linux, and software like JBoss, Tomcat, Apache server, and MQ. His objective is to work in challenging positions that provide opportunities for learning and contributing.
Maximizing Data Lake ROI with Data Virtualization: A Technical DemonstrationDenodo
Watch full webinar here: https://bit.ly/3ohtRqm
Companies with corporate data lakes also need a strategy for how to best integrate them with their overall data fabric. To take full advantage of a data lake, data architects must determine what data belongs in the Lake vs. other sources, how end users are going to find and connect to the data they need as well as the best way to leverage the processing power of the data lake. This webinar will provide you with a deep dive look at how the Denodo Platform for data virtualization enables companies to maximize their investment in their corporate data lake.
Watch on-demand this webinar to learn:
- How to create a logical data fabric with Denodo
- How to leverage the a data lake for MPP Acceleration and Summary Views
- How to leverage Presto with Denodo for file based data lakes (ie. S3, ADLS, HDFS, etc.)
- Rajendra Kumar Sahu is seeking a position that allows for continuous learning and professional development.
- He has over 4 years of experience implementing and developing Maximo 7, 7.5, and 7.6 using agile methodologies and DevOps processes.
- His skills include Maximo data migration, loading, integration, customization, automation scripting, and configuration. He is also experienced with databases like Oracle, DB2, and technologies like WebSphere.
Importing Large Sets of Content from Trusted Partners into your RepositoryBlueFish
The document discusses a solution developed by Blue Fish Development Group to help Solvay Pharmaceuticals import large amounts of content from external partners into its document repository. The solution leveraged existing migration tools to create a simple spreadsheet-based system that allowed partners to upload files without needing access to Solvay's repository. It streamlined the import process, ensured data accuracy, and provided reporting. The flexible design allowed reuse of components and reduced costs compared to custom development.
Grab: Building a Healthy Elasticsearch EcosystemElasticsearch
Grab began developing with Elasticsearch to help arrange team user access privileges. Discover how, through trial and error, Grab was able to go further to build a flexible and scalable Elasticsearch ecosystem.
Jitesh Kumar is a senior associate software analyst with over 3 years of experience in the IT industry. He has strong skills in software design, development, testing, technical support and system support, particularly for supply chain management systems. He has extensive experience with SQL Server 2005/2008/2012, programming languages like SQL, VB.Net, C#, and JavaScript. He has participated in several projects for clients like Dabur India, Reckitt Benckiser, Microsoft, Samsung and others developing and supporting distributor automation systems.
Presenting Data – An Alternative to the View ControlTeamstudio
In this webinar, Paul Della-Nebbia, an IBM Champion, will show how to implement a different alternative for displaying information from Domino views. Paul will cover how to use the Dojo Data Grid (included with XPages) to display a data grid that provides unique features like infinite scrolling, click to sort column headers, adjustable column widths, filtering, and the ability to drag and drop column headers to reorder. As the user scrolls through, the view data is retrieved as needed which improves performance and usability.
Yuriy Chapran - Building microservices.Yuriy Chapran
- Microservices are small, autonomous services that work together to form applications. Each service focuses on doing a single job and communicates through well-defined interfaces.
- There are several common design approaches for microservices including business capability services, API gateways, load balancers, message queues, caching, and circuit breakers. Choreography is preferred over orchestration.
- Implementing microservices provides benefits like independent deployability and scalability but also introduces complexity around distribution, eventual consistency, and operations.
Apricot2017 Request tracing in distributed environmentHieu LE ☁
This document discusses logging and request tracing in distributed environments. It begins by introducing the context of distributed systems like cloud computing. It then reviews the current logging solution of ELK and Graylog and identifies pros and cons. Key requirements for tracing are outlined, including the need for end-to-end debugging. Approaches for workflow-centric tracing are surveyed, including explicit metadata propagation, schema-based, and black-box tracing. Examples of Magpie and Zipkin are provided. The presentation concludes with a demo of request tracing in OpenStack using OSProfiler.
Contino Webinar - Migrating your Trading Workloads to the CloudBen Saunders
Benjamin Wootton, Contino Co-founder and CTO with a decade of IB experience, and Ben Saunders, experienced FIS DevOps consultant, will explore how our DevOps framework (Continuum) can help you move to the cloud as quickly and easily as possible.
This webinar covers:
The foundations for migrating trading apps and data to the cloud swiftly and safely
Ensuring compliance with regulatory controls
Architecting and optimizing your trading applications for optimal cloud performance
Integrating tools and processes to streamline app and data migration
1 Billion Events per Day, Israel 3rd Java Technology Day, June 22, 2009Moshe Kaplan
We presented at the Israeli 3rd Java Technology Day, the largest SUN Microsystems/MySQL event in israel. We presented here the essentials parts of building a real life web/enterprise system that needs to handle the performance needs of 1 billion events per day (a case study from the ad networks billing systems). We presented the adoption rate in the internet, Load Balancers (HAProxy, Apache, Radware, F5, Cisco), Web Servers, In Memory Database (IMDB inc. Memcached, Gigaspaces, Teracotta and Oracle Coherence) and finally Sharding (inc. Veritical, Static Horizontal and dynamic). A great example for a performance boosting architecture.
Similar to Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor - Sebastian Verheughe @ GraphConnect London 2013 (20)
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
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Using Graph Databases in Real-Time to Solve Resource Authorization at Telenor - Sebastian Verheughe @ GraphConnect London 2013
1. Using Graph Databases in Real-Time to
Solve Resource Authorization at Telenor
Graph Connect London – 19 Nov 2013
by Sebastian Verheughe
2. Telenor Norway
Subsidiary of the Telenor Group
~1 billion GBP in mobile revenues 2012
Sebastian Verheughe
Lead Developer for Neo4j solution
Coding Architect
3. Disclaimer
The presentation is not identical to the implementation
due to security reasons but shows how we have
modeled and solved the problem in general.
However, all presented data (numbers & charts) are
real, unfiltered and extracted from the production logs
5. Telenor Norway Middleware Services
Channel
Channel
used by 42 channels
calls 35 sub-systems
10,000 code classes
500 requests/second
20,000 orders/day
Backend
Backend
Channel
Channel
MOBILE
MW
Channel
Channel
Providing business logic
and data for all channels
in the mobile value chain
BUSINESS
LOGIC
& DATA
Backend
Handles users with
access to X00,000
resources
Backend
Backend
Backend
6. Our Problem
20 minutes to calculate all accessible resources
1500 lines of SQL to implement the authorization logic
“solved” by caching data going stale
and the solution did not scale…
7. Why a Graph Database?
Access
Parent Company
User: R. Branson
Which resources
does the user
have access to?
Part of Company
Sales
Finance Production
HR
Sub
The questions we wanted answered
required traversal of tree structures.
Tablet
Subscription
Owner
Sub
Tablet
Uses
Subscription
Phone
8. Tailored Read Model
The Model makes read queries
as simple and efficient as possible.
First find your questions
then model your graph
graph model
=
relational model
10. Conditional Rules
ACCESS is given with the following include parameters:
access to subsidiaries and access to content
Only find children of PARENT COMPANY
given access to subsidiaries is allowed
User
Only look at PART OF COMPANY
given access to content is allowed
Only look at SUBSCRIPTION OWNER
given access to content is allowed
12. Graph Algorithm
Prerequisite: The user node
1. Follow all ACCESS relationships and
read the access parameters on the relationship
2. Follow all PARENT COMPANY relationships given
access to subsidiaries is allowed
3. Follow all PART OF COMPANY relationships given
access to content is allowed
4. Follow all SUBSCRIPTION OWNER relationships given
access to content is allowed
13. Solution Value
1. Performance optimized from minutes to seconds.
2. Simplicity of writing and understanding business rules
for the query traversal.
3. Scalability by performance allowing us to onboard
more corporate customers (project business case)
Autonomous Service
with it’s own life-cycle and data repository.
14. Authorization Complexity
• Not a collection of isolated customer trees *
• Not all users of a customer have equal access
• Not a fixed schema, form or size for all
customers
• Real-time updated with customer & product
data
The data form a highly connected living graph
* Covered later in Technical Details
15. How we Started with Neo4j
1. Searched the internet for articles about graph
database and different solutions.
2. Downloaded and quickly prototyped the solution we
liked that matched our requirements (Neo4j).
3. Workshop with Neo4j and our project developers to
quickly gain competence and ensure design QA.
4. Solution QA with Neo4j before production and help
with performance issues / tuning.
16. Lessons Learned
• Choose a solution/technology that fits your problem
• New way of thinking – build competence in org.
• Profile your java code to make it really fast
• Don’t put everything into the graph (functional creep)
• Need to know how traversal works (e.g. shortest
path)
• Benchmark the graph to evaluate your traversal
speed
17. Alternative In-Memory RDBMS
Option 1: Use existing database
- Performance issues due to shared data / suboptimal
structure
- Complexity since SQL not designed for traversal
Option 2: Separate database
+ Might reach same performance as graph db
+ Familiar technology
- Complexity since SQL not designed for traversal
Decided to go with our instinct
Graph Database
18. Different Graph Structures
get all accessible subscriptions
2 000
1 000
1 700 ms
Company X: 147 000
750 ms
Company Y: 52 000
1300 ms
Company Z: 95 000
Data from test – repeated prod sampling gave ~2.4 sec for 215,000 subscriptions
19. Different Graph Structures
check access to single subscription
2 000
1 000
1 ms
Company X: 147 000
1 ms
Company Y: 52 000
1 ms
Company Z: 95 000
20. Production Performance
retrieve all accessible resources
RDBMS Disk
RDBMS Mem Cached
Graph In-Heap
Company X
12 min
18 sec
< 2 sec
Company Y
22 min
58 sec
< 2 sec
Company Z
3 min
15 sec
< 2 sec
Check single resource access
1 ms
No operational problems in production
25. Implementing the Algorithm
Lets look at the Neo4j Traversal Framework
Iterable<Node> getAccessibleResources(…) {
Evaluator myEvaluator = …
Expander myExpander = …
return Traversal.description()
.evaluator(myEvaluator)
.expander(myExpander)
.traverse(startNode).nodes();
}
26. Implementing the Algorithm
Evaluator is a simple filter, e.g. for Node
type
class MyEvaluator implements Evaluator {
public Evaluation evaluate(Path path) {
if <I am interested in this node>
return Evaluation.INCLUDE_AND_CONTINUE;
else
return Evaluation.EXCLUDE_AND_CONTINUE;
}
}
27. Implementing the Algorithm
The custom Expander contains business
rules!
class ResAuthExpander implements PathExpander<PathExpander> {
…
public … expand(Path path, BranchState<…> state) {
if (path.lastRelationship rel == ACCESS)
accToSub = rel.getProperty(ACCESS_TO_SUBSIDIARIES);
accToCont = rel.getProperty(ACCESS_TO_CONTENT);
state.set( getExpander(accToSub, accToCont) );
}
return state.get().expand(…)
}
Single expander class to control business
28. Implementing the Algorithm
Generates the valid relationships to traverse.
public getExpander(boolean accToSub, boolean accToCont) {
PathExpander exp = StandardExpander.DEFAULT.add(ACCESS,…);
if (accToSub)
exp.add(PARENT_COMPANY,…)
if (accToCont)
exp.add(PART_OF_COMPANY,…).add(SUBSCRIPTION_OWNER,…);
return exp;
}
}
29. U-Turn Strategy
4.
Access
User
Does the user
have access to
subscription X?
3.
5.
Up to find path quickly
Down to check access
6.
2.
7.
1.
8.
X
Subscription
Reversing the traversal increases performance from n/2 to
2d where n and d are tree size and depth (we went from 1s to
30. The Zigzag Problem
What if we also have reversed access to the subscription
payer?
User
Op
IT
E
d
Jo
Subscriptions
Solvable by adding state to the traversal (or check path)
31. The Many-to-Many Problem
The nodes Op & IT may be connected through many
subscriptions
Does the user
have access to
department Op?
Op
IT
Access
User
Subscription
Traversal becomes time consuming (e.g. M2M market)
However, we only needed to implement the rule for direct access to
sub.
32. Deployment View
• Two equal instances of Neo4j embedded in Tomcat
• Access through Java API due to need for custom logic
• Using Neo4j 1.8 without HA (did not like ZooKeeper)
Resource
Authorization
Neo4j
tx log
RDBMS
Message Queue
Resource
Authorization
Neo4j
33. Dual Model Cost
There are some drawbacks with dual models
also
• Not possible to simply join the ACL with resource
tables in the relational database - queries needed
redesign
• The complexity added by code and infrastructure
necessary to manage an additional model.
• Not ordinary competence (in Norway at least)
34. Unexplored Areas
Combining Access Control List & Graph
• Best of both worlds (simple logic, fast lookup)
Algorithm
–
–
–
–
Find all affected users when the graph is updated
Invalidate users access control list
Calculate all accessible resources for each user
Store result in users access control list
Could then skip the U-turn and many-to-many problem.
35. Was is worth it?
Yes!
The user experience is important in
Telenor
37. Web References
• Telenor Norway
• The Project - How NOSQL Paid off for
Telenor
• JavaWorld - Graphs for Security
Editor's Notes
Why: access to secret numbers, access to modify/delete subscriptions, possibility to send/receive messages
We use Neo4j for our business critical services, both customer/product services , but also operational services.A channel is client type, e.g. the web solution for corporate customer, or helpdesk solution, or app, and may consist of many clients
The project business case was based on a future point in time where we could not any more onboard any large corporate customers
Drawing on the white board the required logic made us understand that a graph database might be a good solution
Take the hit on write, and make read easy! (for us, read performance is the problem – not write performance)Also, don’t blindly copy tables/foreign keys into nodes and relationships – drop what’s not needed and remember that relationships may have properties in graph
RDBMS is still mastering the data as it is used in many different use-cases where that is beneficial.
TIME LEFT: 30 minutes (10 used)
The last part is important to us. It was really hard to extract the resource authorization out of the relational database, but not we can much more easy replace the current implementation with another one in the future if neccesary.
Production logs does not contain user data, so just one big organization was sampled to get production data for a specific customer
TIME LEFT: 20 minutes (20 used)Graphperformance based on test environment, see charts in the technical section for production numbers not specific for a unique customer
We only have detailed logs for a short while back – so we cannot review all data since production.First production two years ago with limited traffic, full production since spring 2013
We always continue, since we also have our custom expander. This way, we have a clean separation of concern in our code.We also have more advanced filters peaking around the node before it decides to include or exclude the node
This is the most important part of the code, the one place where we now are able to write down the business logic in a simple and natural way.Note that we only have ONE class containing the business rules independently of which use-case we are running.
The relationships and directions that are allowed to traverse given the different switch parameters.
This is possible since we have a tree graph. Demonstrates the importance of understanding how a graph works, because than you may greatly improve performance by smart traversal strategies.
TIME LEFT: 10 minutes (30 used)
Extra knowledge, such as which subscription you are