Final presentation at pfintern
Download as key, pdf0 likes1,778 views
This presentation discusses Sedue, an open source search engine. It describes Sedue's architecture including its distributed file system, query server, indexer, document repository, and archive manager. It also covers Sedue's real-time indexing capabilities and use of technologies like MongoDB for indexing and data storage.
1 of 31
Downloaded 11 times
Ad
Recommended
FreeDiscovery - information retrieval and e-Discovery in Python, Roman Yurchak
FreeDiscovery - information retrieval and e-Discovery in Python, Roman YurchakPôle Systematic Paris-Region This document provides an overview of the FreeDiscovery open source text mining and machine learning platform. It outlines the key components including text vectorization, supervised machine learning models for document scoring, clustering algorithms, a REST API, and deployment using Python web frameworks. The platform is designed to build search and text analytics applications for document collections.
企業・業界情報プラットフォームSPEEDAにおけるElasticsearchの活用
企業・業界情報プラットフォームSPEEDAにおけるElasticsearchの活用Akira Kitauchi 1. The document describes SPEEDA's use of Elasticsearch to improve search performance over their previous MySQL solution.
2. Key points include how Elasticsearch allowed them to handle a large volume of search queries for 1000 companies and 1000 motors with real-time performance.
3. It also discusses their use of Elasticsearch features like phrase prefix searching and analyzer configurations to support searches in both Japanese and English.
Elasticsearch 설치 및 기본 활용
Elasticsearch 설치 및 기본 활용종민 김 This document provides an overview and instructions for installing and using Elasticsearch. It describes how Elasticsearch is schema-free, distributed, uses JSON documents and the Lucene search engine. It also provides examples of indexing, searching, and configuring documents in Elasticsearch including shards, replicas, node names and master/data nodes.
Hadoop enhancements using next gen IA technologies
Hadoop enhancements using next gen IA technologiesBigdata Meetup Kochi Intel Enhancements on Hadoop platform
- HDFS
Erasure coding using ISA-L library
Encryption using AES-NI
-HBase
Go Big Cache
新浪微博开放平台Redis实战
新浪微博开放平台Redis实战mysqlops This document discusses Redis, a key-value store that is commonly used at Weibo for caching and storing relationship data. Redis has fast read and write performance but has limitations for large datasets due to its fully in-memory design. The document describes how Weibo uses Redis in conjunction with MySQL and Memcached to store relationship data for over 100 million users in a performant and scalable way. Challenges around high memory usage, persistence, and availability are also discussed.
HaaS: HPCC Systems as a Service – BYOD to the Cloud Party
HaaS: HPCC Systems as a Service – BYOD to the Cloud PartyHPCC Systems From the 2017 HPCC Systems Community Day:
Amazon Web Services (AWS) is the premier IaaS provider. It leads the pack by offering more and better services at lower prices. Furthermore, AWS continuously improves and innovates to stay in front. There are numerous reasons to use an IaaS for HPCC Systems instead of dedicated hardware, especially if the workload does not execute 24/7.
AWS has developed several features and tools for launching clusters. CloudFormation provides users a tool to make creating and managing an AWS resources much easier. Foremost it consists of a template (CFT) that defines resources required. The template is parameterizable and flexible so that a single CFT can launch an HPCC Systems cluster with an arbitrary number of nodes, various amount of memory per node, and other configuration options. Second, an Amazon Machine Image (AMI) contains the information needed to launch a compute node, with appropriate software, and configure it for a specific operation. We developed a CFT and an AMI for HPCC Systems.
Additionally, we developed a reference architecture for HPCC Systems in AWS. It is a typical N+1 cluster, N worker nodes and one node (or mode) for cluster wide services such as Dali. The architecture also has storage (i.e., EBS volumes) and networking (i.e., VPN) resources. Significant effort was expended to determine the best set of resources for HPCC Systems clusters.
Furthermore, we created a program to create and manage HPCC Systems clusters in AWS from the command line. This talk will present the tools we created. It also explains and justifies the reference architecture and many of the configuration options.
Vince Freeh
Associate Professor, North Carolina State University
Vincent W. Freeh is an associate professor of computer science at North Carolina State University. He received his Ph.D. in 1996 from the University of Arizona. His research focus is high-performance system software, with emphasis on filesystems, parallel and distributed systems, power-aware computing, and storage systems. Prof Freeh teaches courses in the above research areas as well as in compilers. He has more than 55 referred publications in numerous computer science conferences and scientific journals. He received an NSF CAREER Award and several IBM Faculty Development Awards. He was a captain in the US Army Corps of Engineers before entering graduate school for his MS.
Chin-Jung Hsu
PhD Student, North Carolina State University
Chin-Jung Hsu is a Ph.D. candidate in Computer Science at North Carolina State University. His primary research interests include distributed systems, storage systems, and performance optimization. He interned at NetApp and AT&T Research Lab, where he applied machine learning techniques to distributed storage systems for ensuring performance guarantees. Chin-Jung is currently working on how to efficiently run HPCC Systems applications on the public clouds such as AWS and Azure.
10gen MongoDB Video Presentation at WebGeek DevCup
10gen MongoDB Video Presentation at WebGeek DevCupWebGeek Philippines MongoDB is a document-oriented, horizontally scalable database. It uses dynamic schemas and stores data as JSON-like documents with optional schemas. MongoDB can be scaled out across multiple servers for high availability and large data volumes. Key features include replication, sharding, index types, atomic operations, embedded documents, and MapReduce.
MongoDB: a gentle, friendly overview
MongoDB: a gentle, friendly overviewAntonio Pintus This document provides a gentle, friendly overview of MongoDB. It discusses that MongoDB is a document-oriented, non-relational database that uses JSON-like documents with dynamic schemas. It also covers MongoDB's query language, indexing, data storage and querying, drivers like PyMongo, and how MongoDB provides horizontal scalability through sharding and replication. The document concludes by noting some common use cases for MongoDB and areas it is less suited for.
Innovation for red bull - product portfolio
Innovation for red bull - product portfolioOndrej Ďurják Red Bull is looking to introduce new healthy and active lifestyle products to expand its portfolio beyond energy drinks. The document proposes a "Red Bull Green" product line that would replace caffeine and sugars with natural boosters and complex carbohydrates to provide sustained energy without being unhealthy. It also suggests a champagne mixed with energy drink to enter the club and celebration markets. Exclusive limited edition products made from premium materials would help promote the brand to influencers and regular customers through exclusive marketing campaigns.
RED BULL FENTANYL HIGH
RED BULL FENTANYL HIGHOnodera Masato The document outlines a plan to raise awareness of the dangers of fentanyl by proposing a fictional new energy drink called "Red Bull Fentanyl High" that contains fentanyl. It would generate media coverage and outrage about the potential risks of such a product being consumed by the public. This fake marketing campaign and product release would ultimately be canceled in order to spread the message that fentanyl is an extremely dangerous drug.
Red Bull Media House : MOBILE GIVES YOU WINGS: FROM BRAND TO MEDIA, BIG SCRE...
Red Bull Media House : MOBILE GIVES YOU WINGS: FROM BRAND TO MEDIA, BIG SCRE...1min30 Présentation de la division media de Red Bull, faite le 4 décembre 2012 à Miami lors du MEF, disponible en téléchargement à l'adresse suivante: http://www.mefmobile.org/files/MEF%20Americas%20Presentations/RedBullMediaHouse.pdf
L'intérêt de cette présentation c'est quelle souligne comment une marque est complètement devenu un média au point d'en oublier presque son produit originel l'energy drink. En savoir plus sur cette réflexion sur le blog d'1min30. www.1min30.com
RED BULL MMA
RED BULL MMAMatías Almendras Muñoz El documento describe las diferentes áreas de negocio de Red Bull, incluyendo sus productos energéticos, su historia y énfasis en la presencia de marca. Explica que Red Bull comenzó como una bebida energética tailandesa que fue adaptada para el gusto europeo y ahora se vende en todo el mundo. Resalta que Red Bull es un excelente ejemplo de presencia de marca a través de eventos deportivos, televisión e Internet.
El mundo de redbull
El mundo de redbullinf4ab Red Bull patrocina varios deportes extremos como snowboarding, break dance, skateboarding, freestyle motocross, parkour, longboarding, BMX y salto base. Estos deportes incluyen deslizarse en tabla de snowboard, bailar break dance, patinar en skateboard, acrobacias en motocicleta, correr obstáculos eficientemente, patinar en longboard, hacer acrobacias en bicicleta y saltar desde objetos fijos con paracaídas.
Alex Koppel (Red Bull) iStrategy Presentation 
Alex Koppel (Red Bull) iStrategy Presentation iStrategy Here is Alex Koppel's presentation at iStrategy London in May. He outlines that Red Bull's whole strategy lies within content creation
Presentación de redbull
Presentación de redbullLaura Gomez Red Bull surge en 1982 como una bebida energética. En 1984, el fundador Dietrich Mateschitz se asocia con un empresario tailandés para adaptar la bebida al mercado europeo y luego lanzarla a nivel mundial en 1993. Red Bull busca posicionarse como una marca de estatus dirigida a jóvenes entre 15-30 años que buscan energía para actividades deportivas o de ocio. Compite con otras bebidas energéticas patrocinando eventos extremos para reforzar su imagen.
Presentacion red bull
Presentacion red bulldanimarquezarri Red Bull patrocina varios eventos deportivos como Red Bull X-Fighters de motocross, la Batalla de los Gallos de freestyle rap, y la competición de breakdancing Red Bull BC One. La compañía también promueve el fútbol freestyle, que involucra trucos creativos con el balón usando cualquier parte del cuerpo. Red Bull ha expandido su imperio más allá de las bebidas energéticas para incluir el entretenimiento y deportes extremos.
Presentación producto red bull | ¡Descarga el ppt =D!
Presentación producto red bull | ¡Descarga el ppt =D!Russel Q Se trata de una presentación del producto redbull y sus tintes polemicos o controversiales en su forma de venderse.
Redbull Presentation
Redbull PresentationCaroline Hinman Red Bull is an energy drink made of caffeine, taurine, B vitamins, sugars, and water. It is marketed as a drink that vitalizes the body and mind for activities like studying, work, sports, and going out. Red Bull dominates the energy drink market due to its strong brand identity and targeted promotions. It faces threats from health concerns over caffeine content and competition from organic drinks entering new markets. Red Bull's target market is ages 15-60, focusing on athletes, workers, and party-goers.
Red bull final
Red bull finalEdvinas Vyšniauskas Red Bull is the world's leading energy drink brand. It was founded in 1987 by Dietrich Mateschitz after he was inspired by Asian "tonic drinks". Red Bull uses a unique marketing strategy focused on word-of-mouth promotion and associating the brand with extreme sports and youth culture. Though it faces health concerns and high prices as weaknesses, Red Bull maintains a strong brand and market leadership position through extensive promotion and branding efforts.
Red Bull Final International Business
Red Bull Final International BusinessBinod Hyoju This presentation provides an overview and analysis of Red Bull's operations in India. The presentation is divided among group members who will each cover different aspects of Red Bull's business and marketing strategies in India. One member will discuss Red Bull's distribution network and 4P's approach with a focus on place. Another will cover Red Bull's corporate culture, promotion strategies, and general overview. Additional members will speak on topics like Red Bull's history, SWOT analysis, product information, target country selection, and HRM practices in India. The goal is to make the audience aware of how Red Bull functions in India and its management approach.
Redbull Laser - Product Strategy. 
Redbull Laser - Product Strategy. Vince Usher This is a product strategy I designed with some mates for a Uni Entrepreneurship project. It's a gritty representation of my thinking. I didn't have any hand in the finance side.
Needless to say my ideas and communications thereof, are a bit more polished these days. It's always good to look back and learn.
Psicología del Consumo: el Caso Red Bull
Psicología del Consumo: el Caso Red BullConsumer Truth - Insights & Planning El análisis completo de la Psicología del Consumidor de Red Bull fue realizado por alumnos de la especialidad de psicología social de la Pontificia Universidad Católica del Perú como parte del curso de Comportamiento del Consumidor. Los autores del trabajo fueron Alfredo Díaz, Estefanía Badillo, Natalia Santa Cruz y Humberto Porras. El trabajo fue realizado luego de realizar entrevistas en profundidad y grupos focales a consumidores regulares de Red Bull en la ciudad de Lima. El trabajo completo contiene información sobre los aspectos psicológicos detrás del consumo de Red Bull tales como la motivación y necesidades satisfechas, la personalidad del consumidor, la percepción e imagen de marca y los aspectos culturales relevantes. Desde aquí unas felicitaciones a Alfredo, Estefanía, Natalia y Humberto por su aporte! Más información: www.consumer-insights.blogspot.com
Red Bull Blue Ocean Strategy
Red Bull Blue Ocean StrategyRobert Wensley Red Bull Blue Ocean Strategy
Presentation explores Red Bull's strategic management and marketing tactics.
Presentation by Robert Wensley, Brett Lashley, Joanna Alencastro, Peter Jendrolovics
Harvard University, Summer 2011
Red Bull Presentation for Advertising
Red Bull Presentation for AdvertisingKamil Iqbal Assar Red Bull is an energy drink launched in 1987 that was derived from a Thai drink. It contains caffeine, taurine, B vitamins and sugar. It aims to increase performance, concentration, reaction speed and vigilance. It is popular with athletes, students, and those who need energy boosts. In Pakistan it is distributed through warehouses and sold at universities, parties and sports events. Competitors include other energy drinks and the company addresses challenges through reliable distributors and promotional activities.
Red Bull Marketing Campaign
Red Bull Marketing CampaignJessica Dunning Red Bull has 50% market share in Canada and $2 billion in global sales. It sponsors sports teams associated with its target consumers. Competitors like Monster Energy and Rockstar have gained market share. Red Bull's target market is young urban males aged 16-29 who participate in extreme sports. Its positioning is that Red Bull increases performance and concentration during stressful situations. Its advertising campaign will feature people in different roles where Red Bull helps their performance through print ads in magazines and billboards. The campaign aims to show Red Bull as versatile for different lifestyles and occupations while discouraging mixing it with alcohol.
PFIインターン最終発表
PFIインターン最終発表Shuzo Kashihara The document describes the architecture of a distributed search system. It involves a crawler that collects documents from different sources and stores them in a distributed file system. An indexer extracts keywords from the documents and adds them to an index. Users can search the index via a query server, with search results retrieved from the distributed document repository. The system uses distributed components like the file system and index to improve scalability.
Deployment
Deploymentrogerbodamer This document provides guidance on considerations for deploying MongoDB in production environments. It covers sizing hardware requirements for memory, CPU and I/O; installing and configuring MongoDB; using MongoDB on Amazon EC2; implementing security, backups, and durability; upgrading MongoDB versions; scaling deployments by sharding; and monitoring MongoDB performance.
Deployment Strategies (Mongo Austin)
Deployment Strategies (Mongo Austin)MongoDB The document discusses best practices for deploying MongoDB including sizing hardware with sufficient memory, CPU and I/O; using an appropriate operating system and filesystem; installing and upgrading MongoDB; ensuring durability with replication and backups; implementing security, monitoring performance with tools, and considerations for deploying on Amazon EC2.
KVSの性能、RDBMSのインデックス、更にMapReduceを併せ持つAll-in-One NoSQL: MongoDB 
KVSの性能、RDBMSのインデックス、更にMapReduceを併せ持つAll-in-One NoSQL: MongoDB Rakuten Group, Inc. 窪田 博昭、楽天株式会社
『Mongo Tokyo 2012』講演資料
Rakuten MongoDBの特徴、それを活かした使い方などを楽天・インフォシークニュースの事例などを通じて紹介します。
また機能、性能の検証結果、運用ノウハウ、弱点！の共有。PHPドライバのパッチなども公開します。
MongoDB Best Practices in AWS 
MongoDB Best Practices in AWS Chris Harris This document discusses MongoDB best practices for deploying MongoDB in AWS. It begins with terminology comparing MongoDB and relational databases. It then shows an example data model in SQL and how that same data would be modeled in MongoDB. The document discusses concepts like cursors, indexing, and sharding in MongoDB. It emphasizes the importance of sizing RAM and disk appropriately based on working set size and data access patterns. Finally, it covers replication in MongoDB and different replication set topologies that can be used in AWS for high availability and disaster recovery.
More Related Content
Viewers also liked (17)
Innovation for red bull - product portfolio
Innovation for red bull - product portfolioOndrej Ďurják Red Bull is looking to introduce new healthy and active lifestyle products to expand its portfolio beyond energy drinks. The document proposes a "Red Bull Green" product line that would replace caffeine and sugars with natural boosters and complex carbohydrates to provide sustained energy without being unhealthy. It also suggests a champagne mixed with energy drink to enter the club and celebration markets. Exclusive limited edition products made from premium materials would help promote the brand to influencers and regular customers through exclusive marketing campaigns.
RED BULL FENTANYL HIGH
RED BULL FENTANYL HIGHOnodera Masato The document outlines a plan to raise awareness of the dangers of fentanyl by proposing a fictional new energy drink called "Red Bull Fentanyl High" that contains fentanyl. It would generate media coverage and outrage about the potential risks of such a product being consumed by the public. This fake marketing campaign and product release would ultimately be canceled in order to spread the message that fentanyl is an extremely dangerous drug.
Red Bull Media House : MOBILE GIVES YOU WINGS: FROM BRAND TO MEDIA, BIG SCRE...
Red Bull Media House : MOBILE GIVES YOU WINGS: FROM BRAND TO MEDIA, BIG SCRE...1min30 Présentation de la division media de Red Bull, faite le 4 décembre 2012 à Miami lors du MEF, disponible en téléchargement à l'adresse suivante: http://www.mefmobile.org/files/MEF%20Americas%20Presentations/RedBullMediaHouse.pdf
L'intérêt de cette présentation c'est quelle souligne comment une marque est complètement devenu un média au point d'en oublier presque son produit originel l'energy drink. En savoir plus sur cette réflexion sur le blog d'1min30. www.1min30.com
RED BULL MMA
RED BULL MMAMatías Almendras Muñoz El documento describe las diferentes áreas de negocio de Red Bull, incluyendo sus productos energéticos, su historia y énfasis en la presencia de marca. Explica que Red Bull comenzó como una bebida energética tailandesa que fue adaptada para el gusto europeo y ahora se vende en todo el mundo. Resalta que Red Bull es un excelente ejemplo de presencia de marca a través de eventos deportivos, televisión e Internet.
El mundo de redbull
El mundo de redbullinf4ab Red Bull patrocina varios deportes extremos como snowboarding, break dance, skateboarding, freestyle motocross, parkour, longboarding, BMX y salto base. Estos deportes incluyen deslizarse en tabla de snowboard, bailar break dance, patinar en skateboard, acrobacias en motocicleta, correr obstáculos eficientemente, patinar en longboard, hacer acrobacias en bicicleta y saltar desde objetos fijos con paracaídas.
Alex Koppel (Red Bull) iStrategy Presentation
Alex Koppel (Red Bull) iStrategy Presentation iStrategy Here is Alex Koppel's presentation at iStrategy London in May. He outlines that Red Bull's whole strategy lies within content creation
Presentación de redbull
Presentación de redbullLaura Gomez Red Bull surge en 1982 como una bebida energética. En 1984, el fundador Dietrich Mateschitz se asocia con un empresario tailandés para adaptar la bebida al mercado europeo y luego lanzarla a nivel mundial en 1993. Red Bull busca posicionarse como una marca de estatus dirigida a jóvenes entre 15-30 años que buscan energía para actividades deportivas o de ocio. Compite con otras bebidas energéticas patrocinando eventos extremos para reforzar su imagen.
Presentacion red bull
Presentacion red bulldanimarquezarri Red Bull patrocina varios eventos deportivos como Red Bull X-Fighters de motocross, la Batalla de los Gallos de freestyle rap, y la competición de breakdancing Red Bull BC One. La compañía también promueve el fútbol freestyle, que involucra trucos creativos con el balón usando cualquier parte del cuerpo. Red Bull ha expandido su imperio más allá de las bebidas energéticas para incluir el entretenimiento y deportes extremos.
Presentación producto red bull | ¡Descarga el ppt =D!
Presentación producto red bull | ¡Descarga el ppt =D!Russel Q Se trata de una presentación del producto redbull y sus tintes polemicos o controversiales en su forma de venderse.
Redbull Presentation
Redbull PresentationCaroline Hinman Red Bull is an energy drink made of caffeine, taurine, B vitamins, sugars, and water. It is marketed as a drink that vitalizes the body and mind for activities like studying, work, sports, and going out. Red Bull dominates the energy drink market due to its strong brand identity and targeted promotions. It faces threats from health concerns over caffeine content and competition from organic drinks entering new markets. Red Bull's target market is ages 15-60, focusing on athletes, workers, and party-goers.
Red bull final
Red bull finalEdvinas Vyšniauskas Red Bull is the world's leading energy drink brand. It was founded in 1987 by Dietrich Mateschitz after he was inspired by Asian "tonic drinks". Red Bull uses a unique marketing strategy focused on word-of-mouth promotion and associating the brand with extreme sports and youth culture. Though it faces health concerns and high prices as weaknesses, Red Bull maintains a strong brand and market leadership position through extensive promotion and branding efforts.
Red Bull Final International Business
Red Bull Final International BusinessBinod Hyoju This presentation provides an overview and analysis of Red Bull's operations in India. The presentation is divided among group members who will each cover different aspects of Red Bull's business and marketing strategies in India. One member will discuss Red Bull's distribution network and 4P's approach with a focus on place. Another will cover Red Bull's corporate culture, promotion strategies, and general overview. Additional members will speak on topics like Red Bull's history, SWOT analysis, product information, target country selection, and HRM practices in India. The goal is to make the audience aware of how Red Bull functions in India and its management approach.
Redbull Laser - Product Strategy.
Redbull Laser - Product Strategy. Vince Usher This is a product strategy I designed with some mates for a Uni Entrepreneurship project. It's a gritty representation of my thinking. I didn't have any hand in the finance side.
Needless to say my ideas and communications thereof, are a bit more polished these days. It's always good to look back and learn.
Psicología del Consumo: el Caso Red Bull
Psicología del Consumo: el Caso Red BullConsumer Truth - Insights & Planning El análisis completo de la Psicología del Consumidor de Red Bull fue realizado por alumnos de la especialidad de psicología social de la Pontificia Universidad Católica del Perú como parte del curso de Comportamiento del Consumidor. Los autores del trabajo fueron Alfredo Díaz, Estefanía Badillo, Natalia Santa Cruz y Humberto Porras. El trabajo fue realizado luego de realizar entrevistas en profundidad y grupos focales a consumidores regulares de Red Bull en la ciudad de Lima. El trabajo completo contiene información sobre los aspectos psicológicos detrás del consumo de Red Bull tales como la motivación y necesidades satisfechas, la personalidad del consumidor, la percepción e imagen de marca y los aspectos culturales relevantes. Desde aquí unas felicitaciones a Alfredo, Estefanía, Natalia y Humberto por su aporte! Más información: www.consumer-insights.blogspot.com
Red Bull Blue Ocean Strategy
Red Bull Blue Ocean StrategyRobert Wensley Red Bull Blue Ocean Strategy
Presentation explores Red Bull's strategic management and marketing tactics.
Presentation by Robert Wensley, Brett Lashley, Joanna Alencastro, Peter Jendrolovics
Harvard University, Summer 2011
Red Bull Presentation for Advertising
Red Bull Presentation for AdvertisingKamil Iqbal Assar Red Bull is an energy drink launched in 1987 that was derived from a Thai drink. It contains caffeine, taurine, B vitamins and sugar. It aims to increase performance, concentration, reaction speed and vigilance. It is popular with athletes, students, and those who need energy boosts. In Pakistan it is distributed through warehouses and sold at universities, parties and sports events. Competitors include other energy drinks and the company addresses challenges through reliable distributors and promotional activities.
Red Bull Marketing Campaign
Red Bull Marketing CampaignJessica Dunning Red Bull has 50% market share in Canada and $2 billion in global sales. It sponsors sports teams associated with its target consumers. Competitors like Monster Energy and Rockstar have gained market share. Red Bull's target market is young urban males aged 16-29 who participate in extreme sports. Its positioning is that Red Bull increases performance and concentration during stressful situations. Its advertising campaign will feature people in different roles where Red Bull helps their performance through print ads in magazines and billboards. The campaign aims to show Red Bull as versatile for different lifestyles and occupations while discouraging mixing it with alcohol.
Similar to Final presentation at pfintern (20)
PFIインターン最終発表
PFIインターン最終発表Shuzo Kashihara The document describes the architecture of a distributed search system. It involves a crawler that collects documents from different sources and stores them in a distributed file system. An indexer extracts keywords from the documents and adds them to an index. Users can search the index via a query server, with search results retrieved from the distributed document repository. The system uses distributed components like the file system and index to improve scalability.
Deployment
Deploymentrogerbodamer This document provides guidance on considerations for deploying MongoDB in production environments. It covers sizing hardware requirements for memory, CPU and I/O; installing and configuring MongoDB; using MongoDB on Amazon EC2; implementing security, backups, and durability; upgrading MongoDB versions; scaling deployments by sharding; and monitoring MongoDB performance.
Deployment Strategies (Mongo Austin)
Deployment Strategies (Mongo Austin)MongoDB The document discusses best practices for deploying MongoDB including sizing hardware with sufficient memory, CPU and I/O; using an appropriate operating system and filesystem; installing and upgrading MongoDB; ensuring durability with replication and backups; implementing security, monitoring performance with tools, and considerations for deploying on Amazon EC2.
KVSの性能、RDBMSのインデックス、更にMapReduceを併せ持つAll-in-One NoSQL: MongoDB
KVSの性能、RDBMSのインデックス、更にMapReduceを併せ持つAll-in-One NoSQL: MongoDB Rakuten Group, Inc. 窪田 博昭、楽天株式会社
『Mongo Tokyo 2012』講演資料
Rakuten MongoDBの特徴、それを活かした使い方などを楽天・インフォシークニュースの事例などを通じて紹介します。
また機能、性能の検証結果、運用ノウハウ、弱点！の共有。PHPドライバのパッチなども公開します。
MongoDB Best Practices in AWS
MongoDB Best Practices in AWS Chris Harris This document discusses MongoDB best practices for deploying MongoDB in AWS. It begins with terminology comparing MongoDB and relational databases. It then shows an example data model in SQL and how that same data would be modeled in MongoDB. The document discusses concepts like cursors, indexing, and sharding in MongoDB. It emphasizes the importance of sizing RAM and disk appropriately based on working set size and data access patterns. Finally, it covers replication in MongoDB and different replication set topologies that can be used in AWS for high availability and disaster recovery.
MongoDB as Search Engine Repository @ MongoTokyo2011
MongoDB as Search Engine Repository @ MongoTokyo2011Preferred Networks MongoDB as Search Engine Repository @ MongoTokyo2011
http://www.10gen.com/conferences/mongotokyo2011
Deployment Strategy
Deployment StrategyMongoDB The document provides guidance on deploying MongoDB in production environments. It discusses sizing hardware requirements for memory, CPU, and disk I/O. It also covers installing and upgrading MongoDB, considerations for cloud platforms like EC2, security, backups, durability, scaling out, and monitoring. The focus is on performance optimization and ensuring data integrity and high availability.
Deployment Strategies
Deployment StrategiesMongoDB - The document provides guidance on deploying MongoDB including sizing hardware, installing and upgrading MongoDB, configuration considerations for EC2, security, backups, durability, scaling out, and monitoring. Key aspects discussed are profiling and indexing queries for performance, allocating sufficient memory, CPU and disk I/O, using 64-bit OSes, ext4/XFS filesystems, upgrading to even version numbers, and replicating for high availability and backups.
Splunk as a_big_data_platform_for_developers_spring_one2gx
Splunk as a_big_data_platform_for_developers_spring_one2gxDamien Dallimore Splunk is a platform for collecting, analyzing, and visualizing machine data. It provides real-time search and reporting across IT systems and infrastructure. Splunk indexes data from various sources without needing predefined schemas, and scales to handle large volumes of data from thousands of systems. The presentation covers an overview of the Splunk platform and how it can be used by developers, including custom visualizations, the Java SDK, and integrations with Spring applications.
MongoUK - Approaching 1 billion documents with MongoDB1 Billion Documents
MongoUK - Approaching 1 billion documents with MongoDB1 Billion DocumentsBoxed Ice Presentation given at the MongoUK conference on 18th June 2010 by David Mytton on approaching 1 billion documents in MongoDB.
Andy Parsons Pivotal June 2011
Andy Parsons Pivotal June 2011Andy Parsons This document discusses the author's experience using PostgreSQL in cloud environments over several startup projects. Some key lessons learned include: PostgreSQL can work well on Amazon EC2 but I/O performance is unpredictable; redundant infrastructure is still vulnerable to failures so regular backups are important; and query performance relies heavily on buffer cache warming so load testing is critical. Overall the document emphasizes being pragmatic with PostgreSQL, focusing on architecture choices that minimize I/O bottlenecks and failures in the cloud.
DynamoDB and Amazon Cloudsearch
DynamoDB and Amazon CloudsearchMichael Bohlig The document summarizes an Amazon CloudSearch meetup event in San Francisco on March 28, 2013. The agenda included talks on using CloudSearch with DynamoDB, EDU search applications, tuning search queries, and a user talk from SnapGuide. Jon Handler from Amazon presented on how to integrate CloudSearch with DynamoDB by uploading DynamoDB data to a CloudSearch domain, configuring fields, and keeping the services in sync.
Hadoop World 2011: The Hadoop Stack - Then, Now and in the Future - Eli Colli...
Hadoop World 2011: The Hadoop Stack - Then, Now and in the Future - Eli Colli...Cloudera, Inc. Many people refer to Apache Hadoop as their system of choice for big data management but few actually use just Apache Hadoop. Hadoop has become a proxy for a much larger system which has HDFS storage at its core. The Apache Hadoop based "big data stack" has changed dramatically over the past 24 months and will chance even more over the next 24 months. This talk talks about trends in the evolution of the Hadoop stack, change in architecture and changes in the kinds of use cases that are supported. It will also talk about the role of interoperability and cohesion in the Apache Hadoop stack and the role of Apache Bigtop in this regard.
MongoDB - Who, What & Where!
MongoDB - Who, What & Where!Mark Hillick Introductory presentation to MongoDB - who, what, where & usage in the cloud :) Yes, the #cloud!!!
Brown Bag session with UCD.
BP-3 Taking Your Bulk Content Ingestions to the Next Level
BP-3 Taking Your Bulk Content Ingestions to the Next LevelAlfresco Software Learn about the Alfresco Bulk Filesystem Import Tool, a community developed extension to Alfresco that provides a high performance bulk import feature. Discover how different tuning parameters affect import performance, and learn how to determine the optimum configuration for your Alfresco environment.
Monitoring MongoDB (MongoSV)
Monitoring MongoDB (MongoSV)Boxed Ice Presentation by David Mytton about monitoring MongoDB at the MongoSV conference 3rd Dec 2010.
A full blog series covering everything in this presentation is at http://blog.boxedice.com/mongodb-monitoring/
Operationalizing MongoDB at AOL
Operationalizing MongoDB at AOLradiocats The document summarizes Michael DelNegro's work operationalizing MongoDB at AOL over several years. Key aspects included establishing standards for host setup, directory structure, and build scripts; implementing monitoring with Argus, Nagios, and MMS; performing backups; sharing information through internal documentation; and addressing challenges like requiring more planning from developers. The operationalization effort helped support over 500 MongoDB servers storing data for 30+ active projects at AOL.
MongoDC 2012: "Operationalizing" MongoDB@AOL
MongoDC 2012: "Operationalizing" MongoDB@AOLMongoDB The document summarizes Michael DelNegro's work operationalizing MongoDB at AOL after it was initially introduced by a developer in 2010. Key aspects of the operationalization effort included establishing standards for host setup, directory structure, and build scripts; implementing monitoring with Argus, Nagios, and MMS; performing backups; sharing information through internal documentation; and addressing challenges like requiring more planning from developers. The operationalization operation helped support over 500 MongoDB servers in production running a variety of projects and applications at AOL.
Monitoring MongoDB (MongoUK)
Monitoring MongoDB (MongoUK)Boxed Ice Presentation by David Mytton about monitoring MongoDB at the MongoUK conference 21st Mar 2011.
A full blog series covering everything in this presentation is at http://blog.boxedice.com/mongodb-monitoring/
视觉中国的MongoDB应用实践(QConBeijing2011)
视觉中国的MongoDB应用实践(QConBeijing2011)Night Sailer This document summarizes MongoDB, an open-source document database. It discusses MongoDB's features such as schema flexibility, replication, auto-sharding, and GridFS for storing files. It also provides tips on monitoring MongoDB performance and configuration best practices for replication, sharding, and GridFS.
Ad
More from N Masahiro (20)
Fluentd Project Intro at Kubecon 2019 EU
Fluentd Project Intro at Kubecon 2019 EUN Masahiro Fluentd is a streaming data collector that can unify logging and metrics collection. It collects data from sources using input plugins, processes and filters the data, and outputs it to destinations using output plugins. It is commonly used for container logging, collecting logs from files or Docker and adding metadata before outputting to Elasticsearch or other targets. Fluentbit is a lightweight version of Fluentd that is better suited for edge collection and forwarding logs to a Fluentd instance for aggregation.
Fluentd v1 and future at techtalk
Fluentd v1 and future at techtalkN Masahiro Fluentd v1 provides major improvements over v0.12 including nanosecond event time resolution, multi-core support, Windows support, and new plugin APIs. The new plugin APIs provide well-controlled lifecycles and integrate all output plugins. v1 also introduces a server engine based supervisor, dynamic buffering capabilities, and various plugin helpers. While maintaining compatibility with v0.12 plugins, v1 focuses on ease of use, stability, performance and flexibility.
Fluentd and Distributed Logging at Kubecon
Fluentd and Distributed Logging at KubeconN Masahiro This document discusses distributed logging with containers using Fluentd. It notes the challenges of logging in container environments where logs need to be collected from ephemeral containers and transferred to storage. It introduces Fluentd as a flexible data collection tool that can collect logs from containers using various plugins and methods like log drivers, shared volumes, and application libraries. The document discusses deployment patterns for Fluentd including using it for source-side aggregation to buffer and transfer logs more efficiently and for destination-side aggregation to scale log storage.
Fluentd v1.0 in a nutshell
Fluentd v1.0 in a nutshellN Masahiro This document summarizes Fluentd v1.0 and provides details about its new features and release plan. It notes that Fluentd v1.0 will provide stable APIs and compatibility with previous versions while improving plugin APIs, adding Windows and multicore support, and increasing event time resolution to nanoseconds. The release is planned for Q3 2017 to allow feedback on v0.14 before finalizing v1.0 features.
Fluentd v1.0 in a nutshell
Fluentd v1.0 in a nutshellN Masahiro This document summarizes the key features and changes between versions of Fluentd, an open source data collector.
The main points are:
1) Fluentd v1.0 will provide stable APIs and features while remaining compatible with v0.12 and v0.14. It will have no breaking API changes.
2) New features in v0.14 and v1.0 include nanosecond time resolution, multi-core processing, Windows support, improved buffering and plugins, and more.
3) The goals for v1.0 include migrating more plugins to the new APIs, addressing issues, and improving documentation. A release is planned for Q2 2017.
Presto changes
Presto changesN Masahiro This document summarizes recent updates to Presto, including new data types, connectors, syntax, features, functions, and configuration options. Some key additions are support for DECIMAL, VARCHAR, and new data types; connectors for Redis, MongoDB, and other data sources; transaction support; and a variety of new SQL functions for strings, dates, aggregation, and more. Upcoming work includes prepared statements, a new optimizer, and other performance and usability improvements.
Fluentd at HKOScon
Fluentd at HKOSconN Masahiro Fluentd is a data collector for unified logging that provides a robust core and plugins. It allows for reliable data transfer through error handling and retries. The core handles common concerns like parsing, buffering, and writing data, while plugins handle input, output, and other use cases. Fluentd has a pluggable architecture and processes data through a pipeline of input, parser, filter, buffer, formatter, and output plugins.
Fluentd v0.14 Overview
Fluentd v0.14 OverviewN Masahiro The document summarizes the key features and changes in Fluentd v0.14, including new plugin APIs, plugin storage and helpers, time with nanosecond resolution, a ServerEngine-based supervisor for Windows support, and plans for symmetric multi-core processing, a counter API, and TLS/authentication in future versions. It also benchmarks some performance improvements and outlines the roadmap for Treasure Agent 3.0 based on Fluentd v0.14.
Fluentd and Kafka
Fluentd and KafkaN Masahiro This document discusses using Fluentd to collect streaming data from Apache Kafka. It presents two approaches: 1) the fluent-plugin-kafka plugin which allows Fluentd to act as a producer and consumer of Kafka topics, and 2) the kafka-fluentd-consumer project which runs a standalone Kafka consumer that sends events to Fluentd. Configuration examples are provided for both approaches. The document concludes that Fluentd and Kafka can work together to build reliable and flexible data pipelines.
fluent-plugin-beats at Elasticsearch meetup #14
fluent-plugin-beats at Elasticsearch meetup #14N Masahiro This document summarizes a presentation about integrating Fluentd with Elastic Beats data collection agents. It introduces Beats, their supported outputs including Elasticsearch, and various third party Beats. It then describes the fluent-plugin-beats plugin which allows Fluentd to receive events from Beats using the Lumberjack protocol. An example configuration is shown. Performance tests show Fluentd can handle over 100,000 events/sec while Filebeat is slower at 18,000 events/sec. The conclusion is that Beats are useful for collection but Fluentd may be better than Filebeat for high volume environments.
Dive into Fluentd plugin v0.12
Dive into Fluentd plugin v0.12N Masahiro Update version of Fluentd plugin guide : http://www.slideshare.net/repeatedly/fluentd-meetup-dive-into-fluent-plugin
Technologies for Data Analytics Platform
Technologies for Data Analytics PlatformN Masahiro This document discusses building a data analytics platform and summarizes various technologies that can be used. It begins by outlining reasons for analyzing data like reporting, monitoring, and exploratory analysis. It then discusses using relational databases, parallel databases, Hadoop, and columnar storage to store and process large volumes of data. Streaming technologies like Storm, Kafka, and services like Redshift, BigQuery, and Treasure Data are also summarized as options for a complete analytics platform.
Docker and Fluentd
Docker and FluentdN Masahiro - The document discusses logging for containers using Fluentd, an open source data collector. It describes how Fluentd can provide a unified logging layer, reliably forwarding and aggregating logs from multiple containers and applications in a pluggable way.
- Key points covered include using Fluentd with the new Docker logging drivers to directly collect logs from containers, avoiding performance penalties from other approaches. A demo of Fluentd is also mentioned.
How to create Treasure Data #dotsbigdata
How to create Treasure Data #dotsbigdataN Masahiro This document provides an overview of Treasure Data's big data analytics platform. It discusses how Treasure Data ingests and processes large amounts of schema-less data from various sources in real-time and at scale. It also describes how Treasure Data stores and indexes the data for fast querying using SQL interfaces while maintaining schema flexibility.
Fluentd v0.12 master guide
Fluentd v0.12 master guideN Masahiro This document provides an overview of Fluentd, an open source data collector. It discusses the key features of Fluentd including structured logging, reliable forwarding, and a pluggable architecture. The document then summarizes the architectures and new features of different Fluentd versions, including v0.10, v0.12, and the upcoming v0.14 and v1 releases. It also discusses Fluentd's ecosystem and plugins as well as Treasure Data's use of Fluentd in its log data collection and analytics platform.
Fluentd and Embulk Game Server 4
Fluentd and Embulk Game Server 4N Masahiro This document summarizes Masahiro Nakagawa's presentation on Fluentd and Embulk. Fluentd is a data collector for unified logging that allows for streaming data transfer based on JSON. It is written in Ruby and uses plugins to collect, process, and output data. Embulk is a bulk loading tool that allows high performance parallel processing of data to load it into various databases and storage systems. Both tools use a pluggable architecture to provide flexibility in handling different data sources and targets.
Treasure Data and AWS - Developers.io 2015
Treasure Data and AWS - Developers.io 2015N Masahiro This document discusses Treasure Data's data architecture. It describes how Treasure Data collects and imports log data using Fluentd. The data is stored in columnar format in S3 and metadata is stored in PostgreSQL. Treasure Data uses Presto to enable fast analytics on the large datasets. The document provides details on the import process, storage, partitioning, and optimizations to improve query performance.
Fluentd Unified Logging Layer At Fossasia
Fluentd Unified Logging Layer At FossasiaN Masahiro Masahiro Nakagawa is a senior software engineer at Treasure Data and the main maintainer of Fluentd. Fluentd is a data collector for unified logging that provides a streaming data transfer based on JSON. It has a simple core with plugins written in Ruby to provide functionality like input/output, buffering, parsing, filtering and formatting of data.
Treasure Data and OSS
Treasure Data and OSSN Masahiro - Treasure Data is a cloud data service that provides data acquisition, storage, and analysis capabilities.
- It collects data from various sources using Fluentd and Embulk and stores it in its own columnar database called Plazma DB.
- It offers various computing frameworks like Hive, Pig, and Presto for analytics and visualization with tools like Tableau.
- Presto is an interactive SQL query engine that can query data in HDFS, Hive, Cassandra and other data stores.
Fluentd - RubyKansai 65
Fluentd - RubyKansai 65N Masahiro Masahiro Nakagawa introduced Fluentd, an open source data collector. Fluentd provides a unified logging layer and collects data through a streaming data transfer based on JSON. It is written in Ruby and uses a plugin architecture to allow for various input and output functions. Fluentd is used in production environments for log aggregation, metrics collection, and data processing tasks.
Ad
Recently uploaded (20)
SDG 9000 Series: Unleashing multigigabit everywhere
SDG 9000 Series: Unleashing multigigabit everywhereAdtran Adtran’s SDG 9000 Series brings high-performance, cloud-managed Wi-Fi 7 to homes, businesses and public spaces. Built on a unified SmartOS platform, the portfolio includes outdoor access points, ceiling-mount APs and a 10G PoE router. Intellifi and Mosaic One simplify deployment, deliver AI-driven insights and unlock powerful new revenue streams for service providers.
Contributing to WordPress With & Without Code.pptx
Contributing to WordPress With & Without Code.pptxPatrick Lumumba Contributing to WordPress: Making an Impact on the Test Team—With or Without Coding Skills
WordPress survives on collaboration, and the Test Team plays a very important role in ensuring the CMS is stable, user-friendly, and accessible to everyone.
This talk aims to deconstruct the myth that one has to be a developer to contribute to WordPress. In this session, I will share with the audience how to get involved with the WordPress Team, whether a coder or not.
We’ll explore practical ways to contribute, from testing new features, and patches, to reporting bugs. By the end of this talk, the audience will have the tools and confidence to make a meaningful impact on WordPress—no matter the skill set.
ECS25 - The adventures of a Microsoft 365 Platform Owner - Website.pptx
ECS25 - The adventures of a Microsoft 365 Platform Owner - Website.pptxJasper Oosterveld My slides for ECS 2025.
AI Emotional Actors: “When Machines Learn to Feel and Perform"
AI Emotional Actors: “When Machines Learn to Feel and Perform"AkashKumar809858 Welcome to the era of AI Emotional Actors.
The entertainment landscape is undergoing a seismic transformation. What started as motion capture and CGI enhancements has evolved into a full-blown revolution: synthetic beings not only perform but express, emote, and adapt in real time.
For reading further follow this link -
https://akash97.gumroad.com/l/meioex
Cognitive Chasms - A Typology of GenAI Failure Failure Modes
Cognitive Chasms - A Typology of GenAI Failure Failure ModesDr. Tathagat Varma My talk on Cognitive Chasms at the brownbag session inside Walmart
TrustArc Webinar: Mastering Privacy Contracting
TrustArc Webinar: Mastering Privacy ContractingTrustArc As data privacy regulations become more pervasive across the globe and organizations increasingly handle and transfer (including across borders) meaningful volumes of personal and confidential information, the need for robust contracts to be in place is more important than ever.
This webinar will provide a deep dive into privacy contracting, covering essential terms and concepts, negotiation strategies, and key practices for managing data privacy risks.
Whether you're in legal, privacy, security, compliance, GRC, procurement, or otherwise, this session will include actionable insights and practical strategies to help you enhance your agreements, reduce risk, and enable your business to move fast while protecting itself.
This webinar will review key aspects and considerations in privacy contracting, including:
- Data processing addenda, cross-border transfer terms including EU Model Clauses/Standard Contractual Clauses, etc.
- Certain legally-required provisions (as well as how to ensure compliance with those provisions)
- Negotiation tactics and common issues
- Recent lessons from recent regulatory actions and disputes
New Ways to Reduce Database Costs with ScyllaDB
New Ways to Reduce Database Costs with ScyllaDBScyllaDB How ScyllaDB’s latest capabilities can reduce your infrastructure costs
ScyllaDB has been obsessed with price-performance from day 1. Our core database is architected with low-level engineering optimizations that squeeze every ounce of power from the underlying infrastructure. And we just completed a multi-year effort to introduce a set of new capabilities for additional savings.
Join this webinar to learn about these new capabilities: the underlying challenges we wanted to address, the workloads that will benefit most from each, and how to get started. We’ll cover ways to:
- Avoid overprovisioning with “just-in-time” scaling
- Safely operate at up to ~90% storage utilization
- Cut network costs with new compression strategies and file-based streaming
We’ll also highlight a “hidden gem” capability that lets you safely balance multiple workloads in a single cluster. To conclude, we will share the efficiency-focused capabilities on our short-term and long-term roadmaps.
ELNL2025 - Unlocking the Power of Sensitivity Labels - A Comprehensive Guide....
ELNL2025 - Unlocking the Power of Sensitivity Labels - A Comprehensive Guide....Jasper Oosterveld Sensitivity labels, powered by Microsoft Purview Information Protection, serve as the foundation for classifying and protecting your sensitive data within Microsoft 365. Their importance extends beyond classification and play a crucial role in enforcing governance policies across your Microsoft 365 environment. Join me, a Data Security Consultant and Microsoft MVP, as I share practical tips and tricks to get the full potential of sensitivity labels. I discuss sensitive information types, automatic labeling, and seamless integration with Data Loss Prevention, Teams Premium, and Microsoft 365 Copilot.
End-to-end Assurance for SD-WAN & SASE with ThousandEyes
End-to-end Assurance for SD-WAN & SASE with ThousandEyesThousandEyes End-to-end Assurance for SD-WAN & SASE with ThousandEyes
STKI Israel Market Study 2025 final v1 version
STKI Israel Market Study 2025 final v1 versionDr. Jimmy Schwarzkopf nnual (33 years) study of the Israeli Enterprise / public IT market. Covering sections on Israeli Economy, IT trends 2026-28, several surveys (AI, CDOs, OCIO, CTO, staffing cyber, operations and infra) plus rankings of 760 vendors on 160 markets (market sizes and trends) and comparison of products according to support and market penetration.
Dr Jimmy Schwarzkopf presentation on the SUMMIT 2025 A
Dr Jimmy Schwarzkopf presentation on the SUMMIT 2025 ADr. Jimmy Schwarzkopf Introduction and Background:
Study Overview and Methodology: The study analyzes the IT market in Israel, covering over 160 markets and 760 companies/products/services. It includes vendor rankings, IT budgets, and trends from 2025-2029. Vendors participate in detailed briefings and surveys.
Vendor Listings: The presentation lists numerous vendors across various pages, detailing their names and services. These vendors are ranked based on their participation and market presence.
Market Insights and Trends: Key insights include IT market forecasts, economic factors affecting IT budgets, and the impact of AI on enterprise IT. The study highlights the importance of AI integration and the concept of creative destruction.
Agentic AI and Future Predictions: Agentic AI is expected to transform human-agent collaboration, with AI systems understanding context and orchestrating complex processes. Future predictions include AI's role in shopping and enterprise IT.
LSNIF: Locally-Subdivided Neural Intersection Function
LSNIF: Locally-Subdivided Neural Intersection FunctionTakahiro Harada Neural representations have shown the potential to accelerate ray casting in a conventional ray-tracing-based rendering pipeline. We introduce a novel approach called Locally-Subdivided Neural Intersection Function (LSNIF) that replaces bottom-level BVHs used as traditional geometric representations with a neural network. Our method introduces a sparse hash grid encoding scheme incorporating geometry voxelization, a scene-agnostic training data collection, and a tailored loss function. It enables the network to output not only visibility but also hit-point information and material indices. LSNIF can be trained offline for a single object, allowing us to use LSNIF as a replacement for its corresponding BVH. With these designs, the network can handle hit-point queries from any arbitrary viewpoint, supporting all types of rays in the rendering pipeline. We demonstrate that LSNIF can render a variety of scenes, including real-world scenes designed for other path tracers, while achieving a memory footprint reduction of up to 106.2x compared to a compressed BVH.
https://arxiv.org/abs/2504.21627
Introducing the OSA 3200 SP and OSA 3250 ePRC
Introducing the OSA 3200 SP and OSA 3250 ePRCAdtran Adtran's latest Oscilloquartz solutions make optical pumping cesium timing more accessible than ever. Discover how the new OSA 3200 SP and OSA 3250 ePRC deliver superior stability, simplified deployment and lower total cost of ownership. Built on a shared platform and engineered for scalable, future-ready networks, these models are ideal for telecom, defense, metrology and more.
UiPath Community Zurich: Release Management and Build Pipelines
UiPath Community Zurich: Release Management and Build PipelinesUiPathCommunity Ensuring robust, reliable, and repeatable delivery processes is more critical than ever - it's a success factor for your automations and for automation programmes as a whole. In this session, we’ll dive into modern best practices for release management and explore how tools like the UiPathCLI can streamline your CI/CD pipelines. Whether you’re just starting with automation or scaling enterprise-grade deployments, our event promises to deliver helpful insights to you. This topic is relevant for both on-premise and cloud users - as well as for automation developers and software testers alike.
📕 Agenda:
- Best Practices for Release Management
- What it is and why it matters
- UiPath Build Pipelines Deep Dive
- Exploring CI/CD workflows, the UiPathCLI and showcasing scenarios for both on-premise and cloud
- Discussion, Q&A
👨🏫 Speakers
Roman Tobler, CEO@ Routinuum
Johans Brink, CTO@ MvR Digital Workforce
We look forward to bringing best practices and showcasing build pipelines to you - and to having interesting discussions on this important topic!
If you have any questions or inputs prior to the event, don't hesitate to reach out to us.
This event streamed live on May 27, 16:00 pm CET.
Check out all our upcoming UiPath Community sessions at:
👉 https://community.uipath.com/events/
Join UiPath Community Zurich chapter:
👉 https://community.uipath.com/zurich/
Droidal: AI Agents Revolutionizing Healthcare
Droidal: AI Agents Revolutionizing HealthcareDroidal LLC Droidal’s AI Agents are transforming healthcare by bringing intelligence, speed, and efficiency to key areas such as Revenue Cycle Management (RCM), clinical operations, and patient engagement. Built specifically for the needs of U.S. hospitals and clinics, Droidal's solutions are designed to improve outcomes and reduce administrative burden.
Through simple visuals and clear examples, the presentation explains how AI Agents can support medical coding, streamline claims processing, manage denials, ensure compliance, and enhance communication between providers and patients. By integrating seamlessly with existing systems, these agents act as digital coworkers that deliver faster reimbursements, reduce errors, and enable teams to focus more on patient care.
Droidal's AI technology is more than just automation — it's a shift toward intelligent healthcare operations that are scalable, secure, and cost-effective. The presentation also offers insights into future developments in AI-driven healthcare, including how continuous learning and agent autonomy will redefine daily workflows.
Whether you're a healthcare administrator, a tech leader, or a provider looking for smarter solutions, this presentation offers a compelling overview of how Droidal’s AI Agents can help your organization achieve operational excellence and better patient outcomes.
A free demo trial is available for those interested in experiencing Droidal’s AI Agents firsthand. Our team will walk you through a live demo tailored to your specific workflows, helping you understand the immediate value and long-term impact of adopting AI in your healthcare environment.
To request a free trial or learn more:
https://droidal.com/
Protecting Your Sensitive Data with Microsoft Purview - IRMS 2025
Protecting Your Sensitive Data with Microsoft Purview - IRMS 2025Nikki Chapple Session | Protecting Your Sensitive Data with Microsoft Purview: Practical Information Protection and DLP Strategies
Presenter | Nikki Chapple (MVP| Principal Cloud Architect CloudWay) & Ryan John Murphy (Microsoft)
Event | IRMS Conference 2025
Format | Birmingham UK
Date | 18-20 May 2025
In this closing keynote session from the IRMS Conference 2025, Nikki Chapple and Ryan John Murphy deliver a compelling and practical guide to data protection, compliance, and information governance using Microsoft Purview. As organizations generate over 2 billion pieces of content daily in Microsoft 365, the need for robust data classification, sensitivity labeling, and Data Loss Prevention (DLP) has never been more urgent.
This session addresses the growing challenge of managing unstructured data, with 73% of sensitive content remaining undiscovered and unclassified. Using a mountaineering metaphor, the speakers introduce the “Secure by Default” blueprint—a four-phase maturity model designed to help organizations scale their data security journey with confidence, clarity, and control.
🔐 Key Topics and Microsoft 365 Security Features Covered:
Microsoft Purview Information Protection and DLP
Sensitivity labels, auto-labeling, and adaptive protection
Data discovery, classification, and content labeling
DLP for both labeled and unlabeled content
SharePoint Advanced Management for workspace governance
Microsoft 365 compliance center best practices
Real-world case study: reducing 42 sensitivity labels to 4 parent labels
Empowering users through training, change management, and adoption strategies
🧭 The Secure by Default Path – Microsoft Purview Maturity Model:
Foundational – Apply default sensitivity labels at content creation; train users to manage exceptions; implement DLP for labeled content.
Managed – Focus on crown jewel data; use client-side auto-labeling; apply DLP to unlabeled content; enable adaptive protection.
Optimized – Auto-label historical content; simulate and test policies; use advanced classifiers to identify sensitive data at scale.
Strategic – Conduct operational reviews; identify new labeling scenarios; implement workspace governance using SharePoint Advanced Management.
🎒 Top Takeaways for Information Management Professionals:
Start secure. Stay protected. Expand with purpose.
Simplify your sensitivity label taxonomy for better adoption.
Train your users—they are your first line of defense.
Don’t wait for perfection—start small and iterate fast.
Align your data protection strategy with business goals and regulatory requirements.
💡 Who Should Watch This Presentation?
This session is ideal for compliance officers, IT administrators, records managers, data protection officers (DPOs), security architects, and Microsoft 365 governance leads. Whether you're in the public sector, financial services, healthcare, or education.
🔗 Read the blog: https://nikkichapple.com/irms-conference-2025/
Measuring Microsoft 365 Copilot and Gen AI Success
Measuring Microsoft 365 Copilot and Gen AI SuccessNikki Chapple Session | Measuring Microsoft 365 Copilot and Gen AI Success with Viva Insights and Purview
Presenter | Nikki Chapple 2 x MVP and Principal Cloud Architect at CloudWay
Event | European Collaboration Conference 2025
Format | In person Germany
Date | 28 May 2025
📊 Measuring Copilot and Gen AI Success with Viva Insights and Purview
Presented by Nikki Chapple – Microsoft 365 MVP & Principal Cloud Architect, CloudWay
How do you measure the success—and manage the risks—of Microsoft 365 Copilot and Generative AI (Gen AI)? In this ECS 2025 session, Microsoft MVP and Principal Cloud Architect Nikki Chapple explores how to go beyond basic usage metrics to gain full-spectrum visibility into AI adoption, business impact, user sentiment, and data security.
🎯 Key Topics Covered:
Microsoft 365 Copilot usage and adoption metrics
Viva Insights Copilot Analytics and Dashboard
Microsoft Purview Data Security Posture Management (DSPM) for AI
Measuring AI readiness, impact, and sentiment
Identifying and mitigating risks from third-party Gen AI tools
Shadow IT, oversharing, and compliance risks
Microsoft 365 Admin Center reports and Copilot Readiness
Power BI-based Copilot Business Impact Report (Preview)
📊 Why AI Measurement Matters: Without meaningful measurement, organizations risk operating in the dark—unable to prove ROI, identify friction points, or detect compliance violations. Nikki presents a unified framework combining quantitative metrics, qualitative insights, and risk monitoring to help organizations:
Prove ROI on AI investments
Drive responsible adoption
Protect sensitive data
Ensure compliance and governance
🔍 Tools and Reports Highlighted:
Microsoft 365 Admin Center: Copilot Overview, Usage, Readiness, Agents, Chat, and Adoption Score
Viva Insights Copilot Dashboard: Readiness, Adoption, Impact, Sentiment
Copilot Business Impact Report: Power BI integration for business outcome mapping
Microsoft Purview DSPM for AI: Discover and govern Copilot and third-party Gen AI usage
🔐 Security and Compliance Insights: Learn how to detect unsanctioned Gen AI tools like ChatGPT, Gemini, and Claude, track oversharing, and apply eDLP and Insider Risk Management (IRM) policies. Understand how to use Microsoft Purview—even without E5 Compliance—to monitor Copilot usage and protect sensitive data.
📈 Who Should Watch: This session is ideal for IT leaders, security professionals, compliance officers, and Microsoft 365 admins looking to:
Maximize the value of Microsoft Copilot
Build a secure, measurable AI strategy
Align AI usage with business goals and compliance requirements
🔗 Read the blog https://nikkichapple.com/measuring-copilot-gen-ai/
Evaluation Challenges in Using Generative AI for Science & Technical Content
Evaluation Challenges in Using Generative AI for Science & Technical ContentPaul Groth Evaluation Challenges in Using Generative AI for Science & Technical Content.
Foundation Models show impressive results in a wide-range of tasks on scientific and legal content from information extraction to question answering and even literature synthesis. However, standard evaluation approaches (e.g. comparing to ground truth) often don't seem to work. Qualitatively the results look great but quantitive scores do not align with these observations. In this talk, I discuss the challenges we've face in our lab in evaluation. I then outline potential routes forward.
Palo Alto Networks Cybersecurity Foundation
Palo Alto Networks Cybersecurity FoundationVICTOR MAESTRE RAMIREZ Palo Alto Networks Cybersecurity Foundation
Jira Administration Training – Day 1 : Introduction
Jira Administration Training – Day 1 : IntroductionRavi Teja This presentation covers the basics of Jira for beginners. Learn how Jira works, its key features, project types, issue types, and user roles. Perfect for anyone new to Jira or preparing for Jira Admin roles.
Final presentation at pfintern
- 1. PFI Final Presentation Masahiro Nakagawa Thu, September, 30, 2010 …
- 2. @repeatedly • • kzkindle ( ) • GodBull (RedBull ) • • Sedue
- 3. Sedue Architecture User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 5. Realtime Indexing User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 6. Realtime Indexing • Numeric Range Index • • • • C++ ... make … …
- 7. S3 User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 8. DFS S3 • S3: Amazon • EC2
- 9. etc... • • • • zsh ( )
- 10. etc...
- 11. …
- 13. MongoDB • : http://www.mongodb.org/ • • • •
- 14. Sharding + Replica set
- 15. MongoDB Sharding User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 17. … (2 ) 600insert/s ↓ 2 1 ↓ (2 ) 3 5000 prz ↓ 5000 (500 ) 4 ( :4 : 30 )
- 18. • → • • 100QPS • • mongoimport
- 19. Archive Manager
- 20. Sedue …( ´Д`)
- 21. Archive Manager User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 23. • Heartbeat • Archive Manager • •
- 24. Heartbeat Virtual IP Heartbeat Active Stanby
- 25. Heartbeat × Virtual IP Heartbeat Active Stanby
- 26. Heartbeat Virtual IP Fail Over! Heartbeat Active Stanby
- 27. Connection Pooling ↓ …
- 28. Connection Pooling User Distributed File System Query Document Searchar Indexer Server Repository Archive Manager Config
- 29. • 20% • No Pooling 117s • Pooling 97s • MessagePack 2 0s 60s 120s
- 30. Export
- 31. Red Bull: 58 ( : 66) 2 D 0%!!