Découvrez les dernières fonctionnalités grâce à nos démos et annonces : réplication inter-clusters, indices gelés d'Elasticsearch, Kibana Spaces, et toujours plus d'intégrations de données dans Beats et Logstash.
Descubre las mas recientes y futuras características del Stack: gestión del ciclo de vida de los datos para arquitecturas hot/warm/cold con DataStreams, mejoras en uso de memoria y disco, mejoras en el enrutado de las consultas; Analítica de datos multi lenguaje con query cDSL, SQL, KQL, PromQL y EQL; el nuevo sistema de Alertas y Acciones.
Descubre las características disponibles con demostraciones: la replicación entre clústeres, los índices bloqueados de Elasticsearch, los espacios de Kibana y los datos de integraciones en Beats y Logstash.
Learn about features with demos and announcements, from cross-cluster replication and frozen indices in Elasticsearch to Kibana Spaces and the ever-growing set of data integrations in Beats and Logstash.
Learn about features with demos and announcements, from cross-cluster replication and frozen indices in Elasticsearch to Kibana Spaces and the ever-growing set of data integrations in Beats and Logstash.
Análisis a fondo de roadmap del Elastic StackElasticsearch
Obtén información sobre las características mediante demostraciones y anuncios, desde replicación entre clusters e índices congelados en Elasticsearch hasta Kibana Spaces y el conjunto de integraciones de datos en constante crecimiento en Beats y Logstash.
Building a Real-Time Gaming Analytics Service with Apache DruidImply
At GameAnalytics we receive and process real time behavioural data from more than 100 million daily active users, helping thousands of game studios and developers understand user behaviour and improve their games. In this talk, you will learn how we managed to migrate our legacy backend system from using an in-house built streaming analytics service to Apache Druid, and the lessons learned along the way. By adopting Druid, we have been able to reduce development costs, increase reliability of our systems and implement new features that would have not been possible with our old stack. We will provide an overview of our approach to schema design, segments optimization, creation of our query layer, caching and datasources optimisation, which can help you better understand how you can successfully use Druid as a key component on your data processing and reporting infrastructure.
Optimizing Elastic for Search at McQueen SolutionsElasticsearch
Learn best practices for squeezing every last drop of performance out of Elasticsearch queries and aggregations -- all based off of real-world production clusters.
MoPub, a Twitter company, provides monetization solutions for mobile app publishers and developers around the globe. MoPub receives over 33 Billion ad requests per day generating over 200TB of raw logs every day. We built MoPub Analytics as the analytics platform, using Druid + Imply for our end users who are Publishers, Demand side partners and Internal users.
We will talk about the architecture of the analytics platform, our Druid cluster setup, hardware choices, monitoring, use cases, limiting factors, challenges with lookups and solutions we used.
Watch video:https://imply.io/virtual-druid-summit/analytics-over-terabytes-of-data-at-twitter-apache-druid
Descubre las mas recientes y futuras características del Stack: gestión del ciclo de vida de los datos para arquitecturas hot/warm/cold con DataStreams, mejoras en uso de memoria y disco, mejoras en el enrutado de las consultas; Analítica de datos multi lenguaje con query cDSL, SQL, KQL, PromQL y EQL; el nuevo sistema de Alertas y Acciones.
Descubre las características disponibles con demostraciones: la replicación entre clústeres, los índices bloqueados de Elasticsearch, los espacios de Kibana y los datos de integraciones en Beats y Logstash.
Learn about features with demos and announcements, from cross-cluster replication and frozen indices in Elasticsearch to Kibana Spaces and the ever-growing set of data integrations in Beats and Logstash.
Learn about features with demos and announcements, from cross-cluster replication and frozen indices in Elasticsearch to Kibana Spaces and the ever-growing set of data integrations in Beats and Logstash.
Análisis a fondo de roadmap del Elastic StackElasticsearch
Obtén información sobre las características mediante demostraciones y anuncios, desde replicación entre clusters e índices congelados en Elasticsearch hasta Kibana Spaces y el conjunto de integraciones de datos en constante crecimiento en Beats y Logstash.
Building a Real-Time Gaming Analytics Service with Apache DruidImply
At GameAnalytics we receive and process real time behavioural data from more than 100 million daily active users, helping thousands of game studios and developers understand user behaviour and improve their games. In this talk, you will learn how we managed to migrate our legacy backend system from using an in-house built streaming analytics service to Apache Druid, and the lessons learned along the way. By adopting Druid, we have been able to reduce development costs, increase reliability of our systems and implement new features that would have not been possible with our old stack. We will provide an overview of our approach to schema design, segments optimization, creation of our query layer, caching and datasources optimisation, which can help you better understand how you can successfully use Druid as a key component on your data processing and reporting infrastructure.
Optimizing Elastic for Search at McQueen SolutionsElasticsearch
Learn best practices for squeezing every last drop of performance out of Elasticsearch queries and aggregations -- all based off of real-world production clusters.
MoPub, a Twitter company, provides monetization solutions for mobile app publishers and developers around the globe. MoPub receives over 33 Billion ad requests per day generating over 200TB of raw logs every day. We built MoPub Analytics as the analytics platform, using Druid + Imply for our end users who are Publishers, Demand side partners and Internal users.
We will talk about the architecture of the analytics platform, our Druid cluster setup, hardware choices, monitoring, use cases, limiting factors, challenges with lookups and solutions we used.
Watch video:https://imply.io/virtual-druid-summit/analytics-over-terabytes-of-data-at-twitter-apache-druid
Gian will offer his reflections on the Druid journey to date, plus describe his vision for what Druid will become. He will lay out the near-term Druid roadmap and take your questions.
Watch video: https://imply.io/virtual-druid-summit/apache-druid-vision-and-roadmap-gian-merlino
Apache Druid®: A Dance of Distributed ProcessesImply
Apache Druid® is an open source analytics database powering fresh, fast analytics in companies from AirBnB to Zeotap on clickstream, telemetry, financial transactions, applications and more. In this talk, we open the box on the three distributed processes in Druid led by the coordinator, overlord, and broker, and the ways that these come together to deliver reliable, performant query, ingestion, and management services.
Peter Marshall, Technology Evangelist at Imply
Abstract: Apache Druid® can revolutionise business decision-making with a view of the freshest of fresh data in web, mobile, desktop, and data science notebooks. In this talk, we look at key activities to integrate into Apache Druid POCs, discussing common hurdles and signposting to important information.
Bio: Peter Marshall (https://petermarshall.io) is an Apache Druid Technology Evangelist at Imply (http://imply.io/), a company founded by original developers of Apache Druid. He has 20 years architecture experience in CRM, EDRM, ERP, EIP, Digital Services, Security, BI, Analytics, and MDM. He is TOGAF certified and has a BA degree in Theology and Computer Studies from the University of Birmingham in the United Kingdom.
What Is ELK Stack | ELK Tutorial For Beginners | Elasticsearch Kibana | ELK S...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka tutorial on What Is ELK Stack will help you in understanding the fundamentals of Elasticsearch, Logstash, and Kibana together and help you in building a strong foundation in ELK Stack. Below are the topics covered in this ELK tutorial for beginners:
1. Need for Log Analysis
2. Problems with Log Analysis
3. What is ELK Stack?
4. Features of ELK Stack
5. Companies Using ELK Stack
Apache Druid ingests and enables instant query on many billions of events in real-time. But how? In this talk, each of the components of an Apache Druid cluster is described – along with the data and query optimisations at its core – that unlock fresh, fast data for all.
So, what is the ELK Stack? "ELK" is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
Data Analytics and Processing at Snap - Druid Meetup LA - September 2018Charles Allen
Charles Allen covers data processing, analytics, and insights systems at Snap. Strength points for Druid use cases are called out as are differences in some of the processing systems used.
This is the slide collection from the second talk from:
https://www.meetup.com/druidio-la/events/254080924/
Cloudian HyperStore Storage System is a peer-to-peer software defined storage platform, providing an enterprise grade S3-compliant object storage system on low cost commodity servers. Its multi-tenanted and multi-interface design can support many applications on the same platform.
Archmage, Pinterest’s Real-time Analytics Platform on DruidImply
In this talk, we will talk about:
1) the motivation of switching from Hbase backed analytics system to Druid
2) the architecture design of Druid as a platform in Pinterest (Archmage, Hadoop, Kafka) including a query interface, Archmage, a thrift service in front of Druid which exposes a thrift api to company-wise clients, handles Druid broker hosts discovery, serves as a relay to broker hosts to abstract the async HTTP connection and provides query optimizations transparent to clients including directly translating fixed pattern SQL to Druid native JSON queries to save planning time. In addition, we’ll cover the production Hadoop batch and Kafka real time ingestion pipeline setup and the reason we picked a pull-based solution instead of a push-based solution for real time ingestion.
3) We will also talk about the use cases currently running in production on this platform including their data volume, QPS, Druid cluster setup, the unique challenges we met while onboarding and how we addressed them with extensive tunings to meet SLA and lessons learned for use cases including: partner insights, which provides partners with stats on organic pins; realtime spam detection, which detects user login related anomaly events and pin related spamming events like pin creation and repin; and migrating the backend from Presto to Druid for Ads related experiments data analysis.
Microservices, Continuous Delivery, and Elasticsearch at Capital OneNoriaki Tatsumi
This presentation focuses on the implementation of Continuous Delivery and Microservices principles in Capital One’s
cybersecurity data platform – which ingests ~6 TB of data every day, and where Elasticsearch is a core component.
Log Management
Log Monitoring
Log Analysis
Need for Log Analysis
Problem with Log Analysis
Some of Log Management Tool
What is ELK Stack
ELK Stack Working
Beats
Different Types of Server Logs
Example of Winlog beat, Packetbeat, Apache2 and Nginx Server log analysis
Mimikatz
Malicious File Detection using ELK
Practical Setup
Conclusion
How Netflix Uses Druid in Real-time to Ensure a High Quality Streaming Experi...Imply
Ensuring a consistently great Netflix experience while continuously pushing innovative technology updates is no easy feat.
We'll look at how Netflix turns log streams into real-time metrics to provide visibility into how devices are performing in the field. Including sharing some of the lessons learned around optimizing Druid to handle our load.
One of the most popular use cases for Apache Druid is building data applications. Data applications exist to deliver data into the hands of everyone on a team in a business, and are used by these teams to make faster, better decisions. To fulfill this role, they need to support granular drill down, because the devil is in the details, but also be extremely fast, because otherwise people won't use them!
In this talk, Gian Merlino will cover:
*The unique technical challenges of powering data-driven applications
*What attributes of Druid make it a good platform for data applications
*Some real-world data applications powered by Druid
Splunk: Druid on Kubernetes with Druid-operatorImply
We went through the journey of deploying Apache Druid clusters on Kubernetes(K8s) and created a druid-operator (https://github.com/druid-io/druid-operator). This talk introduces the druid kubernetes operator, how to use it to deploy druid clusters and how it works under the hood. We will share how we use this operator to deploy Druid clusters at Splunk.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. Druid is a complex stateful distributed system and a Druid cluster consists of multiple web services such as Broker, Historical, Coordinator, Overlord, MiddleManager etc each deployed with multiple replicas. Deploying a single web service on K8s requires creating few K8s resources via YAML files and it multiplies due to multiple services inside of a Druid cluster. Now doing it for multiple Druid clusters (dev, staging, production environments) makes it even more tedious and error prone.
K8s enables creation of application (such as Druid) specific extension, called “Operator”, that combines kubernetes and application specific knowledge into a reusable K8s extension that makes deploying complex applications simple.
Learn about how to reduce public cloud storage costs on the AWS and Azure marketplaces with SoftNAS Senior Director of Product Marketing, John Bedrick.
Calculating dynamic pricing, estimated travel times or detecting fraud in real time. These are all the cases where realtime analytics create the differentiation between experiences. Redis comes with built in types to enable realtime processing of complex analytics with data types like sorted sets, hyperloglog, bloom and cuckoo filters and more.
Gian will offer his reflections on the Druid journey to date, plus describe his vision for what Druid will become. He will lay out the near-term Druid roadmap and take your questions.
Watch video: https://imply.io/virtual-druid-summit/apache-druid-vision-and-roadmap-gian-merlino
Apache Druid®: A Dance of Distributed ProcessesImply
Apache Druid® is an open source analytics database powering fresh, fast analytics in companies from AirBnB to Zeotap on clickstream, telemetry, financial transactions, applications and more. In this talk, we open the box on the three distributed processes in Druid led by the coordinator, overlord, and broker, and the ways that these come together to deliver reliable, performant query, ingestion, and management services.
Peter Marshall, Technology Evangelist at Imply
Abstract: Apache Druid® can revolutionise business decision-making with a view of the freshest of fresh data in web, mobile, desktop, and data science notebooks. In this talk, we look at key activities to integrate into Apache Druid POCs, discussing common hurdles and signposting to important information.
Bio: Peter Marshall (https://petermarshall.io) is an Apache Druid Technology Evangelist at Imply (http://imply.io/), a company founded by original developers of Apache Druid. He has 20 years architecture experience in CRM, EDRM, ERP, EIP, Digital Services, Security, BI, Analytics, and MDM. He is TOGAF certified and has a BA degree in Theology and Computer Studies from the University of Birmingham in the United Kingdom.
What Is ELK Stack | ELK Tutorial For Beginners | Elasticsearch Kibana | ELK S...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka tutorial on What Is ELK Stack will help you in understanding the fundamentals of Elasticsearch, Logstash, and Kibana together and help you in building a strong foundation in ELK Stack. Below are the topics covered in this ELK tutorial for beginners:
1. Need for Log Analysis
2. Problems with Log Analysis
3. What is ELK Stack?
4. Features of ELK Stack
5. Companies Using ELK Stack
Apache Druid ingests and enables instant query on many billions of events in real-time. But how? In this talk, each of the components of an Apache Druid cluster is described – along with the data and query optimisations at its core – that unlock fresh, fast data for all.
So, what is the ELK Stack? "ELK" is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
Data Analytics and Processing at Snap - Druid Meetup LA - September 2018Charles Allen
Charles Allen covers data processing, analytics, and insights systems at Snap. Strength points for Druid use cases are called out as are differences in some of the processing systems used.
This is the slide collection from the second talk from:
https://www.meetup.com/druidio-la/events/254080924/
Cloudian HyperStore Storage System is a peer-to-peer software defined storage platform, providing an enterprise grade S3-compliant object storage system on low cost commodity servers. Its multi-tenanted and multi-interface design can support many applications on the same platform.
Archmage, Pinterest’s Real-time Analytics Platform on DruidImply
In this talk, we will talk about:
1) the motivation of switching from Hbase backed analytics system to Druid
2) the architecture design of Druid as a platform in Pinterest (Archmage, Hadoop, Kafka) including a query interface, Archmage, a thrift service in front of Druid which exposes a thrift api to company-wise clients, handles Druid broker hosts discovery, serves as a relay to broker hosts to abstract the async HTTP connection and provides query optimizations transparent to clients including directly translating fixed pattern SQL to Druid native JSON queries to save planning time. In addition, we’ll cover the production Hadoop batch and Kafka real time ingestion pipeline setup and the reason we picked a pull-based solution instead of a push-based solution for real time ingestion.
3) We will also talk about the use cases currently running in production on this platform including their data volume, QPS, Druid cluster setup, the unique challenges we met while onboarding and how we addressed them with extensive tunings to meet SLA and lessons learned for use cases including: partner insights, which provides partners with stats on organic pins; realtime spam detection, which detects user login related anomaly events and pin related spamming events like pin creation and repin; and migrating the backend from Presto to Druid for Ads related experiments data analysis.
Microservices, Continuous Delivery, and Elasticsearch at Capital OneNoriaki Tatsumi
This presentation focuses on the implementation of Continuous Delivery and Microservices principles in Capital One’s
cybersecurity data platform – which ingests ~6 TB of data every day, and where Elasticsearch is a core component.
Log Management
Log Monitoring
Log Analysis
Need for Log Analysis
Problem with Log Analysis
Some of Log Management Tool
What is ELK Stack
ELK Stack Working
Beats
Different Types of Server Logs
Example of Winlog beat, Packetbeat, Apache2 and Nginx Server log analysis
Mimikatz
Malicious File Detection using ELK
Practical Setup
Conclusion
How Netflix Uses Druid in Real-time to Ensure a High Quality Streaming Experi...Imply
Ensuring a consistently great Netflix experience while continuously pushing innovative technology updates is no easy feat.
We'll look at how Netflix turns log streams into real-time metrics to provide visibility into how devices are performing in the field. Including sharing some of the lessons learned around optimizing Druid to handle our load.
One of the most popular use cases for Apache Druid is building data applications. Data applications exist to deliver data into the hands of everyone on a team in a business, and are used by these teams to make faster, better decisions. To fulfill this role, they need to support granular drill down, because the devil is in the details, but also be extremely fast, because otherwise people won't use them!
In this talk, Gian Merlino will cover:
*The unique technical challenges of powering data-driven applications
*What attributes of Druid make it a good platform for data applications
*Some real-world data applications powered by Druid
Splunk: Druid on Kubernetes with Druid-operatorImply
We went through the journey of deploying Apache Druid clusters on Kubernetes(K8s) and created a druid-operator (https://github.com/druid-io/druid-operator). This talk introduces the druid kubernetes operator, how to use it to deploy druid clusters and how it works under the hood. We will share how we use this operator to deploy Druid clusters at Splunk.
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. Druid is a complex stateful distributed system and a Druid cluster consists of multiple web services such as Broker, Historical, Coordinator, Overlord, MiddleManager etc each deployed with multiple replicas. Deploying a single web service on K8s requires creating few K8s resources via YAML files and it multiplies due to multiple services inside of a Druid cluster. Now doing it for multiple Druid clusters (dev, staging, production environments) makes it even more tedious and error prone.
K8s enables creation of application (such as Druid) specific extension, called “Operator”, that combines kubernetes and application specific knowledge into a reusable K8s extension that makes deploying complex applications simple.
Learn about how to reduce public cloud storage costs on the AWS and Azure marketplaces with SoftNAS Senior Director of Product Marketing, John Bedrick.
Calculating dynamic pricing, estimated travel times or detecting fraud in real time. These are all the cases where realtime analytics create the differentiation between experiences. Redis comes with built in types to enable realtime processing of complex analytics with data types like sorted sets, hyperloglog, bloom and cuckoo filters and more.
Analyze your Data Lake, Fast @ Any Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
-Learn how to automatically discover, catalog, and prepare your data for analytics
-Understand how to query data in your data lake without having to transform or load the data into your data warehouse
-See how to analyze data in both your data lake and data warehouse
Datalagring för AI
Vad bör man att tänka på, hur bygger man och vilken skillnad kan IBM's infrastruktur göra.
Talare: Christofer Jensen, Storage Technical Specialist, IBM
Presentationen hölls på Watson Kista Summit 2018
Video in french at https://www.youtube.com/watch?v=9LNnNh63rBI
Sizing an Elasticsearch cluster has to consider many dimensions. In this presentation we go through the different elements and features you should consider to handle big and varying loads of log data.
(ARC311) Decoding The Genetic Blueprint Of Life On A Cloud EcosystemAmazon Web Services
Thermo Fisher Scientific, a world leader in biotechnology, has built a new polymerase chain reaction (PCR) system for DNA sequencing. Designed for low- to midlevel throughput laboratories that conduct real time PCR experiments, the system runs on individual QuantStudio devices. These devices are connected to Thermo Fisher’s cloud computing platform, which is built on AWS using Amazon EC2, Amazon DynamoDB, and Amazon S3. With this single platform, applied and clinical researchers can learn, analyze, share, collaborate, and obtain support. Researchers worldwide can now collaborate online in real time and access their data wherever and whenever necessary. Laboratories can also share experimental conditions and results with their partners while providing a uniform experience for every user and helping to minimize training and errors. The net result is increased collaboration, faster time to market, fewer errors, and lower cost. We have architected a solution that uses Amazon EMR, DynamoDB, Amazon Elasticache, and S3. In this presentation, we share our architecture, lessons learned, best design patterns for NoSQL, strategies for leveraging EMR with DynamoDB, and a flexible solution that our scientist use. We also share our next step in architecture evolution.
AWS Analytics Immersion Day - Build BI System from Scratch (Day1, Day2 Full V...Sungmin Kim
How to build Business Intelligence System from scratch on AWS (Day1, Day2)
------------------------------------------------------------------------------------------
2020-03-18(수)~19(목) 2일 동안 온라인으로 진행한 Online AWS Analytics Immersion Day 전체 발표 자료 입니다.
BI(Business Intelligence) 시스템을 설계하는 과정에서 AWS Analytics 서비스들을 어떻게 활용할 수 있는지 설명 드리고자 만든 자료 입니다.
Target Audience
-------------------
Online Analytics Immersion Day는 다음과 같은 고객을 대상으로 진행됩니다.
- AWS Analytics Services (ex. Kinesis, Athena, Redshift, EMR, etc)의 기본 개념을 알고 있지만, 이러한 서비스 활용 방법 및 데이터 분석 시스템 구축 과정이 궁금하신 분
- 데이터 분석 시스템을 구축한 경험은 있지만, 자신이 만든 시스템을 아키텍처 관점에서
어떻게 평가하고 확인할 수 있는지 궁금하신 분
Data is gravity. Your workloads and processing is dependent on where your data is and how it is stored. With AWS, you have a host of storage options and the key to successfully leverage them is to know when to use which option. This session will explain in details about each of the AWS Storage offerings along with data ingestion optins into the Cloud using Snowball and Snowmobile
Marc Trimuschat,
Head - Business Developement, AWS Storage, AWS APAC
AWS Storage and Database Architecture Best Practices (DAT203) | AWS re:Invent...Amazon Web Services
Learn about architecture best practices for combining AWS storage and database technologies. We outline AWS storage options (Amazon EBS, Amazon EC2 Instance Storage, Amazon S3 and Amazon Glacier) along with AWS database options including Amazon ElastiCache (in-memory data store), Amazon RDS (SQL database), Amazon DynamoDB (NoSQL database), Amazon CloudSearch (search), Amazon EMR (hadoop) and Amazon Redshift (data warehouse). Then we discuss how to architect your database tier by using the right database and storage technologies to achieve the required functionality, performance, availability, and durability—at the right cost.
Traditional data warehouses become expensive and slow down as the volume of your data grows. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it easy to analyze all of your data using existing business intelligence tools for 1/10th the traditional cost. This session will provide an introduction to Amazon Redshift and cover the essentials you need to deploy your data warehouse in the cloud so that you can achieve faster analytics and save costs.
Data processing and analysis is where big data is most often consumed - driving business intelligence (BI) use cases that discover and report on meaningful patterns in the data. In this session, we will discuss options for processing, analyzing and visualizing data. We will also look at partner solutions and BI-enabling services from AWS. Attendees will learn about optimal approaches for stream processing, batch processing and Interactive analytics. AWS services to be covered include: Amazon Machine Learning, Elastic MapReduce (EMR), and Redshift.
(HLS402) Getting into Your Genes: The Definitive Guide to Using Amazon EMR, A...Amazon Web Services
The key to fighting cancer through better therapeutics is a deep understanding of the basic biology of this disease at a cellular and molecular level. Comprehensive analysis of cancer mutations in specific tumors or cancer cell lines by using Life Technologies sequencing and real-time PCR systems generates gigabytes to terabytes of data every day. Our customers bring together this data in studies that seek to discover the genetic fingerprint of cancer. The data typically translates to millions of records in databases that require complex algorithmic processing, cross-application analysis, and interactive visualizations with real-time response (2-3 seconds) to enable users to consume large volumes of complex scientific information.
We have chosen the AWS platform to bring this new era of data analysis power to our customers by using technologies such as Amazon S3, ElastiCache, and DynamoDB for storage and fast access and Amazon EMR for parallelizing complex computations. Our talk tells the story with rich details about challenges and roadblocks in building data-intense, highly interactive applications in the cloud. We also highlight enhanced customer workflows and highly optimized applications with orders of magnitude improvement in performance and scalability.
ABD327_Migrating Your Traditional Data Warehouse to a Modern Data LakeAmazon Web Services
In this session, we discuss the latest features of Amazon Redshift and Redshift Spectrum, and take a deep dive into its architecture and inner workings. We share many of the recent availability, performance, and management enhancements and how they improve your end user experience. You also hear from 21st Century Fox, who presents a case study of their fast migration from an on-premises data warehouse to Amazon Redshift. Learn how they are expanding their data warehouse to a data lake that encompasses multiple data sources and data formats. This architecture helps them tie together siloed business units and get actionable 360-degree insights across their consumer base.
Big Data adoption success using AWS Big Data Services - Pop-up Loft TLV 2017Amazon Web Services
In today’s session we will share with you an overview of what the typical challenges when adoption Big Data are, and how the AWS Big Data platform allows you to tackle this challenges and leverage the right Analytical/Big Data solutions in order to become successful with your strategy (Whiteboard presentation)
Keith Norbie Flash Storage decision methodology - mnvmugKeith Norbie
This is a presentation for the Minnesota VMUG 3/28/2014. This focuses on Flash Storage Buying Criteria and help in decision making. We cover all types of flash (SLC, MLC, eMLC), categories (Host, network, AFA, hybrid), and factors that matters.
Similar to Au cœur de la roadmap de la Suite Elastic (20)
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Eze Castle Integration is a managed service provider (MSP), cloud service provider (CSP), and internet service provider (ISP) that delivers services to more than 1,000 clients around the world. Different departments within Eze Castle have devised their own log aggregation solutions in order to provide visibility, meet regulatory compliance requirements, conduct cybersecurity investigations, and help engineers with troubleshooting infrastructure issues. In 2019, they partnered with Elastic to consolidate the data generated from different systems into a single pane of glass. And thanks to the ease of deployment on Elastic Cloud, professional consultation services from Elastic engineers, and on-demand training courses available on Elastic Learning, Eze Castle was able to go from proof-of-concept to a fully functioning ""Eze Managed SIEM"" product within a month!
Learn about Eze Castle's journey with Elastic and how they grew Eze Managed SIEM from zero to 100 customers In less than 14 months.
Cómo crear excelentes experiencias de búsqueda en sitios webElasticsearch
Descubre lo fácil que es crear búsquedas relevantes y enriquecidas en sitios web de cara al público para impulsar las conversiones, incrementar el consumo de contenido y ayudar a los visitantes a encontrar lo que necesitan. Realiza un recorrido por las herramientas de Elastic a las que puedes sacar partido para transformar con facilidad tu sitio web, lo que incluye nuestro nuevo y potente rastreador web.
Te damos la bienvenida a una nueva forma de realizar búsquedas Elasticsearch
Al igual que la mayoría de las organizaciones modernas, tus equipos probablemente usan más de 10 aplicaciones basadas en la nube a diario, pero dedican demasiado tiempo a buscar la información que necesitan en todas estas. Gracias a las características integradas de Elastic Workplace Search, podrás comprobar lo sencillo que resulta poner el contenido relevante al alcance de tus equipos gracias a la búsqueda unificada para todas las aplicaciones que usan para llevar a cabo su trabajo.
Tirez pleinement parti d'Elastic grâce à Elastic CloudElasticsearch
Découvrez pourquoi Elastic Cloud est la solution idéale pour exploiter toutes les offres d'Elastic. Bénéficiez d'une flexibilité d'achat et de déploiement au sein de Google Cloud, de Microsoft Azure, d'Amazon Web Services ou des trois à la fois. Apprenez quels avantages vous apporte une offre de service géré et déterminez la solution qui vous permet de la gérer par vous-même grâce à des outils intégrés d'automatisation et d'orchestration. Et ce n'est pas tout ! Familiarisez-vous avec les fonctionnalités qui peuvent vous aider à scaler vos opérations au fur et à mesure de l'évolution de votre déploiement, à stocker vos données d'une manière rentable et à optimiser vos recherches. Ainsi, vous n'aurez plus à abandonner de données et obtiendrez les informations exploitables dont vous avez besoin pour assurer le fonctionnement de votre entreprise.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Plongez au cœur de la recherche dans tous ses états.Elasticsearch
À l'instar de la plupart des entreprises modernes, vos équipes utilisent probablement plus de 10 applications hébergées dans le cloud chaque jour, mais passent aussi bien trop de temps à chercher les informations dont elles ont besoin dans ces outils. Grâce aux fonctionnalités prêtes à l'emploi d'Elastic Workplace Search, découvrez combien il est facile de mettre le contenu pertinent à portée de la main de vos équipes grâce à une recherche unifiée sur l'ensemble des applications qu'elles utilisent pour faire leur travail.
Modernising One Legal Se@rch with Elastic Enterprise Search [Customer Story]Elasticsearch
Knowledge management needs in the legal sector, why Linklaters decided to move away from its legacy KM search engine, Kin+Carta's management of the migration process, and how the switch revitalised a well-established system and opened up new possibilities for its future development.
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Like most modern organizations, your teams are likely using upwards of 10 cloud-based applications on a daily basis, but spending far too many hours a day searching for the information they need across all of them. With the out-of-the-box capabilities of Elastic Workplace Search, see how easy it is to put relevant content right at your teams’ fingertips with unified search across all the apps they rely on to get work done.
Building great website search experiencesElasticsearch
Discover how easy it is to create rich, relevant search on public facing websites that drives conversion, increases content consumption, and helps visitors find what they need. Get a tour of the Elastic tools you can leverage to easily transform your website, including our powerful new web crawler.
Keynote: Harnessing the power of Elasticsearch for simplified searchElasticsearch
Get an overview of the innovation Elastic is bringing to the Enterprise Search landscape, and learn how you can harness these capabilities across your technology landscape to make the power of search work for you.
Cómo transformar los datos en análisis con los que tomar decisionesElasticsearch
Descubre las áreas de características estratégicas de Elastic Stack: Elasticsearch, un motor de datos inigualable y Kibana, la ventana que da acceso a Elastic Stack.
En la sesión hablaremos sobre:
Cómo incorporar datos a Elastic Stack
Almacenamiento de datos
Análisis de los datos
Actuar en función de los datos
Explore relève les défis Big Data avec Elastic Cloud Elasticsearch
Spécialisée dans le développement et la gestion de solutions de veille documentaire et commerciale, Explore offre à ses clients une lecture précise et organisée de l’actualités des marchés et projets sur leurs territoires d'intervention. Afin de rendre leur offre plus agile et performante, Explore a choisi l’offre Elastic Cloud hébergée sur Microsoft Azure. Découvrez comment les équipes de production et de développement sont désormais en mesure de mieux exploiter les données pour les clients d’Explore et gagnent du temps sur la gestion de leur infrastructure.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Transforming data into actionable insightsElasticsearch
Learn about the strategic feature areas of the Elastic Stack—Elasticsearch, a data engine like no other, and Kibana, the window into the Elastic Stack.
The session will cover:
Bringing data into the Elastic Stack
Storing data
Analyzing data
Acting on data
"Elastic enables the world’s leading organization to exceed their business objectives and power their mission-critical systems by eliminating data silos, connecting the dots, and transforming data of all types into actionable insights.
Come learn how the power of search can help you quickly surface relevant insights at scale. Whether you are an executive looking to reduce operational costs, a department head striving to do more with fewer tools, or engineer monitoring and protecting your IT environment, this session is for you. "
Empowering agencies using Elastic as a Service inside GovernmentElasticsearch
It has now been four years since the beta release of Elastic Cloud Enterprise which kicked off a wave of the Elastic public sector community running Elastic as a service within Government rather than utilizing purely hosted solutions. Fast forward to 2021 and we have multiple options for multiple mission needs. Learn top tips from Elastic architects and their experience enabling their teams with the automation and provisioning of Elastic tech to change the game in how government delivers solutions.
The opportunities and challenges of data for public goodElasticsearch
Data is an increasingly valuable resource for delivering economic and social benefit. Heather will discuss the challenges and opportunities, and how communities at all levels of the public sector can play a part in leading the change.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
36. Elasticsearch is built for speed
• Every field is indexed
• Indexes built at ingest
• Denormalized data, no joins
• Distributed execution
But needs disk, cpu, memory!
42. Find users who:
• in the previous 12 months
• have used an application
• on today’s Malicious Apps list
• with param “powershell.exe”
43. Find users who:
• in the previous 12 months
• have used an application
• on today’s Malicious Apps list
• with param “powershell.exe”
Limited Join
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44. Find users who:
• in the previous 12 months
• have used an application
• on today’s Malicious Apps list
• with param “powershell.exe”
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