OpenSearch is a community-driven, open source search and analytics suite derived from Elasticsearch 7.10.2 and Kibana 7.10.2. It was initiated by AWS and consists of the OpenSearch search engine and OpenSearch Dashboards visualization interface. OpenSearch aims to provide a true open source search and analytics engine following licensing changes by Elastic that removed Elasticsearch's open source status.
OpenSearch is a specification that describes how to build search services for the open web. It uses XML to describe search services and publishes search results in RSS or Atom formats. Key features include autodiscovery of services, search result descriptions, and URL templates that clients use to compose search requests to the service. Many websites and browsers support OpenSearch to allow discovery and use of new search services.
What is Amazon OpenSearch Service?
OpenSearch is a distributed, open-source search and analytics package that may be used for real-
time application monitoring, log analysis, and internet search, among other things. With OpenSearch
Dashboards, an integrated visualization tool that makes it easy for users to examine their data,
OpenSearch provides a highly scalable solution for quick access and reaction to massive amounts of
data. The Apache Lucene search library, as well as OpenSearch, Elasticsearch, and Apache Solr,
support it. Elasticsearch 7.10.2 and Kibana 7.10.2 were used to create OpenSearch and OpenSearch
Dashboards. The Apache License Version 2.0 applies to all software in the OpenSearch project (ALv2).
In this presentation, we are going to discuss how elasticsearch handles the various operations like insert, update, delete. We would also cover what is an inverted index and how segment merging works.
An introduction to elasticsearch with a short demonstration on Kibana to present the search API. The slide covers:
- Quick overview of the Elastic stack
- indexation
- Analysers
- Relevance score
- One use case of elasticsearch
The query used for the Kibana demonstration can be found here:
https://github.com/melvynator/elasticsearch_presentation
Elasticsearch Tutorial | Getting Started with Elasticsearch | ELK Stack Train...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka Elasticsearch Tutorial will help you in understanding the fundamentals of Elasticsearch along with its practical usage and help you in building a strong foundation in ELK Stack. This video helps you to learn following topics:
1. What Is Elasticsearch?
2. Why Elasticsearch?
3. Elasticsearch Advantages
4. Elasticsearch Installation
5. API Conventions
6. Elasticsearch Query DSL
7. Mapping
8. Analysis
9 Modules
This slide deck talks about Elasticsearch and its features.
When you talk about ELK stack it just means you are talking
about Elasticsearch, Logstash, and Kibana. But when you talk
about Elastic stack, other components such as Beats, X-Pack
are also included with it.
what is the ELK Stack?
ELK vs Elastic stack
What is Elasticsearch used for?
How does Elasticsearch work?
What is an Elasticsearch index?
Shards
Replicas
Nodes
Clusters
What programming languages does Elasticsearch support?
Amazon Elasticsearch, its use cases and benefits
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
Elasticsearch is a free and open source distributed search and analytics engine. It allows documents to be indexed and searched quickly and at scale. Elasticsearch is built on Apache Lucene and uses RESTful APIs. Documents are stored in JSON format across distributed shards and replicas for fault tolerance and scalability. Elasticsearch is used by many large companies due to its ability to easily scale with data growth and handle advanced search functions.
OpenSearch is a specification that describes how to build search services for the open web. It uses XML to describe search services and publishes search results in RSS or Atom formats. Key features include autodiscovery of services, search result descriptions, and URL templates that clients use to compose search requests to the service. Many websites and browsers support OpenSearch to allow discovery and use of new search services.
What is Amazon OpenSearch Service?
OpenSearch is a distributed, open-source search and analytics package that may be used for real-
time application monitoring, log analysis, and internet search, among other things. With OpenSearch
Dashboards, an integrated visualization tool that makes it easy for users to examine their data,
OpenSearch provides a highly scalable solution for quick access and reaction to massive amounts of
data. The Apache Lucene search library, as well as OpenSearch, Elasticsearch, and Apache Solr,
support it. Elasticsearch 7.10.2 and Kibana 7.10.2 were used to create OpenSearch and OpenSearch
Dashboards. The Apache License Version 2.0 applies to all software in the OpenSearch project (ALv2).
In this presentation, we are going to discuss how elasticsearch handles the various operations like insert, update, delete. We would also cover what is an inverted index and how segment merging works.
An introduction to elasticsearch with a short demonstration on Kibana to present the search API. The slide covers:
- Quick overview of the Elastic stack
- indexation
- Analysers
- Relevance score
- One use case of elasticsearch
The query used for the Kibana demonstration can be found here:
https://github.com/melvynator/elasticsearch_presentation
Elasticsearch Tutorial | Getting Started with Elasticsearch | ELK Stack Train...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka Elasticsearch Tutorial will help you in understanding the fundamentals of Elasticsearch along with its practical usage and help you in building a strong foundation in ELK Stack. This video helps you to learn following topics:
1. What Is Elasticsearch?
2. Why Elasticsearch?
3. Elasticsearch Advantages
4. Elasticsearch Installation
5. API Conventions
6. Elasticsearch Query DSL
7. Mapping
8. Analysis
9 Modules
This slide deck talks about Elasticsearch and its features.
When you talk about ELK stack it just means you are talking
about Elasticsearch, Logstash, and Kibana. But when you talk
about Elastic stack, other components such as Beats, X-Pack
are also included with it.
what is the ELK Stack?
ELK vs Elastic stack
What is Elasticsearch used for?
How does Elasticsearch work?
What is an Elasticsearch index?
Shards
Replicas
Nodes
Clusters
What programming languages does Elasticsearch support?
Amazon Elasticsearch, its use cases and benefits
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
Elasticsearch is a free and open source distributed search and analytics engine. It allows documents to be indexed and searched quickly and at scale. Elasticsearch is built on Apache Lucene and uses RESTful APIs. Documents are stored in JSON format across distributed shards and replicas for fault tolerance and scalability. Elasticsearch is used by many large companies due to its ability to easily scale with data growth and handle advanced search functions.
Talk given for the #phpbenelux user group, March 27th in Gent (BE), with the goal of convincing developers that are used to build php/mysql apps to broaden their horizon when adding search to their site. Be sure to also have a look at the notes for the slides; they explain some of the screenshots, etc.
An accompanying blog post about this subject can be found at http://www.jurriaanpersyn.com/archives/2013/11/18/introduction-to-elasticsearch/
Data Con LA 2022 - Pre- Recorded - OpenSearch: Everything You Need to Know Ab...Data Con LA
Seth Muthukaruppan, Consultant at Instacluster
Data Engineering
OpenSearch is an incredibly powerful search engine and analytics suite for ingesting, searching, visualizing, and analyzing your data and it is fully open source. This Apache 2.0-licensed and community-driven collection of technologies harnesses an architecture that combines the powers of Elasticsearch 7.10.2, Kibana 7.10.2 and Apache Lucene. With OpenSearch, users gain a distributed framework featuring particularly powerful scalability, high availability, and database-like capabilities. Attendees at this DataCon LA presentation will come away understanding OpenSearch's architecture and its building-block technology components, including: -- Apache Lucene utilization. Learn how this high-performance Java-based search library utilizes Lucene's inverted search index to delivers incredibly fast search results (while supporting natural language, wildcard, fuzzy, and proximity searches). -- OpenSearch cluster architecture. An OpenSearch cluster is a distributed and horizontally-scalable collection of nodes, which are differentiated based on the operations they perform. Attendees will learn the specific functions of master, master-eligible, data, client, ingest nodes. -- Data organization. Understand how OpenSearch organizes data into indices (which contain documents, which contain fields). -- Internal data structures. Get an in-depth look at how OpenSearch achieves scalability and reliability by breaking up indices into shards and segments, and utilizes translogs. -- Aggregations. See how OpenSearch enables its advanced built-in analytics capabilities through the power of aggregations.
Deep Dive on ElasticSearch Meetup event on 23rd May '15 at www.meetup.com/abctalks
Agenda:
1) Introduction to NOSQL
2) What is ElasticSearch and why is it required
3) ElasticSearch architecture
4) Installation of ElasticSearch
5) Hands on session on ElasticSearch
Introduction to Elasticsearch with basics of LuceneRahul Jain
Rahul Jain gives an introduction to Elasticsearch and its basic concepts like term frequency, inverse document frequency, and boosting. He describes Lucene as a fast, scalable search library that uses inverted indexes. Elasticsearch is introduced as an open source search platform built on Lucene that provides distributed indexing, replication, and load balancing. Logstash and Kibana are also briefly described as tools for collecting, parsing, and visualizing logs in Elasticsearch.
This document provides an overview and introduction to Elasticsearch. It discusses the speaker's experience and community involvement. It then covers how to set up Elasticsearch and Kibana locally. The rest of the document describes various Elasticsearch concepts and features like clusters, nodes, indexes, documents, shards, replicas, and building search-based applications. It also discusses using Elasticsearch for big data, different search capabilities, and text analysis.
Elasticsearch is a distributed, open source search and analytics engine that allows full-text searches of structured and unstructured data. It is built on top of Apache Lucene and uses JSON documents. Elasticsearch can index, search, and analyze big volumes of data in near real-time. It is horizontally scalable, fault tolerant, and easy to deploy and administer.
The document introduces the ELK stack, which consists of Elasticsearch, Logstash, Kibana, and Beats. Beats ship log and operational data to Elasticsearch. Logstash ingests, transforms, and sends data to Elasticsearch. Elasticsearch stores and indexes the data. Kibana allows users to visualize and interact with data stored in Elasticsearch. The document provides descriptions of each component and their roles. It also includes configuration examples and demonstrates how to access Elasticsearch via REST.
This document provides an introduction and overview of Elasticsearch. It discusses installing Elasticsearch and configuring it through the elasticsearch.yml file. It describes tools like Marvel and Sense that can be used for monitoring Elasticsearch. Key terms used in Elasticsearch like nodes, clusters, indices, and documents are explained. The document outlines how to index and retrieve data from Elasticsearch through its RESTful API using either search lite queries or the query DSL.
A brief presentation outlining the basics of elasticsearch for beginners. Can be used to deliver a seminar on elasticsearch.(P.S. I used it) Would Recommend the presenter to fiddle with elasticsearch beforehand.
This document discusses the ELK stack, which consists of Elasticsearch, Logstash, and Kibana. It provides an overview of each component, including that Elasticsearch is a search and analytics engine, Logstash is a data collection engine, and Kibana is a data visualization platform. The document then discusses setting up an ELK stack to index and visualize application logs.
The talk covers how Elasticsearch, Lucene and to some extent search engines in general actually work under the hood. We'll start at the "bottom" (or close enough!) of the many abstraction levels, and gradually move upwards towards the user-visible layers, studying the various internal data structures and behaviors as we ascend. Elasticsearch provides APIs that are very easy to use, and it will get you started and take you far without much effort. However, to get the most of it, it helps to have some knowledge about the underlying algorithms and data structures. This understanding enables you to make full use of its substantial set of features such that you can improve your users search experiences, while at the same time keep your systems performant, reliable and updated in (near) real time.
This document discusses Elasticsearch, an open source search engine that can handle large volumes of data in real time. It is based on Apache Lucene, a full-text search engine, and was developed by Shay Banon in 2010. Elasticsearch stores data in JSON documents and works by indexing these documents so they can be quickly searched. Some key advantages include being RESTful, scalable, simple and transparent, and fast. Disadvantages include only supporting JSON for requests and responses as well as some challenges around processing. The document recommends starting with the official Elasticsearch documentation.
by Darin Briskman, Technical Evangelist, AWS
Elasticsearch is the most popular open-source search and analytics engine - it's easy to use, but not always easy to configure an manage. Learn about Amazon's fully managed service that provides easier deployment, operation, and scale for Elasticsearch. Level: 200
EMR 플랫폼 기반의 Spark 워크로드 실행 최적화 방안 - 정세웅, AWS 솔루션즈 아키텍트:: AWS Summit Online Ko...Amazon Web Services Korea
발표영상 다시보기: https://youtu.be/hPvBst9TPlI
S3 기반의 데이터레이크에서 대량의 데이터 변환과 처리에 사용될 수 있는 가장 대표적인 솔루션이 Apache Spark 입니다. EMR 플랫폼 환경에서 쉽게 적용 가능한 Apache Spark의 성능 향상 팁을 소개합니다. 또한 데이터의 레코드 레벨 업데이트, 리소스 확장, 권한 관리 및 모니터링과 같은 다양한 데이터 워크로드 관리 최적화 방안을 함께 살펴봅니다.
Elasticsearch is a distributed, open source search and analytics engine built on Apache Lucene. It allows storing and searching of documents of any schema in JSON format. Documents are organized into indexes which can have multiple shards and replicas for scalability and high availability. Elasticsearch provides a RESTful API and can be easily extended with plugins. It is widely used for full-text search, structured search, analytics and more in applications requiring real-time search and analytics of large volumes of data.
데이터 분석가를 위한 신규 분석 서비스 - 김기영, AWS 분석 솔루션즈 아키텍트 / 변규현, 당근마켓 소프트웨어 엔지니어 :: AWS r...Amazon Web Services Korea
AWS re:Invent에서는 다양한 고객들의 요구에 맞추어 새로운 분석 및 서버리스 서비스가 대거 출시되었습니다. 본 강연에서는 새롭게 출시된 핵심 분석 기능들과 함께, 누구나 손쉽게 사용할 수 있는 AWS의 분석 서버리스와 On-demand 기능들에 대한 심층적인 정보를 확인하실 수 있습니다.
Centralized log-management-with-elastic-stackRich Lee
Centralized log management is implemented using the Elastic Stack including Filebeat, Logstash, Elasticsearch, and Kibana. Filebeat ships logs to Logstash which transforms and indexes the data into Elasticsearch. Logs can then be queried and visualized in Kibana. For large volumes of logs, Kafka may be used as a buffer between the shipper and indexer. Backups are performed using Elasticsearch snapshots to a shared file system or cloud storage. Logs are indexed into time-based indices and a cron job deletes old indices to control storage usage.
OpenSearch는 배포형 오픈 소스 검색과 분석 제품군으로 실시간 애플리케이션 모니터링, 로그 분석 및 웹 사이트 검색과 같이 다양한 사용 사례에 사용됩니다. OpenSearch는 데이터 탐색을 쉽게 도와주는 통합 시각화 도구 OpenSearch와 함께 뛰어난 확장성을 지닌 시스템을 제공하여 대량 데이터 볼륨에 빠르게 액세스 및 응답합니다. 이 세션에서는 실제 동작 구조에 대한 설명을 바탕으로 최적화를 하기 위한 방법과 운영상에 발생할 수 있는 이슈에 대해서 알아봅니다.
Data Con LA 2022-Open Source or Open Core in Your Data Layer? What Needs to B...Data Con LA
Open source software has progressed from being developed primarily by individuals and small teams to large projects overseen by foundations or commercial entities. There are debates around fully open source projects versus open core models, where core functionality is open but additional features are proprietary. Key considerations for organizations evaluating options include licensing terms, governance structures, impact on branding, available business models, and the overall ecosystem of users and contributors. While open core can provide traditional software vendor advantages, fully open source alternatives aim to avoid vendor lock-in and keep intellectual property communal.
Easy and Scalable Log Analytics with Amazon Elasticsearch Service - ABD326 - ...Amazon Web Services
- Applications generate logs. Infrastructure generates logs. Even humans generate logs (though we usually call that “medical data”). By ingesting and analyzing logs, you can gain understanding of how complex systems operate and quickly discover and diagnose when they don’t work as they should. In this workshop, we ingest and analyze log streams using Amazon Kinesis Firehose and Amazon Elasticsearch Service. You should come with an understanding of AWS fundamentals (Amazon EC2, Amazon S3, and security groups). You need a laptop with a Chrome or Firefox browser.
Talk given for the #phpbenelux user group, March 27th in Gent (BE), with the goal of convincing developers that are used to build php/mysql apps to broaden their horizon when adding search to their site. Be sure to also have a look at the notes for the slides; they explain some of the screenshots, etc.
An accompanying blog post about this subject can be found at http://www.jurriaanpersyn.com/archives/2013/11/18/introduction-to-elasticsearch/
Data Con LA 2022 - Pre- Recorded - OpenSearch: Everything You Need to Know Ab...Data Con LA
Seth Muthukaruppan, Consultant at Instacluster
Data Engineering
OpenSearch is an incredibly powerful search engine and analytics suite for ingesting, searching, visualizing, and analyzing your data and it is fully open source. This Apache 2.0-licensed and community-driven collection of technologies harnesses an architecture that combines the powers of Elasticsearch 7.10.2, Kibana 7.10.2 and Apache Lucene. With OpenSearch, users gain a distributed framework featuring particularly powerful scalability, high availability, and database-like capabilities. Attendees at this DataCon LA presentation will come away understanding OpenSearch's architecture and its building-block technology components, including: -- Apache Lucene utilization. Learn how this high-performance Java-based search library utilizes Lucene's inverted search index to delivers incredibly fast search results (while supporting natural language, wildcard, fuzzy, and proximity searches). -- OpenSearch cluster architecture. An OpenSearch cluster is a distributed and horizontally-scalable collection of nodes, which are differentiated based on the operations they perform. Attendees will learn the specific functions of master, master-eligible, data, client, ingest nodes. -- Data organization. Understand how OpenSearch organizes data into indices (which contain documents, which contain fields). -- Internal data structures. Get an in-depth look at how OpenSearch achieves scalability and reliability by breaking up indices into shards and segments, and utilizes translogs. -- Aggregations. See how OpenSearch enables its advanced built-in analytics capabilities through the power of aggregations.
Deep Dive on ElasticSearch Meetup event on 23rd May '15 at www.meetup.com/abctalks
Agenda:
1) Introduction to NOSQL
2) What is ElasticSearch and why is it required
3) ElasticSearch architecture
4) Installation of ElasticSearch
5) Hands on session on ElasticSearch
Introduction to Elasticsearch with basics of LuceneRahul Jain
Rahul Jain gives an introduction to Elasticsearch and its basic concepts like term frequency, inverse document frequency, and boosting. He describes Lucene as a fast, scalable search library that uses inverted indexes. Elasticsearch is introduced as an open source search platform built on Lucene that provides distributed indexing, replication, and load balancing. Logstash and Kibana are also briefly described as tools for collecting, parsing, and visualizing logs in Elasticsearch.
This document provides an overview and introduction to Elasticsearch. It discusses the speaker's experience and community involvement. It then covers how to set up Elasticsearch and Kibana locally. The rest of the document describes various Elasticsearch concepts and features like clusters, nodes, indexes, documents, shards, replicas, and building search-based applications. It also discusses using Elasticsearch for big data, different search capabilities, and text analysis.
Elasticsearch is a distributed, open source search and analytics engine that allows full-text searches of structured and unstructured data. It is built on top of Apache Lucene and uses JSON documents. Elasticsearch can index, search, and analyze big volumes of data in near real-time. It is horizontally scalable, fault tolerant, and easy to deploy and administer.
The document introduces the ELK stack, which consists of Elasticsearch, Logstash, Kibana, and Beats. Beats ship log and operational data to Elasticsearch. Logstash ingests, transforms, and sends data to Elasticsearch. Elasticsearch stores and indexes the data. Kibana allows users to visualize and interact with data stored in Elasticsearch. The document provides descriptions of each component and their roles. It also includes configuration examples and demonstrates how to access Elasticsearch via REST.
This document provides an introduction and overview of Elasticsearch. It discusses installing Elasticsearch and configuring it through the elasticsearch.yml file. It describes tools like Marvel and Sense that can be used for monitoring Elasticsearch. Key terms used in Elasticsearch like nodes, clusters, indices, and documents are explained. The document outlines how to index and retrieve data from Elasticsearch through its RESTful API using either search lite queries or the query DSL.
A brief presentation outlining the basics of elasticsearch for beginners. Can be used to deliver a seminar on elasticsearch.(P.S. I used it) Would Recommend the presenter to fiddle with elasticsearch beforehand.
This document discusses the ELK stack, which consists of Elasticsearch, Logstash, and Kibana. It provides an overview of each component, including that Elasticsearch is a search and analytics engine, Logstash is a data collection engine, and Kibana is a data visualization platform. The document then discusses setting up an ELK stack to index and visualize application logs.
The talk covers how Elasticsearch, Lucene and to some extent search engines in general actually work under the hood. We'll start at the "bottom" (or close enough!) of the many abstraction levels, and gradually move upwards towards the user-visible layers, studying the various internal data structures and behaviors as we ascend. Elasticsearch provides APIs that are very easy to use, and it will get you started and take you far without much effort. However, to get the most of it, it helps to have some knowledge about the underlying algorithms and data structures. This understanding enables you to make full use of its substantial set of features such that you can improve your users search experiences, while at the same time keep your systems performant, reliable and updated in (near) real time.
This document discusses Elasticsearch, an open source search engine that can handle large volumes of data in real time. It is based on Apache Lucene, a full-text search engine, and was developed by Shay Banon in 2010. Elasticsearch stores data in JSON documents and works by indexing these documents so they can be quickly searched. Some key advantages include being RESTful, scalable, simple and transparent, and fast. Disadvantages include only supporting JSON for requests and responses as well as some challenges around processing. The document recommends starting with the official Elasticsearch documentation.
by Darin Briskman, Technical Evangelist, AWS
Elasticsearch is the most popular open-source search and analytics engine - it's easy to use, but not always easy to configure an manage. Learn about Amazon's fully managed service that provides easier deployment, operation, and scale for Elasticsearch. Level: 200
EMR 플랫폼 기반의 Spark 워크로드 실행 최적화 방안 - 정세웅, AWS 솔루션즈 아키텍트:: AWS Summit Online Ko...Amazon Web Services Korea
발표영상 다시보기: https://youtu.be/hPvBst9TPlI
S3 기반의 데이터레이크에서 대량의 데이터 변환과 처리에 사용될 수 있는 가장 대표적인 솔루션이 Apache Spark 입니다. EMR 플랫폼 환경에서 쉽게 적용 가능한 Apache Spark의 성능 향상 팁을 소개합니다. 또한 데이터의 레코드 레벨 업데이트, 리소스 확장, 권한 관리 및 모니터링과 같은 다양한 데이터 워크로드 관리 최적화 방안을 함께 살펴봅니다.
Elasticsearch is a distributed, open source search and analytics engine built on Apache Lucene. It allows storing and searching of documents of any schema in JSON format. Documents are organized into indexes which can have multiple shards and replicas for scalability and high availability. Elasticsearch provides a RESTful API and can be easily extended with plugins. It is widely used for full-text search, structured search, analytics and more in applications requiring real-time search and analytics of large volumes of data.
데이터 분석가를 위한 신규 분석 서비스 - 김기영, AWS 분석 솔루션즈 아키텍트 / 변규현, 당근마켓 소프트웨어 엔지니어 :: AWS r...Amazon Web Services Korea
AWS re:Invent에서는 다양한 고객들의 요구에 맞추어 새로운 분석 및 서버리스 서비스가 대거 출시되었습니다. 본 강연에서는 새롭게 출시된 핵심 분석 기능들과 함께, 누구나 손쉽게 사용할 수 있는 AWS의 분석 서버리스와 On-demand 기능들에 대한 심층적인 정보를 확인하실 수 있습니다.
Centralized log-management-with-elastic-stackRich Lee
Centralized log management is implemented using the Elastic Stack including Filebeat, Logstash, Elasticsearch, and Kibana. Filebeat ships logs to Logstash which transforms and indexes the data into Elasticsearch. Logs can then be queried and visualized in Kibana. For large volumes of logs, Kafka may be used as a buffer between the shipper and indexer. Backups are performed using Elasticsearch snapshots to a shared file system or cloud storage. Logs are indexed into time-based indices and a cron job deletes old indices to control storage usage.
OpenSearch는 배포형 오픈 소스 검색과 분석 제품군으로 실시간 애플리케이션 모니터링, 로그 분석 및 웹 사이트 검색과 같이 다양한 사용 사례에 사용됩니다. OpenSearch는 데이터 탐색을 쉽게 도와주는 통합 시각화 도구 OpenSearch와 함께 뛰어난 확장성을 지닌 시스템을 제공하여 대량 데이터 볼륨에 빠르게 액세스 및 응답합니다. 이 세션에서는 실제 동작 구조에 대한 설명을 바탕으로 최적화를 하기 위한 방법과 운영상에 발생할 수 있는 이슈에 대해서 알아봅니다.
Data Con LA 2022-Open Source or Open Core in Your Data Layer? What Needs to B...Data Con LA
Open source software has progressed from being developed primarily by individuals and small teams to large projects overseen by foundations or commercial entities. There are debates around fully open source projects versus open core models, where core functionality is open but additional features are proprietary. Key considerations for organizations evaluating options include licensing terms, governance structures, impact on branding, available business models, and the overall ecosystem of users and contributors. While open core can provide traditional software vendor advantages, fully open source alternatives aim to avoid vendor lock-in and keep intellectual property communal.
Easy and Scalable Log Analytics with Amazon Elasticsearch Service - ABD326 - ...Amazon Web Services
- Applications generate logs. Infrastructure generates logs. Even humans generate logs (though we usually call that “medical data”). By ingesting and analyzing logs, you can gain understanding of how complex systems operate and quickly discover and diagnose when they don’t work as they should. In this workshop, we ingest and analyze log streams using Amazon Kinesis Firehose and Amazon Elasticsearch Service. You should come with an understanding of AWS fundamentals (Amazon EC2, Amazon S3, and security groups). You need a laptop with a Chrome or Firefox browser.
The document provides an overview of Open Stack cloud services. It discusses key aspects of Open Source, cloud computing, hypervisors, Open Stack, and compares Open Stack to other cloud platforms like CloudStack and Eucalyptus. The document highlights that Open Stack provides the features required for IaaS cloud services, but some integration work is needed to commercialize it. It also notes that while the platforms differ in codebase and hypervisor support, choosing a good management layer allows portability between platforms.
More at http://cloudify.co
Nati Shalom ask the question - is OpenStack ready for serverless? He discusses Lambda, Azure and Google and where they stand as well as whether OpenStack will make it in this space.
This document introduces Open High Availability Cluster (Open HA Cluster), an open source version of Solaris Cluster. It discusses why high availability is important, how Solaris Cluster provides high availability, available cluster agents, and how developers can use and contribute to Open HA Cluster.
CloudFoundry is a mature and production-ready opensource Platform-as-a-Service. That can serve as standard app deployment and hosting platform for enterprise. This talk will focus around CloudFoundry capabilities as private-PaaS
This document provides an overview of OpenStack cloud administration through a live demonstration. It begins with background on cloud computing and an introduction to OpenStack. Key OpenStack components and architecture are described. The demonstration then shows logging into the OpenStack dashboard and creating and managing virtual resources like instances, volumes, and images to administer the private cloud.
OMA LwM2M Workshop - Julien Vermillard, OMA LwM2M Projects in Eclipse FoundationOpen Mobile Alliance
Julien Vermillard from Sierra Wireless presented during the Open Mobile Alliance LwM2M Workshop event on January 28, 2015. This is a copy of the slides presented for his session titled, "OMA LwM2M Projects in Eclipse Foundation".
Delivering IaaS with Open Source SoftwareMark Hinkle
Mark Hinkle presented on delivering Infrastructure-as-a-Service (IaaS) using open source software. He discussed various open source tools for building cloud computing including hypervisors like KVM and Xen, object storage solutions like OpenStack Swift, and automation/orchestration tools like CloudStack and OpenStack. Hinkle emphasized that open source solutions provide many advantages for cloud computing including lower costs, collaboration, and avoidance of vendor lock-in. He also covered management tools for private clouds and highlighted the importance of automation.
OpenStack Administration by Mobarak Hossain Group Organizer BangladeshMobarak Hossain
This document provides an overview of an OpenStack training organized by Mobarak Hossain. It includes details about Mobarak Hossain's background and experience working for various companies in software and telecom. It also provides a brief history of cloud computing and OpenStack, describing some of the major OpenStack services and concepts. The document concludes with information about hands-on sessions for installing and using OpenStack.
by Andy Mui, Solutions Architect, AWS
Join this workshop to get hands-on experience deploying Docker containers as you break an aging monolithic application into containerized microservices. Using Amazon ECS and the Application Load Balancer, you will create API-based microservices and deploy them leveraging integrations with other AWS services.
Learn how AWS services can make it easier for you to rapidly release new features, help you avoid downtime during deployment, and handle the complexity of updating your applications.
The document discusses security at scale on AWS. It covers several topics:
- AWS security controls including over 70 services, 7,710 audit artifacts and 3,030 audit requirements.
- How AWS handles security at scale through automation, ubiquitous logging and encryption, and rapid detection and response times of under 10 minutes on average.
- AWS services that can help with security including IAM, CloudTrail, GuardDuty, and AWS Config rules.
- Reference architectures that show how to scale infrastructure securely including using multiple availability zones and services like Route 53, S3, CloudFront, and Lambda.
ECM and Open Source Software: A Disruptive Force in ECM SolutionsJeff Potts
Open source software is finally getting the recognition it deserves from analysts like Forrester and Gartner as a disruptive force in IT. Over the years, open source has “climbed up the stack” from operating systems to databases and now to business applications where it has established a firm foothold in the content management space.What should enterprises know about open source content management? Is it really just for Web Content Management (WCM) or does it meet the needs of broader Enterprise Content Management (ECM) deployments? Arelarge enterprises doing big, meaningful content management projects with open source or is its appeal limited to subsets of the market? What about Enterprise 2.0 initiatives? Can you assemble an Enterprise 2.0 solution from open source components? How does it compare with something like Sharepoint?
Co-Presenter: Linda Nichols
Description:
The current state of cloud design and what it takes for an organization to become cloud native. A look ahead at technologies changing the way cloud software is delivered.
Managing Multiple Clouds in an Enteprise - A Heterogenous LensMayur Shintre
This document provides perspectives on managing multiple clouds in an enterprise setting. It begins by defining key terms like heterogeneous and cloud management platform. It then rationalizes the different layers involved in managing clouds from native cloud APIs and UIs to abstraction libraries and cloud management platforms. It characterizes workloads on different lifecycles and recommends strategies for different types. The document advocates starting with infrastructure as code and investing in open source options before a unified management platform. It emphasizes including all stakeholders and using culture and developer enablement in cloud management.
Introducing Open Distro for Elasticsearch - ADB201 - New York AWS SummitAmazon Web Services
Open Distro for Elasticsearch is a 100% open-source distribution of Elasticsearch, the popular search and analytics engine. In this session, we explore its many new advanced features—previously available only in commercial software—including encryption in transit, role-based access control (RBAC), event monitoring and alerting, SQL support, cluster diagnostics, and more. We also show you how you can join the Open Distro for Elasticsearch community to accelerate open innovation for Elasticsearch.
AWS re:Invent 2016: Open Source at AWS—Contributions, Support, and Engagement...Amazon Web Services
Over the last few years, we have seen a dramatic increase in the use of open source projects as the mainstay of architectures in both startups and enterprises. Many of our customers and partners also run their own open source programs and contribute key technologies to the industry as a whole (see DCS201). At AWS we engage with open source projects in a number of ways. We contribute bug fixes and enhancements to popular projects including our work with the Hadoop ecosystem (see BDM401), Chromium (see BAP305) and (obviously) Boto. We have our own standalone projects including the security library s2n (see NET405) and machine learning project MXnet (see MAC401). We also have services that make open source easier to use like ECS for Docker (see CON316), and RDS for MySQL and PostgreSQL (see DAT305). In this session you will learn about our existing open source work across AWS, and our next steps.
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SMS API Integration in Saudi Arabia| Best SMS API ServiceYara Milbes
Discover the benefits and implementation of SMS API integration in the UAE and Middle East. This comprehensive guide covers the importance of SMS messaging APIs, the advantages of bulk SMS APIs, and real-world case studies. Learn how CEQUENS, a leader in communication solutions, can help your business enhance customer engagement and streamline operations with innovative CPaaS, reliable SMS APIs, and omnichannel solutions, including WhatsApp Business. Perfect for businesses seeking to optimize their communication strategies in the digital age.
SOCRadar's Aviation Industry Q1 Incident Report is out now!
The aviation industry has always been a prime target for cybercriminals due to its critical infrastructure and high stakes. In the first quarter of 2024, the sector faced an alarming surge in cybersecurity threats, revealing its vulnerabilities and the relentless sophistication of cyber attackers.
SOCRadar’s Aviation Industry, Quarterly Incident Report, provides an in-depth analysis of these threats, detected and examined through our extensive monitoring of hacker forums, Telegram channels, and dark web platforms.
Artificia Intellicence and XPath Extension FunctionsOctavian Nadolu
The purpose of this presentation is to provide an overview of how you can use AI from XSLT, XQuery, Schematron, or XML Refactoring operations, the potential benefits of using AI, and some of the challenges we face.
Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
UI5con 2024 - Boost Your Development Experience with UI5 Tooling ExtensionsPeter Muessig
The UI5 tooling is the development and build tooling of UI5. It is built in a modular and extensible way so that it can be easily extended by your needs. This session will showcase various tooling extensions which can boost your development experience by far so that you can really work offline, transpile your code in your project to use even newer versions of EcmaScript (than 2022 which is supported right now by the UI5 tooling), consume any npm package of your choice in your project, using different kind of proxies, and even stitching UI5 projects during development together to mimic your target environment.
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
UI5con 2024 - Bring Your Own Design SystemPeter Muessig
How do you combine the OpenUI5/SAPUI5 programming model with a design system that makes its controls available as Web Components? Since OpenUI5/SAPUI5 1.120, the framework supports the integration of any Web Components. This makes it possible, for example, to natively embed own Web Components of your design system which are created with Stencil. The integration embeds the Web Components in a way that they can be used naturally in XMLViews, like with standard UI5 controls, and can be bound with data binding. Learn how you can also make use of the Web Components base class in OpenUI5/SAPUI5 to also integrate your Web Components and get inspired by the solution to generate a custom UI5 library providing the Web Components control wrappers for the native ones.
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Unveiling the Advantages of Agile Software Development.pdfbrainerhub1
Learn about Agile Software Development's advantages. Simplify your workflow to spur quicker innovation. Jump right in! We have also discussed the advantages.
When it is all about ERP solutions, companies typically meet their needs with common ERP solutions like SAP, Oracle, and Microsoft Dynamics. These big players have demonstrated that ERP systems can be either simple or highly comprehensive. This remains true today, but there are new factors to consider, including a promising new contender in the market that’s Odoo. This blog compares Odoo ERP with traditional ERP systems and explains why many companies now see Odoo ERP as the best choice.
What are ERP Systems?
An ERP, or Enterprise Resource Planning, system provides your company with valuable information to help you make better decisions and boost your ROI. You should choose an ERP system based on your company’s specific needs. For instance, if you run a manufacturing or retail business, you will need an ERP system that efficiently manages inventory. A consulting firm, on the other hand, would benefit from an ERP system that enhances daily operations. Similarly, eCommerce stores would select an ERP system tailored to their needs.
Because different businesses have different requirements, ERP system functionalities can vary. Among the various ERP systems available, Odoo ERP is considered one of the best in the ERp market with more than 12 million global users today.
Odoo is an open-source ERP system initially designed for small to medium-sized businesses but now suitable for a wide range of companies. Odoo offers a scalable and configurable point-of-sale management solution and allows you to create customised modules for specific industries. Odoo is gaining more popularity because it is built in a way that allows easy customisation, has a user-friendly interface, and is affordable. Here, you will cover the main differences and get to know why Odoo is gaining attention despite the many other ERP systems available in the market.
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.