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/
Philly PHP: April '17 Elastic Search Introduction by Aditya BhamidpatiRobert Calcavecchia
Â
Philly PHP April 2017 Meetup: Introduction to Elastic Search as presented by Aditya Bhamidpati on April 19, 2017.
These slides cover an introduction to using Elastic Search
Introduction to Elastic Search
Elastic Search Terminology
Index, Type, Document, Field
Comparison with Relational Database
Understanding of Elastic architecture
Clusters, Nodes, Shards & Replicas
Search
How it works?
Inverted Index
Installation & Configuration
Setup & Run Elastic Server
Elastic in Action
Indexing, Querying & Deleting
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
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/
Philly PHP: April '17 Elastic Search Introduction by Aditya BhamidpatiRobert Calcavecchia
Â
Philly PHP April 2017 Meetup: Introduction to Elastic Search as presented by Aditya Bhamidpati on April 19, 2017.
These slides cover an introduction to using Elastic Search
Introduction to Elastic Search
Elastic Search Terminology
Index, Type, Document, Field
Comparison with Relational Database
Understanding of Elastic architecture
Clusters, Nodes, Shards & Replicas
Search
How it works?
Inverted Index
Installation & Configuration
Setup & Run Elastic Server
Elastic in Action
Indexing, Querying & Deleting
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
Global introduction to elastisearch presented at BigData meetup.
Use cases, getting started, Rest CRUD API, Mapping, Search API, Query DSL with queries and filters, Analyzers, Analytics with facets and aggregations, Percolator, High Availability, Clients & Integrations, ...
Check out my Elasticsearch course and get it for only $10:
https://www.udemy.com/elasticsearch-complete-guide/?couponCode=SLIDESHARE10&utm_source=slideshare&utm_campaign=slideshare&utm_medium=referral
Elasticsearch is quite common tool nowadays. Usually as a part of ELK stack, but in some cases to support main feature of the system as search engine. Documentation on regular use cases and on usage in general is pretty good, but how it really works, how it behaves beneath the surface of the API? This talk is about that, we will look under the hood of Elasticsearch and dive deep in the largely unknown implementation details. Talk covers cluster behaviour, communication with Lucene and Lucene internals to literally bits and pieces. Come and see Elasticsearch dissected.
Elasticsearch as a search alternative to a relational databaseKristijan Duvnjak
Â
The volume of data that we are working with is growing every day, the size of data is pushing us to find new intelligent solutions for problem’s put in front of us. Elasticsearch server has proved it self as an excellent full text search solution for big volume’s of data.
Elasticsearch is a powerful, distributed, open source searching technology. By integrating Elasticsearch into your application, you instantly provide a way to search a lot of data very quickly. Elasticsearch has a RESTful API, it scales, its super fast, you can use plugins to customize it, and much more. In this talk I go over the basics of setting up Elasticsearch, creating a search index, importing your data, and doing some basic searching. I also touch on a few advanced topics that will show the flexibility of this awesome service.
ElasticSearch - index server used as a document databaseRobert Lujo
Â
Presentation held on 5.10.2014 on http://2014.webcampzg.org/talks/.
Although ElasticSearch (ES) primary purpose is to be used as index/search server, in its featureset ES overlaps with common NoSql database; better to say, document database.
Why this could be interesting and how this could be used effectively?
Talk overview:
- ES - history, background, philosophy, featureset overview, focus on indexing/search features
- short presentation on how to get started - installation, indexing and search/retrieving
- Database should provide following functions: store, search, retrieve -> differences between relational, document and search databases
- it is not unusual to use ES additionally as an document database (store and retrieve)
- an use-case will be presented where ES can be used as a single database in the system (benefits and drawbacks)
- what if a relational database is introduced in previosly demonstrated system (benefits and drawbacks)
ES is a nice and in reality ready-to-use example that can change perspective of development of some type of software systems.
An introduction to and a couple of examples and tips on how to use Elasticsearch for general data analytics. Examples are based on Elasticsearch version 2.x.
ElasticSearch in Production: lessons learnedBeyondTrees
Â
With Proquest Udini, we have created the worlds largest online article store, and aim to be the center for researchers all over the world. We connect to a 700M solr cluster for search, but have recently also implemented a search component with ElasticSearch. We will discuss how we did this, and how we want to use the 30M index for scientific citation recognition. We will highlight lessons learned in integrating ElasticSearch in our virtualized EC2 environments, and challenges aligning with our continuous deployment processes.
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.
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.
Global introduction to elastisearch presented at BigData meetup.
Use cases, getting started, Rest CRUD API, Mapping, Search API, Query DSL with queries and filters, Analyzers, Analytics with facets and aggregations, Percolator, High Availability, Clients & Integrations, ...
Check out my Elasticsearch course and get it for only $10:
https://www.udemy.com/elasticsearch-complete-guide/?couponCode=SLIDESHARE10&utm_source=slideshare&utm_campaign=slideshare&utm_medium=referral
Elasticsearch is quite common tool nowadays. Usually as a part of ELK stack, but in some cases to support main feature of the system as search engine. Documentation on regular use cases and on usage in general is pretty good, but how it really works, how it behaves beneath the surface of the API? This talk is about that, we will look under the hood of Elasticsearch and dive deep in the largely unknown implementation details. Talk covers cluster behaviour, communication with Lucene and Lucene internals to literally bits and pieces. Come and see Elasticsearch dissected.
Elasticsearch as a search alternative to a relational databaseKristijan Duvnjak
Â
The volume of data that we are working with is growing every day, the size of data is pushing us to find new intelligent solutions for problem’s put in front of us. Elasticsearch server has proved it self as an excellent full text search solution for big volume’s of data.
Elasticsearch is a powerful, distributed, open source searching technology. By integrating Elasticsearch into your application, you instantly provide a way to search a lot of data very quickly. Elasticsearch has a RESTful API, it scales, its super fast, you can use plugins to customize it, and much more. In this talk I go over the basics of setting up Elasticsearch, creating a search index, importing your data, and doing some basic searching. I also touch on a few advanced topics that will show the flexibility of this awesome service.
ElasticSearch - index server used as a document databaseRobert Lujo
Â
Presentation held on 5.10.2014 on http://2014.webcampzg.org/talks/.
Although ElasticSearch (ES) primary purpose is to be used as index/search server, in its featureset ES overlaps with common NoSql database; better to say, document database.
Why this could be interesting and how this could be used effectively?
Talk overview:
- ES - history, background, philosophy, featureset overview, focus on indexing/search features
- short presentation on how to get started - installation, indexing and search/retrieving
- Database should provide following functions: store, search, retrieve -> differences between relational, document and search databases
- it is not unusual to use ES additionally as an document database (store and retrieve)
- an use-case will be presented where ES can be used as a single database in the system (benefits and drawbacks)
- what if a relational database is introduced in previosly demonstrated system (benefits and drawbacks)
ES is a nice and in reality ready-to-use example that can change perspective of development of some type of software systems.
An introduction to and a couple of examples and tips on how to use Elasticsearch for general data analytics. Examples are based on Elasticsearch version 2.x.
ElasticSearch in Production: lessons learnedBeyondTrees
Â
With Proquest Udini, we have created the worlds largest online article store, and aim to be the center for researchers all over the world. We connect to a 700M solr cluster for search, but have recently also implemented a search component with ElasticSearch. We will discuss how we did this, and how we want to use the 30M index for scientific citation recognition. We will highlight lessons learned in integrating ElasticSearch in our virtualized EC2 environments, and challenges aligning with our continuous deployment processes.
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.
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.
See webinar recording of this presentation at: https://resource.alibabacloud.com/webinar/live.htm?&webinarId=67
In this presentation, you will learn all you need to know about Elasticsearch, one of the most widely used open source search platforms in the world. We will walk you through what Elasticsearch is, why you need it, and show common use cases. First, we will introduce Elastic Search and the best practices for deploying it, as well as show what some of the salient features of the platform are. 
In the second part of the webinar, we delve into the various use cases for Elasticsearch and show why it is an excellent platform to query a large dataset. This includes a demo on querying a cluster. Finally, we will show how you can launch an elastic cluster on Alibaba Cloud and how to use Elasticsearch to query a large dataset for an autocomplete use case.
Learn more about Alibaba Cloud’s Elasticsearch offering:
https://www.alibabacloud.com/product/elasticsearch
Filebeat Elastic Search Presentation.pptxKnoldus Inc.
Â
In this session, we will figure out how you can use Filebeat to monitor the Elasticsearch log files, collect log events, and ship them to the monitoring cluster. And how your recent logs are visible on the Monitoring page in Kibana.
A talk that discusses two topics regarding Elasticsearch - multitenancy and scalability and what are the technical details to achieving them efficiently
Elastic Search Capability Presentation.pptxKnoldus Inc.
Â
Elasticsearch is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON document. Distributed search and analytics engine, part of the Elastic Stack. It indexes and analyzes data in real-time, providing powerful and scalable search capabilities for diverse applications.
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
Data Con LA 2022 - Pre- Recorded - OpenSearch: Everything You Need to Know Ab...Data Con LA
Â
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.
Whether you're a developer or just curious about the tech behind search engines, Elasticsearch is worth checking out. From quick search results to analyzing large datasets, Elasticsearch has got you covered. Dive in and explore the endless possibilities.
Centralized Logging Feature in CloudStack using ELK and Grafana - Kiran Chava...ShapeBlue
Â
In this session, Kiran demonstrates how to centralize all the CloudStack-related logs in one place using Elastic Search and generate beautiful dashboards in Grafana. This session simplifies the troubleshooting process involved with CloudStack and quickly helps to resolve the issue.
-----------------------------------------
The CloudStack Collaboration Conference 2023 took place on 23-24th November. The conference, arranged by a group of volunteers from the Apache CloudStack Community, took place in the voco hotel, in Porte de Clichy, Paris. It hosted over 350 attendees, with 47 speakers holding technical talks, user stories, new features and integrations presentations and more.
Modernizing the monolithic architecture to container based architecture apaco...Vinay Kumar
Â
Transform the architecture from monolithic architecture to container/serverless architecture. Speaker would explain how things work with monolithic implementation and what would require to change to the container-based design. Example of Fusion middleware (WebLogic) to new technologies like node.js etc would be given. This session would be more interactive and provides advantages of the container-based system. Container and container management software would be explained.
Kafka and event driven architecture -apacoug20Vinay Kumar
Â
Event-driven architecture in APIs and microservice are very important topics if you are developing modern applications with new technology, platforms. This session explains what is Kafka and how we can use in event-driven architecture. This session explains the basic concepts of publisher, subscriber, streams, and connect. Explain how Kafka works. The session covers developing different functions with different programming languages and shows how they can share messages by using Kafka. What are the options we have in Oracle stack? Which tool make it possible event-driven architecture in Oracle stack. Speaker will also explain Oracle Event HUB, OCI streaming, and Oracle AQ implementation.
Modern application development with oracle cloud sangam17Vinay Kumar
Â
How Oracle cloud helps in building modern application development. This explains Oracle Application container cloud with developer cloud service and etc. Spring boot application deployed in Oracle ACCS and CI/CD part done in Oracle Developer cloud service.
This technical article explains personalization concept in Webcenter Portal. It also provides steps to create a scenario and use it in Webcenter Portal.
Tuning and optimizing webcenter spaces application white paperVinay Kumar
Â
This white paper focuses on Oracle WebCenter Spaces performance problem and analysis after post production deployment. We will tune JVM ( JRocket). Webcenter Portal, Webcenter content and ADF task flow.
Enhancing Performance with Globus and the Science DMZGlobus
Â
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Â
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Â
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Â
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
Â
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
Â
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
Â
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
đź“• Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
Â
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalitĂ di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
đź“• Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨‍🏫👨‍💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Â
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
Â
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Â
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.
2. 2
• O RACL E ACE
• Enterp ris e Arc h itec t
• Au th or of Book “Beginning Oracle
Web Center p ortal 1 2 c”
• O rac le c ertified p ro fes s io n al
• B lo g ger-http ://w w w.tech artifact. com/b logs
• So ftware Con s u ltant
• JAVA EE GUARDI AN
3.
4. 4
• Un der st an din g En terprise S earch
• Elast ic S earch in t rodu ct ion
• Elast ic St ack Arch itect u re
• Elast ic S earch core con cept s
• Elast ic S earch AP Is
• In tegration of Elastic Search with Oracle F MW
• Elast ic S earch plu gin s
• Demo
9. Elastic Search Key Features
9
• Document- oriented : stores complex entities as structured JSON documents and indexes all fields by
default
• RESTful API : API driven, actions can be performed using a simple Restful API.
• Real-Time Data availability and analytics : As soon as data is indexed, it is made available for search and
analytics. It's all real-time.
• Distributed : Allows us to set up as many nodes we need for our requirement. Cluster will manage
everything and it can grow horizontally to a large number.
• Highly available : The cluster is smart enough to detect a new node or failed node to add/remove from
the cluster..
• Full-text & Fuzzy Search
• Multitenancy : In Elasticsearch, an alias for index can be created. Usually a cluster contains multiple
indices. These aliases allow a filtered view of an index to achieve multitenancy.
11. ELK Stack
11
• Logstash helps in centralizing event data such as logs, metrics, or any other data in any format. It can
perform a number of transformations before indexing.
• Elastic search is at the heart of Elastic Stack. It stores all your data and provides search and analytic
capabilities in a scalable way. Elastic search can be used without using any other components to power
your application in terms of search and analytics.
• Kibana is the visualization tool of Elastic Stack which can help you gain powerful insights about your
data in Elastic search.
12. Logstash
12
• Logstash is a plugin-based data collection and processing engine. The Logstash event processing
pipeline has three stages, they are: Inputs, Filters and Outputs.
• Inputs create events, Filters modify the input events, and Outputs ship them to the destination. Inputs
and outputs support codecs which enable you to encode or decode the data as and when it enters or
exits the pipeline without having to use a separate filter. Logstash uses in-memory bounded queues
between pipeline stages by default (Input to Filter and Filter to Output) to buffer events
14. Beats
14
• Beats is a platform of open source lightweight data shippers.
• Beats has a role on the client side whereas logstash is a server side.
• Beats consists of a core library, libbeat, which provides an API for shipping data from the
source, configuring the input options, and implementing logging
15. Beats vs Logstash
15
Beats Logstash
Beats requires fewer resources and consumes
low memory
consumes a lot of memory and requires a
higher amount of resources
Beats are created based on the Go language. Logstash is based on Java requiring JVM
Beats are lightweight data shippers that will
ship your data from multiple systems.
Heavy to install on all the systems from which
you want to collect the logs,
• Beats are data shippers shipping data from a variety of inputs such as files, data streams, or
logs whereas Logstash is a data parser. Though Logstash can ship data, it's not its primary
usage.
• Logstash provides capabilities of ETL (Extract, Transform, and Load), whereas Beats are
lightweight shippers that ship the data.
16. What is Elastic Search
16
“Software that makes massive amounts of
structured and unstructured data usable
for search, logging, analytics, and more
in mission critical system and
application…..”
18. What is Elastic Search
18
• Full text search engine.
• NoSql Database
• Analytics Engine
• Lucene Based
• Inverted indices
• Easy to Scale
• RESTFUL interface (JSON/HTTP)
• Schemaless
• Real time
21. Elastic Search - Core concepts – Node, Type, Document
21
• An index contains one or multiple types.
• A type can be thought of as a table in a relational database. A type has one or more documents.
• A Document a group of fields. Field is key value pair. Document can be thought of as a table as row in
relational database. Its JSON data structure. It is with key value pair.
22. Elastic Search -– Node , Cluster
22
• A Node node is a single server of Elasticsearch ,part of a larger cluster of nodes. It participates
in indexing, searching, and performing other operations supported by Elasticsearch.
• A cluster is formed by one or more nodes. Every Elasticsearch node is always part of a cluster, even if it
is just a single node cluster. A cluster hosts one or more indices and is responsible for providing
operations such as searching, indexing, and aggregations.
23. Elastic Search – Shards
23
• A Shard help in dividing the documents of a single index over multiple nodes. It distribute the data into
multiple node. The process of dividing the data among shards is called sharding.
- It helps in utilizing storage across different nodes of the cluster
- It helps in utilizing the processing power of different nodes of the cluster
- Deafult 5 shards per index, and this is configurable.
24. Elastic Search – Replica
24
• A Replica is copy of shard. It is useful for the failover of any node.
- Each shard in an index can be configured to have zero or more replica shards.
- Replica shards are extra copies of the original or primary shard and provide a high availability of data.
- Also manage the query work load execution across replicas
25. Elastic Search – Inverted Index
25
• A Inverted index is the core data structure of
Elasticsearch.
• It is very similar to index at end of every book.
• Building block for performing fast searches.
• Easy to look up how many occurrences of
terms are present in the index. This is a simple
count aggregation.
• It caters to both search and analytics.
• Elastic search builds an inverted index on all
the fields in the document.
26. Elastic Search – Inverted Index- Continued
26
Document ID Document
1 This is the best
session in Sangam
2 Sangam is cool
3 This is your choice.
Term Frequency Document
This 2 1,3
Sangam 2 1,2
is 3 1,2,3
best 1 1
in 1 1
cool 1 2
your 1 3
the 1 1
choice 1 3
Inverted Index in ESInput Strings
27. Elastic Search – Core concepts - Summary
27
• Nodes get together to form a cluster.
• Clusters provide a physical layer of services on which multiple indexes can be created
• An index may contain one or more types, with each type containing millions or billions of
documents.
• Indexes are split into shards, which are partitions of underlying data within an index. Shards
are distributed across the nodes of a cluster.
• Replicas are copies of primary shards and provide high availability and failover.
• ES stores documents in terms in the inverted index for search and analytics.
28. Core concepts – Data type
28
• Text data
• Numbers
• Booleans
• Binary objects
• Arrays, objects
• Nested types
• Geo-points
• Geo-shapes
• IPv4 and IPv6 addresses.
37. Logging & Monitor with Oracle Fusion Middleware
Problem -
• Each log has to be monitored manually.
• Single place to see application log, system errors, user errors, network metrics etc.
• Requires Ops Admin with special access privileges to access the file
• Normal devs or testers cannot view the data generated in staging or productions environments
• Not a single place to monitor and search the logs.
• Custom user experience according to organization UI standards.
• Great quick search experience.
Solution -
Oracle Enterprise Manager
38. Logging & Monitor with Oracle fusion Middleware
ADF Log Server
OSB Log Server
SOA Log Server
WCP Log Server
BPM Log Server
……. Log Server
Filebeat
Filebeat pull
the log file
Logstash
Parses &
pushes
updates
Elastic search
Transform
& pushes
data to ES
Monitor &
visualization
OFMW
……. Log Server
39. Document search in WebCenter Content
Problem -
• Search for documents with keywords, document number etc.
• Search for text in documents/PDF, Autocad files etc.
• Google like search experience.
• Full text search
- Stemming (developing for mobile matches results for develop for mobile and vice versa.)
- fuzzy matching (service workers matches results for Service Worker)
• Quick and performant search.
• One Search field to search for all document
40. Document search with Oracle WebCenter Content
Elastic
search
WCC
Filters
Oracle
ADF/WCP
RIDC Client/WCC
API
Oracle JET
Oracle ADF
Oracle
WebCenterBrowser
Users Ingesting
document via
User interface
Ingest file and other
information in to ES
Insert
Search
Document
Search in Elastic
Search with text,
keyword
Ingest Attachment
plugin to store
document
Return result with
documnt id to
Java API
Java
Code
Find doc with DocId
Return result doc
1
2
4
3
5
6
7
8
9
10
Insert document with
WCC console or
desktop/API etc
OTS
41. Document search in WebCenter Content
To ingest document Elastic search uses Attachment processor plugin- This
plugin uses Tika library, which is a toolkit developed by Apache, and can
extract metadata and text from a number of file types. Using Tika, this plugin
helps Elasticsearch to extract details from attachments. Common attachment
formats include--PPT, PDF, XLS, and many more.
42. Web Search with ERPs
Problem -
• Multiple sources of data i.e. 3 ERPs – IFS, Oracle E Business, MS Dynamic
• Single Search screen to retrieve result from 3 ERP in WebCenter Portal Screen.
• Google like search experience.
• Full text search .
• Quick and performant search.
• One Search field to search across the ERPs.
43. Web application search with Oracle fusion Middleware
Data
Sync
Elastic
search
Schedular
IFS Ingesting
data via ES
java API
Oracle
ADF
Oracle
JET
WebCenter
Portal
Portal/
User
interface
Users
Oracle JET
Oracle ADF
Oracle
WebCenter
Data ship
via logstash
plugin
Browser
JSON Data
44. Web application search with Oracle JET
ADF Log Server
OSB Log Server
SOA Log Server
WCP Log Server
BPM Log Server
……. Log Server
Filebeat
Filebeat pull
the log file
Logstash
Parses &
pushes
updates
Elastic search
Transform
& pushes
data to ES
Monitor &
visualization
OFMW
Search
Filters