The NoSQL database became famous, because, this technology makes easier storage and fast write/read. However, is the worse you can do with NoSQL? This presentation covers the commons mistakes when a user starts to use NoSQL.
This document provides an overview of Cassandra, a NoSQL database. It discusses key features of Cassandra including its data model, consistency levels, architecture involving commit logs, memtables and SSTables. It also covers gossip protocols, partitioning, replica placement strategies, CQL and user-defined types. The document notes some issues to consider with Cassandra and mentions operations, development tools and JNoSQL, an API for Cassandra.
The document discusses Angular2 and React frameworks, comparing their similarities and differences. It covers topics such as component architecture, syntax, and single-page application routing. Both frameworks take a component-based approach and support server-side rendering. The key differences are that React focuses only on the view layer while Angular is a complete framework, React uses JSX syntax while Angular uses HTML templates, and React renders components directly while Angular uses data binding.
This document discusses how to operate Elastic, an open-source search and analytics engine. It covers how Elastic is used for content and provider searches and the ELK stack. It also outlines how clients connect via an ELB, how Elastic is built using Packer and Chef, monitored with tools like Nagios and Marvel, and migrated between clusters using dual-writes. Finally, it mentions next steps like CloudFormation templates and expanding Elastic usage and clusters.
This document introduces MapReduce and Hadoop using Ruby. It begins with an overview of MapReduce concepts like mapping and reducing data. It then discusses how Hadoop encapsulates these processes and allows defining mappers and reducers to run jobs in parallel across large datasets. The document provides an example of counting character usage in books to demonstrate a simple MapReduce problem. It concludes by recommending some resources for learning more about Hadoop and MapReduce.
TDC2017 | São Paulo - Trilha NOSQL How we figured out we had a SRE team at - ...tdc-globalcode
The document discusses NoSQL databases and compares them to SQL databases. It outlines several NoSQL database models including key-value, document, columnar, and graph databases. It provides examples of querying data using SQL and the graph database query language TinkerPop. The document emphasizes that benchmarks may not accurately reflect real-world performance and that databases need to be modeled to their intended use cases.
ORMs heróis ou vilões dentro da arquitetura de dados? - Otávio gonçalvesiMasters
Com a evolução dos aplicativos nascem novas técnicas, frameworks, linguagens de programação, porém, existe um fato consolidado dentro da arquitetura de software corporativo que é a integração com alguma tecnologia necessária para armazenar as informações inerentes ao sistema. Seja SQL ou NoSQL um ponto importante é que o paradigma das linguagens difere da tecnologia do banco de dados. Com o intuito de facilitar o desenvolvimento surgem as ferramentas que realizam a interpretação entre a camada da aplicação e os bancos. Assim, aparecem grandes desafios: como lidar com essa lacuna multiparadigma? Como favorecer o desenvolvimento sem impactar a performance e a modelagem no banco de dados? O objetivo dessa palestra é falar um pouco desses pontos para que, finalmente, os programadores e os DBAs conseguam viver em paz e harmonia.
ORMs: Heroes or Villains Inside the Architecture?Otávio Santana
In the information age, with new technologies, frameworks, and programming languages, there is an aspect of technology that never changes. All applications need a storage integration related to their system; either SQL or NoSQL, to point out that there is a different paradigm among the development team and the database team. To make developer life easier, new frameworks emerged that convert between the application layer and the database, which includes the famous ORM. Indeed, contemporary challenges appear such as how to handle different paradigms that are in software development and how to make a regular development without impacting on the database.
This document provides 20 tips for SQL Server performance tuning and administration from MVP Ike Ellis. The tips cover topics such as SSIS, SSAS, SSRS, query performance, indexing, partitioning, hardware troubleshooting, scripting, auditing, and more. Ellis advocates spending time on report formatting, using window functions, scripting with PowerShell, enforcing business rules in the database, and logging activities for auditing purposes. He provides various resources and links for further information.
This document provides an overview of Cassandra, a NoSQL database. It discusses key features of Cassandra including its data model, consistency levels, architecture involving commit logs, memtables and SSTables. It also covers gossip protocols, partitioning, replica placement strategies, CQL and user-defined types. The document notes some issues to consider with Cassandra and mentions operations, development tools and JNoSQL, an API for Cassandra.
The document discusses Angular2 and React frameworks, comparing their similarities and differences. It covers topics such as component architecture, syntax, and single-page application routing. Both frameworks take a component-based approach and support server-side rendering. The key differences are that React focuses only on the view layer while Angular is a complete framework, React uses JSX syntax while Angular uses HTML templates, and React renders components directly while Angular uses data binding.
This document discusses how to operate Elastic, an open-source search and analytics engine. It covers how Elastic is used for content and provider searches and the ELK stack. It also outlines how clients connect via an ELB, how Elastic is built using Packer and Chef, monitored with tools like Nagios and Marvel, and migrated between clusters using dual-writes. Finally, it mentions next steps like CloudFormation templates and expanding Elastic usage and clusters.
This document introduces MapReduce and Hadoop using Ruby. It begins with an overview of MapReduce concepts like mapping and reducing data. It then discusses how Hadoop encapsulates these processes and allows defining mappers and reducers to run jobs in parallel across large datasets. The document provides an example of counting character usage in books to demonstrate a simple MapReduce problem. It concludes by recommending some resources for learning more about Hadoop and MapReduce.
TDC2017 | São Paulo - Trilha NOSQL How we figured out we had a SRE team at - ...tdc-globalcode
The document discusses NoSQL databases and compares them to SQL databases. It outlines several NoSQL database models including key-value, document, columnar, and graph databases. It provides examples of querying data using SQL and the graph database query language TinkerPop. The document emphasizes that benchmarks may not accurately reflect real-world performance and that databases need to be modeled to their intended use cases.
ORMs heróis ou vilões dentro da arquitetura de dados? - Otávio gonçalvesiMasters
Com a evolução dos aplicativos nascem novas técnicas, frameworks, linguagens de programação, porém, existe um fato consolidado dentro da arquitetura de software corporativo que é a integração com alguma tecnologia necessária para armazenar as informações inerentes ao sistema. Seja SQL ou NoSQL um ponto importante é que o paradigma das linguagens difere da tecnologia do banco de dados. Com o intuito de facilitar o desenvolvimento surgem as ferramentas que realizam a interpretação entre a camada da aplicação e os bancos. Assim, aparecem grandes desafios: como lidar com essa lacuna multiparadigma? Como favorecer o desenvolvimento sem impactar a performance e a modelagem no banco de dados? O objetivo dessa palestra é falar um pouco desses pontos para que, finalmente, os programadores e os DBAs conseguam viver em paz e harmonia.
ORMs: Heroes or Villains Inside the Architecture?Otávio Santana
In the information age, with new technologies, frameworks, and programming languages, there is an aspect of technology that never changes. All applications need a storage integration related to their system; either SQL or NoSQL, to point out that there is a different paradigm among the development team and the database team. To make developer life easier, new frameworks emerged that convert between the application layer and the database, which includes the famous ORM. Indeed, contemporary challenges appear such as how to handle different paradigms that are in software development and how to make a regular development without impacting on the database.
This document provides 20 tips for SQL Server performance tuning and administration from MVP Ike Ellis. The tips cover topics such as SSIS, SSAS, SSRS, query performance, indexing, partitioning, hardware troubleshooting, scripting, auditing, and more. Ellis advocates spending time on report formatting, using window functions, scripting with PowerShell, enforcing business rules in the database, and logging activities for auditing purposes. He provides various resources and links for further information.
U-SQL - Azure Data Lake Analytics for DevelopersMichael Rys
This document introduces U-SQL, a language for big data analytics on Azure Data Lake Analytics. U-SQL unifies SQL with imperative coding, allowing users to process both structured and unstructured data at scale. It provides benefits of both declarative SQL and custom code through an expression-based programming model. U-SQL queries can span multiple data sources and users can extend its capabilities through C# user-defined functions, aggregates, and custom extractors/outputters. The document demonstrates core U-SQL concepts like queries, joins, window functions, and the metadata model, highlighting how U-SQL brings together SQL and custom code for scalable big data analytics.
The document discusses online analytical processing (OLAP) of large distributed databases. It describes how OLAP differs from relational databases in being schema-less, allowing for high redundancy, lacking referential integrity and transactions, and focusing on non-transactional queries. It also compares OLAP to big data platforms, noting similarities in being schema-less and focusing on distributed processing and storage through MapReduce. The document provides an example architecture for advertising data analysis using OLAP over big data, with an OLAP cache, analytical database, and big data store, utilizing open standards like Java, JDBC, XMLA, and Infinispan.
This Knolx session is all about Slick, a library for accessing relational databases using an interface similar to the Scala collections library.
Through this session, we'll get familiar with slick and how it's better than ORMs. We'll learn how we map Scala datatypes with the relational database in slick, covering most of the basics here and give you everything you need to be productive with the library through a short demo.
The agenda of the session is:
~ What is Slick
~ Features of Slick
~ ORM vs Slick
~ Some Core Concepts
~ How Mapping Occurs?
~ SQL vs Slick Examples
~ Benefits of Slick
~ Supported Databases
Non-relational databases have come with the promise of assisting software in the Big Data age, handling the challenges of variety, velocity, and volume that come with it.
However, several points plague even the most experienced software architects: How do I migrate my data to NoSQL and which one? Where are the relationships? Should I use some ORM? The purpose of this talk is to answer all of these questions and provide some essential tips so that your NoSQL experience is not a disaster.
Worst Practices in Data Warehouse DesignKent Graziano
This presentation was given at OakTable World 2014 (#OTW14) in San Francisco. After many years of designing data warehouses and consulting on data warehouse architectures, I have seen a lot of bad design choices by supposedly experienced professional. A sense of professionalism, confidentiality agreements, and some sense of common decency have prevented me from calling people out on some of this. No more! In this session I will walk you through a typical bad design like many I have seen. I will show you what I see when I reverse engineer a supposedly complete design and walk through what is wrong with it and discuss options to correct it. This will be a test of your knowledge of data warehouse best practices by seeing if you can recognize these worst practices.
The past years, a number of new database systems have appeared, like MongoDB and Redis. Most of them have radically new ways to look at data persistance, where efficient replication is prioritized over advanced query support.
In this talk we will discuss some of the benefits and drawbacks of the new key/value stores and document databases. As an example, we will demonstrate Redis, an advanced key/value store. Redis is different from most other key/value stores on two dimensions: It runs entirely in RAM and it supports a number of advanced data structures with accompanying specialized algorithms.
TypeScript and Angular2 (Love at first sight)Igor Talevski
“We love TypeScript for many things… With TypeScript, several of our team members have said things like ‘I now actually understand most of our own code!’ because they can easily traverse it and understand relationships much better. And we’ve found several bugs via TypeScript’s checks. “
– Brad Green, Engineering Director - AngularJS
ETL Testing Training from Magnitia helps you to learn a step-by-step process that includes ETL Testing introduction, difference between OLAP and OLTP, RDBM, learning data warehousing concepts, its workflow, difference between data warehouse testing and database testing, deploying SQL for checking data and the basis for Business Intelligence.
As a part of ETL Testing Training, you will be exposed to real-life industry scenarios which give you in-depth understanding of Data warehousing and concepts of business intelligence. ETL testing course will help you to become a successful ETL Testing expert.
Aspirants who are interested can attend our ETL Testing training in Hyderabad, or you can take our ETL Testing online training.
Angular JS Institute: NBITS is the best Angular JS Online/Classroom Training Institute in Hyderabad.We provide training from best real time industry experts in Angular 2,Angular 4,Angular 5,Node js, mean stack courses through online and Classroom with Lab facility.
This document summarizes a lunch and learn session on SQL tips and tricks for developers. It covers topics like using indexes to improve performance, avoiding SQL injection, using transactions properly, null value handling, the N+1 query problem, database statistics and tools like Spring Data repositories, IntelliJ SQL support and database versioning. It also discusses NoSQL vs SQL databases and embedded database options for testing.
This document discusses SQL Server worst practices related to design, development, installation, and administration. Some key worst practices highlighted include not normalizing database schemas, using dynamic SQL with hardcoded literals, installing SQL Server with default settings, relying on autogrow for disk space management, and having no monitoring or alerting configured. The document encourages learning from other's mistakes to avoid common pitfalls, and provides resources for best practices analysis and SQL Server troubleshooting.
Building scalable application with sql serverChris Adkin
Chris Adkin has 15 years of IT experience and 14 years of experience as a DBA working with various sectors. He has over 10 years of experience with SQL Server from version 2000. He provides his email and Twitter contact information. The document then discusses various topics related to database design and performance including OLTP vs OLAP characteristics, data modeling best practices, indexing strategies, query optimization techniques, and concurrency control methods.
Migrating Oracle database to PostgreSQLUmair Mansoob
This document discusses migrating an Oracle database to PostgreSQL. It covers initial discovery of the Oracle database features and data types used. A migration assessment would analyze data type mapping, additional PostgreSQL features, and testing requirements. Challenges include porting PL/SQL code, minimizing downtime during migration, and comprehensive testing of applications on the new PostgreSQL platform. Migrating large data sets and ensuring performance for critical applications are also challenges.
SELF - Becoming a Rails Developer - The Rest of the StoryNathanial McConnell
This document provides guidance on becoming a Rails developer beyond just learning the Rails framework. It discusses key competencies needed like understanding Ruby and object-oriented programming. It also recommends learning processes like mentoring, code reviews, and pair programming. Standard learning paths are outlined covering Ruby, Rails, SQL, testing, and more. Advice is given on freelancing, finding clients, and maintaining work-life balance.
This document provides 20 tips for SQL Server performance tuning, SSIS, SSRS, and other Microsoft data tools. The tips cover topics like using SSIS for accessibility, report formatting, hardware troubleshooting using PerfMon and tracing, readable presentations, indexing, windowing functions, scripting with PowerShell, TempDB configuration, prettifying SQL code, dates tables, enforcing business rules in the database, and logging. The document encourages staying involved with SQL Server user groups and provides contact information for the author.
This document provides an overview of NoSQL databases and Oracle's perspective on them. It begins by explaining that NoSQL databases aim to be highly available and able to scale horizontally. It then discusses some of the origins and types of NoSQL databases, including key-value stores, document databases, column family stores, and graph databases. It also covers Brewer's CAP theorem and how NoSQL databases sacrifice consistency for availability and partition tolerance. Finally, it discusses how Oracle has incorporated some NoSQL concepts into its own database technologies over time.
The document compares relational and non-relational databases. Relational databases organize data into tables with rows and columns and use SQL for queries. They are good for structured data but difficult to change. Non-relational databases have flexible schemas and adapt easily but can be less reliable. Examples of relational databases include MySQL and SQL Server, while non-relational options include MongoDB, Cassandra, and Redis.
Looking for best Dot Net training in chennai? VIsit FITA Academy - Leading Software Training Centre offers Real TIme Project Based Training with Job Placement Support.
https://www.fita.in/dot-net-training-in-chennai/
Modern Cloud-Native Jakarta EE Frameworks: tips, challenges, and trends.Otávio Santana
Java has a large number of tools and frameworks to facilitate integration with databases, microservices, and so on. These tools have evolved considerably. It all started with class integrated with XML files and has undergone significant evolution with reflections and annotations within the class definitions. In the cloud-native scenario, requirements have changed and this impacts applications in ways that weren't critical before. For example, cold starts and boot time wasn't critical with application servers but is crucial in serverless and microservices. The objective of this presentation is to talk about how these frameworks behave in the native cloud age and they affect Jakarta EE.
Architecting Cloud Computing Solutions with Java [1.1]Otávio Santana
This document discusses cloud-native concepts and architectures using Java. It begins with an introduction to the speaker, Otavio Santana, and his background. It then covers topics like cloud types, cloud native approaches, and how they apply concepts like microservices, containers, and orchestration. It also discusses Java optimizations for cloud environments and projects like Eclipse MicroProfile that help build cloud native Java applications. It concludes with a demonstration of Platform.sh's polyglot platform as a service that aims to simplify developing, deploying and managing cloud applications.
U-SQL - Azure Data Lake Analytics for DevelopersMichael Rys
This document introduces U-SQL, a language for big data analytics on Azure Data Lake Analytics. U-SQL unifies SQL with imperative coding, allowing users to process both structured and unstructured data at scale. It provides benefits of both declarative SQL and custom code through an expression-based programming model. U-SQL queries can span multiple data sources and users can extend its capabilities through C# user-defined functions, aggregates, and custom extractors/outputters. The document demonstrates core U-SQL concepts like queries, joins, window functions, and the metadata model, highlighting how U-SQL brings together SQL and custom code for scalable big data analytics.
The document discusses online analytical processing (OLAP) of large distributed databases. It describes how OLAP differs from relational databases in being schema-less, allowing for high redundancy, lacking referential integrity and transactions, and focusing on non-transactional queries. It also compares OLAP to big data platforms, noting similarities in being schema-less and focusing on distributed processing and storage through MapReduce. The document provides an example architecture for advertising data analysis using OLAP over big data, with an OLAP cache, analytical database, and big data store, utilizing open standards like Java, JDBC, XMLA, and Infinispan.
This Knolx session is all about Slick, a library for accessing relational databases using an interface similar to the Scala collections library.
Through this session, we'll get familiar with slick and how it's better than ORMs. We'll learn how we map Scala datatypes with the relational database in slick, covering most of the basics here and give you everything you need to be productive with the library through a short demo.
The agenda of the session is:
~ What is Slick
~ Features of Slick
~ ORM vs Slick
~ Some Core Concepts
~ How Mapping Occurs?
~ SQL vs Slick Examples
~ Benefits of Slick
~ Supported Databases
Non-relational databases have come with the promise of assisting software in the Big Data age, handling the challenges of variety, velocity, and volume that come with it.
However, several points plague even the most experienced software architects: How do I migrate my data to NoSQL and which one? Where are the relationships? Should I use some ORM? The purpose of this talk is to answer all of these questions and provide some essential tips so that your NoSQL experience is not a disaster.
Worst Practices in Data Warehouse DesignKent Graziano
This presentation was given at OakTable World 2014 (#OTW14) in San Francisco. After many years of designing data warehouses and consulting on data warehouse architectures, I have seen a lot of bad design choices by supposedly experienced professional. A sense of professionalism, confidentiality agreements, and some sense of common decency have prevented me from calling people out on some of this. No more! In this session I will walk you through a typical bad design like many I have seen. I will show you what I see when I reverse engineer a supposedly complete design and walk through what is wrong with it and discuss options to correct it. This will be a test of your knowledge of data warehouse best practices by seeing if you can recognize these worst practices.
The past years, a number of new database systems have appeared, like MongoDB and Redis. Most of them have radically new ways to look at data persistance, where efficient replication is prioritized over advanced query support.
In this talk we will discuss some of the benefits and drawbacks of the new key/value stores and document databases. As an example, we will demonstrate Redis, an advanced key/value store. Redis is different from most other key/value stores on two dimensions: It runs entirely in RAM and it supports a number of advanced data structures with accompanying specialized algorithms.
TypeScript and Angular2 (Love at first sight)Igor Talevski
“We love TypeScript for many things… With TypeScript, several of our team members have said things like ‘I now actually understand most of our own code!’ because they can easily traverse it and understand relationships much better. And we’ve found several bugs via TypeScript’s checks. “
– Brad Green, Engineering Director - AngularJS
ETL Testing Training from Magnitia helps you to learn a step-by-step process that includes ETL Testing introduction, difference between OLAP and OLTP, RDBM, learning data warehousing concepts, its workflow, difference between data warehouse testing and database testing, deploying SQL for checking data and the basis for Business Intelligence.
As a part of ETL Testing Training, you will be exposed to real-life industry scenarios which give you in-depth understanding of Data warehousing and concepts of business intelligence. ETL testing course will help you to become a successful ETL Testing expert.
Aspirants who are interested can attend our ETL Testing training in Hyderabad, or you can take our ETL Testing online training.
Angular JS Institute: NBITS is the best Angular JS Online/Classroom Training Institute in Hyderabad.We provide training from best real time industry experts in Angular 2,Angular 4,Angular 5,Node js, mean stack courses through online and Classroom with Lab facility.
This document summarizes a lunch and learn session on SQL tips and tricks for developers. It covers topics like using indexes to improve performance, avoiding SQL injection, using transactions properly, null value handling, the N+1 query problem, database statistics and tools like Spring Data repositories, IntelliJ SQL support and database versioning. It also discusses NoSQL vs SQL databases and embedded database options for testing.
This document discusses SQL Server worst practices related to design, development, installation, and administration. Some key worst practices highlighted include not normalizing database schemas, using dynamic SQL with hardcoded literals, installing SQL Server with default settings, relying on autogrow for disk space management, and having no monitoring or alerting configured. The document encourages learning from other's mistakes to avoid common pitfalls, and provides resources for best practices analysis and SQL Server troubleshooting.
Building scalable application with sql serverChris Adkin
Chris Adkin has 15 years of IT experience and 14 years of experience as a DBA working with various sectors. He has over 10 years of experience with SQL Server from version 2000. He provides his email and Twitter contact information. The document then discusses various topics related to database design and performance including OLTP vs OLAP characteristics, data modeling best practices, indexing strategies, query optimization techniques, and concurrency control methods.
Migrating Oracle database to PostgreSQLUmair Mansoob
This document discusses migrating an Oracle database to PostgreSQL. It covers initial discovery of the Oracle database features and data types used. A migration assessment would analyze data type mapping, additional PostgreSQL features, and testing requirements. Challenges include porting PL/SQL code, minimizing downtime during migration, and comprehensive testing of applications on the new PostgreSQL platform. Migrating large data sets and ensuring performance for critical applications are also challenges.
SELF - Becoming a Rails Developer - The Rest of the StoryNathanial McConnell
This document provides guidance on becoming a Rails developer beyond just learning the Rails framework. It discusses key competencies needed like understanding Ruby and object-oriented programming. It also recommends learning processes like mentoring, code reviews, and pair programming. Standard learning paths are outlined covering Ruby, Rails, SQL, testing, and more. Advice is given on freelancing, finding clients, and maintaining work-life balance.
This document provides 20 tips for SQL Server performance tuning, SSIS, SSRS, and other Microsoft data tools. The tips cover topics like using SSIS for accessibility, report formatting, hardware troubleshooting using PerfMon and tracing, readable presentations, indexing, windowing functions, scripting with PowerShell, TempDB configuration, prettifying SQL code, dates tables, enforcing business rules in the database, and logging. The document encourages staying involved with SQL Server user groups and provides contact information for the author.
This document provides an overview of NoSQL databases and Oracle's perspective on them. It begins by explaining that NoSQL databases aim to be highly available and able to scale horizontally. It then discusses some of the origins and types of NoSQL databases, including key-value stores, document databases, column family stores, and graph databases. It also covers Brewer's CAP theorem and how NoSQL databases sacrifice consistency for availability and partition tolerance. Finally, it discusses how Oracle has incorporated some NoSQL concepts into its own database technologies over time.
The document compares relational and non-relational databases. Relational databases organize data into tables with rows and columns and use SQL for queries. They are good for structured data but difficult to change. Non-relational databases have flexible schemas and adapt easily but can be less reliable. Examples of relational databases include MySQL and SQL Server, while non-relational options include MongoDB, Cassandra, and Redis.
Looking for best Dot Net training in chennai? VIsit FITA Academy - Leading Software Training Centre offers Real TIme Project Based Training with Job Placement Support.
https://www.fita.in/dot-net-training-in-chennai/
Modern Cloud-Native Jakarta EE Frameworks: tips, challenges, and trends.Otávio Santana
Java has a large number of tools and frameworks to facilitate integration with databases, microservices, and so on. These tools have evolved considerably. It all started with class integrated with XML files and has undergone significant evolution with reflections and annotations within the class definitions. In the cloud-native scenario, requirements have changed and this impacts applications in ways that weren't critical before. For example, cold starts and boot time wasn't critical with application servers but is crucial in serverless and microservices. The objective of this presentation is to talk about how these frameworks behave in the native cloud age and they affect Jakarta EE.
Architecting Cloud Computing Solutions with Java [1.1]Otávio Santana
This document discusses cloud-native concepts and architectures using Java. It begins with an introduction to the speaker, Otavio Santana, and his background. It then covers topics like cloud types, cloud native approaches, and how they apply concepts like microservices, containers, and orchestration. It also discusses Java optimizations for cloud environments and projects like Eclipse MicroProfile that help build cloud native Java applications. It concludes with a demonstration of Platform.sh's polyglot platform as a service that aims to simplify developing, deploying and managing cloud applications.
Arquitetando soluções de computação em nuvem com JavaOtávio Santana
O Cloud Native se tornou uma grande palavra de ordem em todo o mundo, um termo que é praticamente usado por todos em todos os momentos. Mas o que isso significa? Quais são as vantagens que ele traz ao seu aplicativo e ao seu dia como desenvolvedor ou arquiteto de software? O que há de novo no mundo Java e quais são as etapas a seguir para um aplicativo em nuvem nativo? Esta apresentação é um guia passo a passo que praticamente o guiará na implementação de serviços de computação em nuvem de maneira eficaz e eficiente.
Build, run, and scale your Java applications end to endOtávio Santana
This presentation will talk about a solution to the continuous deployment cloud hosting solution that can scale applications from the smallest projects to those handling millions of visitors. It is ideal for agile software teams because of its unique feature: it can replicate a live production cluster in seconds and create byte-level clones of throwaway dev and staging environments, which makes testing and validation 90% faster.
Jakarta NoSQL: Meet the first Jakarta EE specification in the CloudOtávio Santana
The document discusses Jakarta NoSQL, the first Jakarta EE specification for working with NoSQL databases in the cloud. It introduces different NoSQL database models, including key-value, column family, document, and graph databases. It then describes the Jakarta NoSQL APIs which provide a common way to work with different NoSQL database types through a mapping API and communication API. The specification aims to standardize how Java applications access NoSQL databases in the cloud.
This document discusses how Jakarta EE can be used to access NoSQL databases in cloud applications. It introduces different NoSQL database types and describes issues with using JPA for NoSQL. Jakarta NoSQL provides APIs, mappings, and communication interfaces to access various NoSQL databases from Jakarta EE applications in a standardized way. It supports features like queries, repositories, and handling diversity across NoSQL databases.
Jakarta EE Meets NoSQL in the Cloud Age [DEV6109]Otávio Santana
Let’s be honest: the amount of data collected by applications nowadays is growing at a scary pace. Many of them need to handle billions of users generating and consuming data at an incredible speed. Maybe you are wondering how to create an application like this? What is needed? What benefits can you take from this reality to your project? This session shows how Jakarta EE can meet these needs when you’re working with NoSQL databases in the cloud. It's the same approach used by some of the biggest companies in the world to store, analyze, and get results from really crazy amounts of data. No matter your project size, you can take it to the next level today.
Let’s Make Graph Databases Fun Again with Java [DEV6043]Otávio Santana
It’s a fact: today NoSQL databases are very popular in several areas of the software industry. They have many different uses cases, including graphs. The graph database has a structure that’s pretty different from relational technology and has a lot of successful use cases such as recommendation systems on Facebook and LinkedIn. This session covers what a graph database is and how to use it with Java. With a useful and practical live demo of career recommendation with Neo4J, you will learn how easy it could be to build your next successful application. Today!
Eclipse JNoSQL: One API to Many NoSQL Databases - BYOL [HOL5998]Otávio Santana
This document introduces JNoSQL, an Eclipse project that provides a common API for working with various NoSQL database types. It summarizes each speaker and gives an overview of NoSQL databases and the different types. It then describes JNoSQL's goals of providing a common mapping and communication API along with examples of using its APIs for different database types. Finally, it outlines hands-on examples for using JNoSQL with Redis, MongoDB and Neo4j.
The new generation of data persistence with graphOtávio Santana
1) The document discusses the evolution of data from goods to information and machines, and the transition from SQL to NoSQL databases like key-value, column, document and graph structures.
2) It provides an example of modeling data as a graph database using TinkerPop and Gremlin, showing how to add vertices and edges to represent relationships.
3) Graph databases allow complex queries over relationships, like finding engineers who know other people or might fall in love, which would be difficult in SQL.
Eclipse JNoSQL updates from JCP September 11Otávio Santana
This document discusses NoSQL databases and the Eclipse JNoSQL project. It describes five different types of NoSQL databases - key-value, column family, document, graph, and multi-model. It then discusses issues with using JPA and JDO for NoSQL and introduces the Eclipse JNoSQL solution which provides a common API to work with different NoSQL database types. It also outlines the JNoSQL architecture, support for asynchronous operations, and engagement with JUGs and code specification processes.
Stateless Microservice Security via JWT and MicroProfile - GuatemalaOtávio Santana
The learning curve for REST API security is severe and unforgiving. Specifications promise infinite flexibility, habitually give old concepts new names, and almost seem designed to deliberately confuse. With an aggressive distaste for fancy terminology, the first half of this session delves into OAuth 2.0 with and without JWTs and shows how it falls into two camps: stateful and stateless. Starting at Basic Auth and walking forward, we'll compare each with heavy focus on the wire, showing actual HTTP messages and analyzing their impact on load and security against a baseline Microservice architecture.
The second half of this presentation we'll deep dive into MicroProfile JWT, which offers a clean Java API and standard configuration for consuming JWTs in Java Microservices. Code and demo focused, we'll see a complete MicroProfile JWT, TomEE and AngularJS app running on Oracle Cloud that issues JWTs with custom backend-data, performs server-side verification and injection of claims, and client-side login and refresh. All code in Github, you'll leave ready to bootstrap your next truly secure full-stack project.
Stateless Microservice Security via JWT and MicroProfile - MexicoOtávio Santana
The learning curve for REST API security is severe and unforgiving. Specifications promise infinite flexibility, habitually give old concepts new names, and almost seem designed to deliberately confuse. With an aggressive distaste for fancy terminology, the first half of this session delves into OAuth 2.0 with and without JWTs and shows how it falls into two camps: stateful and stateless. Starting at Basic Auth and walking forward, we'll compare each with heavy focus on the wire, showing actual HTTP messages and analyzing their impact on load and security against a baseline Microservice architecture.
The second half of this presentation we'll deep dive into MicroProfile JWT, which offers a clean Java API and standard configuration for consuming JWTs in Java Microservices. Code and demo focused, we'll see a complete MicroProfile JWT, TomEE and AngularJS app running on Oracle Cloud that issues JWTs with custom backend-data, performs server-side verification and injection of claims, and client-side login and refresh. All code in Github, you'll leave ready to bootstrap your next truly secure full-stack project.
Eclipse JNoSQL: The Definitive Solution for Java and NoSQL DatabaseOtávio Santana
JNoSQL is a framework and collection of tools that make integration between Java applications and NoSQL quick and easy—for developers as well as vendors. The API is easy to implement, so NoSQL vendors can quickly implement, test, and become compliant by themselves. And with its low learning curve and just a minimal set of artifacts, Java developers can start coding by worrying not about the complexity of specific NoSQL databases but only their core aspects (such as graph or document properties). Built with functional programming in mind, it leverages all the features of Java 8. This session covers how the API is structured, how it relates to the multiple NoSQL database types, and how you can get started and involved in this open source technology.
Polyglot Persistence is a fancy term to mean that when storing data, it is best to use multiple data storage technologies, chosen based upon the way data is being used by individual applications or components of a single application
The document discusses different models of management and how open source relates to management approaches. Management 1.0/2.0 refers to traditional top-down hierarchical models while Management 3.0 focuses on self-management, transparency, and product-first approaches. When using open source, companies must consider licensing, intellectual property violations, and whether projects will be considered public domain. Open source development involves community input through a workflow of project proposals, review, incubation, and releases.
Building a Recommendation Engine with Java EEOtávio Santana
Recommender systems have become increasingly popular in recent years and are utilized in a variety of areas, including movies, music, news, books, research articles, search queries, marketplaces, social tags, and products in general. A platform with a recommender system—such as NetFlix, with movies; dating systems, with relationships; and Amazon, with books—makes the user experience exceptional. This presentation covers how to create a recommendation engine with Java EE to rocket your business.
Building a recommendation engine with tinker popOtávio Santana
The document discusses using the TinkerPop graph traversal framework to build a recommendation engine. It provides examples of traversing a graph database to model relationships between entities and executing queries equivalent to SQL queries on the graph. Sample queries demonstrate filtering graph vertices based on properties, retrieving property values, counting results, and traversing edges to find related vertices. The document promotes TinkerPop for complex queries and scaling to large datasets compared to SQL databases.
JNoSQL is an open source project that provides a common API for working with different NoSQL databases. It includes Diana, which defines a common communication layer, and Artemis, a CDI-based annotation framework. The goal is to simplify development of NoSQL applications by handling differences in data models and query languages between databases in a standardized way.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
22. JPA problem for NoSQL
● Saves Async
● Async Callback
● Time to Live (TTL)
● Consistency Level
● SQL based
● Diversity in NoSQL
23. JNoSQL
● Mapping API
● Communication API
● No lock-in
● Divide and conquer
DAO
Mapping
Communication
Document
Key
Column
Graph
DIANA
ARTEMIS
JNoSQ
L
Data Tier
24. Communication Issue
ODocument document = new ODocument(“collection”);
document.field(name, value);
JsonObject jsonObject = JsonObject.create();
jsonObject.put(name, value);
BaseDocument baseDocument = new
BaseDocument();
baseDocument.addAttribute(name, value);
Document document = new Document();
document.append(name, value);
25. Communication Issue
ODocument document = new ODocument(“collection”);
document.field(name, value);
JsonObject jsonObject = JsonObject.create();
jsonObject.put(name, value);
BaseDocument baseDocument = new
BaseDocument();
baseDocument.addAttribute(name, value);
Document document = new Document();
document.append(name, value);
26. Diversity
ColumnEntity entity = ColumnEntity.of(COLUMN_FAMILY);
Column id = Column.of("id", 10L);
entity.add(id);
entity.add(Column.of("version", 0.001));
entity.add(Column.of("name", "Diana"));
entity.add(Column.of("options", Arrays.asList(1, 2, 3)));
//mutiple implementation
columnEntityManager.save(entity);
ColumnQuery query =
select().from(COLUMN_FAMILY).where(ColumnCondition.eq(id)).build();
Optional<ColumnEntity> result = columnEntityManager.singleResult(query);
//cassandra only
List<ColumnEntity> entities = columnEntityManagerCassandra
.cql("select * from newKeySpace.newColumnFamily where id=10;");
columnEntityManagerCassandra.insert(entity, ConsistencyLevel.ALL);