ING Meetup - Migrating Spring Boot Config Annotations to Functional with Kotlin
•Descargar como PPTX, PDF•
1 recomendación•171 vistas
In the latest years, there has been some push-back against frameworks, and more specifically annotations: some call them magic. Obviously, they make understanding the flow of the application harder. Spring and Spring Boot latest versions go along this trend, by offering an additional way to configure beans with explicit code instead of annotations. It's declarative in the sense it looks like configuration, though it's based on Domain-Specific Language(s). This talk aims to demo a step-by-step process to achieve that.
Denunciar
Compartir
Denunciar
Compartir
Recomendados
vKUG - Migrating Spring Boot apps from annotation-based config to Functional
Migrating Spring Boot apps from annotation-based config to Functional with Kotlin - Nicolas Fränkel
In the latest years, there has been some push-back against frameworks, and more specifically annotations: some call them magic. Obviously, they make understanding the flow of the application harder.
Spring and Spring Boot latest versions go along this trend, by offering an additional way to configure beans with explicit code instead of annotations. It’s declarative in the sense it looks like configuration, though it’s based on Domain-Specific Language(s). This talk aims to demo a step-by-step process to achieve that.
GraphQL.net
This presentation gives a short introduction to GraphQL.net, and how ASP.net Core GraphQL services can be easily created and deployed.
SiriusCon 2017 - Sirius Tutorial Demo
During this first session I will present a step-by-step scenario which leads me to create a modeling tool for a Mindstorms Robot. This tool will allow users to define the choreography of a robot: moving forward, rotating, grabin or releasing objects.
From the specification of a dedicated metamodel to the creation of custom graphical editors, including properties views and advanced edition tools, you will see concretely the main stages of a Sirius-based modeling tool's inception.
Packaging AR Content to Wider Audience Using FME
My AR Visualization developers have been using Microsoft Hololens and Oculus Rift hardware to deliver AR experiences for projects for some time and after seeing examples of Angus' & Dmitri's work using FME+ARKit, I explored whether I could use FME to receive and manipulate my AR teams 3D content models into an Apple ARKit project and whether we could package the data in a downsampled form for AWS Sumerian framework webGL.
FME was used to modify the 3D model data and prepare a demonstration ARKit project/modules which is loaded to apple devices and stage a data package for AWS Sumerian to explore both endpoints for AR content delivery to a wider audience on lower form factor hardware.
OSCONF Koshi - Zero downtime deployment with Kubernetes, Flyway and Spring Boot
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day. You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
Safe on FME: Migrating the FME Community
The FME Community has undergone many 'glow ups' over the years, with the most recent being a new Community backing onto Salesforce. This new Community not only looks great, but having all our customer information in one place means we’re able to offer a higher level of support. Win, win!
The risk in moving platforms was whether or not we’d lose any valuable content along the way.
So how did we successfully push 1,642 articles, 3,045 ideas, and 18,450 questions over to Salesforce? With FME, of course!
Join this webinar to learn how Safe Software used FME to perform data migration tasks, including connecting to various APIs, data validation, and restructuring. And, as always, you’ll get plenty of tips and tricks along the way.
KotlinConf - Kotlin and Spring Boot, a match made in heaven
Despite being quite "new", Spring Boot has seen a spectacular start as an amazing kickstarter for Spring-based application.
You can now start your project in a matter of minutes, not days!
On the other hand, you're using magic that read annotations and run the code in obscure way.
Wouldn’t it be great if we could use a language and API that make this magic explicit?
In this talk, I’ll live migrate a Spring Boot "traditional" application to Kotlin DSL.
Come discover how you can now cut through all the mystery and take back control of your code.
Survival 15 06-2011
This document discusses issues with the survival of Eclipse plug-ins when compiling code. It analyzed version release rates between API and non-API plug-ins. There was a misclassification during compilation that has been solved by automating the compilation process. A resolution was reached to manually recompile plug-ins and verify that at least one classified version compiles with its corresponding plug-in.
Recomendados
vKUG - Migrating Spring Boot apps from annotation-based config to Functional
Migrating Spring Boot apps from annotation-based config to Functional with Kotlin - Nicolas Fränkel
In the latest years, there has been some push-back against frameworks, and more specifically annotations: some call them magic. Obviously, they make understanding the flow of the application harder.
Spring and Spring Boot latest versions go along this trend, by offering an additional way to configure beans with explicit code instead of annotations. It’s declarative in the sense it looks like configuration, though it’s based on Domain-Specific Language(s). This talk aims to demo a step-by-step process to achieve that.
GraphQL.net
This presentation gives a short introduction to GraphQL.net, and how ASP.net Core GraphQL services can be easily created and deployed.
SiriusCon 2017 - Sirius Tutorial Demo
During this first session I will present a step-by-step scenario which leads me to create a modeling tool for a Mindstorms Robot. This tool will allow users to define the choreography of a robot: moving forward, rotating, grabin or releasing objects.
From the specification of a dedicated metamodel to the creation of custom graphical editors, including properties views and advanced edition tools, you will see concretely the main stages of a Sirius-based modeling tool's inception.
Packaging AR Content to Wider Audience Using FME
My AR Visualization developers have been using Microsoft Hololens and Oculus Rift hardware to deliver AR experiences for projects for some time and after seeing examples of Angus' & Dmitri's work using FME+ARKit, I explored whether I could use FME to receive and manipulate my AR teams 3D content models into an Apple ARKit project and whether we could package the data in a downsampled form for AWS Sumerian framework webGL.
FME was used to modify the 3D model data and prepare a demonstration ARKit project/modules which is loaded to apple devices and stage a data package for AWS Sumerian to explore both endpoints for AR content delivery to a wider audience on lower form factor hardware.
OSCONF Koshi - Zero downtime deployment with Kubernetes, Flyway and Spring Boot
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day. You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
Safe on FME: Migrating the FME Community
The FME Community has undergone many 'glow ups' over the years, with the most recent being a new Community backing onto Salesforce. This new Community not only looks great, but having all our customer information in one place means we’re able to offer a higher level of support. Win, win!
The risk in moving platforms was whether or not we’d lose any valuable content along the way.
So how did we successfully push 1,642 articles, 3,045 ideas, and 18,450 questions over to Salesforce? With FME, of course!
Join this webinar to learn how Safe Software used FME to perform data migration tasks, including connecting to various APIs, data validation, and restructuring. And, as always, you’ll get plenty of tips and tricks along the way.
KotlinConf - Kotlin and Spring Boot, a match made in heaven
Despite being quite "new", Spring Boot has seen a spectacular start as an amazing kickstarter for Spring-based application.
You can now start your project in a matter of minutes, not days!
On the other hand, you're using magic that read annotations and run the code in obscure way.
Wouldn’t it be great if we could use a language and API that make this magic explicit?
In this talk, I’ll live migrate a Spring Boot "traditional" application to Kotlin DSL.
Come discover how you can now cut through all the mystery and take back control of your code.
Survival 15 06-2011
This document discusses issues with the survival of Eclipse plug-ins when compiling code. It analyzed version release rates between API and non-API plug-ins. There was a misclassification during compilation that has been solved by automating the compilation process. A resolution was reached to manually recompile plug-ins and verify that at least one classified version compiles with its corresponding plug-in.
Morning at Lohika - Spring Boot Kotlin, a match made in Heaven
The document discusses how Kotlin and Spring Boot are well integrated for developing applications. It provides an overview of Kotlin features like null safety and extensions, and how these improve on Java. It also discusses how Spring Boot works well with Kotlin's conventions. The document then shares details of a project to migrate a blog from XML to Markdown files using Kotlin and Spring Boot features like expression body methods and properties.
FME 2021.2: Conquer New Data Challenges with FME Cloud and FME Mobile
FME 2021.2 introduces new capabilities for FME Cloud and FME Mobile to help users conquer new data challenges. FME Cloud provides an easy way to deploy FME Server in the cloud within 10 minutes with automated backups and security handled. The new FME Cloud interface makes instance management simpler. FME Mobile updates include improved user experiences, attribute display in FME AR, and external GPS support for high accuracy location data collection.
Josh Atwell - Infrastructure Extensibility at Home and in DevOps
Josh Atwell presented an Ignite talk on infrastructure extensibility at home and in DevOps. The talk discussed how APIs and SDKs can be used to manage infrastructure and integrate with common tools, providing agility to change infrastructure programmatically and maximize available features. Atwell also covered how policy-based management uses policies to define identity and behavior consistently across many resources, helping to control and monitor configuration drift.
Solving The Deployment Problem
The document proposes a System Settings API to solve issues with functional configuration management and deployment in sites. The API would provide a central location for all site configuration, support change logging, and allow pluggable storage mechanisms. This would make adding features less disruptive and merging configuration across environments easier. The API is designed to support storing structured data and allow modules to specify how and when settings are loaded. New potential features include pluggable storage options, configuration version control, and a configuration server to propagate changes.
How to Pivot Workflows with FME Tools
Have you wondered how you can make the power of FME more available? Guido Stein, a Safe Software Professional, will share lessons learned creating a series of tools for managing a GIS database which can import from DGN CAD data and export to DGN or other GIS output. The toolset developed started with fmw files, became part of a workflow using Microsoft Access as a GUI, and is now a FME Server toolset with a web app interface.
IFTTT Introduction
IFTTT is a service that allows users to create connections between different web services and apps without coding. Users can create "Recipes" that trigger an action when a specific event occurs by selecting from available "Channels". For example, a user could create a Recipe that logs their entry and exit times from their office to a Google Spreadsheet automatically whenever they enter or exit a designated area. Recipes can be organized into "Collections" for specific purposes like automated timesheets.
Extreme automation
Michele Orselli discusses techniques for extreme automation in software development. Some key points include:
- Using tools like Puppet, Vagrant, and local DNS servers to automate project setup and server configuration across multiple machines and projects.
- Implementing techniques like build automation, configuration management, and data migrations to reduce deployment times and ensure consistency.
- Employing practices like test-driven development, continuous integration/delivery, and infrastructure as code to improve efficiency and allow developers to focus on delivering business value.
OSCONF Jaipur - A Hitchhiker's Tour to Containerizing a Java application
As “the Cloud” becomes more and more widespread, now is a good time to assess how you can containerize your Java application. I assume you’re able to write a a Dockerfile around the generated JAR. However, each time the application’s code will change, the whole image will need to be rebuilt. If you’re deploying to a local Kubernetes cluster environment, this increases that much the length of the feedback loop.
In this demo-based talk, I’ll present different ways to get your Java app in a container: Dockerfile, Jib, and Cloud Native Buildpacks. We will also have a look at what kind of Docker image they generate, how they layer the images, whether those images are compatible with skaffold, etc.
GeekOut - Configuration Management with Kubernetes, a Spring-Boot use-case
Come discover what options Kubernetes allows in terms of configuration management!
Docker images are supposed to (and should be) immutable. Given that the same image should be promoted from the development environment to the production environment, it needs to be parameterized in each environment.
Kubernetes provides different ways to do that. On the other, the Spring Boot platform allows a wide range of configuration options. In this talk, I’ll go through (and demo!) what common options are available, and what pro(s)/con(s) each of them have.
AllTheTalks.online - A Streaming Use-Case: And Experiment in Continuous Deplo...
Nicolas Fränkel proposes an experimental use case of continuous deployment of bytecode by dynamically loading Java agents into a running JVM using the Attach API. The agent would use the Instrumentation API to modify bytecode of running applications by redefining classes in order to deploy changes made by a continuous integration pipeline without restarting the JVM. Current limitations include a lack of tagging and an inability to add/remove fields or methods via redefinition. Improvements could include streaming changes directly from the CI pipeline and adding metadata to classes from the Git tag.
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
How to leverage Azure ML, automated machine learning, and Streamlit to build and test machine learning apps quickly? Find out about our favorite Hackathon stack and walk away with some code to build and user-test your own machine learning ideas fast.
Experimentation, bringing machine learning ideas in front of users, is essential to innovation. Yet, in our corporate hackathons, our data science team has struggled many times with how to build and deploy user-facing machine learning ideas in just a single day.
Over the past 2+ years, we have developed a routine around using Azure Machine Learning, automated machine learning, and Streamlit to build and user test machine learning ideas quickly. The aim of this talk is to pass on practical, technical knowledge to fellow data scientists about how to leverage this stack to achieve high build and user test speeds.
During the talk, we will walk through the process of building a computer vision system for identifying trash in images via an app using the open-source TACO dataset (http://tacodataset.org/). Working through a Jupyter notebook, we will load the data into Azure Machine Learning and trigger an automated machine learning run on the data. In this context, we will quickly get to know the training and testing metrics available in Azure ML to evaluate the model. We will then download the machine learning model as a file packaged in the open-source ONNX format (https://onnx.ai/). Using the open-source Python web application framework Streamlit (https://github.com/streamlit/streamlit), we will program an application in which users can upload images and embed the machine learning model in it to identify trash in these images. Using a to-be-published infrastructure-as-code pipeline on Azure DevOps, we will deploy the application to the public internet on the Azure platform. From here, users can test it.
The stack and code presented in this talk will enable fellow data scientists to accelerate their data science development, leading to quicker experimentation and, therefore, to faster innovation of products with machine learning at their core.
JCon - Zero-Downtime-Deployment with Kubernetes, Spring Boot and Flyway
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
VoxxedDays Cluj - Zero-downtime deployment with Kubernetes, Spring Boot and F...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day. You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point.
In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
DevOpsDays Madrid - Zero-downtime deployment with Kubernetes, Spring Boot and...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
workshop_8_c__.pdf
This document provides instructions for students to implement the execution of map and reduce tasks on workers in a MapReduce system. It details expected outcomes such as deploying MapReduce applications to Azure Kubernetes and developing an HTTP interface. It also provides suggestions on implementing Python code wrappers to execute mapper and reducer functions, saving intermediate and final results, and delivering required code and demos.
Advanced angular
Slides for meetup @Talentica Software on 25th January 2020
Topics Covered:
1. Dependency Injection
2. Ng-schematics
3. How to structure your apps
4. Deployment
London Java Community - An Experiment in Continuous Deployment of JVM applica...
A couple of years ago, continuous integration in the JVM ecosystem meant Jenkins. Since that time, a lot of other tools have been made available. But new tools don’t mean new features, just new ways. Besides that, what about continuous deployment? There’s no tool that allows deploying new versions of a JVM-based application without downtime. The only way to achieve zero downtime is to have multiple nodes deployed on a platform, and let that platform achieve that e.g. Kubernetes.
And yet, achieving true continuous deployment of bytecode on one single JVM instance is possible if one changes one’s way of looking at things. What if the compilation could be seen as changes? What if those changes could be stored in a data store, and a listener on this data store could stream those changes to the running production JVM via the Attach API?
In this talk, we'll demo exactly that using Hazelcast and Hazelcast Jet - but it’s possible to re-use the principles that will be shown using other streaming technologies.
Zero-downtime deployment on Kubernetes with Hazelcast
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day because we need to handle state. Though it would be much easier to have stateless apps, and despite our best efforts in this direction, state is found in (at least) two places: sessions and databases.
You need to think keeping the state while stopping and starting application nodes. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema change with the help of Hazelcast, while keeping the service up during the entire update process.
Orchestrate Your End-to-end Mainframe Application Release Pipeline
What steel and concrete are to a skyscraper, the mainframe is to the global economy. The mainframe is the transactional backbone for 96 of the world’s top 100 banks, 23 of the 25 top US retailers and 9 out of 10 of the world’s largest insurance companies.
When you think of a mainframe, you probably think of an old green computer screen. Did you know you can use the same modern tools and techniques with mainframes that you use with cloud and mobile?
With the growth of mission-critical mainframe workloads showing no signs of slowing down, application delivery cannot remain slow and complex. Organizations must apply the same DevOps processes to the mainframe as they do with other platforms.
Compuware and XebiaLabs enable large enterprises to automatically build, test and deploy mainframe releases within a cross-platform application release pipeline.
JavaDay Istanbul - 3 improvements in your microservices architecture
While a microservices architecture is more scalable than a monolith, it has a direct hit on performance.
To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I’ll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it. Hint: it’s much easier than one would expect.
XP Days Ukraine - Zero-downtime deployment with Kubernetes, Spring Boot and F...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
Bootstrap4XPages
The document provides information about Bootstrap4XPages, a plugin that brings the Bootstrap front-end framework to XPages applications. It discusses what Bootstrap is, the benefits of using it, and how the Bootstrap4XPages plugin works. The plugin provides Bootstrap styling for XPages components out of the box. It can be installed on Domino servers and in Designer. The document demonstrates how to enable Bootstrap styling on an XPages application by selecting the Bootstrap4XPages library and theme. It also covers creating layouts, views, dialogs, and other application elements using Bootstrap styled XPages components. Custom themes and upcoming features are mentioned. Contributions to the open source project are welcomed.
Más contenido relacionado
La actualidad más candente
Morning at Lohika - Spring Boot Kotlin, a match made in Heaven
The document discusses how Kotlin and Spring Boot are well integrated for developing applications. It provides an overview of Kotlin features like null safety and extensions, and how these improve on Java. It also discusses how Spring Boot works well with Kotlin's conventions. The document then shares details of a project to migrate a blog from XML to Markdown files using Kotlin and Spring Boot features like expression body methods and properties.
FME 2021.2: Conquer New Data Challenges with FME Cloud and FME Mobile
FME 2021.2 introduces new capabilities for FME Cloud and FME Mobile to help users conquer new data challenges. FME Cloud provides an easy way to deploy FME Server in the cloud within 10 minutes with automated backups and security handled. The new FME Cloud interface makes instance management simpler. FME Mobile updates include improved user experiences, attribute display in FME AR, and external GPS support for high accuracy location data collection.
Josh Atwell - Infrastructure Extensibility at Home and in DevOps
Josh Atwell presented an Ignite talk on infrastructure extensibility at home and in DevOps. The talk discussed how APIs and SDKs can be used to manage infrastructure and integrate with common tools, providing agility to change infrastructure programmatically and maximize available features. Atwell also covered how policy-based management uses policies to define identity and behavior consistently across many resources, helping to control and monitor configuration drift.
Solving The Deployment Problem
The document proposes a System Settings API to solve issues with functional configuration management and deployment in sites. The API would provide a central location for all site configuration, support change logging, and allow pluggable storage mechanisms. This would make adding features less disruptive and merging configuration across environments easier. The API is designed to support storing structured data and allow modules to specify how and when settings are loaded. New potential features include pluggable storage options, configuration version control, and a configuration server to propagate changes.
How to Pivot Workflows with FME Tools
Have you wondered how you can make the power of FME more available? Guido Stein, a Safe Software Professional, will share lessons learned creating a series of tools for managing a GIS database which can import from DGN CAD data and export to DGN or other GIS output. The toolset developed started with fmw files, became part of a workflow using Microsoft Access as a GUI, and is now a FME Server toolset with a web app interface.
IFTTT Introduction
IFTTT is a service that allows users to create connections between different web services and apps without coding. Users can create "Recipes" that trigger an action when a specific event occurs by selecting from available "Channels". For example, a user could create a Recipe that logs their entry and exit times from their office to a Google Spreadsheet automatically whenever they enter or exit a designated area. Recipes can be organized into "Collections" for specific purposes like automated timesheets.
Extreme automation
Michele Orselli discusses techniques for extreme automation in software development. Some key points include:
- Using tools like Puppet, Vagrant, and local DNS servers to automate project setup and server configuration across multiple machines and projects.
- Implementing techniques like build automation, configuration management, and data migrations to reduce deployment times and ensure consistency.
- Employing practices like test-driven development, continuous integration/delivery, and infrastructure as code to improve efficiency and allow developers to focus on delivering business value.
La actualidad más candente (7)
Morning at Lohika - Spring Boot Kotlin, a match made in Heaven
Morning at Lohika - Spring Boot Kotlin, a match made in Heaven
FME 2021.2: Conquer New Data Challenges with FME Cloud and FME Mobile
FME 2021.2: Conquer New Data Challenges with FME Cloud and FME Mobile
Josh Atwell - Infrastructure Extensibility at Home and in DevOps
Josh Atwell - Infrastructure Extensibility at Home and in DevOps
Similar a ING Meetup - Migrating Spring Boot Config Annotations to Functional with Kotlin
OSCONF Jaipur - A Hitchhiker's Tour to Containerizing a Java application
As “the Cloud” becomes more and more widespread, now is a good time to assess how you can containerize your Java application. I assume you’re able to write a a Dockerfile around the generated JAR. However, each time the application’s code will change, the whole image will need to be rebuilt. If you’re deploying to a local Kubernetes cluster environment, this increases that much the length of the feedback loop.
In this demo-based talk, I’ll present different ways to get your Java app in a container: Dockerfile, Jib, and Cloud Native Buildpacks. We will also have a look at what kind of Docker image they generate, how they layer the images, whether those images are compatible with skaffold, etc.
GeekOut - Configuration Management with Kubernetes, a Spring-Boot use-case
Come discover what options Kubernetes allows in terms of configuration management!
Docker images are supposed to (and should be) immutable. Given that the same image should be promoted from the development environment to the production environment, it needs to be parameterized in each environment.
Kubernetes provides different ways to do that. On the other, the Spring Boot platform allows a wide range of configuration options. In this talk, I’ll go through (and demo!) what common options are available, and what pro(s)/con(s) each of them have.
AllTheTalks.online - A Streaming Use-Case: And Experiment in Continuous Deplo...
Nicolas Fränkel proposes an experimental use case of continuous deployment of bytecode by dynamically loading Java agents into a running JVM using the Attach API. The agent would use the Instrumentation API to modify bytecode of running applications by redefining classes in order to deploy changes made by a continuous integration pipeline without restarting the JVM. Current limitations include a lack of tagging and an inability to add/remove fields or methods via redefinition. Improvements could include streaming changes directly from the CI pipeline and adding metadata to classes from the Git tag.
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
How to leverage Azure ML, automated machine learning, and Streamlit to build and test machine learning apps quickly? Find out about our favorite Hackathon stack and walk away with some code to build and user-test your own machine learning ideas fast.
Experimentation, bringing machine learning ideas in front of users, is essential to innovation. Yet, in our corporate hackathons, our data science team has struggled many times with how to build and deploy user-facing machine learning ideas in just a single day.
Over the past 2+ years, we have developed a routine around using Azure Machine Learning, automated machine learning, and Streamlit to build and user test machine learning ideas quickly. The aim of this talk is to pass on practical, technical knowledge to fellow data scientists about how to leverage this stack to achieve high build and user test speeds.
During the talk, we will walk through the process of building a computer vision system for identifying trash in images via an app using the open-source TACO dataset (http://tacodataset.org/). Working through a Jupyter notebook, we will load the data into Azure Machine Learning and trigger an automated machine learning run on the data. In this context, we will quickly get to know the training and testing metrics available in Azure ML to evaluate the model. We will then download the machine learning model as a file packaged in the open-source ONNX format (https://onnx.ai/). Using the open-source Python web application framework Streamlit (https://github.com/streamlit/streamlit), we will program an application in which users can upload images and embed the machine learning model in it to identify trash in these images. Using a to-be-published infrastructure-as-code pipeline on Azure DevOps, we will deploy the application to the public internet on the Azure platform. From here, users can test it.
The stack and code presented in this talk will enable fellow data scientists to accelerate their data science development, leading to quicker experimentation and, therefore, to faster innovation of products with machine learning at their core.
JCon - Zero-Downtime-Deployment with Kubernetes, Spring Boot and Flyway
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
VoxxedDays Cluj - Zero-downtime deployment with Kubernetes, Spring Boot and F...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day. You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point.
In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
DevOpsDays Madrid - Zero-downtime deployment with Kubernetes, Spring Boot and...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
workshop_8_c__.pdf
This document provides instructions for students to implement the execution of map and reduce tasks on workers in a MapReduce system. It details expected outcomes such as deploying MapReduce applications to Azure Kubernetes and developing an HTTP interface. It also provides suggestions on implementing Python code wrappers to execute mapper and reducer functions, saving intermediate and final results, and delivering required code and demos.
Advanced angular
Slides for meetup @Talentica Software on 25th January 2020
Topics Covered:
1. Dependency Injection
2. Ng-schematics
3. How to structure your apps
4. Deployment
London Java Community - An Experiment in Continuous Deployment of JVM applica...
A couple of years ago, continuous integration in the JVM ecosystem meant Jenkins. Since that time, a lot of other tools have been made available. But new tools don’t mean new features, just new ways. Besides that, what about continuous deployment? There’s no tool that allows deploying new versions of a JVM-based application without downtime. The only way to achieve zero downtime is to have multiple nodes deployed on a platform, and let that platform achieve that e.g. Kubernetes.
And yet, achieving true continuous deployment of bytecode on one single JVM instance is possible if one changes one’s way of looking at things. What if the compilation could be seen as changes? What if those changes could be stored in a data store, and a listener on this data store could stream those changes to the running production JVM via the Attach API?
In this talk, we'll demo exactly that using Hazelcast and Hazelcast Jet - but it’s possible to re-use the principles that will be shown using other streaming technologies.
Zero-downtime deployment on Kubernetes with Hazelcast
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day because we need to handle state. Though it would be much easier to have stateless apps, and despite our best efforts in this direction, state is found in (at least) two places: sessions and databases.
You need to think keeping the state while stopping and starting application nodes. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema change with the help of Hazelcast, while keeping the service up during the entire update process.
Orchestrate Your End-to-end Mainframe Application Release Pipeline
What steel and concrete are to a skyscraper, the mainframe is to the global economy. The mainframe is the transactional backbone for 96 of the world’s top 100 banks, 23 of the 25 top US retailers and 9 out of 10 of the world’s largest insurance companies.
When you think of a mainframe, you probably think of an old green computer screen. Did you know you can use the same modern tools and techniques with mainframes that you use with cloud and mobile?
With the growth of mission-critical mainframe workloads showing no signs of slowing down, application delivery cannot remain slow and complex. Organizations must apply the same DevOps processes to the mainframe as they do with other platforms.
Compuware and XebiaLabs enable large enterprises to automatically build, test and deploy mainframe releases within a cross-platform application release pipeline.
JavaDay Istanbul - 3 improvements in your microservices architecture
While a microservices architecture is more scalable than a monolith, it has a direct hit on performance.
To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I’ll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it. Hint: it’s much easier than one would expect.
XP Days Ukraine - Zero-downtime deployment with Kubernetes, Spring Boot and F...
Kubernetes allows a lot. After discovering its features, it’s easy to think it can magically transform your application deployment process into a painless no-event. For Hello World applications, that is the case. Unfortunately, not many of us do deploy such applications day-to-day.
You need to think about application backward compatibility, possible rollback, database schema migration, etc. I believe the later is one of the biggest pain point. In this talk, I’ll demo how to update a Spring Boot app deployed on a Kubernetes cluster with a non-trivial database schema migration with the help of Flyway, while keeping the service up during the entire update process.
Bootstrap4XPages
The document provides information about Bootstrap4XPages, a plugin that brings the Bootstrap front-end framework to XPages applications. It discusses what Bootstrap is, the benefits of using it, and how the Bootstrap4XPages plugin works. The plugin provides Bootstrap styling for XPages components out of the box. It can be installed on Domino servers and in Designer. The document demonstrates how to enable Bootstrap styling on an XPages application by selecting the Bootstrap4XPages library and theme. It also covers creating layouts, views, dialogs, and other application elements using Bootstrap styled XPages components. Custom themes and upcoming features are mentioned. Contributions to the open source project are welcomed.
Create a copy of your SharePoint farm with SPDocKit and AutoSPInstaller
SPDocKit helps you generate an XML configuration file that you can use with AutoSPInstaller to create a new SharePoint farm that is the same as or similar to your current farm environment.
The configuration file reduces the time needed to deploy SharePoint, and since everything is reusable, you can create production and staging/testing environments that are identical.
Achieving end-to-end visibility into complex event-sourcing transactions usin...
Event-sourcing systems usage like Kafka is growing rapidly among Node.js applications. Building systems around an event-driven architecture simplifies horizontal scalability in distributed computing models and makes them more resilient to failure. With these advantages, we face new challenges - how to get visibility into these complex processes.
Event-driven architecture is async by nature. Tracking the communication between different components is both extremely difficult and important when debugging or figuring out bottlenecks in the system.
In this talk, I will present ways to achieve end-to-end and granular visibility into complex event-sourcing transactions using distributed tracing. I will use open-source tools like OpenTelemetry, Jaeger, and Zipkin to showcase a complex Node.js system using Kafka.
OpenStack Glance Project Update
Glance is the OpenStack image service that provides services to store, browse, share, distribute, and manage disk images and metadata. It is deployed by 97% of OpenStack clouds. Contributor numbers grew for the Ocata release but declined after budget cuts impacted the core reviewer team. The presentation outlines features added in recent releases and themes for upcoming releases, and asks for help contributing in various ways.
Effective .NET Core Unit Testing with SQLite and Dapper
- The document discusses effective unit testing for .NET Core applications that use SQLite and Dapper for data access.
- It motivates the importance of unit testing, then demonstrates how to set up an in-memory SQLite database to run tests against instead of a live SQL Server database for isolation.
- Best practices like test-driven development, code coverage reports, and writing tests for bug fixes are also covered, with examples shown of integrating the XUnit testing framework.
It’s 2021. Why are we -still- rebooting for patches? A look at Live Patching.
Presented by: Igor Seletskiy
Presented at the All Things Open 2021
Raleigh, NC, USA
Raleigh Convention Center
Abstract: IT Teams know the drill. New security bulletins, new issues, new patches to deploy. Schedule another maintenance operation and prepare for system downtime.
There is a better way to do things. Live patching has been around in the Linux Kernel for some time now, but adoption has not been ideal so far - either because of a lack of trust in the technology or just lack of awareness - or sysadmins just enjoy interrupting their workloads or users.
Live patching consists of two aspects. First, there has to be a mechanism for function redirection in the kernel. As in many things, the kernel actually provides three different subset of tools that provide this functionality - kprobes, fprobes and Livepatching. Secondly, Live Patching relies on a set of tools to generate the actual patches to deploy, replacing the old code with new one. This is arguably the most involved part: you need to fit your new code in the proper space, you can’t overwrite other unrelated code and you need to maintain compatibility with other functions. If you change your parameter list, for example, its game over - something will break in the worst possible way.
In this talk we’ll go over issues like Consistency model, patch generation, deployment mechanisms and identify situations that are ideal candidates for live patching instead of traditional patching operations.
Similar a ING Meetup - Migrating Spring Boot Config Annotations to Functional with Kotlin (20)
OSCONF Jaipur - A Hitchhiker's Tour to Containerizing a Java application
OSCONF Jaipur - A Hitchhiker's Tour to Containerizing a Java application
GeekOut - Configuration Management with Kubernetes, a Spring-Boot use-case
GeekOut - Configuration Management with Kubernetes, a Spring-Boot use-case
AllTheTalks.online - A Streaming Use-Case: And Experiment in Continuous Deplo...
AllTheTalks.online - A Streaming Use-Case: And Experiment in Continuous Deplo...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
JCon - Zero-Downtime-Deployment with Kubernetes, Spring Boot and Flyway
JCon - Zero-Downtime-Deployment with Kubernetes, Spring Boot and Flyway
VoxxedDays Cluj - Zero-downtime deployment with Kubernetes, Spring Boot and F...
VoxxedDays Cluj - Zero-downtime deployment with Kubernetes, Spring Boot and F...
DevOpsDays Madrid - Zero-downtime deployment with Kubernetes, Spring Boot and...
DevOpsDays Madrid - Zero-downtime deployment with Kubernetes, Spring Boot and...
London Java Community - An Experiment in Continuous Deployment of JVM applica...
London Java Community - An Experiment in Continuous Deployment of JVM applica...
Zero-downtime deployment on Kubernetes with Hazelcast
Zero-downtime deployment on Kubernetes with Hazelcast
Orchestrate Your End-to-end Mainframe Application Release Pipeline
Orchestrate Your End-to-end Mainframe Application Release Pipeline
JavaDay Istanbul - 3 improvements in your microservices architecture
JavaDay Istanbul - 3 improvements in your microservices architecture
XP Days Ukraine - Zero-downtime deployment with Kubernetes, Spring Boot and F...
XP Days Ukraine - Zero-downtime deployment with Kubernetes, Spring Boot and F...
Create a copy of your SharePoint farm with SPDocKit and AutoSPInstaller
Create a copy of your SharePoint farm with SPDocKit and AutoSPInstaller
Achieving end-to-end visibility into complex event-sourcing transactions usin...
Achieving end-to-end visibility into complex event-sourcing transactions usin...
Effective .NET Core Unit Testing with SQLite and Dapper
Effective .NET Core Unit Testing with SQLite and Dapper
It’s 2021. Why are we -still- rebooting for patches? A look at Live Patching.
It’s 2021. Why are we -still- rebooting for patches? A look at Live Patching.
Más de Nicolas Fränkel
SnowCamp - Adding search to a legacy application
Most applications evolve to a point where they need to provide search capabilities. But updating an application is always a risk. Plus, sometimes, you don’t have access to the source code. The easiest way to access the data is by getting them directly from the database.
The initial load is the easiest step. However, how do you keep the search index in sync with the database? How do you keep the latency between the search store and the source of truth, so your users don’t have to wait for the next run of the batch to access the newest changes?
In this live coding session, we will show you how you can solve this issue by connecting Elasticsearch to the database with a touch of Hazelcast.
Un CV de dévelopeur toujours a jour
On dit que GitHub est le CV d'un développeur. Un rapide coup d'œil à votre historique de commit et les recruteurs savent tout de vous. Cette approche comporte quelques problèmes. La plupart des entreprises ne publient même pas leur code sous une licence Open Source. Si vous travaillez pour l'une d'entre elles, et si vous n'êtes pas un développeur Open Source les soirs et les week-ends, alors vous n'avez aucune chance.
Récemment, GitHub a permis un certain degré de personnalisation de son profil. Ainsi, même si votre historique de commit a plus de blanc que de vert, vous pouvez fournir un bon point d'entrée pour les employeurs potentiels. Mais ça ne vaut que l'effort que vous y mettez et les données perdent leur valeur rapidement. Pourtant, avec un peu de travail et l'aide d'outils d'automatisation (tels que GitHub Actions), vous pouvez présenter un profil toujours à jour.
jLove - A Change-Data-Capture use-case: designing an evergreen cache
When one’s app is challenged with poor performances, it’s easy to set up a cache in front of one’s SQL database. It doesn’t fix the root cause (e.g. bad schema design, bad SQL query, etc.) but it gets the job done. If the app is the only component that writes to the underlying database, it’s a no-brainer to update the cache accordingly, so the cache is always up-to-date with the data in the database.
Things start to go sour when the app is not the only component writing to the DB. Among other sources of writes, there are batches, other apps (shared databases exist unfortunately), etc. One might think about a couple of ways to keep data in sync i.e. polling the DB every now and then, DB triggers, etc. Unfortunately, they all have issues that make them unreliable and/or fragile.
You might have read about Change-Data-Capture before. It’s been described by Martin Kleppmann as turning the database inside out: it means the DB can send change events (SELECT, DELETE and UPDATE) that one can register to. Just opposite to Event Sourcing that aggregates events to produce state, CDC is about getting events out of states. Once CDC is implemented, one can subscribe to its events and update the cache accordingly. However, CDC is quite in its early stage, and implementations are quite specific.
In this talk, I’ll describe an easy-to-setup architecture that leverages CDC to have an evergreen cache.
BigData conference - Introduction to stream processing
This document discusses stream processing and summarizes a presentation about the topic. It introduces Hazelcast Jet as a stream processing engine and covers open data standards like GTFS. It also describes a demo that uses GTFS data to enrich public transit vehicle position updates in real-time using Hazelcast Jet. The presentation discusses streaming approaches, benefits over batch processing, and provides an overview of stream processing concepts.
ADDO - Your own Kubernetes controller, not only in Go
In Kubernetes, operators allow the API to be extended to your heart content. If one task requires too much YAML, it’s easy to create an operator to take care of the repetitive cruft, and only require a minimum amount of YAML.
On the other hand, since its beginnings, the Go language has been advertised as closer to the hardware, and is now ubiquitous in low-level programming. Kubernetes has been rewritten from Java to Go, and its whole ecosystem revolves around Go. For that reason, It’s only natural that Kubernetes provides a Go-based framework to create your own operator. While it makes sense, it requires organizations willing to go down this road to have Go developers, and/or train their teams in Go. While perfectly acceptable, this is not the only option. In fact, since Kubernetes is based on REST, why settle for Go and not use your own favorite language?
In this talk, I’ll describe what is an operator, how they work, how to design one, and finally demo a Java-based operator that is as good as a Go one.
TestCon Europe - Mutation Testing to the Rescue of Your Tests
Unit testing ensures your production code is relevant. But what does ensure your testing code is relevant? Come discover mutation testing and make sure your never forget another assert again.
In the realm of testing, the code coverage metrics is the most often talked about. However, it doesn’t mean that the test has been useful or even that an assert has been coded. Mutation testing is a strategy to make sure that the test code is relevant.
In this talk, Nicolas will explain how Code Coverage is computed and what its inherent flaw is. Afterwards, he will describe how Mutation Testing work and how it helps pointing out code that is tested but leave out corner cases. He will also demo PIT, a Java production-grade framework that enables Mutation Testing.
GeekcampSG 2020 - A Change-Data-Capture use-case: designing an evergreen cache
CDC is a brand new approach that "turns the database inside out": it allows to get events out of the database state. This can be leveraged to get a cache that is never stale.
OSCONF Hyderabad - Shorten all URLs!
At a point in the past, it was forecast that Java would die, but the JVM platform would be its legacy. And in fact, for a long time, the JVM has been tremendously successful. Wikipedia itself lists a bunch of languages that run on it, some of them close to Java e.g. Kotlin, some of them very remote e.g. Clojure.
But nowadays, the Cloud is becoming ubiquitous. Containerization is the way to go to alleviate some of the vendor lock-in issues. Kubernetes is a de facto platform. If a container needs to be killed for whatever reason (resource consumption, unhealthy, etc.), a new one needs to replace it as fast as possible. In that context, the JVM seems to be a dead-end: its startup time is huge in comparison to a native process. Likewise, it consumes a lot of memory that just increase the monthly bill.
What does that mean for us developers? Has all the time spent in learning the JVM ecosystem been invested with no hope of return over investment? Shall we need to invest even more time in new languages, frameworks, libraries, etc.? That is one possibility for sure. But we can also leverage our existing knowledge, and embrace the Cloud and containers ways with the help of some tools.
In this talk, I’ll create a simple URL shortener with a “standard” stack: Kotlin, JAX-RS and Hazelcast. Then, with the help of Quarkus and GraalVM, I’ll turn this application into a native executable with all Cloud/Container related work has been moved to the build process.
Devclub.lv - Introduction to stream processing
While “software is eating the world”, those who are able to best manage the huge mass of data will emerge out on the top.
The batch processing model has been faithfully serving us for decades. However, it might have reached the end of its usefulness for all but some very specific use-cases. As the pace of businesses increases, most of the time, decision-makers prefer slightly wrong data sooner, than 100% accurate data later. Stream processing – or data streaming – exactly matches this usage: instead of managing the entire bulk of data, manage pieces of them as soon as they become available.
JOnConf - A CDC use-case: designing an Evergreen Cache
This document discusses using change data capture (CDC) and Hazelcast Jet to build an evergreen cache that remains in sync with a database. It covers alternatives to cache invalidation like polling and triggers, introduces CDC and the Debezium implementation, and proposes a Jet job that watches database change events, analyzes them, and updates the cache accordingly to solve the cache freshness problem.
London In-Memory Computing Meetup - A Change-Data-Capture use-case: designing...
When one’s app is challenged with poor performances, it’s easy to set up a cache in front of one’s SQL database. It doesn’t fix the root cause (e.g. bad schema design, bad SQL query, etc.) but it gets the job done. If the app is the only component that writes to the underlying database, it’s a no-brainer to update the cache accordingly, so the cache is always up-to-date with the data in the database.
Things start to go sour when the app is not the only component writing to the DB. Among other sources of writes, there are batches, other apps (shared databases exist, unfortunately), etc. One might think about a couple of ways to keep data in sync i.e. polling the DB every now and then, DB triggers, etc. Unfortunately, they all have issues that make them unreliable and/or fragile.
In this talk, I will describe an easy-to-setup architecture that leverages CDC to have an evergreen cache.
JUG Tirana - Introduction to data streaming
This talk will be about the reasons behind the new stream processing model, how it compare to the old batch model, what are their pros and cons, and a list of existing technologies implementing stream processing with their most prominent characteristics. It will contain details of one possible use-case of data streaming that is not possible with batches: display in (near) real-time all trains in Switzerland and their position on a map, beginning with an overview of all the requirements and the design. Finally, using an OpenData endpoint and the Hazelcast platform,showing a working demo implementation of it.
Java.IL - Your own Kubernetes controller, not only in Go!
In Kubernetes, operators allow the API to be extended to your heart content. If one task requires too much YAML, it’s easy to create an operator to take care of the repetitive cruft, and only require a minimum amount of YAML.
On the other hand, since its beginnings, the Go language has been advertised as closer to the hardware, and is now ubiquitous in low-level programming. Kubernetes has been rewritten from Java to Go, and its whole ecosystem revolves around Go. For that reason, It’s only natural that Kubernetes provides a Go-based framework to create your own operator. While it makes sense, it requires organizations willing to go down this road to have Go developers, and/or train their teams in Go. While perfectly acceptable, this is not the only option. In fact, since Kubernetes is based on REST, why settle for Go and not use your own favorite language?
In this talk, I’ll describe what is an operator, how they work, how to design one, and finally demo a Java-based operator that is as good as a Go one.
vJUG - Introduction to data streaming
The document discusses stream processing and provides an overview of Hazelcast Jet. It begins with explaining why streaming is useful and describes different streaming approaches like event-driven programming. It then provides details on Hazelcast Jet, including its concepts of pipelines and jobs. The document also discusses open data standards like GTFS and demonstrates a sample streaming pipeline that enriches public transportation data from open APIs.
OSCONF - Your own Kubernetes controller: not only in Go
This document discusses creating Kubernetes operators and controllers using different programming languages besides Go. It suggests that a Java-based controller is possible using the GraalVM, which allows creating native executables from Java bytecode. Key points covered include what controllers and operators are, that no specific technology stack is required, and that the JVM could be a good option for controller development with GraalVM's support for polyglot programming and creating native applications.
Tech talks - 3 performance improvements
While a microservices architecture is more scalable than a monolith, it has a direct hit on performance.
To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I’ll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it.
Hint: it’s much easier than one would expect.
SouJava- 3 easy performance improvements in your microservices architecture
While a microservices architecture is more scalable than a monolith, it has a direct hit on performance.
To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I'll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it. Hint: it's much easier than one would expect.
JUG SF - Introduction to data streaming
While “software is eating the world”, those who are able to best manage the huge mass of data will emerge out on the top.
The batch processing model has been faithfully serving us for decades. However, it might have reached the end of its usefulness for all but some very specific use-cases. As the pace of businesses increases, most of the time, decision makers prefer slightly wrong data sooner, than 100% accurate data later. Stream processing - or data streaming - exactly matches this usage: instead of managing the entire bulk of data, manage pieces of them as soon as they become available.
In this talk, I’ll define the context in which the old batch processing model was born, the reasons that are behind the new stream processing one, how they compare, what are their pros and cons, and a list of existing technologies implementing the latter with their most prominent characteristics. I’ll conclude by describing in detail one possible use-case of data streaming that is not possible with batches: display in (near) real-time all trains in Switzerland and their position on a map. I’ll go through the all the requirements and the design. Finally, using an OpenData endpoint and the Hazelcast platform, I’ll try to impress attendees with a working demo implementation of it.
SCALE - Stream processing and Open Data, a match made in Heaven
While “software is eating the world”, those who are able to best manage the huge mass of data will emerge out on the top.
Some countries in Europe understand the potential there's in existing data that sits behind closed fences, and passed laws to make this data available to everyone.
On the other hand, the batch processing model gets more and more obsolete: users want the information as soon as possible. While there’s a trade-off between correctness of data, and its speed of delivery, most business decisions do not rely on 100% correct data.
In this talk, I’ll explain how one can leverage the data related to public transportation in Switzerland, to display them in (near) real-time on a map.
ConFoo - 3 performance improvements
While a microservices architecture is more scalable than a monolith, it has a direct hit on performance.
To cope with that, one performance improvement is to set up a cache. It can be configured for database access, for REST calls or just to store session state across a cluster of server nodes. In this demo-based talk, I'll show how Hazelcast In-Memory Data Grid can help you in each one of those areas and how to configure it.
Más de Nicolas Fränkel (20)
jLove - A Change-Data-Capture use-case: designing an evergreen cache
jLove - A Change-Data-Capture use-case: designing an evergreen cache
BigData conference - Introduction to stream processing
BigData conference - Introduction to stream processing
ADDO - Your own Kubernetes controller, not only in Go
ADDO - Your own Kubernetes controller, not only in Go
TestCon Europe - Mutation Testing to the Rescue of Your Tests
TestCon Europe - Mutation Testing to the Rescue of Your Tests
GeekcampSG 2020 - A Change-Data-Capture use-case: designing an evergreen cache
GeekcampSG 2020 - A Change-Data-Capture use-case: designing an evergreen cache
JOnConf - A CDC use-case: designing an Evergreen Cache
JOnConf - A CDC use-case: designing an Evergreen Cache
London In-Memory Computing Meetup - A Change-Data-Capture use-case: designing...
London In-Memory Computing Meetup - A Change-Data-Capture use-case: designing...
Java.IL - Your own Kubernetes controller, not only in Go!
Java.IL - Your own Kubernetes controller, not only in Go!
OSCONF - Your own Kubernetes controller: not only in Go
OSCONF - Your own Kubernetes controller: not only in Go
SouJava- 3 easy performance improvements in your microservices architecture
SouJava- 3 easy performance improvements in your microservices architecture
SCALE - Stream processing and Open Data, a match made in Heaven
SCALE - Stream processing and Open Data, a match made in Heaven
Último
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
June Patch Tuesday
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Main news related to the CCS TSI 2023 (2023/1695)
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 .
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Digital Marketing Trends in 2024 | Guide for Staying Ahead
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.5th LF Energy Power Grid Model Meet-up Slides
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.
Generating privacy-protected synthetic data using Secludy and Milvus
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.
Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20
Último (20)
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
ING Meetup - Migrating Spring Boot Config Annotations to Functional with Kotlin
- 1. @nicolas_frankel Migrating Spring Boot apps from annotation-based config to Functional with Kotlin
- 2. @nicolas_frankel • Developer, team lead, architect, whatever it takes • Recently Developer Advocate • Love Spring • Love Kotlin Me, myself and I
- 3. @nicolas_frankel Hazelcast HAZELCAST IMDG is an operational, in-memory, distributed computing platform that manages data using in-memory storage, and performs parallel execution for breakthrough application speed and scale. HAZELCAST JET is the ultra fast, application embeddable, 3rd generation stream processing engine for low latency batch and stream processing.
- 4. @nicolas_frankel • Open Source • Backed by Pivotal • Built on the shoulders of the Spring framework • Convention over configuration Spring Boot
- 5. @nicolas_frankel • Magic • Via annotations • Solution: • Remove annotations • Functional configuration for the win The issue
- 7. @nicolas_frankel Going further • Spring-Fu • Ko-Fu • Ja-Fu • Experimental!
- 8. @nicolas_frankel Kofu configuration for Spring Boot Kofu configuration is currently developed in Spring Fu, an incubator intended to ultimately contribute features related to Kotlin and functional configuration to Spring Framework, Boot and Data
- 9. @nicolas_frankel Kofu configuration for Spring Boot • Explicit configuration via a Kotlin DSL • Based on Spring Boot infrastructure used in a functional way • No feature enabled based on classpath detection • Both declarative and programmatic • Faster startup and lower memory consumption • Minimal reflection & annotations usage • Pure lambdas, no CGLIB proxy
- 10. @nicolas_frankel
- 11. @nicolas_frankel
- 12. @nicolas_frankel • Controller to routes • Logic in handlers • Kotlin Beans DSL • Kotlin Routes DSL • Reactive is not necessary anymore… till a point Takeaways
- 13. @nicolas_frankel
- 14. @nicolas_frankel • https://blog.frankel.ch/ • @nicolas_frankel • https://git.io/fN3Qv Thanks!