Speaking

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

It has been said that GitHub is a developer's CV; just a quick look at someone's commit history can tell recruiters all they need to know. But what if your company doesn't publish their source code in a public GitHub repo? GitHub recently allowed developers the ability to customize their profiles, so even if your commit history has more white than green, for example, you can provide a good entry-point for potential employers. But just like anything else, the result will only be as good as the effort you put in, and the data can get outdated fast. However, with a bit of work and the help of automation tools like GitHub Actions, you can ensure that your GitHub profile is always up-to-date. In this session, Nicolas will show attendees how to achieve this using his own setup as an example.

You shouldn't do microservices If you do, you're probably having tons of technical issues.In the good old days, applications were simple A browser send a request to a webapp endpoint; the latter fetched data from a database and returned the response. Mobile clients changed this approach.The display area of mobile clients is smaller:just smaller for tablets, much smaller for phones. A possible solution would be to return all data and let each client filter out the unnecessary one Unfortunately, phone clients also suffer from poorer bandwidth Hence, over-fetching is not an option Each client requires a different subset of the data. To avoid the over-fetching issue above, each microservice needs to serve the data strictly necessary for each kind of client It introduces coupling between a microservice to its clients. Backend For Front-end is an approach to tackle this issue In this talk, I'll describe it, its possible implementations and demo them.

API management solutions, also known as API gateways, are a must in the day and age of APIs. However, once you’ve set up such a gateway, you can use it for different purposes unrelated to APIs. In this talk, I want to show you how to improve the security of web apps.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

However you're using your Kubernetes cluster, you'll sooner or later need to direct traffic into it. At this point, you're spoiled with choice. Kubernetes provides no less than three different objects: NodePort, Ingress, and LoadBalancer. Of course, each of them comes with its limitations. For example, LoadBalancer requires a dedicated implementation provided by Cloud Platforms but not with most local distributions. Moreover, Kubernetes is introducing a new Gateway API, adding one more way to direct traffic to the cluster. In this talk, I'd like to offer an overview of all four options, with their pros and cons, and a more in-depth explanation of the new Gateway API.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

The last few years we have seen the rise of microservice architectures. At the same time, the term "monolith" has taken on a negative connotation. With the additional option of serverless, it's easy for software architects to be confused as to what architecture to design. In this talk, we will have a hard (and honest) look at these different approaches, and their respective pros and cons. We will also see how it's possible to move from one to another when the context changes.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

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.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

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.

Micro services are ubiquitous. However, most companies that implement micro services do not reap their full benefits - at best. At worst, it’s an epic failure. There are reasons for micro services: independent deployment of business capabilities. However, the unspoken assumption is that you need to deploy all capabilities all the time. My experience has shown me that it’s plain wrong. Some capabilities need frequent deployment, while some are much more stable. In "the past", we used Rule Engines to allow updating business rules without deployment. While it solved the problem, this approach had issues. Between introducing a Rule Engine and migrating your complete system to micro services, I believe that there’s a middle path, and that this path is Function-as-a-Service. In this talk, I’ll detail every point I’ve made above, and show how one can use Serverless to pragmatically design a system that allows deploying as often as you need.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

En tant que développeurs nous travaillons de plus en plus dans un monde interconnecté. Peut-être êtes vous en train de développer des microservices ? Peut-être exposez vous vos APIs sur le web ? Dans tous les cas, ces APIs web sont la colle qui maintient votre architecture en place. Dans le monde java, nous avons la chance d’avoir à disposition de nombreuses librairies pour nous aider à traiter tous les problèmes connexes: limitation de débit, authentification, découverte de services et bien d’autres. Cependant, ces problèmes sont transverses. Ils impactent toutes nos applications de la même manière. Aussi peut-être que les librairies ne sont pas la solution optimale à ces problèmes. Les API Gateways sont populaires et très utilisées de nos jours pour transfèrer cesz problèmes des applications vers un point central. Dans cette présentation, je décrirai en détail certains de ces problèmes et comment tirer profit d’une API Gateway. Puis je listerai les différentes solutions disponibles sur le marché. Enfin je terminerai par une démo d’APISIX, un projet de la fondation Apache, construit au dessus de NGINX et qui offre de nombreuses fonctionnalités qui peuvent aider vos développements.

As developers, we live more and more in an interconnected world. Perhaps you’re developing microservices? Maybe you’re exposing your APIs on the web? In all cases, web APIs are the glue that binds our architecture together. In the Java world, we are very fortunate to have a lot of libraries to help us manage related concerns: rate limiting, authentication, service discovery; you name it. Yet, these concerns are cross-cutting. They impact all our applications in the same way. Perhaps libraries are not the optimal way to handle them. API Gateways are a popular and nowadays quite widespread way to move these concerns out of the applications to a central place. In this talk, I’ll describe in more detail some of these concerns and how you can benefit from an API Gateway. Then, I’ll list some of the available solutions on the market. Finally, I’ll demo APISIX, an Apache-managed project built on top of NGINX that offers quite a few features to help you ease your development.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

When you publish your first HTTP API, you’re more focused on short-term issues than planning for the future. However, chances are you’ll be successful, and you’ll hit the wall. How do you evolve your API without breaking the contract with your existing users? In this talk, I’ll first show you some tips and tricks to achieve that: moving your endpoints, deprecating them, monitoring who’s using them, and letting users know about the new endpoints. The talk is demo-based, and I’ll use the Apache APISIX project for it.

Vous avez une source de données représentant la source de vérité. Vous avez besoin d'utiliser ces données d'une autre façon afin de couvrir d'autres cas d'utilisation (cache, indexation, recherche, business intelligence...). Pour cela, pas de magie, il vous faudra dupliquer la donnée, souvent dans un autre format, afin de pouvoir répondre à votre besoin. Mais comment conserver la données toujours synchronisée avec la source de vérité ? Le tout, sans même pouvoir toucher l'application métier. Dans cette session 100% live coding, nous vous donnerons une recette simple pour surmonter ces difficultés en utilisant un pattern de "Change Data Capture".

with David Pilato

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.