QSON: New Java JSON parser for Quarkus

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Quarkus has a new JSON parser and object mapper called QSON. It does bytecode generation for the Java classes you want to map to and from JSON around a small core library. I’m not going to get into details on how to use it, just visit the github page for more information.

I started this project because I noticed a huge startup time for Jackson as relative to the other components within Quarkus applications. IIRC it was taking about 20% of the boot time for a simple JAX-RS microservice. So the initial prototype was to see how much I could improve boot time and I was pleasantly surprised that the parser I implemented was a bit better than Jackson at runtime too!

The end result was that boot time improved about 20% for a simple Quarkus JAX-RS microservice. The runtime performance is also better in most instances too. Here are the numbers from a JMH benchmark I did:

Benchmark                           Mode  Cnt       Score   Error  Units
MyBenchmark.testParserAfterburner  thrpt    2  223630.276          ops/s
MyBenchmark.testParserJackson      thrpt    2  218748.065          ops/s
MyBenchmark.testParserQson         thrpt    2  251086.874          ops/s
MyBenchmark.testWriterAfterburner  thrpt    2  189243.175          ops/s
MyBenchmark.testWriterJackson      thrpt    2  168637.541          ops/s
MyBenchmark.testWriterQson         thrpt    2  177855.879          ops/s

These are runtime throughput numbers so the higher the better. Qson is better than regular Jackson and Jackson+Afterburner for json to object mapping (reading/parsing). For output, Qson is better than regular Jackson, but is a little behind Afterburner.

There’s still some work to do for Qson. One of the big things I need is a maven and gradle plugin to handle bytecode generation so that Qson can be used outside of Quarkus. We’ll also be adding more features to Qson like custom mappings. One thing to note though is that I won’t add features that hurt performance, increase memory footprint, or hurt boot time.

Over time, we’ll be integrating Qson as an option for any Quarkus extension that needs Json object mapping. So far, I’ve done integration with JAX-RS (Resteasy). Funqy is a prime candidate next.

Quarkus Serverless Strategy

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What is Serverless?

Serverless architectures allow us to scale our services from zero instances to many based on request and event traffic.  The advantages are clear.  If our services are idle most of the day, why should we have to pay a cloud provider for a full day or waste scarce resources in our company’s private cloud?  Why should we have to plan for peak load when our architecture can scale up for this peak load automatically based on volume of incoming traffic?  Serverless solves these types of problems.

Function as a Service (FaaS) is also part of the Serverless paradigm and focuses on exposing one remote function per deployment.  It is a more fine grain approach than Microservices, with the idea being that you can be more agile at getting functionality to market with even smaller deployment.  AWS Lambda and Azure Functions are an example of FaaS implementations.   FaaS frameworks like AWS Lambda and Azure Functions not only bring autoscaling to your services, but they’ve started to make it much easier to deploy your code to the cloud.  In a Lambda or Azure environment, developers don’t worry about the container anymore and can just focus on pushing their code.  FaaS environments have started to take the “Ops” out of “DevOps”.

Java’s Disadvantages

Unless you’re focusing solely on batch processing, one of the disadvantages of a Serverless architecture is the instance spin up time.  In other words, the cold-start latency.  If you need milliseconds to response to a client request, and your service spinup is measured in seconds, then you have a problem.

Java frameworks like Spring, Hibernate, Microprofile, Java EE and other technologies traditionally have been slow to boot and even microservices written in these technologies take seconds to start up.  This is because most of these frameworks do all their configration and metadata processing at boot time.  Spring and Hibernate scan classes for annotations.  Hibernate additionally builds SQL queries.  They do the same exact pre-processing every single time they are spun up.

Java also has a huge memory problem.  If FaaS is the way to go and you’re having many more fine grain deployments, then Java based deployments are going to take up a huge amount of memory.  Some cloud environments also charge based on the memory used compounding the issue.

Quarkus Perfect Match for Serverless

Quarkus’s core values are to drastically reduce memory footprint and boot time for Java based applications and services.  There are two of the biggest concerns when dealing with Serverless architectures.  Quarkus has moved most of the pre-processing that frameworks like Spring and Hibernate do from boot time to build time.  This approach has drastically reduced service spin up and memory footprint.  Quarkus has also smoothed out the rough edges with Graal so that you can compile your Java microservices into native executables which provide even faster boot time and a lesser memory footprint than running with the JVM.

Quarkus Serverless Strategy

The Quarkus team is tackling Serverless in a variety of ways:

  • Enhance existing Serverless Java stacks out of the box
  • Bring the Java ecosystem to existing Serverless Java stacks
  • Provide portability between Serverless stacks through traditional, mature, existing Java APIs
  • Provide a new Java function API (Funqy) that is portable across Serverless providers

Quarkus Enhances Lambda

By modifying your pom and adding a few Quarkus AWS Lambda integration dependencies like the Quarkus maven plugin, you can compile your AWS Lambda Java projects into a native binary that the AWS Lambda Custom Runtime can consume.  Watch your cold-start latency and memory footprint drop dramatically.  Try it out yourself.

The idea here is to bring Graal support to AWS Lambda through Quarkus in a seemless way.  We have smoothed out the rough edges Graal introduces for a variety of AWS SDKs.

Pull in Java Ecosystem

Another part of the Quarkus Serverless strategy is to pull in the Java ecosystem into existing Serverless stacks.  Through Quarkus your AWS Lambda classes can inject service components via Spring DI or CDI.  You’re not stuck with using whatever AWS SDK provides and can use the mature Java frameworks you’ve been using for years.

import com.amazonaws.services.lambda.runtime.Context;
import com.amazonaws.services.lambda.runtime.RequestHandler;
import org.springframework.beans.factory.annotation.Autowired;

public class GreetingLambda implements RequestHandler<String, String> {

    @Autowired
    GreetingService service;

    @Override
    public String handleRequest(String name, Context context) {
        return service.greeting(name);
    }
}

Avoid Vendor Lock-in

Let’s face it.  If you use AWS, Azure, or any other cloud provider SDKs, then you are locked into that platform.  If AWS jacks up their prices down the road, you’re going to have a tough time moving off their platform.  Quarkus helps alleviate this issue by providing integration between REST and HTTP frameworks like JAX-RS, Spring MVC, Servlet, and Vertx.Web with AWS Lambda and Azure Functions.  Let REST and HTTP be your portable architecture between cloud providers and avoid vendor lock-in by using REST frameworks that you’ve been using for years.  Try it out with AWS Lambda or Azure Functions.

One great thing about using our JAX-RS or Spring MVC support with AWS Lambda or Azure Functions is that you’re not stuck with one REST endpoint per deployment.  You can deploy existing microservices as one Lambda deployment if you desire.  This alleviates some of the management issues that an explosion of function deployments might create down the road as you can aggregate as many endpoints as you want into one Lambda deployment.

Funqy Cross Platform Functions

The final piece of our Quarkus Serverless Strategy is a new cross-platform function API called Funqy.  Quarkus Funqy is a simple API that allows you to write functions that are usable in a variety of FaaS environment:  AWS Lambda, Azure Functions, Knative Events, and more.

public class MyClass {
   @Funq
   public MyOutput myFunction(MyInput input) {
     ...
   }
}

Funqy is still in development.  We’ll have a follow up blog as soon as it is ready to release.

More to come

Quarkus will continue to revise and expand our Serverless Strategy.  Come try out our integrations and new APIs.

Quarkus unifies reactive and imperative for REST

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The latest release of Quarkus has unified Vert.x Web, Servlet (Undertow), and JAX-RS (Resteasy) under one I/O abstraction.  Specifically, Servlet and JAX-RS were written on top of Vert.x.

What this means for you is that if you are using Vert.x, Servlet, and/or JAX-RS in one application they will all share the same io and worker thread pools.  Scarce resources are now reused.  Because everything is unified under Vert.x, there’s a lot of future optimizations and features that we can bring to Resteasy and the JAX-RS coding model.  More info on this coming soon!

 

Keycloak 1.1.Beta 1 Released: SAML, Clustering, Tomcat 7

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(Copied from Stian’s announcement) Pretty big feature release:
  • SAML 2.0 support.  Keycloak already supports OpenID Connect, but with this release we’re also introducing support for SAML 2.0.  We did this by pulling in and building on top of Picketlink’s SAML libraries.
  • Vastly improved clustering support.  We’ve also significantly improved our clustering support, for the server and application adapters. The server can now be configured to use an invalidation cache for realm meta-data and user profiles, while user-sessions can be stored in a distributed cache allowing for both increased scalability and availability. Application adapters can be configured for either sticky-session or stateless if sticky-sessions are not available. We’ve also added support for nodes to dynamically register with Keycloak to receive for example logout notifications.
  • Adapter multi-tenancy support.  Thanks to Juraci Paixão Kröhling we now have multi-tenancy support in application adapters. His contribution makes it easy to use more than one realm for a single application. It’s up to you to decide which realm is used for a request, but this could for example be depending on domain name or context-path. For anyone interested in this feature there’s a simple example that shows how to get started.
  • Tomcat 7 Adapter.  A while back Davide Ungari contributed a Tomcat 7 application adapter for Keycloak, but we haven’t had time to document, test and make it a supported adapter until now.
What’s next?
The next release of Keycloak should see the introduction of more application adapters, with support for JBoss BRMS, JBoss Fuse, UberFire, Hawt.io and Jetty.
For a complete list of all features and fixes for this release check out JIRA.
I’d like to especially thank all external contributors, please keep contributing! For everyone wanting to contribute Keycloak don’t hesitate, it’s easy to get started and we’re here to help if you need any pointers.

Resteasy 3.0.9 Released

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I really want to thank Ron Sigal, Weinan Li, and the rest of the Resteasy community for having my back the last 5 months while I was focused on other things.  Thanks for your hard work and patience.  3.0.9.Final is a maintenance release.  There are a few minor migration notes you should read before you upgrade, but most applications shouldn’t be affected.  We’ll try and do another maintenance release in like 6-8 weeks.  Check out resteasy.jboss.org for download links, jira release notes, and documentation.

Keycloak 1.0 Final Released

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After 1 year of hard work, the team is proud to release our first final 1.0 release of Keycloak.  We’ve stabilized our database schemas, improved performance, and refactored our SPIs and you should be good to go!  I don’t want to list all the features, but check out our project website at http://keycloak.org for more information.  You can find our download links there as well as screen cast tutorials on our documentation page.

What’s Next?

Keycloak 1.1 will be our integration release where we start bringing Keycloak to different protocols, projects, and environments.  Here’s a priority list of what we’re tackling

  • SAML 2.0 – by merging with Picketlink IDP
  • Uberfire/BRMS adapter
  • Fuse FSW adapter
  • EAP 6.x and Wildfly console integration
  • Tomcat 7 adapter
  • …More planned, but we’ll see how fast we can move before we announce anymore

In parallel, we hope to look into a few new features:

  • Internationalization
  • TOTP Improvements like allowing multiple token generators
  • IP Filtering

Keycloak 1.0 RC 1 Released

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Many bugs fixes and cleanup.  Not much for features although we did add a ton of tooltips to the admin console.  We’re getting very close to a final release and are still on schedule to release 2nd week on September.

See keycloak.org for links to download and documentation.

Keycloak Beta 4 Released

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After a summer of multiple vacations from various team members, we’re finally ready to release Keycloak 1.0 Beta 4.  There’s not a lot of new features in the release because we focused mainly on performance, creating new SPIs, refactoring code, improving usability, and lastly fixing bugs. 64 issues completed.  As usually go to the main keycloak.org page to find download links and to browse our documentation, release notes, or view our screencast tutorials.  Here are some of the highlights of the release:

  • Server side memory cache for all UI pages.
  • Cache-control settings for UI pages
  • Server side cache for all backend metadata: realms, applications, and users.
  • In-memory implementation for user sessions
  • New Federation SPI.  Gives you a lot of flexibility to federation external stores into Keycloak
  • Improved LDAP/Active Directory support
  • Token validation REST API
  • Support for HttpServletRequest.logout()
  • Lots and lots of bugs fixes and minor improvements

You should see a big performance increase with this release as everything is cachable in memory and the database can be fully bypassed.

1.0 Final is on the way!

What’s next for Keycloak?  This month we will be focusing on resolving the remaining issues logged in Jira, improving our test coverage, and updating our documentation and screencasts.  No new major features.  We’ll have a RC release around 3rd week of August, then our first Final release 2nd week of September!

 

Keycloak Beta-1 Released!

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Keycloak Beta-1 has been released!  We’re edging closer to 1.0! Please visit the Keycloak website for links to documentation and downloads.  A lot of hard work the last few months by Stian, Marek, myself and other contributors to bring you loads of new features and improvements:

  • LDAP/Active Directory integration built on Picketlink.  Thanks Marek!
  • User Session management – can now view login IP address and which applications and oauth clients have open tokens.  Works with any type of app too.  Can view and manage sessions through user account pages or admin console
  • Audit log for important events.  Integration with admin console and ability to receive emails on certain events.
  • Account log viewable in user account management pages
  • Export database.  Allows you to export a full dump of keycloak database into an encrypted file.  Will help out tremendously to migrate between Keycloak versions.
  • Authentication SPI.  Allows you to plug in different mechanisms to retrieve and authenticate users.
  • Theme support for the admin console and any sent email.
  • Per-realm admin console.  You can now designate a user within a realm that is an admin of that realm.
  • Documented the Admin REST API finally.  (Docs still kinda suck here)
  • CORS support for Admin REST API
  • Improvements in Javascript adapter.  Including OpenID Connect session iframe style for single-sign out and support for Cordova.
  • Support for relative URLs when configuring admin console
  • Server configuration file
  • Social Only Logins
  • Installed application adapter
  • Expanded the number of example projects

What’s next? This is the last major feature release of Keycloak.  We will now be focusing on performance, clustering, security audits, testing, documentation, and usability for the next few releases.  We hope to release 1.0 Final sometime in July.

 

Resteasy 3.0.7.Final Released

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Ron fixed a few bugs in validation. Netty improvements. A few other bug fixes here and there.

As usual, follow links from jboss.org/resteasy to download and view documentation and release notes.

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