DDevelopment & Design

Spring Boot 2.0 HTTP request metrics with Micrometer

Introduction

Brand new Spring Boot 2.0 has just been released and TouKs couldn’t wait to try it in the production. One of the newly added features that we investigated was metrics system based on Micrometer library (https://micrometer.io/). In this post I will cover some of our experiences with this so far.

The goal was to get basic HTTP request metrics, report them to InfluxDB and draw some fancy graphs in Grafana. In particular we needed:

  • Throughput – total number of requests in given time unit
  • Response status statistics – how many 200-like and 500-like response occurred
  • Response time statistics: mean, median, percentiles

What was wrong with Dropwizard metrics

Nothing that I am aware of. Metrics Spring integration however is a different story….

Last stable release of Metrics Spring (v. 3.1.3) was in late 2015 and it was compatible with Dropwizard Metrics (v. 3.1.2). From this time Dropwizard Metrics moved to version 4 and 5, but Metrics Spring literally died. This causes a couple of rather unpleasant facts:

  • There are some known bugs that will never be solved
  • You can’t benefit from Dropwizard Metrics improvements
  • Sooner or later you will use a library that depends on a different version of Dropwizard Metrics and it will hurt

As an InfluxDB user I was also facing some problems with reporting tags. After a couple of tries we ended up using an obscure Graphite interface that was luckily compatible with Influx.

Let’s turn on the metrics

Adding metrics to your Spring Boot project can be done in three very simple steps. First add a dependency to micrometer-registry-xxx, where xxx is your favourite metrics storage. In our case:

<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-influx</artifactId>
</dependency>

 

Now it is time for just a little bit of configuration in application.yml:

management:
  metrics:
    export:
      influx:
        uri: http://localhost:8086
        db: services
        step: 5s  ### <- (1)

 

And a proper configuration bean:

@Configuration public class MetricsConfig {
    private static final Duration HISTOGRAM_EXPIRY = Duration.ofMinutes(10);
    
    private static final Duration STEP = Duration.ofSeconds(5);
    
    @Value
    ("${host_id}") private String hostId;
    
    @Value
    ("${service_id}") private String serviceId;
    
    @Bean 
    public MeterRegistryCustomizer < MeterRegistry > metricsCommonTags() { // (2)
        return registry - > registry.config()
        .commonTags("host", hostId, "service", serviceId) // (3)
        .meterFilter(MeterFilter.deny(id - > { // (4)
                String uri = id.getTag("uri");
                return uri != null && uri.startsWith("/swagger");
            }))
            .meterFilter(new MeterFilter() {
                @Override 
                public DistributionStatisticConfig configure(Meter.Id id, DistributionStatisticConfig config) {
                    return config.merge(DistributionStatisticConfig.builder().percentilesHistogram(true).percentiles(0.5, 0.75, 0.95) // (5)
                    .expiry(HISTOGRAM_EXPIRY) // (6)
                    .bufferLength((int)(HISTOGRAM_EXPIRY.toMillis() / STEP.toMillis())) // (7)
                    .build());
                }
            });
    }
}

 

Simple as that. For sure it is not the minimal working example, but I believe some of our ideas are worth mentioning.

Dive into configuration

Config is rather self-explanatory, but let’s take a look at couple of interesting features.

(1) Step defines how often data is sent by reporter. This value should be related to your expected traffic, because you don’t want to see 90% of zeros.

(2) Be aware that there can be many reporters sharing the same config. Customising each behaviour can be done by using more specific type parameter e.g. InfluxMeterRegistry.

(3) Tags that will be added to every metric. As you can see it’s very handy for identifying hosts in a cluster.

(4) Skipping not important endpoints will limit unwanted data.

(5) A list of percentiles you would like to track

(6)(7) Histograms are calculated for some defined time window where more recent values have bigger impact on final value. The bigger time window you choose, the more accurate statistics are, but the less sudden will be changes of percentile value in case of very big or very small response time. It is also very important to increase buffer length as you increase expiry time.

Afterthought

We believe that migrating to Micrometer is worth spending time as configuration and reporting becomes simpler. The only thing that surprised us was reporting rate of throughput and status counts rather than cumulative values. But this is another story to be told…

Special thanks to Arek Burdach for support.

Scala / Java developer at TouK since 2015. Passionate West Coast Swing dancer :)

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DDevelopment & Design

Grails session timeout without XML

This article shows clean, non hacky way of configuring featureful event listeners for Grails application servlet context. Feat. HttpSessionListener as a Spring bean example with session timeout depending on whether user account is premium or not.

Common approaches

Speaking of session timeout config in Grails, a default approach is to install templates with a command. This way we got direct access to web.xml file. Also more unnecessary files are created. Despite that unnecessary files are unnecessary, we should also remember some other common knowledge: XML is not for humans.

Another, a bit more hacky, way is to create mysterious scripts/_Events.groovy file. Inside of which, by using not less enigmatic closure: eventWebXmlEnd = { filename -> ... }, we can parse and hack into web.xml with a help of XmlSlurper.
Even though lot of Grails plugins do it similar way, still it’s not really straightforward, is it? Besides, where’s the IDE support? Hello!?

Examples of both above ways can be seen on StackOverflow.

Simpler and cleaner way

By adding just a single line to the already generated init closure we have it done:
class BootStrap {


    def init = { servletContext ->    

        servletContext.addListener(OurListenerClass)    

    }    

}

Allrighty, this is enough to avoid XML. Sweets are served after the main course though :)

Listener as a Spring bean

Let us assume we have a requirement. Set a longer session timeout for premium user account.
Users are authenticated upon session creation through SSO.

To easy meet the requirements just instantiate the CustomTimeoutSessionListener as Spring bean at resources.groovy. We also going to need some source of the user custom session timeout. Let say a ConfigService.
beans = {    

    customTimeoutSessionListener(CustomTimeoutSessionListener) {    

        configService = ref('configService')    

    }    

}

With such approach BootStrap.groovy has to by slightly modified. To keep control on listener instantation, instead of passing listener class type, Spring bean is injected by Grails and the instance passed:
class BootStrap {


    def customTimeoutSessionListener


    def init = { servletContext ->    

        servletContext.addListener(customTimeoutSessionListener)

    }    

}

An example CustomTimeoutSessionListener implementation can look like:
import javax.servlet.http.HttpSessionEvent    

import javax.servlet.http.HttpSessionListener    

import your.app.ConfigService    


class CustomTimeoutSessionListener implements HttpSessionListener {    


    ConfigService configService


    @Override    

    void sessionCreated(HttpSessionEvent httpSessionEvent) {    

        httpSessionEvent.session.maxInactiveInterval = configService.sessionTimeoutSeconds

    }    


    @Override    

    void sessionDestroyed(HttpSessionEvent httpSessionEvent) { /* nothing to implement */ }    

}
Having at hand all power of the Spring IoC this is surely a good place to load some persisted user’s account stuff into the session or to notify any other adequate bean about user presence.

Wait, what about the user context?

Honest answer is: that depends on your case. Yet here’s an example of getSessionTimeoutMinutes() implementation using Spring Security:
import org.springframework.security.core.context.SecurityContextHolder    


class ConfigService {


    static final int 3H = 3 * 60 * 60

    static final int QUARTER = 15 * 60


    int getSessionTimeoutSeconds() {    


        String username = SecurityContextHolder.context?.authentication?.principal    

        def account = Account.findByUsername(username)    


        return account?.premium ? 3H : QUARTER

    }    

}
This example is simplified. Does not contain much of defensive programming. Just an assumption that principal is already set and is a String - unique username. Thanks to Grails convention our ConfigService is transactional so the Account domain class can use GORM dynamic finder.
OK, config fetching implementation details are out of scope here anyway. You can get, load, fetch, obtain from wherever you like to. Domain persistence, principal object, role config, external file and so on...

Any gotchas?

There is one. When running grails test command, servletContext comes as some mocked class instance without addListener method. Thus we going to have a MissingMethodException when running tests :(

Solution is typical:
def init = { servletContext ->

    if (Environment.current != Environment.TEST) {    

        servletContext.addListener(customTimeoutSessionListener)    

    }    

}
An unnecessary obstacle if you ask me. Should I submit a Jira issue about that?

TL;DR

Just implement a HttpSessionListener. Create a Spring bean of the listener. Inject it into BootStrap.groovy and call servletContext.addListener(injectedListener).