springboot的http.server.requests服务请求流程源码

 更新时间:2023年12月01日 09:31:38   作者:codecraft  
这篇文章主要为大家介绍了springboot的http.server.requests服务请求流程源码,有需要的朋友可以借鉴参考下,希望能够有所帮助,祝大家多多进步,早日升职加薪

本文主要研究一下springboot的http.server.requests

http.server.requests

org/springframework/boot/actuate/autoconfigure/metrics/MetricsProperties.java

public static class Server {
            private final ServerRequest request = new ServerRequest();
            /**
             * Maximum number of unique URI tag values allowed. After the max number of
             * tag values is reached, metrics with additional tag values are denied by
             * filter.
             */
            private int maxUriTags = 100;
            public ServerRequest getRequest() {
                return this.request;
            }
            public int getMaxUriTags() {
                return this.maxUriTags;
            }
            public void setMaxUriTags(int maxUriTags) {
                this.maxUriTags = maxUriTags;
            }
            public static class ServerRequest {
                /**
                 * Name of the metric for received requests.
                 */
                private String metricName = "http.server.requests";
                /**
                 * Whether the trailing slash should be ignored when recording metrics.
                 */
                private boolean ignoreTrailingSlash = true;
                //......
            }   
        }
MetricsProperties.Server.ServerRequest定义了http.server.requests这个metrics名

WebMvcMetricsAutoConfiguration

org/springframework/boot/actuate/autoconfigure/metrics/web/servlet/WebMvcMetricsAutoConfiguration.java

@Configuration(proxyBeanMethods = false)
@AutoConfigureAfter({ MetricsAutoConfiguration.class, CompositeMeterRegistryAutoConfiguration.class,
        SimpleMetricsExportAutoConfiguration.class })
@ConditionalOnWebApplication(type = ConditionalOnWebApplication.Type.SERVLET)
@ConditionalOnClass(DispatcherServlet.class)
@ConditionalOnBean(MeterRegistry.class)
@EnableConfigurationProperties(MetricsProperties.class)
public class WebMvcMetricsAutoConfiguration {
    private final MetricsProperties properties;
    public WebMvcMetricsAutoConfiguration(MetricsProperties properties) {
        this.properties = properties;
    }
    @Bean
    @ConditionalOnMissingBean(WebMvcTagsProvider.class)
    public DefaultWebMvcTagsProvider webMvcTagsProvider(ObjectProvider<WebMvcTagsContributor> contributors) {
        return new DefaultWebMvcTagsProvider(this.properties.getWeb().getServer().getRequest().isIgnoreTrailingSlash(),
                contributors.orderedStream().collect(Collectors.toList()));
    }
    @Bean
    public FilterRegistrationBean<WebMvcMetricsFilter> webMvcMetricsFilter(MeterRegistry registry,
            WebMvcTagsProvider tagsProvider) {
        ServerRequest request = this.properties.getWeb().getServer().getRequest();
        WebMvcMetricsFilter filter = new WebMvcMetricsFilter(registry, tagsProvider, request.getMetricName(),
                request.getAutotime());
        FilterRegistrationBean<WebMvcMetricsFilter> registration = new FilterRegistrationBean<>(filter);
        registration.setOrder(Ordered.HIGHEST_PRECEDENCE + 1);
        registration.setDispatcherTypes(DispatcherType.REQUEST, DispatcherType.ASYNC);
        return registration;
    }
    @Bean
    @Order(0)
    public MeterFilter metricsHttpServerUriTagFilter() {
        String metricName = this.properties.getWeb().getServer().getRequest().getMetricName();
        MeterFilter filter = new OnlyOnceLoggingDenyMeterFilter(
                () -> String.format("Reached the maximum number of URI tags for '%s'.", metricName));
        return MeterFilter.maximumAllowableTags(metricName, "uri", this.properties.getWeb().getServer().getMaxUriTags(),
                filter);
    }
    @Bean
    public MetricsWebMvcConfigurer metricsWebMvcConfigurer(MeterRegistry meterRegistry,
            WebMvcTagsProvider tagsProvider) {
        return new MetricsWebMvcConfigurer(meterRegistry, tagsProvider);
    }
}
WebMvcMetricsAutoConfiguration定义了webMvcTagsProvider,可以接收WebMvcTagsContributor对tag进行定制,还注册了WebMvcMetricsFilter、MeterFilter、metricsWebMvcConfigurer

DefaultWebMvcTagsProvider

org/springframework/boot/actuate/metrics/web/servlet/DefaultWebMvcTagsProvider.java

public class DefaultWebMvcTagsProvider implements WebMvcTagsProvider {
    private final boolean ignoreTrailingSlash;
    private final List<WebMvcTagsContributor> contributors;
    public DefaultWebMvcTagsProvider() {
        this(false);
    }
    /**
     * Creates a new {@link DefaultWebMvcTagsProvider} that will provide tags from the
     * given {@code contributors} in addition to its own.
     * @param contributors the contributors that will provide additional tags
     * @since 2.3.0
     */
    public DefaultWebMvcTagsProvider(List<WebMvcTagsContributor> contributors) {
        this(false, contributors);
    }
    public DefaultWebMvcTagsProvider(boolean ignoreTrailingSlash) {
        this(ignoreTrailingSlash, Collections.emptyList());
    }
    /**
     * Creates a new {@link DefaultWebMvcTagsProvider} that will provide tags from the
     * given {@code contributors} in addition to its own.
     * @param ignoreTrailingSlash whether trailing slashes should be ignored when
     * determining the {@code uri} tag.
     * @param contributors the contributors that will provide additional tags
     * @since 2.3.0
     */
    public DefaultWebMvcTagsProvider(boolean ignoreTrailingSlash, List<WebMvcTagsContributor> contributors) {
        this.ignoreTrailingSlash = ignoreTrailingSlash;
        this.contributors = contributors;
    }
    @Override
    public Iterable<Tag> getTags(HttpServletRequest request, HttpServletResponse response, Object handler,
            Throwable exception) {
        Tags tags = Tags.of(WebMvcTags.method(request), WebMvcTags.uri(request, response, this.ignoreTrailingSlash),
                WebMvcTags.exception(exception), WebMvcTags.status(response), WebMvcTags.outcome(response));
        for (WebMvcTagsContributor contributor : this.contributors) {
            tags = tags.and(contributor.getTags(request, response, handler, exception));
        }
        return tags;
    }
    @Override
    public Iterable<Tag> getLongRequestTags(HttpServletRequest request, Object handler) {
        Tags tags = Tags.of(WebMvcTags.method(request), WebMvcTags.uri(request, null, this.ignoreTrailingSlash));
        for (WebMvcTagsContributor contributor : this.contributors) {
            tags = tags.and(contributor.getLongRequestTags(request, handler));
        }
        return tags;
    }
}
DefaultWebMvcTagsProvider实现了WebMvcTagsProvider接口,其构造器可以接收WebMvcTagsContributor,对tag进行定制;默认的tag为WebMvcTags.method(method)、WebMvcTags.uri(uri)、WebMvcTags.exception(exception)、WebMvcTags.status(status)、WebMvcTags.outcome(outcome)

WebMvcMetricsFilter

org/springframework/boot/actuate/metrics/web/servlet/WebMvcMetricsFilter.java

public class WebMvcMetricsFilter extends OncePerRequestFilter {
    private final MeterRegistry registry;
    private final WebMvcTagsProvider tagsProvider;
    private final String metricName;
    private final AutoTimer autoTimer;
    /**
     * Create a new {@link WebMvcMetricsFilter} instance.
     * @param registry the meter registry
     * @param tagsProvider the tags provider
     * @param metricName the metric name
     * @param autoTimer the auto-timers to apply or {@code null} to disable auto-timing
     * @since 2.2.0
     */
    public WebMvcMetricsFilter(MeterRegistry registry, WebMvcTagsProvider tagsProvider, String metricName,
            AutoTimer autoTimer) {
        this.registry = registry;
        this.tagsProvider = tagsProvider;
        this.metricName = metricName;
        this.autoTimer = autoTimer;
    }
    @Override
    protected boolean shouldNotFilterAsyncDispatch() {
        return false;
    }
    @Override
    protected void doFilterInternal(HttpServletRequest request, HttpServletResponse response, FilterChain filterChain)
            throws ServletException, IOException {
        TimingContext timingContext = TimingContext.get(request);
        if (timingContext == null) {
            timingContext = startAndAttachTimingContext(request);
        }
        try {
            filterChain.doFilter(request, response);
            if (!request.isAsyncStarted()) {
                // Only record when async processing has finished or never been started.
                // If async was started by something further down the chain we wait
                // until the second filter invocation (but we'll be using the
                // TimingContext that was attached to the first)
                Throwable exception = (Throwable) request.getAttribute(DispatcherServlet.EXCEPTION_ATTRIBUTE);
                record(timingContext, request, response, exception);
            }
        }
        catch (NestedServletException ex) {
            response.setStatus(HttpStatus.INTERNAL_SERVER_ERROR.value());
            record(timingContext, request, response, ex.getCause());
            throw ex;
        }
        catch (ServletException | IOException | RuntimeException ex) {
            record(timingContext, request, response, ex);
            throw ex;
        }
    }
    //......
}
WebMvcMetricsFilter继承了OncePerRequestFilter,其doFilterInternal方法通过TimingContext来维护timerSample,然后在filterChain.doFilter(request, response)之后进行record

record

private void record(TimingContext timingContext, HttpServletRequest request, HttpServletResponse response,
            Throwable exception) {
        Object handler = getHandler(request);
        Set<Timed> annotations = getTimedAnnotations(handler);
        Timer.Sample timerSample = timingContext.getTimerSample();
        if (annotations.isEmpty()) {
            if (this.autoTimer.isEnabled()) {
                Builder builder = this.autoTimer.builder(this.metricName);
                timerSample.stop(getTimer(builder, handler, request, response, exception));
            }
        }
        else {
            for (Timed annotation : annotations) {
                Builder builder = Timer.builder(annotation, this.metricName);
                timerSample.stop(getTimer(builder, handler, request, response, exception));
            }
        }
    }
    private Timer getTimer(Builder builder, Object handler, HttpServletRequest request, HttpServletResponse response,
            Throwable exception) {
        return builder.tags(this.tagsProvider.getTags(request, response, handler, exception)).register(this.registry);
    }
record方法主要执行timerSample.stop(getTimer(builder, handler, request, response, exception))

timerSample

micrometer-core-1.5.9.jar!/io/micrometer/core/instrument/Timer.class

public static class Sample {
        private Tags tags = Tags.empty();
        private final long startTime;
        private final Clock clock;
        Sample(Clock clock) {
            this.clock = clock;
            this.startTime = clock.monotonicTime();
        }
        public long stop(Timer timer) {
            long durationNs = this.clock.monotonicTime() - this.startTime;
            timer.record(durationNs, TimeUnit.NANOSECONDS);
            return durationNs;
        }
        @Incubating(
            since = "1.4.0"
        )
        public long stop(MeterRegistry registry, Builder timerBuilder) {
            return this.stop(timerBuilder.tags((Iterable)this.tags).register(registry));
        }
        @Incubating(
            since = "1.4.0"
        )
        public Sample tags(String... tags) {
            return this.tags((Iterable)Tags.of(tags));
        }
        @Incubating(
            since = "1.4.0"
        )
        public Sample tags(Iterable<Tag> tags) {
            this.tags = this.tags.and(tags);
            return this;
        }
    }
Timer.Sample的stop方法主要执行timer.record(durationNs, TimeUnit.NANOSECONDS)

PrometheusTimer

io/micrometer/prometheus/PrometheusTimer.java

public class PrometheusTimer extends AbstractTimer {
    private static final CountAtBucket[] EMPTY_HISTOGRAM = new CountAtBucket[0];
    private final LongAdder count = new LongAdder();
    private final LongAdder totalTime = new LongAdder();
    private final TimeWindowMax max;
    private final HistogramFlavor histogramFlavor;
    @Nullable
    private final Histogram histogram;
    PrometheusTimer(Id id, Clock clock, DistributionStatisticConfig distributionStatisticConfig, PauseDetector pauseDetector, HistogramFlavor histogramFlavor) {
        super(id, clock,
                DistributionStatisticConfig.builder()
                        .percentilesHistogram(false)
                        .serviceLevelObjectives()
                        .build()
                        .merge(distributionStatisticConfig),
                pauseDetector, TimeUnit.SECONDS, false);
        this.histogramFlavor = histogramFlavor;
        this.max = new TimeWindowMax(clock, distributionStatisticConfig);
        if (distributionStatisticConfig.isPublishingHistogram()) {
            switch (histogramFlavor) {
                case Prometheus:
                    histogram = new TimeWindowFixedBoundaryHistogram(clock, DistributionStatisticConfig.builder()
                            .expiry(Duration.ofDays(1825)) // effectively never roll over
                            .bufferLength(1)
                            .build()
                            .merge(distributionStatisticConfig), true);
                    break;
                case VictoriaMetrics:
                    histogram = new FixedBoundaryVictoriaMetricsHistogram();
                    break;
                default:
                    histogram = null;
                    break;
            }
        } else {
            histogram = null;
        }
    }
    @Override
    protected void recordNonNegative(long amount, TimeUnit unit) {
        count.increment();
        long nanoAmount = TimeUnit.NANOSECONDS.convert(amount, unit);
        totalTime.add(nanoAmount);
        max.record(nanoAmount, TimeUnit.NANOSECONDS);
        if (histogram != null)
            histogram.recordLong(TimeUnit.NANOSECONDS.convert(amount, unit));
    }
    @Override
    public long count() {
        return count.longValue();
    }
    @Override
    public double totalTime(TimeUnit unit) {
        return TimeUtils.nanosToUnit(totalTime.doubleValue(), unit);
    }
    @Override
    public double max(TimeUnit unit) {
        return max.poll(unit);
    }
    public HistogramFlavor histogramFlavor() {
        return histogramFlavor;
    }
    /**
     * For Prometheus we cannot use the histogram counts from HistogramSnapshot, as it is based on a
     * rolling histogram. Prometheus requires a histogram that accumulates values over the lifetime of the app.
     *
     * @return Cumulative histogram buckets.
     */
    public CountAtBucket[] histogramCounts() {
        return histogram == null ? EMPTY_HISTOGRAM : histogram.takeSnapshot(0, 0, 0).histogramCounts();
    }
    @Override
    public HistogramSnapshot takeSnapshot() {
        HistogramSnapshot snapshot = super.takeSnapshot();
        if (histogram == null) {
            return snapshot;
        }
        return new HistogramSnapshot(snapshot.count(),
                snapshot.total(),
                snapshot.max(),
                snapshot.percentileValues(),
                histogramCounts(),
                snapshot::outputSummary);
    }
}
PrometheusTimer继承了AbstractTimer,默认histogram为null

PrometheusMeterRegistry

io/micrometer/prometheus/PrometheusMeterRegistry.java

protected io.micrometer.core.instrument.Timer newTimer(Meter.Id id, DistributionStatisticConfig distributionStatisticConfig, PauseDetector pauseDetector) {
        PrometheusTimer timer = new PrometheusTimer(id, clock, distributionStatisticConfig, pauseDetector, prometheusConfig.histogramFlavor());
        applyToCollector(id, (collector) ->
                addDistributionStatisticSamples(distributionStatisticConfig, collector, timer, tagValues(id), false));
        return timer;
    }
PrometheusMeterRegistry的newTimer创建的是PrometheusTimer,同时applyToCollector调用了addDistributionStatisticSamples

addDistributionStatisticSamples

private void addDistributionStatisticSamples(DistributionStatisticConfig distributionStatisticConfig, MicrometerCollector collector,
                                                 HistogramSupport histogramSupport, List<String> tagValues, boolean forLongTaskTimer) {
        collector.add(tagValues, (conventionName, tagKeys) -> {
            Stream.Builder<Collector.MetricFamilySamples.Sample> samples = Stream.builder();
            HistogramSnapshot histogramSnapshot = histogramSupport.takeSnapshot();
            ValueAtPercentile[] percentileValues = histogramSnapshot.percentileValues();
            CountAtBucket[] histogramCounts = histogramSnapshot.histogramCounts();
            double count = histogramSnapshot.count();
            if (percentileValues.length > 0) {
                List<String> quantileKeys = new LinkedList<>(tagKeys);
                quantileKeys.add("quantile");
                // satisfies https://prometheus.io/docs/concepts/metric_types/#summary
                for (ValueAtPercentile v : percentileValues) {
                    List<String> quantileValues = new LinkedList<>(tagValues);
                    quantileValues.add(Collector.doubleToGoString(v.percentile()));
                    samples.add(new Collector.MetricFamilySamples.Sample(
                            conventionName, quantileKeys, quantileValues, v.value(TimeUnit.SECONDS)));
                }
            }
            Collector.Type type = distributionStatisticConfig.isPublishingHistogram() ? Collector.Type.HISTOGRAM : Collector.Type.SUMMARY;
            if (histogramCounts.length > 0) {
                // Prometheus doesn't balk at a metric being BOTH a histogram and a summary
                type = Collector.Type.HISTOGRAM;
                List<String> histogramKeys = new LinkedList<>(tagKeys);
                String sampleName = conventionName + "_bucket";
                switch (prometheusConfig.histogramFlavor()) {
                    case Prometheus:
                        histogramKeys.add("le");
                        // satisfies https://prometheus.io/docs/concepts/metric_types/#histogram
                        for (CountAtBucket c : histogramCounts) {
                            final List<String> histogramValues = new LinkedList<>(tagValues);
                            histogramValues.add(Collector.doubleToGoString(c.bucket(TimeUnit.SECONDS)));
                            samples.add(new Collector.MetricFamilySamples.Sample(
                                    sampleName, histogramKeys, histogramValues, c.count()));
                        }
                        // the +Inf bucket should always equal `count`
                        final List<String> histogramValues = new LinkedList<>(tagValues);
                        histogramValues.add("+Inf");
                        samples.add(new Collector.MetricFamilySamples.Sample(
                                sampleName, histogramKeys, histogramValues, count));
                        break;
                    case VictoriaMetrics:
                        histogramKeys.add("vmrange");
                        for (CountAtBucket c : histogramCounts) {
                            final List<String> histogramValuesVM = new LinkedList<>(tagValues);
                            histogramValuesVM.add(FixedBoundaryVictoriaMetricsHistogram.getRangeTagValue(c.bucket()));
                            samples.add(new Collector.MetricFamilySamples.Sample(
                                    sampleName, histogramKeys, histogramValuesVM, c.count()));
                        }
                        break;
                    default:
                        break;
                }
            }
            samples.add(new Collector.MetricFamilySamples.Sample(
                    conventionName + (forLongTaskTimer ? "_active_count" : "_count"), tagKeys, tagValues, count));
            samples.add(new Collector.MetricFamilySamples.Sample(
                    conventionName + (forLongTaskTimer ? "_duration_sum" : "_sum"), tagKeys, tagValues, histogramSnapshot.total(TimeUnit.SECONDS)));
            return Stream.of(new MicrometerCollector.Family(type, conventionName, samples.build()),
                    new MicrometerCollector.Family(Collector.Type.GAUGE, conventionName + "_max", Stream.of(
                            new Collector.MetricFamilySamples.Sample(conventionName + "_max", tagKeys, tagValues,
                                    histogramSnapshot.max(getBaseTimeUnit())))));
        });
    }
addDistributionStatisticSamples会判断isPublishingHistogram,是则发布HISTOGRAM,否则发布SUMMARY(默认为否),之后给samples添加_count及_sum的sample,最后额外添加一个_max的gauge

示例

示例1

Timer timer = meterRegistry.timer("abc", "a", "b");
timer.record(Duration.of(100, ChronoUnit.SECONDS));

最后产生的metrics如下

# HELP abc_seconds_max  
# TYPE abc_seconds_max gauge
abc_seconds_max{a="b",} 0.0
# HELP abc_seconds  
# TYPE abc_seconds summary
abc_seconds_count{a="b",} 1.0
abc_seconds_sum{a="b",} 100.0

示例2

http.server.requests的prometheus指标
# HELP http_server_requests_seconds_max
# TYPE http_server_requests_seconds_max gauge
http_server_requests_seconds_max{}
# TYPE http_server_requests_seconds summary
http_server_requests_seconds_count{}
http_server_requests_seconds_sum{}

grafana展示

HTTP Server Requests Count

{
              "expr": "http_server_requests_seconds_count{instance=\"$instance\", application=\"$application\"}",
              "format": "time_series",
              "interval": "",
              "intervalFactor": 1,
              "legendFormat": "{{method}} [{{status}}] - {{uri}}",
              "refId": "A"
            }

HTTP Server Requests Sum

{
              "expr": "http_server_requests_seconds_sum{instance=\"$instance\", application=\"$application\"}",
              "format": "time_series",
              "interval": "",
              "intervalFactor": 1,
              "legendFormat": "{{method}} [{{status}}] - {{uri}}",
              "refId": "A"
            }

HTTP Server Requests Max

{
              "expr": "http_server_requests_seconds_max{instance=\"$instance\", application=\"$application\"}",
              "format": "time_series",
              "interval": "",
              "intervalFactor": 1,
              "legendFormat": "{{method}} [{{status}}] - {{uri}}",
              "refId": "A"
            }

Total Requests

{
          "expr": "sum(increase(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\"}[150s]))",
          "format": "time_series",
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "",
          "refId": "A"
        }

Request Count

{
          "expr": "irate(http_server_requests_seconds_count{instance=\"$instance\", application=\"$application\", uri!~\".*actuator.*\"}[5m])",
          "format": "time_series",
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{method}} [{{status}}] - {{uri}} -{{reqPath}}",
          "refId": "A"
        }

Failed Requests

{
          "expr": "sum(increase(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\", uri=~\"$uri\", status!=\"200\"}[$__interval]))",
          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A"
        }

Req / sec

{
          "expr": "sum(irate(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\"}[1m]))",
          "format": "time_series",
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "",
          "refId": "A"
        }

Requests per second

{
          "expr": "rate(http_server_requests_seconds_count{application=\"$application\", instance=\"$instance\"}[1m])",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "{{method}}-{{status}}-{{uri}}",
          "refId": "A"
        }

Top 10 Most Used API endpoints

{
          "expr": "topk(10, sum by(uri, method) (rate(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\"}[1m])))",
          "format": "time_series",
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "",
          "refId": "A"
        }

Error Rate

{
          "expr": "sum(increase(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\", uri=~\"$uri\", status!=\"200\"}[$__interval])) / sum(increase(http_server_requests_seconds_count{application=\"$application\", instance=~\"$instance\", uri=~\"$uri\"}[$__interval])) * 100",
          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A"
        }

Mean response time

{
          "expr": "rate(http_server_requests_seconds_sum{application=\"$application\", instance=\"$instance\"}[1m])/rate(http_server_requests_seconds_count{application=\"$application\", instance=\"$instance\"}[1m])",
          "format": "time_series",
          "instant": false,
          "intervalFactor": 1,
          "legendFormat": "{{method}}-{{status}}-{{uri}}",
          "refId": "A"
        }

Response Time

{
          "expr": "irate(http_server_requests_seconds_sum{instance=\"$instance\", application=\"$application\", exception=\"None\", uri!~\".*actuator.*\"}[5m]) / irate(http_server_requests_seconds_count{instance=\"$instance\", application=\"$application\", exception=\"None\", uri!~\".*actuator.*\"}[5m])",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "{{method}} [{{status}}] - {{uri}}",
          "refId": "A"
        }

Response time of 50%, 75%, 90%, 95% of requests

{
          "expr": "histogram_quantile(0.95, sum(rate(http_server_requests_seconds_bucket{application=\"$application\", instance=\"$instance\"}[1m])) by (le))",
          "format": "time_series",
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "95%",
          "refId": "A"
        },
        {
          "expr": "histogram_quantile(0.9, sum(rate(http_server_requests_seconds_bucket{application=\"$application\", instance=\"$instance\"}[1m])) by (le))",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "90%",
          "refId": "B"
        },
        {
          "expr": "histogram_quantile(0.75, sum(rate(http_server_requests_seconds_bucket{application=\"$application\", instance=\"$instance\"}[1m])) by (le))",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "75%",
          "refId": "C"
        },
        {
          "expr": "histogram_quantile(0.5, sum(rate(http_server_requests_seconds_bucket{application=\"$application\", instance=\"$instance\"}[1m])) by (le))",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "50%",
          "refId": "D"
        }

小结

springboot的WebMvcMetricsAutoConfiguration给mvc提供了http.server.requests指标,类型为timer,当输出到prometheus的时候,默认是没有开启Histogram,输出的是一个_max的gauge,以及summary类型(_count及_sum)。

以上就是springboot的http.server.requests请求流程源码解读的详细内容,更多关于springboot http.server.requests请求的资料请关注脚本之家其它相关文章!

相关文章

  • idea 自动生成类注释和方法注释的实现步骤

    idea 自动生成类注释和方法注释的实现步骤

    这篇文章主要介绍了idea 自动生成类注释和方法注释的实现步骤,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧
    2019-12-12
  • SpringBoot Logback日志记录到数据库的实现方法

    SpringBoot Logback日志记录到数据库的实现方法

    这篇文章主要介绍了SpringBoot Logback日志记录到数据库的实现方法,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧
    2019-11-11
  • 通过实例了解Java 8创建Stream流的5种方法

    通过实例了解Java 8创建Stream流的5种方法

    这篇文章主要介绍了通过实例了解Java 8创建Stream流的5种方法,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
    2019-12-12
  • 关于spring项目中无法加载resources下文件问题及解决方法

    关于spring项目中无法加载resources下文件问题及解决方法

    在学习Spring过程中,TestContext框架试图检测一个默认的XML资源位置,再resources下创建了一个com.example的文件夹,执行时,报错,本文给大家介绍spring项目中无法加载resources下文件,感兴趣的朋友跟随小编一起看看吧
    2023-10-10
  • jwt生成token和token解析基础详解

    jwt生成token和token解析基础详解

    这篇文章主要为大家介绍了jwt生成token和token解析基础,有需要的朋友可以借鉴参考下,希望能够有所帮助,祝大家多多进步,早日升职加薪
    2023-11-11
  • Mybatis useGeneratedKeys参数用法及问题小结

    Mybatis useGeneratedKeys参数用法及问题小结

    这篇文章主要介绍了Mybatis useGeneratedKeys参数用法及遇到的问题,本文给大家介绍的非常详细,对大家的学习或工作具有一定的参考借鉴价值,需要的朋友可以参考下
    2022-05-05
  • java控制台实现学生管理系统

    java控制台实现学生管理系统

    这篇文章主要为大家详细介绍了java控制台实现简单的学生管理系统,文中示例代码介绍的非常详细,具有一定的参考价值,感兴趣的小伙伴们可以参考一下
    2022-02-02
  • java关于并发模型中的两种锁知识点详解

    java关于并发模型中的两种锁知识点详解

    在本篇文章了小编给大家整理的是一篇关于java关于并发模型中的两种锁知识点详解内容,有兴趣的朋友们可以学习下。
    2021-04-04
  • 浅谈Java中SimpleDateFormat 多线程不安全原因

    浅谈Java中SimpleDateFormat 多线程不安全原因

    SimpleDateFormat是Java中用于日期时间格式化的一个类,本文主要介绍了浅谈Java中SimpleDateFormat 多线程不安全原因,感兴趣的可以了解一下
    2024-01-01
  • Java线程通讯的实现方法总结

    Java线程通讯的实现方法总结

    线程通讯指的是多个线程之间通过共享内存或消息传递等方式来协调和同步它们的执行,线程通讯的实现方式主要有以下两种:共享内存和消息传递,本文详细介绍了Java线程是如何通讯的,感兴趣的同学可以参考阅读
    2023-05-05

最新评论