序
对于系统服务的监控，tcp层通常是用heartbeat来进行，最简单的比如ping-pong。对于http层，来说springboot的actuator内置了/health的endpoint，很方便地规范了每个服务的健康状况的api，而且HealthIndicator可以自己去扩展，增加相关依赖服务的健康状态，非常灵活方便而且可扩展。
/health实例
{
"status": "UP",
"custom": {
"status": "UNKNOWN",
"custom": {
"status": "UNKNOWN",
"msg": "mock down to test aggregator"
}
},
"diskSpace": {
"status": "UP",
"total": 249779191808,
"free": 57925111808,
"threshold": 10485760
}
}
status枚举
/**
* Convenient constant value representing unknown state.
*/
public static final Status UNKNOWN = new Status("UNKNOWN");
/**
* Convenient constant value representing up state.
*/
public static final Status UP = new Status("UP");
/**
* Convenient constant value representing down state.
*/
public static final Status DOWN = new Status("DOWN");
/**
* Convenient constant value representing out-of-service state.
*/
public static final Status OUT_OF_SERVICE = new Status("OUT_OF_SERVICE");
/health的两个贴心点
对于多个HealthIndicator的status，spring boot默认对其进行aggregrate，然后计算最顶层的status字段的值，而且对于status是DOWN或者是OUT_OF_SERVICE的，返回的http的状态码是503，这对于应用监控系统来说真是大大的贴心啊，再总结一下：
- 自动聚合多个HealthIndicator的status
- 对于status是DOWN或者是OUT_OF_SERVICE的，返回503
这样应用监控系统一来就无需去解析返回结果，直接根据http的状态码就可以判断了，非常方便，太省心了有没有。
HealthAggregator
/**
* Base {@link HealthAggregator} implementation to allow subclasses to focus on
* aggregating the {@link Status} instances and not deal with contextual details etc.
*
* @author Christian Dupuis
* @author Vedran Pavic
* @since 1.1.0
*/
public abstract class AbstractHealthAggregator implements HealthAggregator {
@Override
public final Health aggregate(Map<String, Health> healths) {
List<Status> statusCandidates = new ArrayList<Status>();
for (Map.Entry<String, Health> entry : healths.entrySet()) {
statusCandidates.add(entry.getValue().getStatus());
}
Status status = aggregateStatus(statusCandidates);
Map<String, Object> details = aggregateDetails(healths);
return new Health.Builder(status, details).build();
}
/**
* Return the single 'aggregate' status that should be used from the specified
* candidates.
* @param candidates the candidates
* @return a single status
*/
protected abstract Status aggregateStatus(List<Status> candidates);
/**
* Return the map of 'aggregate' details that should be used from the specified
* healths.
* @param healths the health instances to aggregate
* @return a map of details
* @since 1.3.1
*/
protected Map<String, Object> aggregateDetails(Map<String, Health> healths) {
return new LinkedHashMap<String, Object>(healths);
}
}
OrderedHealthAggregator#aggregateStatus
@Override
protected Status aggregateStatus(List<Status> candidates) {
// Only sort those status instances that we know about
List<Status> filteredCandidates = new ArrayList<Status>();
for (Status candidate : candidates) {
if (this.statusOrder.contains(candidate.getCode())) {
filteredCandidates.add(candidate);
}
}
// If no status is given return UNKNOWN
if (filteredCandidates.isEmpty()) {
return Status.UNKNOWN;
}
// Sort given Status instances by configured order
Collections.sort(filteredCandidates, new StatusComparator(this.statusOrder));
return filteredCandidates.get(0);
}
可以看出是对status进行排序，然后取第一个的状态，其中statusOrder如下：
private List<String> statusOrder;
/**
* Create a new {@link OrderedHealthAggregator} instance.
*/
public OrderedHealthAggregator() {
setStatusOrder(Status.DOWN, Status.OUT_OF_SERVICE, Status.UP, Status.UNKNOWN);
}
排序方法
/**
* {@link Comparator} used to order {@link Status}.
*/
private class StatusComparator implements Comparator<Status> {
private final List<String> statusOrder;
StatusComparator(List<String> statusOrder) {
this.statusOrder = statusOrder;
}
@Override
public int compare(Status s1, Status s2) {
int i1 = this.statusOrder.indexOf(s1.getCode());
int i2 = this.statusOrder.indexOf(s2.getCode());
return (i1 < i2 ? -1 : (i1 == i2 ? s1.getCode().compareTo(s2.getCode()) : 1));
}
}
即Status.DOWN, Status.OUT_OF_SERVICE, Status.UP, Status.UNKNOWN优先级依次递减。status中一旦有出现DOWN的情况，整体的status就是DOWN，依次类推。
