Enterprise Java

Spring Boot and Micrometer with InlfuxDB Part 2: Adding InfluxDB

Emmanouil GkatziourasFebruary 27th, 2020Last Updated: February 25th, 2020

1 778 1 minute read

Since we added our base application it is time for us to spin up an InfluxDB instance.

We shall follow a previous tutorial and add a docker instance.

docker run –rm -p 8086:8086 –name influxdb-local influxdb

Time to add the micrometer InfluxDB dependency on our pom

<dependencies>
...
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-actuator</artifactId>
        </dependency>
        <dependency>
            <groupId>io.micrometer</groupId>
            <artifactId>micrometer-core</artifactId>
            <version>1.3.2</version>
        </dependency>
        <dependency>
            <groupId>io.micrometer</groupId>
            <artifactId>micrometer-registry-influx</artifactId>
            <version>1.3.2</version>
        </dependency>
...
</dependencies>

Time to add the configuration through the application.yaml

management:
  metrics:
    export:
      influx:
        enabled: true
        db: devjobsapi
        uri: http://127.0.0.1:8086
  endpoints:
    web:
      expose: "*"

Let’s spin up our application and do some requests.
After some time we can check the database and the data contained.

docker exec -it influxdb-local influx
> SHOW DATABASES;
name: databases
name
----
_internal
devjobsapi
> use devjobsapi
Using database devjobsapi
> SHOW MEASUREMENTS
name: measurements
name
----
http_server_requests
jvm_buffer_count
jvm_buffer_memory_used
jvm_buffer_total_capacity
jvm_classes_loaded
jvm_classes_unloaded
jvm_gc_live_data_size
jvm_gc_max_data_size
jvm_gc_memory_allocated
jvm_gc_memory_promoted
jvm_gc_pause
jvm_memory_committed
jvm_memory_max
jvm_memory_used
jvm_threads_daemon
jvm_threads_live
jvm_threads_peak
jvm_threads_states
logback_events
process_cpu_usage
process_files_max
process_files_open
process_start_time
process_uptime
system_cpu_count
system_cpu_usage
system_load_average_1m

That’s pretty awesome. Let’s check the endpoints accessed.

> SELECT*FROM http_server_requests;
name: http_server_requests
time                count exception mean        method metric_type outcome status sum         upper       uri
----                ----- --------- ----        ------ ----------- ------- ------ ---         -----       ---
1582586157093000000 1     None      252.309331  GET    histogram   SUCCESS 200    252.309331  252.309331  /actuator
1582586157096000000 0     None      0           GET    histogram   SUCCESS 200    0           2866.531375 /jobs/github/{page}

Pretty great! The next step would be to visualise those metrics.

Published on Java Code Geeks with permission by Emmanouil Gkatziouras, partner at our JCG program. See the original article here: Spring Boot and Micrometer with InlfuxDB Part 2: Adding InfluxDB

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