![]() I skipped over “When you page me in the middle of the night you will give me the info I need to find the problem” from the goals, and a few other things that should be part of every project. If you want to discuss what I have shown, head to and start a conversation. In future articles I will go into topics like alerting, machine learning, and bringing in custom data sources. Earlier I said that you should not limit yourself in the type and amount of data that you bring in decide what will help you prevent downtime and expand your list of sources. You can do the same and see logs, metrics, synthetic testing of your APIs, APM traces, and more. In this article I covered several ways of collecting data from and about your application and the infrastructure. You can read about logging best practices for Java apps and watch a video showing a Spring Boot application getting a logging overhaul. This helps correlate a record from the application log with a database metric and an APM trace. By adopting the Elastic Common Schema in the Spring Boot app, the logs are both clear and consistent with the other data sources we are ingesting. It specifies a common set of fields for logs and metrics that is used by all of the Elastic Beats, and it is extendable by you. The Elastic Common Schema is a powerful way to correlate information from multiple sources. To add custom spans and more, see the documentation. There is so much more to do with APM, in this article we are just looking at the out of the box traces with zero code changes. This makes it easy to pinpoint and fix performance problems quickly. Looking into the AddNewUser transactions (which is where Heartbeat is performing synthetic API testing) I can see the breakdown of a transaction: ElasticĪnd digging into the “INSERT INTO user” span I can see the SQL used, transaction ID, etc.: Elastic Out of the box and without any code changes you will see detailed performance information on response time for incoming requests, database queries, calls to caches, external HTTP requests, JVM metrics, errors, and more. Launch APM and navigate to your service: Elastic mvnw spring-boot:run and sourcing the environment variables in the Maven Wrapper: exec "$JAVACMD" \ -javaagent./elastic-apm-agent.jar \ _name=$ soon as the application is started, the API tests set up earlier with Heartbeat will result in traces in Elasticsearch. I prefer to use environment variables for the javaagent properties, so I take the details provided and set the environment variables: $ cat environment export ELASTIC_APM_SERVER_URL= export ELASTIC_APM_SECRET_TOKEN=WjyW67R0eSWDhILWDD export ELASTIC_APM_SERVICE_NAME=winter-mysql export ELASTIC_APM_APP_PACKAGES=com.example The process is provided in Kibana Home > Add APM > Java and consists of downloading the jar file and using the Java instrumentation API to start the agent. Open the Home > Add data > APM page, choose Java, and download the jar file: Elastic Load the APM Kibana objects Elastic By adding the APM jar file to the command used to launch the application I get distributed tracing so I can see where my app is spending time (whether it is in the Java code or in the calls to MariaDB). ElasticĪnd Elastic Distributed tracing of the application including the databaseĮlastic APM instruments your applications to ship performance metrics to Elasticsearch for visualization in Kibana with the APM app. At the bottom of that page is a link to the Uptime App. Run the setup command and start Heartbeat as directed in Kibana > Add metric data > Uptime monitors. When you are instructed to edit the heartbeat.monitors setting in the heartbeat.yml file, replace the existing monitor with this API test: # Configure monitors inline heartbeat.monitors: - type: http name: SpringToDoApp schedule: 5s' urls: [" check.request: method: POST headers: 'Content-Type': 'application/x-status: 200 body: - Saved - saved response.include_body: 'always' Install Heartbeatįollow the instructions in Kibana Home > Add metric data > Uptime monitors. Heartbeat monitors the availability of services by testing API endpoints for proper responses, checking websites for content and response codes, verifying ICMP pings, etc. ![]() By automating the testing with Heartbeat, the response time and test results are available alongside the logs, APM, and other metrics for the service. This is often done manually by using curl or the Postman API Client. In order to measure proper functionality of the API endpoints we need to POST some URL encoded data, read the response, and verify it. Of 2 API test results and response time measurements
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