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Java Cloud Computing: Monitoring and Logging Best Practices
Monitoring Best Practices
Logging best practices
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Java Cloud Computing: Monitoring and Logging Best Practices

Jun 01, 2024 pm 04:59 PM
java cloud computing

Effective monitoring and logging in a cloud computing environment requires: Monitoring key metrics using tools like Prometheus, Jaeger, and Grafana, and setting up alerts and notifications to track application health. Adopt a logging framework such as Log4j or Logback, use reasonable log levels, and use MDC to add contextual information. Practical examples show how to use Prometheus to monitor Spring Boot applications, and use Log4j and Jaeger to log distributed system requests.

Java Cloud Computing: Monitoring and Logging Best Practices

Java Cloud Computing: Monitoring and Logging Best Practices

In a cloud computing environment, monitoring and logging are essential to ensure application stability and Performance is critical. This guide will show you how to use Java for effective monitoring and logging, and provide practical examples.

Monitoring Best Practices

Use monitoring tools:

  • Prometheus: an open source time series database that provides rich indicator collection and visualization functions .
  • Jaeger: Distributed tracing system for tracking and analyzing request latency.
  • Grafana: Data visualization and dashboarding tool that makes data visual and easy to understand.

Collect key indicators:

  • HTTP request time and status code
  • Database response time
  • Memory and CPU Usage
  • Errors and Exceptions

Set up alerts and notifications:

  • Configure thresholds and triggers when they occur Trigger alerts when abnormal conditions occur.
  • Use notification channels such as email, text message, or Slack to ensure that incidents are handled promptly.

Logging best practices

Choose the right logging framework:

  • Log4j: Popular Java logging framework, Provides high configurability and scalability.
  • Logback: A replacement for Log4j, providing a more concise and flexible configuration system.

Use reasonable levels:

  • ERROR: Serious error or exception
  • WARN: Potential problem or unusual condition
  • INFO: General information and application status
  • DEBUG: For debugging and troubleshooting

##Use log context:

    Use MDC (Mapped Diagnostic Context) to add additional information to the log message, such as user ID or request identifier.
  • This helps correlate log entries when investigating issues.
Practical case

1. Monitor Spring Boot application

Use Prometheus and Grafana to monitor Spring Boot application:

import io.micrometer.core.annotation.Timed;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class MyController {
    @Timed
    @GetMapping("/")
    public String home() {
        return "Hello, world!";
    }
}
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Add Prometheus dependencies and configure the dashboard:

<dependency>
    <groupId>io.micrometer</groupId>
    <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
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# Grafana dashboard configuration
dashboardSections:
  - title: My App Monitoring
    panels:
      - title: Request Latency
        type: graph
        datasource: Prometheus
        targets:
          - expr: histogram_quantile(0.99, sum(rate(http_server_requests_seconds_bucket[5m])))
            legend: Latency (99th percentile)
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2. Logging distributed system

Use Log4j and Jaeger to record requests from the distributed system:

import io.jaegertracing.Configuration;
import io.jaegertracing.ScopeManager;
import io.jaegertracing.internal.samplers.ConstSampler;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class DistributedController {
    private static final Logger logger = LogManager.getLogger();

    // Configure Jaeger tracer
    static {
        Configuration config = new Configuration("my-app")
                .withSampler(new ConstSampler(true))
                .withScopeManager(new ScopeManager());
        Tracer tracer = config.getTracer();
    }

    @GetMapping("/distributed")
    public String distributed() {
        Span span = Tracer.currentSpan();
        logger.info("Span ID: {}", span.getSpanId());
        return "Distributed request";
    }
}
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Add Jaeger dependencies and configure Tracing:

<dependency>
    <groupId>io.jaegertracing</groupId>
    <artifactId>jaeger-spring-boot-starter</artifactId>
</dependency>
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# Jaeger configuration
spring.sleuth.exporter=jaeger
spring.sleuth.jaeger.sampler.param=true
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