Jaeger can show metrics, but it's not its primary function. Jaeger is primarily a distributed tracing system that exposes metrics in Prometheus format. To use Jaeger for metrics, you need to configure it properly and set up a compatible backend. Let's explore how you can leverage Jaeger's metrics capabilities and integrate them with other monitoring tools for comprehensive performance visualization.

Understanding Jaeger's Capabilities in Metrics Monitoring

Jaeger's main purpose is distributed tracing — tracking requests as they flow through your microservices architecture. However, it also exposes some built-in metrics in Prometheus format. These metrics provide insights into Jaeger's internal operations and the traces it collects.

To enable metrics reporting in Jaeger, you use specific command-line options when starting the Jaeger components. The metrics exposed by Jaeger are different from the traces it collects: metrics are aggregated numerical data points, while traces represent detailed information about individual requests.

Types of Metrics Available in Jaeger

Jaeger offers several types of metrics:

  1. Runtime metrics: These include memory usage and CPU utilization of Jaeger components.
  2. Tracing-specific metrics: Span counts, latency distributions, and other trace-related data points fall into this category.
  3. Custom application metrics: With some additional configuration, you can integrate your application's custom metrics into Jaeger's metrics pipeline.

Enabling Metrics in Jaeger

To start collecting metrics with Jaeger, follow these steps:

  1. Choose a metrics backend — Prometheus is a popular and well-supported option.
  2. Configure Jaeger to use the selected backend. For Prometheus, use the -metrics-backend prometheus flag when starting Jaeger components.
  3. Set up your metrics backend to scrape the Jaeger metrics endpoint.

Here's an example of how to start the Jaeger agent with Prometheus metrics enabled:

jaeger-agent --metrics-backend prometheus

After configuration, verify that the metrics endpoint is accessible. For Prometheus, this is typically at /metrics on the configured port.

Visualizing Jaeger Metrics

While Jaeger's UI primarily focuses on trace visualization, you have several options for visualizing the metrics it exposes:

  1. Jaeger UI: Offers basic metrics visualization capabilities, mainly for Jaeger's internal operations.
  2. Grafana dashboards: Provide more advanced and customizable visualizations for Jaeger metrics.
  3. Existing monitoring solutions: Integrate Jaeger metrics into your current monitoring setup for a unified view.

To create meaningful metrics dashboards:

  • Focus on key performance indicators relevant to your system.
  • Combine Jaeger-specific metrics with application and infrastructure metrics for a comprehensive view.
  • Use consistent naming conventions and units across your dashboards.

Service Performance Monitoring (SPM) in Jaeger

Jaeger's Service Performance Monitoring (SPM) feature offers additional insights into your services' performance. SPM provides key performance indicators such as request rates, error rates, and latency percentiles.

To enable SPM in Jaeger:

  1. Set the -query.max-clock-skew-adjustment flag when starting the Jaeger query service.
  2. Configure your Jaeger client to send the necessary metadata with spans.

Interpreting SPM data helps identify performance bottlenecks and optimize your services. Look for patterns in latency spikes, error rate increases, or unusual request volumes to guide your optimization efforts.

Combining Tracing and Metrics for Comprehensive Monitoring

The real power of Jaeger's metrics capabilities shines when combined with its tracing functionality. This combination provides a holistic view of your system's performance:

  • Traces offer detailed insights into individual requests.
  • Metrics provide aggregated performance data over time.

To achieve this synergy:

  1. Use OpenTelemetry for unified observability data collection. It supports both tracing and metrics, seamlessly integrating with Jaeger.
  2. Correlate trace data with metrics for root cause analysis. For example, link a latency spike in your metrics to specific slow traces.

Here's a basic example of using OpenTelemetry to send both traces and metrics to Jaeger:

from opentelemetry import trace
from opentelemetry.exporter.jaeger import JaegerExporter
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor

# Set up the Jaeger exporter
jaeger_exporter = JaegerExporter(
    agent_host_name="localhost",
    agent_port=6831,
)

# Set up the tracer
trace.set_tracer_provider(TracerProvider())
tracer = trace.get_tracer(__name__)

# Create a span processor
span_processor = BatchSpanProcessor(jaeger_exporter)

# Add the span processor to the tracer
trace.get_tracer_provider().add_span_processor(span_processor)

# Now you can create spans and they will be exported to Jaeger
with tracer.start_as_current_span("my_span"):
    print("Hello, World!")

Key Takeaways

  • Jaeger can show metrics, primarily by exposing them in Prometheus format.
  • Enabling metrics in Jaeger requires specific configuration and backend setup.
  • Visualization options include Jaeger UI, Grafana, and custom dashboards.
  • Combining tracing and metrics provides a holistic view of system performance.

FAQs

How do I enable metrics collection in Jaeger?

Enable metrics collection in Jaeger by starting its components with the appropriate flags, such as --metrics-backend prometheus for Prometheus integration.

Can Jaeger replace dedicated metrics monitoring tools?

While Jaeger can expose metrics, it's not designed to replace dedicated metrics monitoring tools. It's best used in conjunction with specialized metrics solutions for comprehensive monitoring.

What's the difference between Jaeger's metrics and traditional APM metrics?

Jaeger's metrics focus on its internal operations and trace-related data, while traditional APM metrics often cover a broader range of application and infrastructure performance indicators.

How can I correlate Jaeger traces with application metrics?

Use a unified observability framework like OpenTelemetry to collect both traces and metrics. This allows you to link trace IDs with corresponding metric timestamps for correlation.

Consider SigNoz as an Alternative to Jaeger

While Jaeger is a popular choice for distributed tracing, it's worth considering SigNoz as an alternative solution. SigNoz is an open-source application performance monitoring (APM) and observability platform that offers:

  • Integrated metrics, traces, and logs in a single platform
  • Built-in support for ClickHouse as the storage backend, providing excellent query performance and data compression
  • User-friendly interface for visualizing and analyzing trace data
  • Easy setup and configuration, with both self-hosted and cloud options available

SigNoz cloud is the easiest way to run SigNoz. Sign up for a free account and get 30 days of unlimited access to all features. Get Started - Free CTA You can also install and self-host SigNoz yourself since it is open-source. With 18,000+ GitHub stars, open-source SigNoz is loved by developers. Find the instructions to self-host SigNoz.

If you're looking for a comprehensive observability solution that goes beyond just distributed tracing, SigNoz might be the right fit for your needs. It provides a seamless experience for developers and operations teams, combining the power of metrics, traces, and logs in one tool.

To learn more about how SigNoz compares to Jaeger and how it can enhance your observability stack, visit https://signoz.io.

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