Logging in Microservices with Node.js

When working with microservices architecture and Node.js, it is important to enable and check logs.

We’ll start this chapter by understanding the core concepts of logging in microservices with Node.js. Logging is a critical aspect of microservices architecture, providing valuable insights into behavior, performance, and issues within a distributed system. In Node.js microservices, various logging techniques and libraries are employed to capture relevant information and robust logging systems for your Node.js microservices.

In a microservices architecture, logging plays a crucial role. Let me summarize what happens when there is no proper logging:

• Lack of visibility: Without logging, it becomes challenging to track and understand what’s happening within individual microservices. You won’t have insights into their behavior, events, or transactions.
• Troubleshooting difficulties: When issues arise, troubleshooting...

Choosing a logging framework and defining log levels

Logging is a crucial aspect of microservices, aiding in debugging, performance monitoring, and system analysis. By selecting an appropriate logging library and implementing best practices, you can build a robust logging system for your Node.js microservices.

Choosing a logging library

A logging library is a piece of software that can help you generate and manage log data from your Node.js application. Logging libraries can provide various features, such as different log levels, log formats, log transports, and log aggregation. Logging libraries can also improve the performance and functionality of your application by reducing the overhead of console.log and providing more information and control over your log data.

Selecting a suitable logging library is the first step. Some popular logging libraries for Node.js include the following:

• Winston: A versatile logging library with support for multiple transports (console...

Structured logging, log transport, and storage

Structured logging, log transport, and storage are related concepts that can help you manage and analyze your application logs more effectively. Let’s look at structured logging in depth in this section.

Structured logging

Structured logging is a method of logging where log messages are formatted as a set of key-value pairs or as JSON objects. This format makes logs more machine-readable and allows for easier parsing, filtering, and analysis. When combined with appropriate log transport and storage mechanisms, structured logging becomes a powerful tool for monitoring and troubleshooting in microservices architectures.

Here are some benefits of structured logging:

• Machine readability: Structured logs are easily parseable by machines, facilitating automated log analysis.
• Contextual information: Key-value pairs allow the inclusion of contextual information with log messages, aiding in troubleshooting.
• Consistency...

Log filtering, sampling, error handling, and exception logging

In a microservices architecture, effective log filtering, sampling, error handling, and exception logging are crucial for managing logs efficiently and gaining insights into the system’s behavior.

Here’s how you can approach these aspects:

• Log filtering: Log filtering involves selectively capturing and storing log entries based on specific criteria. This is essential for managing the volume of logs and focusing on relevant information.

  Here is its implementation with Winston (Node.js):

  const winston = require('winston');

  const logger = winston.createLogger({

    format: winston.format.simple(),

    transports: [

      new winston.transports.Console(),

      new winston.transports.File({ filename: 'error.log', level: 'error' }),

      new winston.transports.File({ filename: 'combined.log' }),

   ...

Context propagation, monitoring, and analyzing logs

Context propagation, monitoring, and log analysis are critical aspects of managing microservices in a distributed system. In this section, we take a deeper look at context propagation.

Context propagation

In microservices, where requests can traverse multiple services, propagating context information is essential for tracking and understanding the flow of requests. Contextual information, often in the form of headers or tokens, allows you to correlate logs across different microservices.

Here is an example of context propagation. In a Node.js environment with Express.js, you can use middleware to propagate context information:

// Middleware to add context to requests
app.use((req, res, next) => {
  // Add a unique request ID to the request
  req.requestId = generateRequestId();
  // Log the start of the request
  logger.info(`[${new Date()}] Start processing request ${req.requestId...

Summary

In this chapter, we have learned a lot about microservices and how to monitor microservices in Node.js using several principles and tools.

In summary, logging in microservices with Node.js is a crucial aspect of ensuring observability, troubleshooting, and maintaining the health of a distributed system. Here’s a summary of key points:

• Logging libraries: Use logging libraries such as Winston in Node.js for structured and flexible logging.
• Log levels: Utilize different log levels (for example, error, warn, info, debug) to categorize and prioritize logs based on severity.
• Structured logging: Implement structured logging by formatting logs as key-value pairs or JSON objects for better machine readability.
• Context propagation: Propagate contextual information (for example, request IDs) across microservices to correlate logs and trace the flow of requests.
• Error handling: Implement error handling and exception logging to capture detailed information...

Quiz time

• What are some popular logging libraries for Node.js?
• What is structured logging?
• What are log filtering, sampling, error handling and exception logging?