Observability in Microservices: The Fundamentals

observability provides visibility into the inner workings of microservices , making it easier to monitor and manage the flow of requests and interactions between services a good observability strategy is critical to ensure the reliability and efficiency of an architecture's applications the fundamental principles of observability the principles of observability measurability , understandability , and actionability work together to provide comprehensive insights into the system's behavior measurability measurability is the ability to quantify, measure, and track the performance and behavior of microservices in a system achieving measurability involves collecting and analyzing data from various sources, such as logs, metrics, and traces to gain insights into the health and efficiency of the microservices and identify any potential issues or bottlenecks measurability provides the data needed to make informed decisions and optimize the microservice architecture every system should be instrumented to generate and capture relevant data that provides a comprehensive, accurate, and consistent view of the system's behavior this will help you promptly identify and address any issues or performance degradation understandability understandability is the ability to make sense of the data and information collected about a microservice, including its performance, behavior, and overall health achieving understandability requires a clear understanding of the microservice architecture, its interactions with other microservices, and the various tools and technologies used to monitor and collect data additional information, such as context, metadata, and annotations should accompany the data to help identify patterns and correlations diagnose issues and problems make informed decisions about optimizing and improving the microservice the data should also be presented through a user friendly dashboard or visual interface actionability actionability is taking action based on the data and insights provided by observability tools it means that the data gathered through observability should be accessible, understandable, and provide clear information on the root cause of any issues, enabling teams to make informed decisions and take effective action to resolve them this can include identifying performance bottlenecks detecting errors identifying opportunities for optimization insights should always be actionable, meaning they can be used to make specific changes to the system to improve its behavior designing observable services to design observable services, developers should implement patterns such as health check apis log aggregation distributed tracing exception tracking application metrics audit logging health check apis what is a health check api? health check apis allow a client to query the status or health of a server or system it provides a way to monitor a system's health and performance and determine if it is functioning as expected the health check api typically returns a response that indicates whether the system is healthy, degraded, or unhealthy why you need a health check api health check apis provide a simple and consistent way to monitor the health of an application or system sometimes, a service isn’t working correctly and can't handle requests this service disruption could be because it's still starting up, encountered a bug, lost connection to its database, or is too busy to handle requests by having a standardized way of checking a system's health, developers and operators can quickly and easily identify and troubleshoot any issues that arise this visibility can significantly improve the overall reliability and uptime of the system in addition to improving reliability and uptime, health check apis can also help to reduce the time and effort required to diagnose and fix issues by having a consistent and standardized way of checking a system's health, developers and operators can quickly identify the source of any problems and focus their efforts on fixing them health check apis can also easily integrate into a broader observability stack, such as a logging or monitoring platform this integration allows developers and operators to easily monitor the health of their systems and applications in real time, giving them a complete and up to date view of the system's health example health check api here is an example of a health check api in javascript pseudocode // define endpoint for health check health check endpoint = "/health" // define success message and status code success message = "ok" success code = 200 // function to handle health check requests function handlehealthcheckrequest(request) // perform any necessary checks // if checks pass, return success message and status code if checkspass return success message, success code // otherwise, return an error message and appropriate status code else return "not ok", 500 // map endpoint to function route health check endpoint to handlehealthcheckrequest in this implementation, the handlehealthcheckrequest function performs any necessary health checks and returns either a success message and success code or an error message and appropriate status code if the checks fail the endpoint health check endpoint is mapped to the handlehealthcheckrequest function, which is executed when a request is made to the endpoint the system is considered healthy if the response is a 200 status code with an "ok" status the system is considered degraded or unhealthy if the response is a 500 status code with a "not ok" status log aggregation what is log aggregation? log aggregation involves collecting data from multiple logging sources and consolidating them into a central location for storage and analysis the collected log data is often used to diagnose issues with systems and applications, monitor system performance and usage, and detect security incidents why you need log aggregation according to observe inc , 78% of organizations ingest over 100 gb of observability data daily log aggregation is important for five main reasons centralized view of log data log aggregation provides a centralized view of log data from multiple sources, making it easier to identify trends and patterns in the data and diagnose and troubleshoot system issues improved visibility log aggregation helps improve visibility into the system by making it easier to search, filter, and analyze log data in real time this ability helps identify issues faster, reducing downtime and increasing system availability scalability log aggregation helps to scale log management by enabling you to store and process large volumes of log data this is especially important in large and complex systems, where log data can be generated from many different sources compliance log aggregation can help with compliance by providing a centralized repository for storing log data, which can be used to meet auditing and compliance requirements better monitoring log aggregation enables better system monitoring by making it easier to identify and alert on issues in real time for example, you can use log aggregation to detect and alert on trends and patterns in log data, such as a sudden increase in error messages or a specific type of error message some popular log aggregation tools include elk stack (elasticsearch, logstash, and kibana), graylog, sumo logic, and splunk these tools typically provide features such as log searching, alerting, dashboards, and reports example log aggregation (elk stack) here is an example of log aggregation in action using the elk stack (elasticsearch, logstash, and kibana) collecting log data logstash collects log data from multiple sources for example, logstash can collect log data from apache web servers, system logs, and application logs storing log data the collected log data is then stored in elasticsearch, a distributed, scalable search and analytics engine analyzing log data kibana analyzes the log data stored in elasticsearch kibana provides a user friendly interface for searching and visualizing log data, making it easier for it teams to identify and resolve problems creating dashboards and reports using kibana, it teams can create dashboards and reports to monitor system performance and usage, detect security incidents, and track key metrics over time for example, the it team could create a dashboard that displays the number of error messages generated by their apache web servers over time the dashboard would help the team identify trends in error messages, enabling them to resolve issues proactively and improve system performance , while log aggregation pipelines send logs to a centralized logging server to aid in troubleshooting distributed tracing identifies each external request with a unique id and tracks requests as they flow between services exception tracking reports exceptions to a service that de duplicates them, alerts developers, and tracks resolution application metrics maintain metrics such as counters and gauges and expose them to metrics servers, while audit logging keeps track of user actions relevance of observability in microservices visibility with multiple independent services working together, it can be challenging to understand the flow of requests and interactions between services observability provides visibility into the inner workings of a microservices architecture, making it easier to monitor and manage debugging issues can arise in one service and affect the overall system in a microservices environment observability provides the data and insights needed to quickly identify and resolve issues, ensuring the smooth operation of the application performance optimization observability provides data on the performance of each service and the overall system, allowing for continuous performance optimization this helps to ensure that the application runs at optimal performance levels and provides a positive user experience observability is critical for managing and maintaining a microservices architecture the principles of measurability, understandability, and actionability work together to understand the system's behavior comprehensively by understanding the relevance of observability in a microservices world, organizations can improve the reliability and efficiency of their applications