Microservices Observability and Monitoring

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Modern applications seldom fail in predictable ways and, with the surge in the complexity of such applications, detecting the exact cause of errors that occur in the production environment after an application has been deployed, has become excruciatingly difficult – it is not possible to be prepared for all eventualities in advance.

The reasons for such failures being obscure, the need for an efficient and effective real-time application monitoring process is important. Here is where observability and monitoring come into play. In this article we will examine observability and monitoring from a software architect’s perspective.

What is Observability in Software Architecture?

An application might fail in the production environment for reasons aplenty. To debug your application successfully and find the root cause of the issues, you should instrument your application’s components to be observable. But what does this mean, exactly?

Observability involves having the right data to assist a developer in such a way that you can get answers to problems that occur in a production environment. Observability provides raw, granular data that can be used to get an insight into complex and distributed systems. It comprises a set of activities that involve collecting, analyzing, and measuring various diagnostic information such as logs, metrics, traces, events, and so forth.

An observable system can help you to understand why a request failed, the performance bottlenecks, etc. Given the rise in microservices usage or adoption in the past few years, it is crucial that your system is observable for efficient debugging and diagnosis.

The Three Pillars of Observability in Software Architecture

Observability refers to telemetry that your application provides, and it requires insight into the three pillars, namely: metrics, traces, and logs. These three pillars constitute the golden triangle of observability and can help you unlock the ability to build applications better.

Although metrics, logs and traces have their distinctly separate purposes, they work together to help you gain insights into the performance and behavior of your applications. You can create better applications when they’re observable – the best part is that you can begin with whatever data that you have. This section talks about these three pillars.

Metrics

Metrics constitute a numeric representation of data that is measured over periodic intervals of time. For example, metrics will reveal the number of requests a service can process per second and the total resources used by a method – for example, CPU, Memory, and so on.

Traces

A trace consists of ID, name and time value. It helps you understand the complete lifecycle of a request. Such requests might span across multiple systems as well. You can take advantage of traces to profile microservices-based applications, Serverless applications, or containerized applications. You can analyze trace data to ascertain the system’s health and identify and resolve issues quickly. You can derive both metrics and traces from the logs generated by the application.

Logs

Logs are time stamped records that can provide software architects and developers with comprehensive information about the resources in use. Logs can provide you insights into what went wrong and what changed in the system’s behavior at that time. Logs comprise structured or unstructured information (usually text) that is generated when the application is in execution. We usually look at the generated logs when things go bad. You can investigate the logs, analyze them, and then debug and troubleshoot your application’s code to identify the issues or defects that have occurred.

Introduction to Microservices Monitoring

Monitoring lets you know what is broken and why it has been broken. It is important for analyzing long term trends that can be utilized for building dashboards and sending alerts. Monitoring helps you to detect known failures. For example, you may want to keep an eye on an application for issues such as a lack of available disk space, failure of I/O bound services, and so on. If you would like monitoring to be effective, it is imperative that you’re able to identify the core set of metrics that can provide you insights into the health of a system. You can take advantage of metrics and logs to understand the state of your system.

Monitoring Microservices-based Applications

When monitoring microservices-based applications, you must have a comprehensive understanding of the performance and availability of the API calls for all the services in the application. You should monitor the containers including the services that are running inside them. You should be able to take advantage of orchestration systems to alert on service performance from time to time. You should monitor APIs as well and map the monitoring process to your organizational structure.

Observability vs Monitoring

The terms observability and monitoring might seem like synonyms, but they are not the same. Monitoring and observability complement each other but they differ in their purposes. While the former lets you know when something goes wrong, the latter helps you to understand why it went wrong.

Monitoring is what you do, and observability is the resource you have at your disposal. When you’re to monitor the application, you should have an insight into the data you need to monitor. Monitoring is a process which tracks performance and identifies issues and anomalies. It also describes the internal state, health, performance, and other important characteristics.

Observability provides the necessary insights that help in the monitoring process. You might think of observability as an insight that you should have to know what needs to be monitored. Monitoring comes after observability – once these insights are available, monitoring determines what needs to be done once a system is observable.

Tools and Platforms for Observability and Monitoring

Here is a list of the popular tools/platforms for observability and monitoring of microservices applications.

Sentry – This is a client-side performance monitoring solution that helps your team in faster time to the market.
Sensu – This is yet another monitoring tool for Microservices that collects metrics, analyzes them and sends notifications as well. Sumo logic – Sumo logic is a great tool for monitoring, securing, and optimizing your applications.
Dynatrace – Dynatrace is an application performance monitoring (APM) solution adept at monitoring and managing user experience, infrastructure, application performance, response time and cloud environments.

The Do-it-Yourself Approach to Observability

Observability is essential to modern organizations since it provides the necessary insights to ensure that services are delivered in such a manner that business demand is fulfilled in totality. Many organizations adopt a DIY approach to observability which involves a manual approach. You can also choose to build the entire application stack – adopting the do-it-yourself (DIY) option. However, the downside of this approach is that it takes up a lot of time – so it is not recommended.