Microservice Monitoring Tools + Best Practices

Microservice Monitoring Tools + Best Practices

Microservices are one of the hottest app architectures in the current market. They easily solve some of the most common problems with monolithic and service-oriented architecture. The ability to split your application into multiple smaller components and develop as well as monitor them individually opens up a whole new world of possibilities.

However, this also brings with it a new set of problems. Monitoring distributed applications requires thinking outside of the box. Conventional tools and techniques do not turn out to be effective when it comes to microservices monitoring.

In this guide, we will share some of the common best practices you can follow to get the most out of your microservices monitoring efforts. We will also share with you a list of tools that you can use to get started with microservices monitoring easily.

Use these links to find your way across the guide:

What is Microservice Monitoring

Before learning how to do microservices monitoring right, let’s take a quick tour into the basics of microservices and monitoring.

Microservices Architecture

Before diving into what microservices monitoring is, let’s first take a quick look at microservices architecture. The microservices architecture is a way of structuring software applications in which each functional component of the app is broken down and isolated as smaller services—resulting in the name microservices. This architecture has a number of benefits over monoliths and service-oriented architecture.

Microservices Monitoring

Since this architecture has been picking up pace, it is essential to understand how to monitor it correctly. In-code instrumentation has been a popular method of hacking into any application with monitoring tools. However, you need to be careful with microservices when setting up monitoring constructs.

Since the microservices architecture breaks down an application into several independent parts, the role of the network suddenly becomes very important. Most inter-services rely on API calls to interact with each other, and monitoring these calls can give great insight into the performance of your application.

There are high chances that you would opt for containerization to deploy your application to the end-users efficiently. Therefore, you can gain additional insights into your app’s performance by monitoring container-specific metrics. Also, monitoring a containerized app that is orchestrated by a tool like Kubernetes is very different from monitoring a traditional app. You can not depend on traditional instrumentation as scaling your app to thousands of containers will also scale your monitoring agents to the same number, adding unnecessary overhead to the cost and performance of your app.

Similar to the cases mentioned, there are a few other things that you need to keep in mind when setting up a microservices monitoring system. We will share more on that in a later section.

Why Monitor Microservices?

In order to implement an effective microservices monitoring setup, you need to find the right motivation. This section lists some promising benefits that a microservices monitoring setup adds to your business.

Reduce and Prevent Failure

Just like any other form of monitoring, microservices monitoring is vital to ensure that your microservices-based application does not fail. Aside from simply preventing your app from crashing, microservices monitoring can help you gain deeper insights into its performance and make optimizations that result in higher output or reduced costs.

If you do your monitoring right, you can even go so far as to predict performance issues before they occur. This can, in turn, help you prevent total failures from happening. It can be a huge step in delivering on the promises you make to your customers.

Meet SLAs

Coming to promises, you need to honor the Service Level Agreements that you set out for your app’s performance. Service Level Agreements (SLAs) are agreements that you make with your clients/users regarding the quality of service you will offer them. SLAs have legal implications, and failing to meet them can result in legal issues with your stakeholders.

Microservices monitoring not only helps you comply with SLAs, but also helps you to figure out where you stand viz-a-viz your SLAs. Without an effective monitoring setup, it would become impossible to gauge the quality of service you are offering to your users.

Identify Patterns That Are Otherwise Hard to Notice in Monolithic Apps

Since monoliths are coupled tighter than microservices-based apps, it can be difficult to track everything that happens inside them. Without this visibility, you might be missing out on crucial insights into how you can further optimize your system’s performance.

Monitoring the performance and behavior of your microservices will help you understand the behavior of each component in isolation. This creates a high chance for you to notice any collective or independent trends across your app and leverage them to optimize your operations further.

Optimize End-user Experience

Optimization is always at the core of monitoring. By monitoring your microservices, you come one step closer to understanding how your development efforts are reflected on to the user. You might be doing your best job by researching the most-liked features and taking care of all possible best practices, but a small memory leak or an endpoint failure might put them all to waste. And while you will be unaware of such performance losses, your users might face them while using your services.

Therefore, you need to ensure that you monitor your apps from external sources as well. You should have synthetic agents set up to hit your app at fixed intervals from around the globe and run predefined scripts of tests to ensure that everything is working as expected. This will not only perfect your app’s user experience it will also provide you with valuable feedback during the development process.

Important Metrics to Monitor

Here are some metrics that you should consider keeping an eye out for when you set up monitoring in your microservices-based application.

App-Specific Metrics

These are highly specific to the application. These are basically metrics that are related to the business logic of your app. For example, the number of active users would be a metric for a live streaming app, or the number of shoppers browsing through an e-commerce app would be another app-specific metric.

The purpose of tracking these metrics is to gather high-level data from the application to support business operations as well as support developers in identifying app usage anomalies.

Platform-Specific Metrics

Now we come down a level in the metrics hierarchy. Platform-specific metrics are focused on the underlying infrastructure of the application. These can include anything from database query execution times to the average response time of an endpoint. These metrics do not take business logic into consideration but are rather targeted at providing low-level system statistics.

System Events

Apart from the app-specific and platform-specific, there are a number of external factors that might affect your app’s performance. System events are events that occur in the system that your app is running on and are capable of causing performance disruptions to your app. For example, new deployments are considered quite resource-intensive, and they might affect the end-user experience while they are occurring.

Microservice Monitoring Tools

To help you get started with microservices monitoring, here are a few tools.

Scout APM

Scout APM is a pioneer lightweight, production-ready application monitoring tool that has recently started offering microservices monitoring capabilities. Some of the key features of this tool are:

Scout’s offering is unique because it provides so much more than just microservices monitoring in the same place. You get an add-on for error monitoring, enhanced alerting capabilities, and easy integrations with Slack and PagerDuty.

Prometheus

Prometheus is one of the best one-size-fits-all solutions for almost all types of application monitoring. You can configure Prometheus to collect your system and app-specific metrics, and it will prepare a time-series collection of this data. You can also hook it up with Grafana for detailed visualizations and graphs.

Some of the best features offered by Prometheus are:

DataDog

DataDog is one of the premiers in the field of observability and monitoring. It offers a wide variety of services, including infrastructure observability, log management, application performance monitoring, and more. DataDog also offers great support for microservices monitoring.

Some of the top features offered by DataDog are:

LightStep

Lightstep is a rather young entrant in the field of observability platforms. It has been quite popular for its clean design and ease of use. Most of the tool’s features are still evolving, but it still offers tough competition to some of the established market leaders in this domain.

Here are some of the top features of this tool:

Microservice Monitoring Best Practices for Implementation

Now that you have enough information about microservices, here are some tips and best practices you can follow to get the most out of them.

Monitor What’s Inside The Containers

Containers are the building blocks of microservices. The speed, portability, and flexibility that containers offer are unmatched, and it enables developers to collaborate on and deploy applications in production environments with ease.

In regards to their internal structure, containers are nearly black boxes to most of the infrastructure around them. It reduces the coupling between containers and their environment. But when it comes to debugging issues, it can cause hindrances.

From the DevOps point of view, you need visibility inside containers to ensure that everything is working as expected. Therefore you need to switch to instrumentation to gather metrics on what’s going on inside your containers. However, instrumentation in containers varies a lot in non-containerized environments, mostly because instrumentation agents that live inside non-containerized applications can add additional dependencies to containers. The Idea with containers is to reduce dependencies as much as possible hence this concept doesn’t work well for them. On top of that, adding monitoring agents to thousands of running containers isn’t the best use of available resources.

Potential solutions at this point are

Treat Logs, Metrics, and Traces as One Event Stream 

Traces, metrics, and logs are the three pillars of observability. To ensure that you monitor all aspects of your microservices-based app, you need to make it as observable as possible. One of the first steps to do that is to collect all relevant logs, metrics, and traces and unify them as one event stream for easier processing.

This data will not only help you in monitoring and identifying issues that occur at the moment but also enable you to pick up on trends and patterns that can predict when an issue might occur in the future.

Start With a Few Services & Metrics At First

Go slow, go steady. One of the best ways to start with something is to focus on quality rather than quantity. A similar rule applies to monitoring.

When beginning to monitor microservices, focus on a couple of services and metrics in the beginning. This will not only help you streamline your whole monitoring process but also give you detailed insights on the selected set of metrics and services and enable you to understand what you truly need out of your monitoring efforts. 

Also, prefer the services that are the easiest to change and are relatively less important than others in your system so that even if you mess up, you do not cause substantial damage to your business operations.

Opt for Container-Native Microservices Monitoring Wherever Possible

When monitoring microservices, you should always try to look for container-native solutions so that they can dive deep into the technology’s specifics, such as namespace, ReplicaSets, pods, etc., and provide you with customized and useful data.

You can leverage this to provide highly customized and relevant alerts to your developers and reduce alert fatigue. You also have the ability to set dedicated and relevant thresholds and not rely on general metrics to know when your system is acting out.

Prefer Health Checks Over Passive Monitoring

Manually gathering data from applications is considered a passive form of monitoring. Health checks are an innovative and proactive method of regularly testing a service. 

Why rely on the health check if it only returns a fixed value and does not cover the complete functionality of the service? It does help to check if the basic functionalities are up. If a simple health check fails, you can be sure that your service has a fundamental issue.

You can also implement health checks in a more complex manner. Health checks can check the end-to-end integration between a service and its dependent services. Such Health checks simulate the occurrence of some real work being done. You can also integrate health checks as a part of your CI/CD pipelines. This will notify you of any issues with your deployment before it is rolled out to your users. 

You can then choose to roll back the changes and investigate or move ahead and fix the incoming issues later. Health checks are usually recommended for microservices since the dependencies are highly distributed, and monitoring each service’s deployment is essential.

Monitor Your APIs

One of the most important parts of a microservices-based application is the network, which is essentially made up of API calls. Therefore to ensure that your microservices are able to interact well with each other, you need to monitor the API calls that facilitate communication between them,

If a response is not conveyed correctly or in time, the execution of other dependent microservices can be hampered. It might even start a chain reaction that ultimately takes away the uptime of your application. Monitoring API transactions can help you avoid such a situation. 

API monitoring provides a big-picture analysis for the health of each application component and acts as an indicator of the overall health of your application as well. API monitoring guides your team when they are unsure of where and when an issue occurs so that they can set to resolve it quickly.

Another way to look at this is that your APIs are the backbones of your microservices-based application. Even though there might not be a direct SLA or KPI based on their performance, they play a role major enough to disrupt other well-defined SLAs of your system. Therefore keeping a check on them is vital to maintaining the set quality of services for your end-users.

And last (but certainly not the least), being able to trace API calls as they travel through your app is a very important requirement for deep debugging. Since most of the app in a microservices-based architecture is divided into separate components, sound API monitoring practices can give way to an easier end-to-end debugging experience.

Get Started with Microservice Monitoring

Microservices are one of the best architectures to adopt for modern applications. This is owed to their modularity and loose coupling between components. However, this can cause issues in other aspects of application development, particularly monitoring and logging.

Conventional monitoring tools usually do not give optimum results with microservices apps. Hence, it is important that you employ tools & techniques that keep this unique and powerful structure at the core of their focus and provide you with the most observability possible in your applications.

Scout APM is one such tool. Scout has recently started to offer microservices monitoring services. Feel free to check out the tool with a 14-day free trial!