Architecture & DesignAn Introduction to Semantic Monitoring for Microservices

An Introduction to Semantic Monitoring for Microservices

Today’s businesses’ need applications that are glitch-free, reliable, scalable, and high performant. Since availability and performance is mission critical, you may not want to wait for your end-users to report a problem in production.

To detect problems early, you should be able to monitor your applications to know if your applications are working as expected and responding to user actions quickly.

Semantic monitoring – also known as synthetic monitoring – is an active monitoring approach used to test a microservices-based application. This article presents a discussion on why semantic monitoring is excellent for microservices.

What is Microservices Architecture?

In recent years, Microservices architecture has been an emerging trend in software design, promising numerous benefits such as quicker time to market, improved scalability, and loosely coupled components. It has transformed how software is created, tested, and delivered, providing advantages such as improved agility, resilience, and application scalability.

Read: An Introduction to Microservices.

Microservices Checklist

What is Semantic Monitoring?

Monitoring of web applications can broadly be classified into two categories – passive monitoring and active monitoring. While the former inspects the performance in real-time by monitoring the logins, clicks, site hits and other server transactions, the latter takes advantage of the necessary algorithms to predict future network states.

Semantic Monitoring is an innovative approach that combines automated testing with monitoring to identify business requirements that are not met in production when it comes to monitoring data.

Semantic monitoring (also known as synthetic monitoring) is the process of running a chunk of an application’s automated tests against a live production system in a consistent manner. The results or findings are then sent to a monitoring service, which receives notifications when anything goes wrong. This method combines automated testing with monitoring to identify business requirements not being met in the production environment.

The Difficulty of Monitoring Microservices

A microservices-based application is a collection of services that are built using a variety of technologies that are either homogeneous or heterogeneous in nature. Additionally, the rapid deployments of such applications make it excruciatingly difficult to monitor microservices-based applications.

Although there are many benefits in having a system decomposed into several services, monitoring applications built using microservices architecture is complex and challenging. As an example, if the health of one or more services has been reported as healthy, it doesn’t necessarily mean that the integration points between them is healthy as well.

Since microservices is a relatively new concept which has become popular for the last few years, you wouldn’t find many monitoring practices for microservices available. Basically, the two strategies used for monitoring microservices include: Service layer monitoring and Semantic monitoring.

While the former checks if the services are working as expected, the latter can be used for providing insights on whether the business transactions are working as desired, availability of the services and the overall performance of the microservices application.

Read: Microservices Observability and Monitoring.

Why Semantic Monitoring?

Typically, microservices-based applications are deployed in a container format and monitored using the basic container monitoring architecture, which monitors CPU and memory usage metrics. Container infrastructures often lack a sophisticated monitoring system. Even if there is one, it would hardly have the capability to monitor business process semantics. As a result, we must consider two monitoring vectors for microservices: service layer monitoring and semantic monitoring.

Semantic Monitoring for Microservices

Albeit a painful task, microservices monitoring is important for the success of microservices architecture. However, there are many constraints and challenges involved. As an example, with simultaneous execution of many different services, it often becomes difficult to ascertain the root cause of a failure. Here’s where Semantic monitoring comes for the rescue.

Ideally, a monitoring solution should be able to collect data and send out alerts if there is an anomaly. Synthetic transaction monitoring or semantic monitoring does just that and much more. It is an altogether new approach towards monitoring an application using synthetic transactions by emulating end user flows. This is achieved by running a subset of an application’s automated tests against a production system at regular intervals of time.

These tests mimic end user flows and check for availability, functionality, performance, and response times. The results are then fed to a monitoring solution. This process of verifying the semantic correctness of a system is known as semantic monitoring. Semantic monitoring is particularly useful for monitoring e-commerce and other high traffic sites as well as microservices applications.

Types of Semantic Monitoring

Basically, there are three types of semantic monitoring. These include the following:

  • Availability Monitoring – availability monitoring is also known as uptime monitoring and is used to check if the site or the service is up and running and is accessible.
  • Performance Monitoring – performance monitoring is used to check for page load speed, backend response times and slow performance.
  • Transaction Monitoring – transaction monitoring is used to check if a transaction is working as expected.

Benefits of Semantic Monitoring for Microservices

In this section we’ll examine the benefits of Semantic monitoring for microservices.

Measure, Baseline and Analyze Performance Trends

Semantic monitoring is used to check your application’s availability and performance from an end user’s point of view. You can take advantage of semantic monitoring to measure, baseline, and evaluate your application’s performance patterns. It can help identify areas where improvements are needed. You can then build performance improvement strategies for your application.

By incorporating semantic monitoring into your production environment enables you to verify that transactions are performing as expected in production, enabling you to provide better-quality applications and services to your customers.

Faster Resolution and Alerts

Synthetic monitoring helps you to detect and fix issues before the end users of the application. Synthetic monitoring keeps a watch on the APIs, websites and mobile applications and sends out alerts proactively. Such alerts are typically sent when there is a performance problem or there is an availability issue. This enables you to identify the problem and fix it much before such problems impact the end users.

Validate Business Transactions

You should take advantage of semantic monitoring to validate both the service and business layers of your application. It can be used to mimic business processes or user transactions that include searching data, logging in, adding, modifying, or deleting items, and also monitor their performance. Semantic monitoring can help as a mechanism to validate business transactions, i.e., to verify if a transaction performs as expected in the production environment.

What Semantic Monitoring Can’t Do for Developers

Semantic monitoring will not be able to troubleshoot server or network problems. You should not use it to analyze each web page in your application. Creating and maintaining scripts for semantic monitoring in an application is a time-consuming exercise due to which it is used for monitoring only the critical flows of an application.

While semantic monitoring can monitor your application at any time of the day, it doesn’t cover all scenarios. These tests cannot simulate the network or the geographical location or all the end user’s activities. It just tests a subset of the operations – precisely, the critical flows in your application.

Microservices Architecture Tutorials

Modern distributed applications and communication services are becoming more complicated, with a plethora of heterogeneous subsystems. As such, it is challenging to manage such systems coherently. Semantic monitoring combines test execution with real-time monitoring to constantly assess your application.

Take advantage of Semantic monitoring to proactively monitor your microservices applications. Semantic monitoring combines test execution with real-time monitoring to constantly validate application behavior. It is especially useful for verifying microservices and how they interact at runtime.

Read more tutorials about the Microservices Architecture.

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