The microservices architecture is a software development strategy in which applications are broken down into smaller components called microservices. Each microservice is responsible for a specific task or business function and communicates with other microservices through application programming interfaces (APIs). Effectively managing a microservices application requires monitoring, much like any other IT infrastructure.
While continuous monitoring (CM) in microservices can be challenging — with many components spread across different clouds and systems — it is still necessary for a good user experience and protection against business losses. Forrester research shows that every dollar spent on user experience has a return on investment (ROI) of 9,900%. A continuous monitoring program can improve user experience by tracking feedback after updates, identifying performance bottlenecks and allowing developers to respond to critical bugs quickly.
This article discusses the importance of CM in microservices, how to implement it, and a few microservices monitoring best practices and tools.
What is continuous monitoring in microservices?
Continuous monitoring is a DevOps pillar that allows teams to gain visibility into application performance, security threats, compliance violations and the overall health of the development pipeline. With continuous monitoring, DevOps teams can quickly respond to problems and keep application downtime to a minimum. These processes are automated using various continuous control monitoring software.
Microservices monitoring tracks application uptime, performance, API transactions, security and log monitoring in real time. Metrics such as system response, API response, transaction time and volume are collected and analyzed to determine the application’s health.
How microservices can be monitored?
It is best to start monitoring early in the development lifecycle to reduce the risk of unanticipated problems surfacing late. Monitoring should also include test environments to complement testing procedures and provide better feedback.
The following are critical metrics to be monitored in microservices:
Golden signal metrics
These are the four most important metrics to monitor in microservices.
- Latency: the time it takes for a request to be serviced.
- Traffic: the volume of requests, typically the number of requests per second.
- Error rate: how often a failure is experienced on a request.
- Saturation: how close a service is to being used at full capacity, typically tracked as a percentage.
Watch our webinar to learn more about designing microservices and implementing operations such as security, monitoring and DevOps.
Why is continuous monitoring helpful?
Monitoring microservices provides the following benefits:
- All systems fail eventually but the performance degradation is often gradual. Monitoring can detect these degraded states and alert system owners to prevent total failure.
- Another benefit of continuously monitoring microservices is to check whether service level agreements (SLAs) with third parties are being honored or violated. This check ensures that service providers are delivering the agreed-upon level of service.
- Effective monitoring helps teams reduce the mean time-to-resolution (MTTR) by providing data on the root cause of the errors. Knowing where the error occurred and under what conditions makes it possible to recover the affected service quickly.
- Monitoring data collected over time provides valuable information on system failure patterns. Dev teams can use these metrics to improve overall performance and pinpoint development processes that need refinement.
- Microservice APM tools filter data to highlight the most critical events. Development teams can use these tools and dashboards to prioritize errors, saving time and effort while ensuring the application stays secure and running.
- Continuous monitoring in microservices also provides forensic data that gives insight into how the application performs in the post-production phase. Developers can validate and analyze this data to build better applications and services.
Continuous Monitoring: Best Practices
Here are 4 microservices monitoring best practices that dev teams can follow:
- Use kernel-level monitoring for containers
A survey by VMware found that, on average, 50% of applications are containerized. Containers are used in microservice development to increase portability and speed but often appear as black boxes that are difficult to monitor. Whereas agents-based monitoring is typical in virtual virtual machines, it is too heavy-weight for many containerized applications. Instead, kernel-level monitoring allows you to gain insights across the applications and containers on a host.
- Set alerts for service performance and experience
For containerized microservice applications, typically orchestrated using Kubernetes, it is important to set alerts focusing on application performance and end-user experience. Instead of focusing on the performance of individual containers or microservice instances, it is more effective to emphasize performance and end-user experience at the level of the overall service.
- Monitor APIs
It is imperative to monitor APIs because they are the main way users and other services interact with a microservice. Monitoring APIs can help developers see patterns in user behavior, identify areas that need optimization, and understand end-to-end user experience.
- Automate metric collection
Microservices are often deployed in dynamic environments across multiple locations or clouds. CM methods must aggregate data from various sources and be automated to monitor an application as it scales up. Automating manual processes avoids bottlenecks, and reduces human error.
Best tool to achieve continuous monitoring for authorization in a microservice architecture
The Enterprise OPA Manager (Styra DAS) is a central manager and control plane for the Open Policy Agent (OPA) authorization engine. OPA can be deployed alongside each service instance in a microservice application to handle authorization decisions. The Enterprise OPA Manager dashboard enables continuous monitoring in microservices authorization by collecting and aggregating authorization decisions.
The Enterprise OPA Manager integrates with popular open-source monitoring tools, such as Prometheus. Using the Prometheus integration, Enterprise OPA Manager can export data and metrics to help you complete the full picture and benefit from automated alerts.
Is continuous monitoring part of DevOps?
CM is an essential part of DevOps as it improves the overall performance and security of the development pipeline. This practice makes DevOps processes more efficient and results in high-quality applications.
What is meant by continuous delivery in microservices?
Continuous delivery is an automated process that moves code changes and updates into the production environment.
What is semantic monitoring?
Semantic monitoring (also called synthetic monitoring) runs the application’s automated tests against a live production system at regular intervals. Any failures in these tests can be reported to the continuous monitoring service.