Monitoring Microservices

A key part of the production environment is monitoring and alerting. Monitoring microservices is crucial for understanding how apps are functioning and identifying issues to prevent system failures.

By adopting a microservice architecture, a typical monolith application is broken into individual components. Each of these components runs its own programming language and database being deployed, scaled and upgraded independently.

The real challenge here is An increase in the number of distributed components you need to monitor makes it difficult to manage the system.

The complexity of microservices illustrated through the Netflix and Amazon Deathstars

Netflix is one of the earliest adopters of microservices, and one of the most discussed. Today, the Netflix application leverages 500+ microservices and API Gateways that handles over 2 billion API edge requests daily.

Also Uber reported in late 2014 with 4,000 proprietary microservices and a growing number of open source systems that needed to be monitored, posed a challenge for monitoring their complex microservices system.

Structure of microservices at Amazon. Looks almost like a Death Star but is way more powerful. Learn more about microservices at Amazon?here.?

Principles To Monitor Microservices Given the dramatic changes in software delivery, monitoring requires an overhaul to perform accurately in the microservice environment. But, what is the principle behind which microservice monitoring actually works? Monitoring microservices have some principles, including:

1. Monitoring containers and what’s inside

2. Regular alert on the service performance rather than container performance

3. Monitoring multi-location and elastic services

4. Monitoring APIs

5. Mapping monitoring to organizational structure.

These principles of monitoring microservices will enable you to establish effective monitoring while addressing both organizational and technological changes.

Also below is some of popular microservices monitoring tools

Prometheus

Prometheus is also an open-source metrics-based system for monitoring. It has a simple, powerful data model and a query language to help developers in analyzing the performance of infrastructure and applications. Software's like Docker and Kubernetes already have Prometheus client libraries while other third-party software that doesn’t have Prometheus format metrics can implement hundreds of available integrations.

Reimann

Reimann is a monitoring tool that aggregates events from applications or hosts and feeds them into a stream processing language enabling them to be manipulated, summarized and actioned. It can also track events and allows build checks taking advantage of combinations and sequences of events. Additionally, it offers notifications the ability to send events to other storage and services.

Datadog

Datadog is a monitoring tool for cloud-based applications that offers monitoring of servers, tools, databases and services via a SaaS-based analytics platform. It can be used for monitoring Docker performance by collecting metrics of all the containers.

Elastic Stack

Elastic Stack is an end-to-end software stack that helps in search and analysis solutions. It can help in getting data from any source in any format to enable searching, analyzing and visualizing real-time data.

Kibana

Kibana is a dashboard and virtualization tools attached to ElasticSearch. It can help in creating graphs and dashboards. Having its web server, it can run on any host connecting ElasticSearch back end.

Conclusion

With the help of the above-mentioned principles and tools for monitoring microservices, it will become easier and efficient for the development teams to control the errors and other slowdowns of the system. Not only the data tracing will help in identifying the issues and resolve them but also allows developers or DevOps teams to measure system health and performance to understand the effect of change while prioritizing areas of improvements.

References

https://thenewstack.io/led-amazon-microservices-architecture https://www.slideshare.net/gjuljo/microservices-architectures-become-a-unicorn-like-netflix-twitter-and-hailo

#distributedsystems ?#microservices #monitoring