Microservice environments need monitoring

What do you monitor in Microservices?

The traditional way of managing and expanding monolithic enterprise applications becomes problematic with their increasing size and complexity. The switch to microservices offers a solution: applications are structured there as a collection of loosely coupled services. This makes it easier to create, expand and scale services. But how exactly does microservice differ from monolithic architecture? And what are the advantages and challenges?

Which framework is best for Microservices?

More flexibility and scalability through microservices

The basic idea behind a microservice architecture is that applications are easier to create and maintain when they are broken down into small, seamless pieces. The software functionality is isolated in several independent modules. These are individually responsible for the execution of precisely defined independent tasks.

The modules communicate with each other via simple, universally accessible application programming interfaces (Apis). Each microservice can use a different programming language or database, so that new technologies can be tried and integrated at any time. In addition, the code blocks can also be used to expand legacy systems without having to make any major changes to their code base.

Thus, companies gain many times more flexibility through microservices. You can react faster and more purposefully to changes, try new things and save resources. Since the individual components are isolated from each other, each function can be designed in such a way that it is oriented to the company-specific requirements and capacities.

Which tool is used to monitor Microservices?

This makes it possible to scale much more accurately and efficiently. For example, if you want to add a new functionality to an application, you don’t have to convert the entire application. This procedure is not only faster, it also provides more stability in the application.

If a new software component does not work properly or fails, only this single, relatively simple microservice is affected - not the entire application. Thus, the company can afford to experiment with new processes or algorithms without being able to lose much.

Microservices make troubleshooting easier

With monolithic architectures, developers often face the problem that all functions and extensions build on the same base code. Different teams work independently on certain functions and tasks, but it is inevitable that they will constantly change parts of the common code. Each change also always affects at least one neighbor team.

In a microservice architecture, this problem does not exist. Each development team is responsible for a certain number of microservices, sometimes only for a single microservice. The code blocks are interconnected by Apis, but do not share a common base code. In this way, the individual teams can act more freely, but bear greater responsibility for their functions.

Features of Microservices Automated Monitoring?

In addition, it is possible to form smaller development teams that are very flexible in their area of responsibility and can fully concentrate on the microservices assigned to them. This increases the productivity.

Newly added developers can be integrated faster, because it is easier to understand small, isolated functionalities than an entire monolithic application. The increased productivity also affects the troubleshooting: It is easier to monitor smaller structures and fix bugs quickly.

Container vs Serverless approaches

For many developers, containers are the predestined architecture for microservices, with docker containers in particular prevailing. They are usually constructed in such a way that several containers together form an application. However, anyone who deals with the topic cannot ignore Kubernetes - the open source system is considered the new standard for container orchestration. Renowned public cloud providers such as Google, AWS and Azure use Kubernetes effectively. On-premise solutions such as Openshift also rely on the orchestration solution.

However, microservices can also be used without containers

The serverless approach AWS Lambda from Amazon allows the deployment of individual written functions in Java, Javascript and Python (Function-as-a-Service). Which solution is the more useful depends on the available resources, the requirements for the application and the required security standards.

Complexity in Microservice Architectures

But a microservice architecture also brings challenges. While smaller code blocks are easier for developers to understand and manage, the applications themselves are built up of many more components - and these components have more connections. These dependencies increase the overall complexity of the application, which can lead to problems.

A special focus should be placed on 

Application Performance Monitoring (APM). As so many moving parts play a role in a single transaction and every millisecond delay can affect ease of use, troubleshooting performance issues is becoming more complex than ever.

Close monitoring helps

To quickly identify and fix problems and errors, it is necessary to closely monitor the microservice architecture. A comprehensive overview of the entire structure as well as deep insights into all commands and transactions is based on three pillars:

• monitoring the relationship between the applications and the infrastructure in which they are running;

• Monitoring of the application architecture: how the various components are connected and
• Track individual transactions to detect errors.

Overview of hosts, applications and their connections

Infrastructure and applications are inextricably linked and influence each other. Ideally, the monitoring tool used displays the performance data in real time in a view. This allows connections to be quickly detected and major failures to be avoided.

In addition, it is necessary to monitor the connections between the individual instances and their general state. Again, ideally, these metrics are monitored in a direct context. This makes it easier to identify the cause of a problem in an emergency. In addition, one should always keep an eye on upstream and downstream applications: Has the problem possibly taken its origin in an upstream application? Or does it affect downstream services?

Distributed tracing for monitoring across all services

At the code level, traces help to see where performance issues arise in a transaction. This tracking is all about accuracy - and the ability to gain deep insight into the trace details.

Traces use automatic instrumentation at the code level to illuminate the relationships between the code, performance and occurring errors. Distributed tracing continues this technique adapted to microservice architectures. In an architecture based on microservices, where a request goes through many different services until a complete page is displayed to the user, this approach is essential.

Microservice Monitoring is Typically done with Three Approaches

A distributed trace provides information about all services, data storage and other components involved in a request. In this way, one gains a comprehensive understanding of the relationships of all involved processes, how long they last and how they depend on each other.

The true strength of distributed tracing is that traces can be tracked across services, containers or applications. This is a great advantage, especially for microservices that are hosted externally. Especially with AWS Lambda, for example, the difficulty is that development teams have too little insight into what is really happening in the lambda function and what dependence such a function has on other native services. With the help of distributed tracing, developer teams can also bring light into this "black box".

Every service failure costs time and money

Microservices provide development teams with exactly what they need in the business world of digitalization and disruption: speed, scalability, flexibility, productivity and reliability of applications. But microservice-based structures bring a high degree of complexity.

The challenge for developers is to cope with this complexity through end-to-end monitoring with meaningful analyses. They show the developer teams where problems exist or where processes can be improved. Every failure of a service costs time, money and sometimes customer trust. Therefore, it makes sense to invest in the speed, flexibility and reliability of microservice architectures and their stringent maintenance.
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