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Microservices Architecture: Challenges with Managing and Deploying

The trend of transitioning from monolithic applications to microservices is gaining momentum, with many technology leaders embarking on this modernization initiative.

Microservices represent a software development approach where applications are divided into smaller, autonomous components.

This style of architecture has become popular among businesses all over the world, especially those that want to speed up the delivery process and increase the rate of deployment. Microservices offer several benefits, including improved resilience, faster delivery, enhanced scalability, and quicker time-to-market. Microservices are becoming a big deal in the software development industry because of the growing need for more flexible, scalable, and reliable software applications.

While microservices offer many benefits, they also come with several challenges that can make managing and deploying them difficult. In this blog, we are going to explore the problems that arise when deploying these independent services to production.

Challenges of Managing and Deploying Microservices Architecture

When you deploy a monolithic application, you run multiple copies of a single, usually large application that are all the same. Most of the time, you set up N physical or virtual servers and run M copies of the application on each one. Putting a monolithic application into use isn't always easy, but it's much easier than putting a microservices application into use.

A microservices application consists of hundreds or even thousands of services. They’re written in a variety of languages and frameworks. Each one is like a small application that has its own deployment, resource, scaling, and monitoring needs.

Challenges with Managing Microservices
Challenges with Managing Microservices

Even more difficult is that services must be deployed quickly, reliably, and at a low cost, even though they are complicated. Managing and deploying microservices can be hard for teams of different sizes in different ways, depending on how well the microservice boundaries are set and how well the inter-service dependencies are set.

Let’s look at some of the most common problems that teams encounter when managing their multi-repo architecture.

a) Service Discovery

Working on a microservices application requires you to manage service instances with dynamic locations. Depending on things like auto-scaling, service upgrades, and failures, it may be necessary to make changes to these instances while they are running. In such a case, these instances' dependent services must be informed.

Suppose you are developing code that invokes a REST API service. To make a request, the code requires the IP address and port of the service instance.

In a microservices architecture, the number of instances will vary, and their locations will not be specified in a configuration file. Therefore, it is difficult to determine the number of services at a given time.

Complex web of interconnected services
Complex web of interconnected services

In a cloud-based microservices environment, where network locations are assigned on the fly, service discovery is needed to find service instances in those locations.

One way to tackle this challenge is by using a service registry that keeps track of all the available services in the system. For instance, microservices-based applications frequently use Netflix's Eureka as a service registry.

b) Monitoring and Observability

Services in a multi-repo system communicate with each other in order to serve the business purpose they’re entitled to do. The calls between services can penetrate deep through many layers, making it hard to understand how they depend on each other. In such a situation, monitoring and observability are required. They both, when combined, work as a proactive approach and an aid while doing RCA.

But in a microservices architecture, it can be challenging to monitor and observe the entire system effectively. In a traditional monolithic application, monitoring can be done at the application level. However, in a microservices-based application, monitoring needs to be done at the service level. Each microservice needs to be monitored independently, and the data collected needs to be aggregated to provide a holistic view of the system, which can be challenging.

In 2019, Amazon experienced a major outage in their AWS Elastic Load Balancer service. The issue was caused by a problem with the monitoring system, which failed to detect the issue in time, leading to a prolonged outage.

To monitor and observe microservices effectively, organizations need to use specialized monitoring tools that can provide real-time insights into the entire system's health. These tools need to be able to handle the large volume of data generated by the system and be able to correlate events across different services.

  • Every service/ component/ server should be monitored.

  • Suppose a service talks to 7 other services before giving out a response, so tracing the complete path it followed becomes super critical to monitor and log to know the root cause of failure.

c) Scalability

Switching to microservices makes it possible to scale in a big way, but that makes it harder to manage them. Rightly allocating resources and the ability to scale up or scale down when in demand put forward a major concern.

Rather than managing a single application running on a single server, or spread across several servers with load-balancing, the current scenario involves managing various application components written in different programming languages, operating on diverse hardware, running on separate virtualization hypervisors, and deployed across multiple on-premise and cloud locations. To handle increased demand for the application, it's essential to coordinate all underlying components to scale, or identify which components need to be scaled.

There might be scenarios where a service is heavily loaded with traffic and needs to be scaled up in order to match the increased demand. It is even more crucial to make sure that the entire system remains responsive and resilient during the scaling process.

  • Fault Tolerance

Each microservice is designed to perform a specific function and communicates with other microservices to deliver the final product or service. In a poorly designed microservices infrastructure, any failure or disruption in one microservice can affect the entire system's performance, leading to downtime, errors, or data loss.

d) Testing

Testing becomes super complex when it comes to microservices. Each service needs to be tested individually, and there needs to be a way to test the interactions between services. Microservices architecture is designed to allow continuous integration and deployment, which means that updates are frequently made to the system. This can also make it difficult to test and secure the system as a whole because changes are constantly being made.

One common way to test microservices is to use contract testing, which involves using predefined contracts to test how the services interact with each other. HyperTest is a popular tool that follows contract testing framework to test microservices-based applications.

HyperTest's dashboard showing test results
HyperTest's dashboard showing test results

Additionally, testing needs to be automated, and it needs to be done continuously to ensure that the system is functioning correctly. Since rapid development is inherent to microservices, teams must test each service separately and in conjunction, to evaluate the overall stability and quality of such distributed systems.

e) Security

Each service needs to be secured individually, and the communication between services needs to be secure. Additionally, there needs to be a centralized way to manage access control and authentication across all services.

According to a survey conducted by NGINX, security is one of the biggest challenges that organizations face when deploying microservices.

One popular approach to securing microservices is using API gateways, which act as a proxy between the client and the microservices. API gateways can perform authentication and authorization checks, as well as rate limiting and traffic management. Kong is a popular API gateway that can be used to secure microservices-based applications.


To effectively handle these challenges, organizations must adopt appropriate strategies, tools, and processes. This includes implementing automation, containerization, and continuous integration and deployment (CI/CD) practices.

Additionally, it is essential to have a strong collaboration between teams, as well as comprehensive testing and monitoring procedures. With careful planning and execution, microservices architecture can help organizations achieve their goals of faster delivery, better scalability, and improved customer experiences.

We have compiled extensive research into one of our whitepaper, titled "Testing Microservices,” to address this significant obstacle presented by microservices. Check it out to learn the tried-and-true method that firms like Atlassian, SoundCloud, and others have used to solve this issue.


What is Microservices Architecture?

Microservices architecture is a way of building software where you break it into tiny, separate pieces, like building with Lego blocks. Each piece does a specific task and can talk to the others. It makes software more flexible and easier to change or add to because you can work on one piece without messing up the whole thing.

Why use microservices?

What are the benefits of Microservices Architecture?

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