The possible drawbacks of microservices, a crucial element of cloud-native design, are among the primary causes. Let’s find out 10 disadvantages of Microservices and how to overcome them.

Not everyone is prepared to embrace cloud-native architecture, despite its growing popularity. The possible drawbacks of microservices, a crucial element of cloud-native design, are among the primary causes. Let’s find out 10 disadvantages of Microservices and how to overcome them.

What are the disadvantages of Microservices?

These days, cloud-native architectures that make use of Docker and Kubernetes deployments are becoming more and more popular. Teams that opt for microservices can gain from a number of benefits, such as:

• Microservices give users the freedom to select from a variety of architectures, languages, procedures, and tools.
• They adhere to well-known best practices like event-driven architectures and domain-driven design.
• They facilitate more rapid and flexible product releases.
• Microservices are supported at runtime by technologies like Docker and Kubernetes, which can operate on common hardware.

Nonetheless, application development teams must be aware of microservices’ limits. Before switching from a dependable monolith to several smaller components that carry out the same task, you need to be aware of the difficulties that come with microservices architecture and know how to overcome or adjust to them.

The following categories best describe the main drawbacks of microservices:

• Network topology intricacy.
• Automated deployment is necessary.
• Challenges with dependency management and integration
• Difficulties with compatibility and data translation.
• Network congestion risk.
• Overall decline in performance
• Kinda expensive.
• Testing, monitoring, and auditing complexity
• Debugging and resolving organizational inertia barriers can be challenging.

1. Complexity in Network Topology

The architecture becomes much more complex when a monolithic application is divided into a subset of autonomous microservices that interact with one another via a network.

Consider dividing a monolithic program into ten microservices, for instance. This necessitates upgrading numerous tasks:

• Scalability: Rather than focusing on just one application, you must be able to scale ten.
• Security: Rather than securing one API endpoint, you should secure ten.
• Version control: You now have to oversee ten distinct repositories for every microservice rather than just one Git repository.
• Construct: Rather than building one package, you should construct ten.
• Deployment: You must deploy ten distinct artifacts rather than a single application.

It goes without saying that managing several smaller programs is more difficult than managing a single, monolithic one. One of the primary drawbacks of microservices design is its complexity.

2. Automated deployment is necessary

Large-scale online applications can benefit greatly from microservices architecture, but testing, deployment, and maintenance can be challenging. Due to the enormous number of services in enterprise-grade systems, automation is necessary because manual installation is not practical.

Businesses implementing microservices architecture must incorporate automation tools like Terraform, Jenkins, and GitHub. Employees must also possess strong scripting abilities.

It takes a substantial time and resource commitment to implement automation consistently and thoroughly. However, in order for businesses to benefit from microservices, this investment is required.

3. Integration and Dependency Management Challenges

It takes a lot of work to standardize data communication between microservices.

Microservices are created separately and set up in separate containers. Standardized JSON or XML file interchange and improved integration of RESTful endpoints are necessary for these separate and autonomous microservices to communicate with one another during runtime.

Integration and Dependency Management Challenges

Additionally, one of the biggest challenges is maintaining dependencies between microservices. Because modifications to one component may have unexpected effects on other components, RESTful endpoints are especially susceptible to attacks.

A monolithic program, on the other hand, does not require a RESTful API or a common data interchange format because its components communicate directly using Java or Python-based APIs. Additionally, at compile time, every interaction is verified.

4. Issues with Data Translation and Interoperability

Although it would be ideal if all microservices used the same protocols and data structures, this is frequently not the case in real-world scenarios. For instance, two separate HTTP protocols may be used by a REST microservice and a gRPC microservice that are attempting to communicate. There is incompatibility as a result.

Using a translation mechanism, such a proxy, is one method to overcome this problem.

Microservices data translation has its own set of difficulties. You may think of this as a postal code in one service and a ZIP code in another.

The issue of translating data context has existed for many years. This issue is lessened by monolithic programs, which keep all of the data in a single database. Microservices architectures, however, make this problem more difficult. One of the biggest challenges when an application has dozens or even hundreds of microservices is providing data translation between them.

5. Risk of Network Congestion

Microservices exchange JSON and XML data via HTTP and communicate through RESTful APIs. Network congestion is frequently caused by the use of microservices, which increases network traffic.

However, private local subnets, where network capacity may be readily expanded, are where the majority of microservices’ communication takes place. However, performance is another drawback of microservices, which is exacerbated by the volume of XML and JSON data on the network.

6. A decline in overall performance

Generally speaking, microservices systems use more resources than monolithic structures of the same size. More memory, CPU cycles, and network bandwidth are needed for microservices.

All of the parts of a monolithic application work together in a single process, and hardware-level interactions take place. Standard methods are used by components to interface with one another, increasing performance overhead. Additionally, because shared data is in memory, components within the same process can access it instantly, lowering latency.

A Comparison of Microservices and Monolithic:

Consider how interactions between microservices differ from those within a monolithic application:

Microservices generate more steps and utilize more network than components “talking” directly in a monolithic, which results in higher expenses and noticeably worse performance. The second drawback of microservices is their cost, which is a result of their performance and resource utilization issues.

7. Expensive

The following will occur when a monolithic application is divided into several microservices:

• Higher overall memory capacity.
• When employing numerous virtual machines or containers, resources are duplicated.
• Usage of bandwidth when contacting RESTful web services.
• More CPU cycles are needed to read, send, process, and put together JSON files.
• These days, businesses must pay for cloud computing services on a pay-per-use basis. Cloud expenses increase when an application uses more CPU or memory.

A major drawback of microservices is that their architecture necessitates more resources than monolithic apps, which raises operating costs.

8. Monitoring’s complexity

Kubernetes clusters, where ephemeral containers supply the microservices required for cloud-native apps to operate, are frequently used for their deployment. However, logging, monitoring, and auditing are quite challenging due to the transient nature of microservices, particularly on multinode networks.

Unless a background daemon process transfers the log data from the container to another dependable storage place, log files will be destroyed instantly whenever a Docker container running a microservice is shut down. Although this problem is lessened by programs like the open-source Fluentd, it is still a worry.

On the other hand, all logging, monitoring, and auditing data are usually stored in a single directory on the server in a monolithic architecture, which frequently includes an integrated log rotation system. The maintenance of logging and monitoring is considerably easier with a monolith.

One of the main disadvantages of microservices designs is the extra work needed to handle log files, trace files, and audit data on a cloud-native cluster.

9. Challenges with Debugging and Troubleshooting

It is as difficult to find and fix issues in a microservices architecture as it is to combine trace and log files. Determining the precise location and cause of a failed request can be challenging when it passes through several microservices housed in different runtime environments. On the other hand, troubleshooting a monolithic application just involves tracking the unsuccessful request’s course across a single server.

Furthermore, it can be difficult to replicate the precise route used by a failed request, particularly in settings where containerized microservices are started and terminated regularly.

Distributed Debugging:

It can be difficult to debug a microservices application. A thorough monitoring strategy is necessary to track a request’s journey across an architecture that could include hundreds of interacting microservices, each running in an own container. Monitoring must offer a thorough understanding of the system, even though logging offers some insight into how microservices operate internally.

Numerous tools, including commercial products like Datadog, Dynatrace, and Wavefront, as well as open source initiatives like Jaeger and Zipkin, are designed to make debugging easier by offering distributed tracing capabilities. A strong monitoring plan is necessary to keep an eye on both internal and external processes in the microservices that comprise the application, regardless of the tool used.

10. Organizational Inertia Obstacles

Overcoming organizational inertia is one of the major obstacles to deploying microservices in a corporation.

Adopting new tools, implementing cutting-edge development techniques, and learning new skills are some of the commitments needed to transition from a monolithic architecture to microservices. Many organizations find it easier to keep their current monolithic system and adhere to current practices when there is no strong argument for adopting “cloud-native” methodologies and reworking them.

Nonetheless, organizational inertia can be overcome by strong arguments. IT may be reluctant to switch from monolithic to microservices if it believes that the drawbacks of microservices exceed the advantages, which is totally fine. Monolithic architectures still have a place in contemporary IT, and not all businesses are prepared for or require a “cloud-native” paradigm.

In conclusion

Increased flexibility, scalability, stability, performance, and less dependencies between application components are just a few of the significant advantages that come with using microservices in web applications. Businesses must, however, also take into account certain difficulties, such as integrating and synchronizing microservices, the expenses of development and operation, and how to handle issues when overburdened.