Microservices Architecture: Tools, Challenges, And How to Mitigate Them
- Pratichha S.
- Jul 19
- 7 min read
Microservices Architecture: Overview
MSA or Microservices Architecture is an approach to software development that functions by breaking down a robust and complex application into a group of small and autonomous services. These services interact with one another using well-defined interfaces. In recent years, microservices architecture has witnessed a consistent increase in its usage due to the benefits over conventional monolithic architecture (opengroup, 2023).
Some of its benefits include agility, reliability, scalability, faster project development, and flexibility. However, MSA also comes with some significant risks and challenges. These include latency, monitoring, testing, complexity, cost, and security.
Therefore, it is essential to do careful planning and give significant consideration to the organizational goals and needs before adopting an MSA (MuleSoft, 2016).
Spotify, which is a predominant audio streaming platform worldwide, has adopted MSA to do away with the challenges posed by its monolithic application. You can read this exclusive Spotify MSA case study here.
Differences between Service-Oriented Architecture vs Microservices Architecture
Service-oriented architecture vs Microservices Architecture are widely used architectural models for building modular software systems. Although both aim to break down applications into manageable services, they differ in how services are structured, deployed, and maintained (AWS, 2025).
Parameter | Microservices Architecture (MSA) | Service-Oriented Architecture (SOA) |
Scope | Microservices focus on narrow, business-specific tasks and operate independently. | SOA targets broader enterprise functions with shared service components. |
Implementation | Each microservice is developed, deployed, and managed as a separate unit. | SOA integrates multiple services through a centralized enterprise service bus. |
Communication | Microservices communicate through lightweight APIs such as REST or publish-subscribe methods. | SOA uses a centralized messaging system like SOAP or AMQP for service interaction. |
Data Storage | Each microservice has its own data store, supporting complete data independence. | SOA services use a shared data layer that promotes reusability across systems. |
Deployment | Microservices are easy to deploy on cloud platforms using containerization and automation tools. | SOA deployment is more complex due to tightly coupled services and less flexibility. |
Reusability | Microservices prioritize independence over component sharing, with less emphasis on reuse. | SOA promotes sharing of components and services across multiple applications. |
Speed | Microservices offer faster performance by allocating resources individually without contention. | SOA may face latency issues as services compete for shared communication resources. |
Governance | Microservices allow teams to define their own rules for data management and service behavior. | SOA uses centralized governance and shared data policies across the system. |
Best Use Case | Microservices work best for cloud-native apps and agile environments requiring rapid scaling. | SOA is more suitable for integrating legacy systems and enterprise-wide service reuse. |
Tools for Microservices, Description, and License
In a service-oriented architecture, choosing the right tools for microservices is crucial for managing containerization, orchestration, and API communication. These microservices tools simplify deployment, scaling, and monitoring while supporting enterprise-grade service architecture. Below is a categorized overview of popular microservices tools, along with their license types and brief descriptions (Swimm, 2024).
Tool Category | Name | License | Short Description |
Containerization and Orchestration | Docker | Apache-2.0 | Enables packaging of applications into containers, supports deployment and scaling. |
Kubernetes | Apache-2.0 | Apache-2.0 | Manages containerized applications with automated deployment and scaling. |
OpenShift | Apache-2.0 | Apache-2.0 | Kubernetes-based platform with developer tools and CI/CD pipeline integration. |
Nomad | Business Source License | Business Source License | Lightweight orchestrator for both containerized and legacy workloads. |
API Gateways and Management | Kong | Apache-2.0 | Scalable API gateway with routing, rate limiting, and plugin extensibility. |
NGINX | BSD-2-Clause | BSD-2-Clause | High-performance reverse proxy and load balancer with flexible routing. |
AWS API Gateway | Apache-2.0 | Apache-2.0 | Fully managed AWS service for building, deploying, and managing secure APIs at scale. |
Service Mesh | Istio | Apache-2.0 | Enables secure service-to-service communication with observability, retries, and traffic management. |
Linkerd | Apache-2.0 | Apache-2.0 | Lightweight and Kubernetes-native mesh focused on security and real-time observability with minimal overhead. |
Consul Connect | Business Source License | Business Source License | Offers service mesh with service discovery, segmentation, and secure communication, integrates with Nomad and Kubernetes. |
Documentation and Collaboration | Swimm | Commercial | Auto-generates and updates documentation within the developer workflow for legacy codebases. |
Confluence | Commercial | Commercial | Atlassian's platform for centralized documentation, team collaboration, and integration with JIRA. |
Notion | MIT | MIT | All-in-one workspace for docs, tasks, and team collaboration with database and Kanban support. |
Distributed Tracing and Monitoring | Jaeger | Apache-2.0 | Distributed tracing tool to troubleshoot performance and latency issues in microservices. |
Prometheus | Apache-2.0 | Apache-2.0 | Time-series monitoring system with alerting, used widely in microservice environments and integrates with Grafana. |
Grafana | AGPL-3.0 | AGPL-3.0 | Visualization and dashboard tool that supports real-time monitoring from multiple data sources. |
Zipkin | Apache-2.0 | Apache-2.0 | Distributed tracing system that provides detailed views of call paths and tracks request flows across services. |
Service Discovery | Etcd | Apache-2.0 | Distributed key-value store used in Kubernetes for cluster state, service discovery, and configuration consistency. |
Eureka | Apache-2.0 | Apache-2.0 | Netflix’s tool for dynamic service registration and discovery, used in Spring Cloud environments. |
Zookeeper | Apache-2.0 | Apache-2.0 | Centralized service for configuration management and service discovery in distributed systems. |
CI/CD Pipeline | Jenkins | MIT | Open-source automation server for continuous integration and delivery with a large plugin ecosystem. |
Configuration Management | Ansible | GPL-3.0 | Agentless automation tool that manages configurations via YAML playbooks across distributed environments. |
Spring Cloud Config | Apache-2.0 | Apache-2.0 | Manages external configuration for distributed systems, enabling updates from a centralized config source. |
Logging and Log Management | ELK Stack | MIT | Combines Elasticsearch, Logstash, and Kibana to visualize and manage large-scale logs in real-time. |
Fluentd | Apache-2.0 | Apache-2.0 | Unifies log data from various sources and forwards them to storage or analysis systems like ELK. |
Loki | Apache-2.0 | Apache-2.0 | Log aggregation system designed to work with Grafana, optimized for storing and querying logs from Kubernetes environments. |
Security and Authentication | OAuth2 | BSD-3-Clause | Framework for secure, token-based authorization; supports token-based authentication. |
Keycloak | Apache-2.0 | Apache-2.0 | Open-source identity and access management tool with SSO, OAuth2, and RBAC support. |
HashiCorp Vault | MPL-2.0 | MPL-2.0 | Manages secrets, access, and encryption keys to secure sensitive data. |
Testing Tools | Postman | Apache-2.0 | API testing tool for sending requests, debugging, and automating REST API tests. |
WireMock | Apache-2.0 | Apache-2.0 | API mocking tool to simulate external APIs; ideal for isolated microservice testing. |
JUnit | EPL-2.0 | EPL-2.0 | Unit testing framework for Java, ideal for TDD with support for assertions and suites. |
Challenges of Adopting MSA as a Software Development Philosophy and How to Mitigate Them
Despite the various benefits mentioned above, adopting MSA as a software development philosophy also poses some significant challenges and risks. These include:
Monitoring Risk
With MSA, it becomes pretty challenging to monitor the system. This is because the system tends to have thousands of instances operating at the same time. Each of these instances tends to have its own metrics and logs.
Resolution: To mitigate this issue, the company must have a reliable and robust monitoring system. As a result, it will be able to gather, analyze, and aggregate data from all the modules or services, besides offering a holistic view of the health and performance of the system (Hámori, 2016).
Latency Risk
MSA tends to increase the latency of a system. This is because there is no single calling process under this architecture. Instead, a company needs to call or communicate with several other services. These additional services then call more services. As a result of each of these calls, the latency of the system keeps increasing.
Resolution: For this, it is essential for a company to leverage the interaction between its services and lessen the number of calls as much as it can (Hámori, 2016).
Complexity Risk
The embracing of MSA tends to increase the level of complexity of the system. This is because the system is now composed of multiple autonomous components that are required to be coordinated and managed. Consequently, it becomes more difficult to grasp the overall structure of the application and to troubleshoot problems that may emerge.
Resolution: To mitigate this issue, a company needs to prepare consistent and clear standards and guidelines to develop, test, deploy, and document microservices. Besides that, the organization also needs to create a good governance model that is well-equipped to delimit the roles and responsibilities of various teams and ensure alignment with the goals of the organization (Solo.io, 2023).
Testing Risk
With MSA, it is more difficult to test and deploy the services in comparison to monolithic applications. This is because each microservice has to be evaluated and deployed separately.
Resolution: To mitigate this issue, a company needs to ensure that it employs a more consistent and comprehensive testing strategy that can cover various levels of testing. These testing levels include unit, contract, integration, and end-to-end. Besides that, the companies also need to use a good stubbing and mocking framework that has the capability to simulate other services’ behaviour without depending on them (Solo.io, 2023).
Security Risk
Protecting an application based on MSA is far more challenging than securing a monolithic application. This is because the former entails securing multiple elements and their interactions, besides ensuring that they comply with relevant standards and regulations.
Resolution: To mitigate this issue, companies need to employ a robust and secure authorization and authentication mechanism that will possess the capability to protect access and communication between various services. Besides that, companies need to make sure that they use a reliable and robust encryption and decryption system so that it is able to secure the data that is at rest or in transit (Solo.io, 2023).
Why Would You Opt for a Microservices Architecture
You, as a business or organization, might opt for MSA when you need to scale components independently, deploy features rapidly, or ensure strong fault isolation. It is especially useful if your system requires flexibility to use different technologies across services. However, it is best suited for growing applications, as smaller projects may benefit from starting with a monolith before transitioning (Kong, 2024).
References
Hámori, F. (2016, February 23). How Enterprises Benefit From Microservices Architectures. RisingStack Engineering. https://blog.risingstack.com/how-enterprises-benefit-from-microservices-architectures/
MuleSoft. (2016, October 13). Spotify Composes Application Network with MuleSoft’s Anypoint Platform. MuleSoft. https://www.mulesoft.com/press-center/spotify-devops-microservices
opengroup. (2023). Microservices Architecture – What is a Microservices Architecture? Www.opengroup.org. https://www.opengroup.org/soa/source-book/msawp/p2.htm
Solo.io. (2023). What Are Microservices? Architecture, Challenges, and Tips. Solo.io. https://www.solo.io/topics/microservices/#:~:text=Testing%20and%20deployment%3A%20With%20microservices%2C%20it%20can%20be
Spotify. (2023). Spotify — Innovation. Spotify. https://newsroom.spotify.com/linernotes-innovation/
Stackify. (2019, November 14). 6 Key Benefits of Microservices Architecture. Stackify. https://stackify.com/6-key-benefits-of-microservices-architecture/
AWS. (2025). SOA vs Microservices - Difference Between Architectural Styles - AWS. Amazon Web Services, Inc. https://aws.amazon.com/compare/the-difference-between-soa-microservices/
Kong. (2024, December 4). What are Microservices? Examples and Benefits. Kong Inc. https://konghq.com/blog/learning-center/what-are-microservices
Swimm. (2024, November 19). Top 36 Microservices Tools for 2025. Swimm. https://swimm.io/learn/microservices/top-36-microservices-tools-for-2025