In the world of software development, one single application can’t handle all the load and even if it does, it’s harder to maintain and can be slower to update. To make this easy, having the apps broken down into smaller parts is needed, which is the new way of building applications, and this led to the microservices development.

However, microservices tools are the most important aspect that can help the complexities of the system run smoothly.

Microservices Testing Tools

Testing in microservices is crucial because every service interacts with others, and a single issue can affect the whole system. To ensure reliability, testing tools help validate APIs, check integrations, and perform performance and contract testing. These are an essential part of any DevOps managed services strategy.

Popular tools include:

• Postman – This microservices tool is perfect for API testing, automation, and contract validation between services.
• JUnit / TestNG – Widely used for unit and integration testing in Java-based microservices.
• Karate – Combines API testing, performance testing, and mocking in a single lightweight framework.
• WireMock – Great for mocking dependencies, letting you test microservices in isolation.

Together, these tools ensure that each microservice is independently tested, reliable, and performs well when integrated into the larger ecosystem- such a process which many microservices consulting services teams specialize in.

Development Tools 

Spring Boot

Spring Boot excels in microservices development by reducing the need for complex setup. It simplifies the development of production-ready applications by automatically configuring the application based on the libraries in your project. And this is something every DevOps development company value when accelerating delivery pipelines. This feature makes it easy for developers to avoid having to manually configure every component.

The latest Spring Boot 3.5.7 release (October 2025) continues to enhance stability and operational performance. It includes 69 bug fixes, documentation improvements, and dependency upgrades, showcasing the project’s commitment to polish and reliability. As the final minor release in the 3.x series, Spring Boot 3.5 focuses on operational refinement, improved observability, configuration management, and better control over production environments, preparing applications for the upcoming 4.x generation.

Spring Boot includes several out-of-the-box features like health checks, metrics, and application monitoring via Spring Boot Actuator. Maintaining applications becomes easier with minimal setup, as Spring Boot provides production-grade features that integrate seamlessly with monitoring and DevOps tools.

Visual Studio Code 

A popular versatile code editor of 2025, perfect for microservices development. It’s lightweight and powerful, which is ideal for quick editing and daily coding tasks. What makes it so unique? Having a minimalistic size, it can support powerful features that rival full-fledged IDEs, such as intelligent code completion, debugging, and version control integration. And another advantage of this microservices tool is tailoring the VS Code to your exact needs. Working in Python, JavaScript, C++, or even niche languages, there’s an extension that will make development easier. 

It’s compatible with popular frameworks like React, Angular, and Vue for frontend, and Express, Flask, and Django for back end. its integration capabilities with microservices tools like Kubernetes, Docker, and Istio, and connects to cloud services like AWS, Azure, and Google Cloud. 

Why bother setting up a complex local development environment when you can just SSH into the cloud and code directly on your server or container? With its remote development features like Remote SSH, why not skip the hassle of managing local setups and deploy your code straight to the cloud? 

Golang 

It is a preferred language for microservices development and being a modern programming language, it is often the choice for building scalable, high-performance applications, particularly in cloud computing and microservices. This microservice tool has a clean syntax, it’s simple and easy to understand. Focusing on simplicity, Go eliminates complex features like inheritance, method overloading, and generics. 

Go is ideal for teams and new developers with its minimalist approach, solely focusing on solving problems rather than learning the intricacies of the language.

Go compiles directly to machine code, which when combined with its statically typed system, results in ultra-fast program execution. Also, Go’s garbage collector takes care of memory like a pro that is quietly cleaning up after you, without causing any lag or slowdowns. Now you know why your app is performing high! 

It is widely used for building web APIs and backend services. Furthermore, Uber uses Go to power parts of its high-performance microservices architecture. 

While Go remains a top choice for building scalable cloud-native services, recent industry trends show that its adoption has stabilized. Many organizations continue to rely on Go for infrastructure and backend systems, even as Java, .NET, and Node.js remain popular alternatives for microservices development.

Messaging and Communication Tools 

RabbitMQ 

It’s the most popular message broker used in modern distributed systems. Message queuing is a unique feature of this Microservices tool, this is a powerful mechanism that ensures messages are reliably sent, received, and processed asynchronously, without the need for services to be directly connected or to wait for each other.

RabbitMQ’s support for multiple protocols is particularly valuable in microservices development which allows it to integrate with various systems and devices, from traditional enterprise applications to Internet of Things (IoT) devices. It supports both internal and external security measures, so it’s suited for data integrity and confidentiality are important. 

It is used for real-time communication systems like chat applications, live notifications, and streaming updates. It’s capable of handling many-to-many communication as it supports publish-subscribe (via fanout exchanges) and message routing. 

While RabbitMQ remains a reliable message broker, teams today often choose between RabbitMQ and Kafka depending on whether they need message queuing or stream processing. Additionally, newer brokers like Redis Streams and NATS are being adopted for lightweight, event-driven microservices.

Apache Kafka 

In the microservices ecosystem, both RabbitMQ and Kafka play vital but distinct roles. While RabbitMQ excels at traditional message queuing, Kafka shines in large-scale event streaming and data processing scenarios.

Developers also now explore newer messaging technologies like Redis Streams, NATS, or Apache Pulsar to meet specialized requirements in lightweight and cloud-native deployments.

It is a distributed streaming platform as well as a message broker which makes it an essential microservices tool to handle real-time data feeds. It has the ability to manage huge streams of data that have low latency. For data pipelines, event sourcing, and fault-tolerant systems—Kafka is reliable highly. 

This tool can easily handle increased load as it is designed as a distributed system. Surprisingly it can store and process trillions of events per day while maintaining performance. It offers high durability and Fault Tolerance, so messages aren’t lost, even if a node crashes. 

Kafka provides exactly one semantics which is critical for systems like financial transactions where duplicate message processing could result in inconsistent data or errors. 

In retail, banking, or e-commerce, companies use Kafka to stream real-time transactional data for analytics. So that makes Kafka a key technology in microservice development in these industries. Monitoring website traffic and purchasing patterns in real-time to generate personalized recommendations or detect fraudulent activities. 

Monitoring and Observability Tools 

Grafana 

Turn raw data into beautiful, actionable insights with Grafana, it’s a powerful open-source platform for data visualization, monitoring, and alerting. With its customizable dashboards, you can visualize multiple data sources in a single view. It acts as a centralized hub where you can pull in data from a wide variety of sources, giving you a comprehensive view of your infrastructure, applications, and services without needing to switch between different tools. 

In microservice development, Grafana’s alerting capabilities are based on custom thresholds and conditions with which you can set up automated alerts to stay ahead of potential issues. One of its features Grafana Loki for Logs, logs provides contextual troubleshooting to pinpoint the root cause of issues quickly. This lets you focus on upgrading the application’s uptime. 

Datadog 

The ultimate monitoring and analytics platform for cloud infrastructure and applications! It is an industry-leading cloud-scale monitoring and analytics platform. One of its outstanding features is unified monitoring for the entire stack, including cloud infrastructure, containers, microservices, and serverless applications. This all-in-one approach lets you monitor everything from one place. 

For microservice tools, Datadog provides real-time dashboards that give you immediate visibility into system performance. Datadog’s APM is your app’s personal detective that lets you zoom in on your app’s performance, from the backend to the frontend. It helps to uncover the bottlenecks that are slowing things down.

Datadog’s 400+ integrations make connecting to services like AWS, GCP, and Docker as easy as clicking “install.” You can simply skip the custom setup and get straight to monitoring like a pro. 

The popular microservices tools that are used for monitoring include Grafana, Datadog, and Prometheus often combined with tracing tools such as OpenTelemetry and Jaeger to achieve full-stack observability.

Prometheus 

An open-source monitoring and alerting toolkit where users can store rich metadata with the metrics, thanks to its multi-dimensional data model. In microservices environments, Prometheus becomes a key component of the monitoring stack.

PromQL (Prometheus Query Language) enables complex operations like calculating averages, rates, and percentiles, and even combining multiple metrics into a single query result. With built-in alerting, Prometheus defines custom rules based on metrics; that includes triggering alerts when conditions like high error rates or resource spikes occur.

Expanding Observability: OpenTelemetry and Jaeger

Beyond metrics and logs, distributed tracing has become a crucial observability pillar in 2025. Tools like OpenTelemetry and Jaeger track how requests flow across multiple microservices, helping teams detect latency, dependency failures, and performance bottlenecks.
Modern observability stacks often integrate Prometheus, Grafana, and Datadog with OpenTelemetry for end-to-end visibility—offering a unified view across logs, metrics, and traces to ensure microservices run smoothly and efficiently.

Microservices Orchestration Tools

Kubernetes

The undisputed leader in orchestration, Kubernetes automates container deployment, scaling, and management. Its declarative configuration model and self-healing capabilities make it ideal for running complex microservices at scale. Even if containers fail, new ones spin up automatically, keeping the system running smoothly.

It also supports service discovery, load balancing, and rolling updates. Developers can release new versions without downtime. Modern microservice architectures often combine Kubernetes with CI/CD pipelines for continuous deployment and with service meshes like Istio for fine-grained control.

Docker Swarm

While simpler than Kubernetes, Docker Swarm offers native container orchestration directly integrated into Docker. It’s ideal for teams looking for a lightweight and straightforward setup that supports clustering, scaling, and load balancing out of the box. Swarm uses the same Docker CLI and API, making it easier for teams transitioning from local development to production orchestration.

Microservices Governance Tools

Kong Enterprise

Kong is more than just an API Gateway, its enterprise edition introduces policy enforcement, authentication, and rate-limiting features essential for API governance. It integrates with CI/CD pipelines and offers analytics dashboards for API usage, helping organizations manage thousands of microservices efficiently.

Apigee

Google’s Apigee provides comprehensive API lifecycle management from design and deployment to security and analytics. It supports OAuth, quota management, and traffic shaping to keep APIs safe and performant. In large enterprises, Apigee is key for maintaining governance across global microservice deployments.

Microservices Tracing Tools

OpenTelemetry

OpenTelemetry is an open-source observability framework that standardizes how you collect traces, metrics, and logs from distributed systems. It acts as the foundation for monitoring and debugging microservices by exporting telemetry data to platforms like Grafana, Datadog, or Jaeger.
By integrating OpenTelemetry, teams get consistent and vendor-neutral observability.

Jaeger

Developed by Uber, Jaeger specializes in distributed tracing, helping identify bottlenecks, latencies, and failures across service calls. It visualizes trace paths end-to-end, showing exactly where requests slow down. Together with Prometheus and Grafana, Jaeger forms a complete observability stack for microservice-based architectures.

Microservices Architecture Tools

Architectural tools help design, visualize, and manage complex service dependencies, ensuring scalability and maintainability from the start.

ArchUnit

A lightweight testing library for Java that enforces architectural rules. It ensures developers adhere to defined boundaries, preventing unintended dependencies or architectural drift — a common challenge in large microservice systems.

Structurizr

Created by Simon Brown, Structurizr helps teams visualize their software architecture using the C4 model. It bridges the gap between design and implementation, making it easy to communicate service interactions, infrastructure layouts, and deployment patterns clearly.

AWS Well-Architected Tool

Offered by AWS, this tool evaluates your cloud-based microservice architecture against best practices in performance, reliability, and security. It gives actionable insights to ensure each microservice is designed for long-term scalability and operational efficiency.

Microservices Testing Tools List (2025 Quick Reference)

Here’s a consolidated list of popular tools in 2025, organized by purpose:

Emerging and Supporting Tools in Modern Microservices (2025 and beyond)

As microservices continue to evolve, organizations are moving beyond traditional development and monitoring tools. The focus now includes service connectivity, API management, automation, and intelligent operations. Below are some of the emerging categories and tools shaping microservices ecosystems in 2025.

Then list concise items:

• Service Mesh (Istio, Linkerd): Automates secure service-to-service communication, observability, and traffic control within Kubernetes clusters.
• API Gateways (Kong, Spring Cloud Gateway): Manage, route, and secure external and internal API calls between microservices.
• Tracing and Observability (OpenTelemetry, Jaeger): Provide distributed tracing and deep visibility into requests flowing across microservices.
• Serverless and Event-Driven Architectures (AWS Lambda, Google Cloud Functions, Knative): Enable teams to build lightweight, on-demand microservices that scale automatically.
• AI/Ops and Intelligent Monitoring (New Relic AI, Dynatrace Davis AI): Use machine learning to predict performance bottlenecks and automate issue resolution.

Final Thoughts

In conclusion, how do you create apps that thrive under pressure? By using the best microservices tools for the job! These tools not only simplify development but also improve monitoring, troubleshooting, and scalability across microservices architectures. Whether you are looking to streamline deployment, monitor system health, or optimize performance, the right tools can make all the difference. At DevOps Experts India, offer expert services to help you leverage these top microservices tools and take your development process to the next level. So why not make the obvious choice and consider the best?

FAQs

1. Which tool is used for microservices?

There isn’t just one different tool that serves different stages of the microservices lifecycle. The right choice depends on your tech stack, scalability needs, and infrastructure.

For development, Spring Boot, Golang, and Visual Studio Code are widely used.
For orchestration, Kubernetes and Docker Swarm manage and scale containers.
For monitoring and observability, Prometheus, Grafana, Datadog, and Open Telemetry are the most popular.
For communication, RabbitMQ and Kafka handle messaging between services.

2. Is Jira a microservice?

No, Jira is not a microservice. It’s a project management and issue-tracking tool built using a microservice-like architecture in its modern versions. But Jira can be used alongside microservice tools to manage development tasks, monitor progress, and track bugs or deployments across distributed teams.

3. What are the 3 C’s microservices?

The 3 C’s of microservices stand for:

Componentization – Breaking applications into independent, reusable services.
Continuous Delivery – Automating builds, tests, and deployments for faster releases.
Collaboration – Enabling DevOps teams to work together seamlessly across the microservice lifecycle.
These three pillars ensure microservices remain scalable, maintainable, and agile.

4. Can a REST API be a microservice?

A REST API can be part of a microservice, but it isn’t a microservice by itself.
A microservice is a complete, independently deployable unit that owns its data and business logic, it often exposes its functionality through a REST API. So, while REST is a common communication style in microservices, the service itself includes much more such as code, database, logic, and infrastructure.