Top 5 technologies for building a microservices architecture
Microservices are one of the most important software architecture trends of 2020. In a microservices architecture, an application is arranged as a collection of loosely coupled services. Each microservice is a self-contained piece of business functionality with a clear interface. With independently developer components, microservices make an application easier to maintain.
As this technology gains popularity, more and more tools and technologies have emerged to support microservices. So, how do we know which to use?
To help boost your microservices development, I’ve compiled a list of the top 5 technologies for building a microservices architecture.
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Microservice Architecture: Practical Implementation
What to consider before adopting microservices architecture#
Microservices architecture forms the base for products being built at companies like Amazon, Netflix, Spotify, and Uber. When compared with a traditional monolithic application, microservices offer the following benefits:
- Modular: By splitting an application into smaller components, it becomes easier to understand, develop, and test the application.
- Scalable: Since microservices are implemented and deployed independently, they can be monitored and scaled independently.
- Robustness: When a memory leak exists in a microservice, only that microservice is affected. The other microservices keep running.
- Security: Because microservices are isolated, the entire system is not affected by attacks to one microservice.
Note: Microservices can be implemented in different programming languages and might use different infrastructures.
A typical microservice architecture consists of an API or communication gateway, service discovery, the service, and a database or cache.
Despite these benefits, microservices architecture also comes with its own challenges, from implementation to migration and maintenance. Some of the prominent challenges adopting a microservices architecture poses include:
- The operation of a microservice system requires more effort than running a deployment monolith, since many more deployable units exist.
- Since all testing must be done independently, one microservice can block the test stage and prevent the deployment of the other microservices.
- Changes that affect multiple microservices are more difficult to implement than the changes that concern several modules of a deployment monolith.
In the next section, we will go over a simple microservices architecture design and the top technologies that can be used to develop each component in the design.
Docker and Kubernetes#
Docker is a software platform that allows you to build, test, and deploy software as self-contained packages called containers. These Docker containers can be deployed anywhere, and each container contains all the resources and configuration it needs to run.
Kubernetes acts as a complement to Docker, especially at scale. It’s typically used to help tackle some of the operating complexities when moving to scale multiple containers, deployed across multiple servers.
Docker and Kubernetes can be used together to act as a flexible base for your microservices-based system, easily scaling up as the workload increases or vice versa.
Benefits of Docker for Microservices#
Docker is a lightweight option for building a microservices architecture. All components of a microservice can be packed into a Docker image and remain isolated from other microservices.
Docker makes it easy to deploy your software as you only have to distribute Docker images using Dockerfiles.
With Docker Compose, multiple containers can be coordinated to build an entire system of microservices with containers. We can also use Docker Machine to install Docker environments on a server.
Note: Docker requires rethinking regarding operation. So, for some cases, you may need alternative technologies. For example, when deploying several Java web applications on a single Java web server.
REST#
Microservices have to communicate with other microservices. One tool that can be used for this is REST (Representational State Transfer). REST is an architectural design pattern for building RESTful APIs.
REST allows services to communicate directly via HTTP. Requests and responses are handled in standard formats like XML, HTML, or JSON.
REST is a natural choice for most microservices, since many of them are Web Applications. It is possible to upgrade to HTTP/2.0 where necessary, reducing the need for other protocols like gRPC, which is based on ProtocolBuffer and HTTP/2.0.
Benefits of REST for Microservices#
REST is a great tool for building a scalable microservice, since they are stateless and modular. The REST pattern allows the client and the server to be implemented independently without the knowledge of the other entity. This means that code at either side can be modified without effecting each other.
Note: Pact is a great framework for writing tests of a REST interface in a programming language. This results in a JSON file containing the REST requests and the expected responses.
Redis#
Redis is an open source, in-memory data structure store. It is one of the most popular key-value or NoSQL databases. Although it is an in-memory database, it provides support for persisting data, master-replica replication, and it performs well when compared to traditional database systems.
Redis is commonly used as a primary database for your application using Redis in persistent mode. It is also isa single-threaded application so, for databases, you never have to worry about record locks. In this pattern, entities are stored with hash operations. Redis is commonly built on top of the Spring Cloud or Spring Boot frameworks.
Benefits of Redis for Microservices#
As we know, microservices must maintain their own state using a database. Service data should be isolated from other data layers to enable uncoupled scaling. Redis, alongside Redis clustering or Redis Sentinel, fits many of these requirements, including low-latency final response.
Redis can be leveraged by your application in many different ways. Redis is widely used in microservices architecture because it can serve as a cache or as the service’s primary database. Depending on your requirements, Redis can also act as a message broker or cache.
Keep the learning going.#
Learn popular recipes for tech stacks that can be used to implement microservices, as well as the pros and cons of each. By the end of this course, you’ll be an industry-ready, microservice pro.
Prometheus
Prometheus is an open-source systems monitoring and alerting tool originally developed at SoundCloud. It implements a multi-dimensional data model and provides data store and data scrapers. Data is stored as key-value pairs in memory cached files.
Prometheus uses a simple query language that forms the foundation of task monitoring. This includes visualisation features for alters and statistics.
Benefits of Prometheus for Microservices#
For microservices, Prometheus’s support for multi-dimensional data collection and querying is a particular strength. Prometheus also offers an extensible data model, which allows you to attach arbitrary key-values dimensions to a time series.
Prometheus is known for its simple design and ability to create minimalist applications, so Prometheus is ideal for simple microservice-based applications. It is also useful for distributed, cloud-native environments.
Note: Prometheus is less suites for cases that require accurate second-by-second data scrapes.
Consul
Consul is a service discovery technology that ensures microservices can communicate with each other. It has some features that distinguishes it from other service discovery solutions, including:
- Having an HTTP REST API and support for DNS
- Auto-generation of configuration files using Consul Template
- It can perform health checks and exclude services from service discovery when the health check fails.
Consul is very flexible. Due to the DNS interface and Consul Template it can be used with many technologies. This is particularly important in the context of microservices. While a system might not need to use a variety of technologies from the start, in the long term it is advantageous to be able to integrate new technologies.
Benefits of Consul for Microservices#
Setting up a microservices system with Consul is great option for a synchronous system, as its infrastructure meets the typical challenges of synchronous microservices:
- Service discovery: This feature is covered by Consul and is useful for integrating new technologies to your microservices.
- Increased transparency: Consul is fully transparent and can be used without any code dependencies.
- Configuration: Consul can be used to configure the microservices. Both service discovery and configuration can be implemented.
- Load Balancing: With Consul DNS, Consul implements load balancing transparently with the DNS server.
For each microservice, Apache HTTPD must have an entry in its configuration file. For this, Consul Template can be used. Consul Template ensures that a microservice can be reached from outside as soon as it has registered with Consul.
Note: Consul is written in Go. Monitoring and deployment differs from Java microservices.
Service Mesh: Managing Traffic, Security, and Resilience at Scale#
As microservices grow in number and complexity, managing service-to-service communication becomes a major challenge.
A service mesh addresses this by handling networking, security, observability, and reliability — without adding complexity to your application code.
Modern implementations like Istio Ambient Mesh, Cilium Service Mesh (eBPF), and Linkerd provide:
Automatic mTLS encryption
Traffic shaping, circuit breaking, and fault injection
Observability and policy enforcement at the network layer
These are now considered essential for large-scale microservice deployments where reliability and visibility are critical.
Example: Traffic Splitting in Istio#
apiVersion: networking.istio.io/v1alpha3kind: VirtualServicemetadata:name: paymentsspec:hosts:- paymentshttp:- route:- destination:host: paymentssubset: v2weight: 80- destination:host: paymentssubset: v1weight: 20
API Gateways and the Kubernetes Gateway API#
In microservice environments, managing multiple APIs independently becomes cumbersome.
An API gateway serves as a unified entry point for:
Routing and load balancing
Authentication and rate limiting
Monitoring and request transformation
Popular tools include Kong, Envoy Gateway, and Traefik.
In Kubernetes-native environments, the Gateway API (which supersedes Ingress) provides a flexible, extensible standard for routing traffic into your cluster.
Service-to-Service Communication: REST, gRPC, and GraphQL#
While REST remains popular, modern architectures increasingly use gRPC and GraphQL for specialized needs:
gRPC (built on HTTP/2): fast, type-safe, and supports bidirectional streaming — ideal for internal microservices.
GraphQL: enables flexible client queries across multiple services, reducing over-fetching and under-fetching.
A common modern pattern:
REST for public APIs
gRPC for internal, high-performance communication
GraphQL for aggregating and querying multiple backends efficiently
Event-Driven Communication and Messaging#
Not all microservices should communicate synchronously.
For scalable, decoupled, or real-time systems, asynchronous event-driven messaging is key.
Technologies like Apache Kafka, RabbitMQ, NATS, and Apache Pulsar enable:
Communication via events instead of direct requests
Replayable logs for fault tolerance
Reduced inter-service dependencies
This architecture improves resilience and allows microservices to evolve independently.
Observability and OpenTelemetry#
Modern observability goes beyond metrics — it combines logs, metrics, and traces for a full system view.
While Prometheus remains the go-to for metrics, OpenTelemetry has become the industry standard for instrumentation and telemetry collection.
Combine OpenTelemetry with tools like Grafana Tempo (for traces) or Jaeger to gain:
End-to-end request tracing
Unified telemetry pipelines
Real-time insights into distributed performance
Security and Supply Chain Protection#
With more moving parts, microservices are inherently more exposed to risk.
Modern architectures enforce security at every layer:
mTLS and workload identity via SPIFFE/SPIRE
Policy enforcement using OPA Gatekeeper or Kyverno
Supply chain security using cosign (image signing), SLSA, and SBOMs like CycloneDX
Security is now a first-class concern, not an afterthought.
Deployment and GitOps Workflows#
Deployment practices have evolved alongside microservices.
GitOps — using Git as the single source of truth for cluster state — is now the preferred method for continuous delivery.
Tools like Argo CD and Flux automatically reconcile your cluster with configuration declared in Git.
GitOps enforces:
Consistency
Auditability
Security via version-controlled, peer-reviewed changes
It also makes rollbacks trivial and simplifies disaster recovery.
For safer feature rollouts, Argo Rollouts enables progressive delivery methods such as:
Canary releases
Blue-green deployments
A/B testing
Teams increasingly pair GitOps with policy-as-code (Kyverno, OPA) and continuous verification (Flagger, Keptn) to build automated, self-healing pipelines.
Comparison of Modern Deployment Strategies#
Rolling Update | Gradually replaces old pods with new ones | Default choice for most updates | Minimal downtime, easy to automate | Harder to roll back quickly |
Blue-Green | Runs two environments (blue=current, green=new) and switches traffic | Mission-critical services | Zero downtime, instant rollback | Requires double resources |
Canary Release | Gradually releases to a subset of users | Risk-sensitive environments | Early feedback, safer releases | More complex setup |
A/B Testing | Routes traffic to multiple versions to compare | Feature experimentation | Real-world metrics, data-driven | Requires analytics and routing tools |
Shadow Deployment | Sends real traffic to new version invisibly | Pre-release validation | Detects issues before rollout | Higher infrastructure cost |
By aligning deployment strategy with risk tolerance and user expectations, GitOps enables continuous delivery without instability.
Serverless and Microservices: The Next Frontier#
For workloads that don’t need constant uptime, serverless platforms like Knative bring scale-to-zero capabilities to Kubernetes.
This allows event-driven microservices that scale automatically and minimize cost.
Ideal for:
Scheduled jobs and background tasks
Burst workloads with unpredictable traffic
Event-triggered pipelines or integrations
Compute is only allocated when needed, reducing cost and improving utilization.
Modern platforms like Knative Eventing and OpenFaaS now extend serverless beyond FaaS:
Event routing and filtering for workflow control
Trigger-based pipelines connecting multiple services
Integration with Kafka and NATS for reactive architectures
These features enable real-time, event-driven pipelines with automatic scalability.
The Hybrid Future: Microservices + Serverless#
As serverless matures, the line between traditional microservices and event-driven architectures continues to blur.
Most teams now adopt a hybrid model combining:
Long-running microservices for core business logic
Serverless components for on-demand, event-driven tasks
This approach delivers the best of both worlds — combining efficiency, scalability, and flexibility — and is rapidly becoming the standard pattern for modern distributed system design.
What to learn next#
Congrats! You’ve now learned the top 5 technologies for building a microservices architecture. Using these tools will make your development and deployment process far easier, and they empower highly scalable applications.
There is still a lot to learn, and, depending on your requirements, other top technologies may be beneficial. You should look into:
- Asynchronous communication with Atom
- Messaging and Kafka
- Erueka for Service Discovery
- Hystrix for Resilience
- PaaS with Cloud Foundry
- and more
To learn more about the tools we discussed today and to get started with your next steps, check out Educative’s course Microservice Architecture: Practical Implementation. This course covers the most popular microservices tech stacks and learn how to implement complex, industry-standard architectures.
Or, if you want to get more familiar with microservices in general, Introduction to Microservice Principles and Concepts is a great jumping off point. You’ll learn microservices in depth, strategies for migrating old systems, and technologies for implementing microservices.
Happy learning!
