Kubernetes alternatives to Spring Java framework

Spring Cloud and Kubernetes both complement each other to build a cloud-native platform and run microservices on the Kubernetes containers. Kubernetes provides many features which are similar to Spring Cloud and Spring Config Server features.

Spring framework has been around for many years. Even today, many organizations prefer to go with Spring because it provides many advanced features with simple ready-to-use libraries. It’s a great deal when Spring developers will only take care of business logic source code and configuration code is managed by DevOps/DevSecOps operation teams or automated CI/CD tools.

Important Note about Netflix OSS: Starting from the Spring Cloud Greenwich release Train, Netflix OSS, Hystrix, Ribbon, and Zuul are entering into maintenance mode and are now deprecated. This means that there won’t be any new features added to these modules, and the Spring Cloud team will only fix bugs and security issues. The maintenance mode does not include the Eureka module. Spring provides regular releases and patches for its libraries; however, Netflix OSS is almost not active and is not being used by organizations.

Let’s discuss a couple of challenges of cloud configuration code with Spring Cloud and Spring Config Server for microservices architecture:

  • Tight coupling of business logic and configuration source code: Spring configuration provides tight coupling with business logic code, which makes the code-heavy and also makes it difficult to debug production issues. It slows down releases for new business features due to the tight integration of business logic with cross-cutting configuration source code.
  • Extra coding and testing effort: For new feature releases one extra testing effort is required to test new features mainly during integration, regression, and load testing. We need to test the entire code with cross-cutting configurations even for minor code changes in the business logic.
  • Slow build and deployment: It takes extra time to load, deploy, and run heavy code because of the strong bonding of configuration and business logic. It consumes extra CPU and RAM for all business-specific API calls.

Spring doesn’t provide these important features:

  • Continuous Integration (CI): It doesn’t address any CI-related concerns. It only handles the build microservices part.
  • Self-healing of infrastructure: It doesn’t care about self-healing and restarting apps for any crashes. It provides health check APIs and observability features using actuator/micrometer support with Prometheus.
  • Dependency on Java framework: It only supports Java programming language.

Kubernetes alternatives of Spring Cloud

Here are a few better alternatives of Kubernetes for Spring libraries:

Spring CloudKubernetes
Service discoveryK8s provides Cluster API, a service that exposes microservices across all namespaces since “kube-dns” allows lookup. It also provides integration with the ingress controller and K8s ingress resources to intelligently route incoming traffic to designated service.K8s provides ConfigMap and secret to externalize configuration at the infra side natively which is maintained by the DevOps team.
Load balancingNetflix Ribbon provides client-side load balancing on HTTP/TCP requests.K8s provides load balancer services. It’s the responsibility of K8s service to load balance.
Configuration managementSpring Config Server externalizes configuration management through code configuration.K8s services and ingress resources fulfill partial API gateways features like routing and load balancing. K8s supports service mesh architecture implementation tools like Istio, which provides most of the API gateway-related features like service discovery, and API tracing. It’s not a replacement for the external API gateway.
API GatewaySpring Cloud Gateway and Zuul2 provide all API gateway features like request routing, caching, authentication, authorization, API level load balancing, rate limiting, circuit breaker, and so on.K8s provides the same features with health checks, resource isolation, and service mesh.
Resilience and fault toleranceSpring Boot Admin supports scaling and self-healing of applications. It’s used for managing and monitoring Spring Boot applications. Each application is considered a client and registers to the admin server. Spring Boot Actuator endpoints help to monitor the environment.Resilence4j, and Spring Retry projects provide resiliency and fault tolerance mechanisms. They provide circuit breaker, timeout, and retry features.
Scaling and self-healingSpring Batch, Spring Cloud Task, and Spring Cloud Data Flow (SCDF) have capabilities to schedule/on-demand and run batch jobs. Spring tasks can run short-living jobs. A short-lived task could be a Java process or a shell script.Netflix Eureka. Not recommended to use for cloud-native modern applications.
Batch jobsSpring Batch, Spring Cloud Task, and Spring Cloud Data Flow (SCDF) have capabilities to schedule/on-demand and run batch jobs. Spring tasks can run short-living jobs. A short-lived task could be a Java process, a shell script.K8s also provides scheduled Cron job features. It executes batch jobs and provides limited scheduling features. It also works together with Spring Batch.


Spring provides tons of features and has had a proven Java-based framework for many years! Kubernetes provides complimentary features which are comparable with Spring features and can be replaced to extract configuration code from the business logic. Cloud-native microservices’ service architecture (MSA) and 12/15 factor principles recommend keeping cross-cutting configuration code outside of the business logic code. Configuration should be stored and managed separately. In MSA, the same configuration can be shared across many microservices, that’s why configuration should be stored externally and be available for all microservices applications. Also, these configurations should be managed by DevOps teams.

This helps developers to focus only on business logic programming. It will definitely make release faster with lower development costs. Also, building and deployment will be faster for microservices apps. Kubernetes provides better alternatives to replace these legacy Spring libraries features, many of them are deprecated or in the maintenance phase. Kubernetes also provides Service Mesh support.

These Kubernetes alternatives are really helpful for microservices applications and complimentary to the Spring Java framework for microservices development!

My first book release!! Cloud Native Microservices with Spring and Kubernetes (453 pages)

I am happy to announce release of my first book “Cloud Native Microservices with Spring and Kubernetes” with BPB Publications!! It’s all about design, build and deploy scalable cloud native microservices on container using the Spring framework and Kubernetes. Need your support! Please buy and review this book on Amazon. Also, share book detail with your IT software engineers colleagues and friends.

The main objective of this book is to give an overview of cloud-native microservices, their architecture, design patterns, best practices, use cases, and practical coverage of modern applications. This book covers a strong understanding of microservices, API first approach, Testing, Observability, API Gateway, Service Mesh, and Kubernetes alternatives of Spring Cloud. This book covers the implementation of various design patterns of developing cloud native microservices using Spring framework, docker and Kubernetes. It also covers containerization concepts and hands-on code exercises.

After reading this book, the readers will have a holistic understanding of building, running, and managing cloud native microservices applications on Kubernetes containers.

It’s the first book on this subject in India by any Indian writer, which is also economical than foreign publications. This book is about learning of software application design and development using Microservices, Spring and Kubernetes based technologies. It’s useful for software developers, cloud engineers, DevOps and technical architects.

Available on:

This book is available in paperback and Kindle (eBook on free Kindle app on Android/iOS/Laptop/Desktop) editions on amazon and BPB in most of the countries of North America, Europe, the Middle East, Asia, and Africa.

Refer free preview and TOC/Index of this book:


What you will learn:

  • Learn fundamentals of microservice and design patterns.
  • Perform end-to-end microservices testing using Cucumber.
  • Learn microservices development using Spring Boot and Kubernetes.
  • Learn to develop reactive, event-driven, and batch microservices.
  • Perform end-to-end microservices testing using Cucumber.
  • Implement API gateway, authentication & authorization, load balancing, caching, and rate limiting.
  • Learn observability and monitoring techniques of microservices

Who this book is for:
This book is for the Spring Developers, Microservice Developers, Cloud Engineers, DevOps Consultants, Technical Architect and Solution Architects.

Table of Contents (Chapters):
1. Overview of Cloud Native microservices
2. Microservice design patterns
3. API first approach
4. Build microservices using the Spring Framework
5. Batch microservices
6. Build reactive and event-driven microservices
7. The API gateway, security, and distributed caching with Redis
8. Microservices testing and API mocking
9. Microservices observability
10. Containers and Kubernetes overview and architecture
11. Run microservices on Kubernetes
12. Service Mesh and Kubernetes alternatives of Spring Cloud


  • Complete coverage on how to design, build, run, and deploy modern cloud native microservices.
  • Includes numerous sample code exercises on microservices, Spring and Kubernetes.
  • Develop a stronghold on Kubernetes, Spring, and the microservices architecture.
  • Complete guide of application containerization on Kubernetes containers.
  • Coverage on managing modern applications and infrastructure using observability tools.

Chapter 1: Overview of Cloud Native microservices, introduces cloud native modern applications, cloud first overview, benefits, types of clouds, classification, and the need for cloud native modern applications. It will cover detailed microservices (MSA ) overview, characteristics, motivations, benefits, best practices, architecture principles, challenges and solutions, application modernization spectrum, twelve-factor apps, and beyond twelve-factor apps.s

Chapter 2: Microservice design patterns, introduces various microservices design patterns with use cases, advantages, and disadvantages.

Chapter 3: API first approach, discusses fundamentals of the API first approach. It discusses details of the REST overview, API model, best practices, design principles, components, security, communication protocols, and how to document dynamically with OpenAPI Swagger. It discusses API design planning, specifications, API management tools, and testing API with SwaggerHub inspector and PostMan REST client.

Chapter 4: Build microservices using the Spring Framework, is a key chapter of Spring Boot and Spring Cloud components with hands-on lab exercises. It will cover steps to build microservice using the REST API framework. It covers the Spring Cloud config server and resiliency of microservices practical aspects.

Chapter 5: Batch microservices, introduces batch microservices, use cases, Spring Cloud Task, and Spring Batch. It discusses hands-on lab exercises using Spring Cloud Data Flow (SCDF) and Kafka. It also discusses a few Spring batch practices, auto-scaling techniques, batch orchestration, and compositions methods for sequential or parallel batch processing. Last but not the least; it talks about alerts and monitoring of Spring Cloud Task and Spring Batch.

Chapter 6:  Build reactive and event-driven microservices, describes building of reactive microservices, non-blocking synchronous APIs, and event-driven asynchronous microservices. It covers steps to develop sample reactive microservices with Spring’s project Reactor, Spring WebFlux, and event-driven asynchronous microservices. It discusses Spring Cloud Stream, Zookeeper, SpringBoot, and overview of Kafka. It also covers hands-on lab exercises of event-driven asynchronous microservices using Spring Cloud Stream and Kafka.

Chapter 7:  API gateway, security, and distributed caching with Redis, introduces the API Gateway overview, features, advantages, and best practices. It covers hands-on lab exercises to expose REST APIs of microservices externally with the Spring Cloud Gateway. It covers distributed caching overview and hands-on lab exercises using Redis. It discusses API gateway rate limiting and Implementation of API gateway rate limiting with Redis and Spring Boot. Last but not the least, it covers best practices of API Security. Implementation of SSO using Spring Cloud Gateway, Spring Security, Oauth2, Keycloak, OpenId, and JWT tokens.

Chapter 8: Microservices testing and API mocking, describes important aspects of microservices testing practices, challenges, benefits, testing strategy, testing pyramid, and different types of microservices testing. It covers implementation of the integration testing framework using Behavioral Driven Development (BDD) with hands-on code examples. It also discusses microservices testing tools and best practices of microservices testing. It covers the role of testing in the microservices CI/CD pipeline. Last but not the least; it talks about API mocking and hands-on lab implementation with the WireMock framework.

Chapter 9: Microservices observability, covers detail observability and monitoring overview and techniques of microservices with the Spring actuator, micrometer health APIs, and Wavefront APM. It covers application logging overview, best practices, simple logging, and log aggregation of distributed microservices with implementation using Elasticsearch, Fluentd, and Kibana (EFK) on the Kubernetes container. It discusses the need of APM performance and telemetry monitoring tools for distributed microservices and how to trace multiple microservices in a distributed environment. It also covers hands-on lab implementation of monitoring microservices with Prometheus and Grafana.

Chapter 10: Containers and Kubernetes overview and architecture, is a key chapter which introduces containers, docker, docker engine containerization, Buildpacks, components of docker files, build docker files, run docker files, and inspect docker images. It covers docker image registry and how to persist docker images in image container registries. It covers an overview of Kubernetes, need, and architecture. Last but not the least; it covers a detailed introduction of Kubernetes resources.

Chapter 11: Run microservices on Kubernetes, discusses practical aspects of Kubernetes, installation, and configuration with monitoring and visualization tools with Octant and Proxy. It discusses how to create and manage Kubernetes clusters in detail. It discusses hands-on exercises of creating docker images of Java microservices, pushing it to the Docker hub container image registry, and deploying to Kubernetes clusters. It covers hands-on lab examples of exposing API endpoints of microservices outside the Kubernetes cluster by using the Nginx ingress controller. Last but not the least; it covers various popular and useful Kubernetes application deployment and configuration of management tools.

Chapter 12: Service Mesh and Kubernetes alternatives of Spring Cloud, covers a detailed overview and benefits of GitOps and Service Mesh. It covers the Istio Service Mesh architecture and deployment of microservices on Kubernetes with Argo CD. Last but not the least; it discusses various Kubernetes alternatives of Spring Cloud projects and popular cloud buzzwords!

About the Author
Rajiv Srivastava is the founder of cloudificationzone.com, which is a cloud native modern application tech blog site. He is a cloud solution architect and modern application specialist with 17+ years of work experience in software development and architectural design.


1.      Spring framework

2.      API first approach

3.      Cloud Native

4.      Microservices observability

5.      API testing

6.      API gateway

7.      Microservices observability

8.      Service mesh

9.      API gateway

10.    Redis distributed caching

11.    Kafka

12.    Spring Cloud

13.    Service discovery

14.    Spring cloud data flow

15.    Ingress controller

A quick introduction of Cluster API

In this blog we will understand how multi Kubernetes clusters can be managed and orchestrated using the Cluster API  control plane tool.

Cluster API

It’s a sub-project of Kubernetes which works on declarative API and provides support for CRD (Custom Resource Definition), which manages K8s and VMs based on CRD configuration. Cluster API always checks current K8s clusters on worker nodes status and compares them with desired state which is provided by DevOps team using CRD config files. It provides provisioning of multiple K8s clusters which could be spread to multiple nodes/hosts. It extends the functionality of K8s for multi-node cluster management with Kubeadm API.

Cluster API orchestrates  and manages the lifecycle of worker nodes where K8s clusters are provisioned. Also, manages multiple K8s clusters upgrades, failover, rollback etc.

Tip: Cluster API manages K8s clusters of multi-cloud including on-prem and hybrid.

Started by the Kubernetes Special Interest Group (SIG) Cluster Lifecycle, the Cluster API project uses Kubernetes style APIs and patterns to automate cluster lifecycle management.

Refer Cluster API docs here: https://cluster-api.sigs.k8s.io/

Cluster API cluster management reference architecture

These are important components of Cluster API:

Infrastructure provider

Basic hardware infrastructure providers such as Vmware, public infra providers such as AWS, GCP, Azure etc.

Bootstrap provider

It’s also called Cluster API bootstrap provider Kubeadm (CABPK). It generates cluster certificates, initialize/bootstrap control planes. It turns the Machine into a K8s Node. It uses the Kubeadm tool.


It manages the lifecycle of K8s clusters on multiple nodes. Kubeadm is a tool built to provide best-practice “fast paths” for creating Kubernetes clusters. It performs the actions necessary to get a minimum viable, secure cluster up and running in a user friendly way.

Kubeadm: https://kubernetes.io/docs/reference/setup-tools/kubeadm/

Control plane

Control plane is a set of services which manages multiple K8s clusters and scale on production environments. It manages and provisioned dedicated machines/VMs, running static pods for components such as kube-apiserver, kube-controller-manager and kube-scheduler.

The default provider uses kubeadm to bootstrap the control plane.

Custom Resource Definitions (CRDs)

It’s a set of K8s YAML configuration files which maintain desired K8s cluster state. It can be persisted on Git server for platform automation for Cluster API based K8s clusters.


It defines configuration of machines like VM etc. It’s a declarative spec for an infrastructure component hosting a Kubernetes Node. It’s like POD on K8s.


It provides declarative updates for Machines and MachineSets.


It maintains a stable set of Machines running at any given time. It’s like a ReplicaSet of K8s.


It defines the conditions when a Node should be considered unhealthy. If the Node has any unhealthy conditions for a given user-configured time, the MachineHealthCheck initiates remediation of the Node. Remediation of Nodes is performed by deleting the corresponding Machine and creating a new one like ReplicaSet. It always maintains the same set of Machine configuration which has been provided in the CRD file.


It contains the Machine or Node role-specific initialization data (usually cloud-init) used by the Infrastructure Provider to bootstrap a Machine into a Node.