Alternatives to Spring Cloud logo

Alternatives to Spring Cloud

Cloud Foundry, Spring Boot, Istio, Kubernetes, and Netflix OSS are the most popular alternatives and competitors to Spring Cloud.
595
536
+ 1
0

What is Spring Cloud and what are its top alternatives?

Spring helps development teams everywhere build simple, portable, fast and flexible JVM-based systems and applications.
Spring Cloud is a tool in the Container Tools category of a tech stack.

Top Alternatives to Spring Cloud

  • Cloud Foundry

    Cloud Foundry

    Cloud Foundry is an open platform as a service (PaaS) that provides a choice of clouds, developer frameworks, and application services. Cloud Foundry makes it faster and easier to build, test, deploy, and scale applications. ...

  • Spring Boot

    Spring Boot

    Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration. ...

  • Istio

    Istio

    Istio is an open platform for providing a uniform way to integrate microservices, manage traffic flow across microservices, enforce policies and aggregate telemetry data. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes, Mesos, etc. ...

  • Kubernetes

    Kubernetes

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...

  • Netflix OSS

    Netflix OSS

    It provides tools and services to get the most out of your (big) data. It also provides runtime containers, libraries and services that power microservices. ...

  • Eureka

    Eureka

    Eureka is a REST (Representational State Transfer) based service that is primarily used in the AWS cloud for locating services for the purpose of load balancing and failover of middle-tier servers. ...

  • Docker

    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application ‚ÄĒ from legacy to what comes next ‚ÄĒ and securely run them anywhere ...

  • Consul

    Consul

    Consul is a tool for service discovery and configuration. Consul is distributed, highly available, and extremely scalable. ...

Spring Cloud alternatives & related posts

Cloud Foundry logo

Cloud Foundry

140
248
4
Deploy and scale applications in seconds on your choice of private or public cloud
140
248
+ 1
4
PROS OF CLOUD FOUNDRY
  • 1
    Perfectly aligned with springboot
  • 1
    Free distributed tracing (zipkin)
  • 1
    Application health management
  • 1
    Free service discovery (Eureka)
CONS OF CLOUD FOUNDRY
    Be the first to leave a con

    related Cloud Foundry posts

    Spring Boot logo

    Spring Boot

    13.8K
    11.7K
    841
    Create Spring-powered, production-grade applications and services with absolute minimum fuss
    13.8K
    11.7K
    + 1
    841
    PROS OF SPRING BOOT
    • 127
      Powerful and handy
    • 121
      Easy setup
    • 111
      Java
    • 83
      Spring
    • 79
      Fast
    • 39
      Extensible
    • 32
      Lots of "off the shelf" functionalities
    • 27
      Cloud Solid
    • 21
      Caches well
    • 19
      Many receipes around for obscure features
    • 18
      Modular
    • 18
      Productive
    • 17
      Integrations with most other Java frameworks
    • 16
      Spring ecosystem is great
    • 16
      Fast Performance With Microservices
    • 14
      Community
    • 13
      Auto-configuration
    • 11
      Easy setup, Community Support, Solid for ERP apps
    • 11
      One-stop shop
    • 10
      Easy to parallelize
    • 9
      Cross-platform
    • 9
      Easy setup, good for build erp systems, well documented
    • 8
      Easy setup, Git Integration
    • 8
      Powerful 3rd party libraries and frameworks
    • 2
      Kotlin
    • 2
      It's so easier to start a project on spring
    CONS OF SPRING BOOT
    • 18
      Heavy weight
    • 17
      Annotation ceremony
    • 10
      Many config files needed
    • 7
      Java
    • 5
      Reactive
    • 4
      Excellent tools for cloud hosting, since 5.x

    related Spring Boot posts

    Praveen Mooli
    Engineering Manager at Taylor and Francis · | 14 upvotes · 1.6M views

    We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

    To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

    To build #Webapps we decided to use Angular 2 with RxJS

    #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

    See more

    Is learning Spring and Spring Boot for web apps back-end development is still relevant in 2021? Feel free to share your views with comparison to Django/Node.js/ ExpressJS or other frameworks.

    Please share some good beginner resources to start learning about spring/spring boot framework to build the web apps.

    See more
    Istio logo

    Istio

    549
    968
    41
    Open platform to connect, manage, and secure microservices, by Google, IBM, and Lyft
    549
    968
    + 1
    41
    PROS OF ISTIO
    • 10
      Zero code for logging and monitoring
    • 8
      Service Mesh
    • 7
      Great flexibility
    • 4
      Ingress controller
    • 3
      Easy integration with Kubernetes and Docker
    • 3
      Powerful authorization mechanisms
    • 3
      Resiliency
    • 3
      Full Security
    CONS OF ISTIO
    • 8
      Performance

    related Istio posts

    Anas MOKDAD
    Shared insights
    on
    KongKongIstioIstio

    As for the new support of service mesh pattern by Kong, I wonder how does it compare to Istio?

    See more
    Kubernetes logo

    Kubernetes

    30.5K
    25.1K
    595
    Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
    30.5K
    25.1K
    + 1
    595
    PROS OF KUBERNETES
    • 152
      Leading docker container management solution
    • 121
      Simple and powerful
    • 96
      Open source
    • 71
      Backed by google
    • 55
      The right abstractions
    • 24
      Scale services
    • 17
      Replication controller
    • 9
      Permission managment
    • 6
      Simple
    • 5
      Cheap
    • 5
      Supports autoscaling
    • 3
      Promotes modern/good infrascture practice
    • 3
      Reliable
    • 3
      No cloud platform lock-in
    • 3
      Self-healing
    • 3
      Open, powerful, stable
    • 3
      Scalable
    • 2
      Quick cloud setup
    • 2
      A self healing environment with rich metadata
    • 2
      Captain of Container Ship
    • 1
      Custom and extensibility
    • 1
      Expandable
    • 1
      Easy setup
    • 1
      Gke
    • 1
      Golang
    • 1
      Backed by Red Hat
    • 1
      Everything of CaaS
    • 1
      Runs on azure
    • 1
      Cloud Agnostic
    • 1
      Sfg
    CONS OF KUBERNETES
    • 13
      Poor workflow for development
    • 10
      Steep learning curve
    • 5
      Orchestrates only infrastructure
    • 2
      High resource requirements for on-prem clusters

    related Kubernetes posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 37 upvotes · 3.5M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Yshay Yaacobi

    Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

    Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

    After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

    See more
    Netflix OSS logo

    Netflix OSS

    56
    75
    0
    A set of frameworks and libraries to solve distributed-systems problems at scale
    56
    75
    + 1
    0
    PROS OF NETFLIX OSS
      Be the first to leave a pro
      CONS OF NETFLIX OSS
        Be the first to leave a con

        related Netflix OSS posts

        Eureka logo

        Eureka

        222
        513
        60
        AWS Service registry for resilient mid-tier load balancing and failover.
        222
        513
        + 1
        60
        PROS OF EUREKA
        • 19
          Easy setup and integration with spring-cloud
        • 8
          Health checking
        • 7
          Circuit breaker
        • 6
          Netflix battle tested components
        • 6
          Web ui
        • 5
          Monitoring
        • 5
          Service discovery
        • 4
          Open Source
        CONS OF EUREKA
          Be the first to leave a con

          related Eureka posts

          Docker logo

          Docker

          91.8K
          71.4K
          3.8K
          Enterprise Container Platform for High-Velocity Innovation.
          91.8K
          71.4K
          + 1
          3.8K
          PROS OF DOCKER
          • 817
            Rapid integration and build up
          • 688
            Isolation
          • 515
            Open source
          • 502
            Testa­bil­i­ty and re­pro­ducibil­i­ty
          • 457
            Lightweight
          • 215
            Standardization
          • 180
            Scalable
          • 104
            Upgrading / down­grad­ing / ap­pli­ca­tion versions
          • 86
            Security
          • 83
            Private paas environments
          • 33
            Portability
          • 25
            Limit resource usage
          • 15
            I love the way docker has changed virtualization
          • 15
            Game changer
          • 12
            Fast
          • 11
            Concurrency
          • 7
            Docker's Compose tools
          • 4
            Because its fun
          • 4
            Easy setup
          • 4
            Fast and Portable
          • 3
            Makes shipping to production very simple
          • 2
            It's dope
          • 1
            Open source and highly configurable
          • 1
            Simplicity, isolation, resource effective
          • 1
            Highly useful
          • 1
            MacOS support FAKE
          • 1
            Its cool
          • 1
            Docker hub for the FTW
          • 1
            Package the environment with the application
          • 1
            Very easy to setup integrate and build
          CONS OF DOCKER
          • 7
            New versions == broken features
          • 4
            Documentation not always in sync
          • 3
            Moves quickly
          • 3
            Unreliable networking

          related Docker posts

          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 2.2M views

          Our whole DevOps stack consists of the following tools:

          • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
          • Respectively Git as revision control system
          • SourceTree as Git GUI
          • Visual Studio Code as IDE
          • CircleCI for continuous integration (automatize development process)
          • Prettier / TSLint / ESLint as code linter
          • SonarQube as quality gate
          • Docker as container management (incl. Docker Compose for multi-container application management)
          • VirtualBox for operating system simulation tests
          • Kubernetes as cluster management for docker containers
          • Heroku for deploying in test environments
          • nginx as web server (preferably used as facade server in production environment)
          • SSLMate (using OpenSSL) for certificate management
          • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
          • PostgreSQL as preferred database system
          • Redis as preferred in-memory database/store (great for caching)

          The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

          • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
          • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
          • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
          • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
          • Scalability: All-in-one framework for distributed systems.
          • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
          See more
          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 21 upvotes · 4M views

          Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

          It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

          I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

          We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

          If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

          The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

          Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

          See more
          Consul logo

          Consul

          929
          1.1K
          202
          A tool for service discovery, monitoring and configuration
          929
          1.1K
          + 1
          202
          PROS OF CONSUL
          • 59
            Great service discovery infrastructure
          • 35
            Health checking
          • 27
            Distributed key-value store
          • 25
            Monitoring
          • 23
            High-availability
          • 11
            Web-UI
          • 10
            Token-based acls
          • 6
            Gossip clustering
          • 5
            Dns server
          • 1
            Docker integration
          CONS OF CONSUL
            Be the first to leave a con

            related Consul posts

            John Kodumal

            As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data‚ÄĒthis is made HA with the use of Patroni and Consul.

            We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

            See more

            Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

            Apps
            • Web: a mix of JavaScript/ES6 and React.
            • Desktop: And Electron to ship it as a desktop application.
            • Android: a mix of Java and Kotlin.
            • iOS: written in a mix of Objective C and Swift.
            Backend
            • The core application and the API written in PHP/Hack that runs on HHVM.
            • The data is stored in MySQL using Vitess.
            • Caching is done using Memcached and MCRouter.
            • The search service takes help from SolrCloud, with various Java services.
            • The messaging system uses WebSockets with many services in Java and Go.
            • Load balancing is done using HAproxy with Consul for configuration.
            • Most services talk to each other over gRPC,
            • Some Thrift and JSON-over-HTTP
            • Voice and video calling service was built in Elixir.
            Data warehouse
            • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
            Etc
            See more