Towards a Lightweight Multi-Cloud DSL for Elastic and Transferable Cloud-native Applications

Cloud-native applications are intentionally designed for the cloud in order to leverage cloud platform features like horizontal scaling and elasticity – benefits coming along with cloud platforms. In addition to classical (and very often static) multi-tier deployment scenarios, cloud-native applications are typically operated on much more complex but elastic infrastructures. Furthermore, there is a trend to use elastic container platforms like Kubernetes, Docker Swarm or Apache Mesos. However, especially multi-cloud use cases are astonishingly complex to handle. In consequence, cloud-native applications are prone to vendor lock-in. Very often TOSCA-based approaches are used to tackle this aspect. But, these application topology defining approaches are limited in supporting multi-cloud adaption of a cloud-native application at runtime. In this paper, we analyzed several approaches to define cloud-native applications being multi-cloud transferable at runtime. We have not found an approach that fully satisfies all of our requirements. Therefore we introduce a solution proposal that separates elastic platform definition from cloud application definition. We present first considerations for a domain specific language for application definition and demonstrate evaluation results on the platform level showing that a cloud-native application can be transfered between different cloud service providers like Azure and Google within minutes and without downtime. The evaluation covers public and private cloud service infrastructures provided by Amazon Web Services, Microsoft Azure, Google Compute Engine and OpenStack.

Transcript

1. Towards a Lightweight Multi-Cloud DSL
   for Elastic and Transferable Cloud-native
   Applications
   Peter-Christian Quint, Nane Kratzke (Speaker)
   8th International Conference on Cloud Computing and Services Science (CLOSER 2018); Madeira, Funchal, Portugal, 2018
   

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2. The next 20 minutes are about ...
   • Context of our research
   • Cloud applications and vendor lock-in
   • Infrastructure-agnostic platform transferability
   • Platform-agnostic application definition
   • Resulting requirements for a „Cloud Programming
   Language“
   • Language proposal and evalution
   • Conclusion
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems
   2
   Paper URL
   Presentation URL
   Speaker Deck
   

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3. Research Methodology
   Cloud TRANSIT
   3
   [KQ2017a] Kratzke, N., &
   Quint, P.-C. (2017).
   Understanding Cloud-native
   Applications after 10 Years
   of Cloud Computing - A
   Systematic Mapping
   Study. Journal of Systems
   and Software, 126 (April).
   [KP2016] Kratzke, N., &
   Peinl, R. (2016). ClouNS - a
   Cloud-Native Application
   Reference Model for
   Enterprise Architects.
   In 2016 IEEE 20th
   International Enterprise
   Distributed Object
   Computing Workshop
   (EDOCW) (pp. 1–10).
   [Kra2017a] Kratzke, N.
   (2017). Smuggling Multi-
   Cloud Support into Cloud-
   native Applications using
   Elastic Container Platforms.
   In Proceedings of the 7th
   Int. Conf. on Cloud
   Computing and Services
   Science (CLOSER
   2017) (pp. 29–42).
   Understanding cloud-application engineering
   approaches and vendor lock-in drivers
   Reference
   Modeling
   Infrastructure-
   agnostic
   platform
   transferability
   concept
   This
   presentations
   focus
   Platform-
   agnostic
   cloud
   application
   definition
   

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4. Can we solve cloud orchestration problems
   differently?
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems
   4
   TOSCA
   [QK2018a] Quint, P.-C., & Kratzke, N. (2018). Towards a Lightweight Multi-Cloud DSL for Elastic and Transferable Cloud-native
   Applications. In Proceedings of the 8th Int. Conf. on Cloud Computing and Services Science (CLOSER 2018, Madeira, Portugal).
   UCAML
   [Kra2017a] Kratzke, N. (2017). Smuggling Multi-Cloud Support into Cloud-native Applications using Elastic Container Platforms.
   In Proceedings of the 7th Int. Conf. on Cloud Computing and Services Science (CLOSER 2017) (pp. 29–42).
   PLAIN
   Jolie
   (1st language
   for micro-
   services)
   Montesi F., Guidi C., Zavattaro G. (2014) Service-Oriented
   Programming with Jolie. In: Bouguettaya A., Sheng Q., Daniel
   F. (eds) Web Services Foundations. Springer, New York, NY
   

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5. Requirements for a
   Cloud Programming Language (practicitioner point of view)
   R1: Containerized Deployment
   The DSL must be designed to describe and label a
   containerized deployment of discoverable services.
   R2: Application Scaling
   The DSL must be designed to describe elastic services.
   R3: Compendiously
   The DSL must be designed to be lightweight and pragmatic.
   R4: Multi-Cloud Support
   The DSL must be designed to support multi-cloud operations
   (including multi-cloud scheduling constraints)
   R5: Infrastructure agnostic
   The DSL must be designed to be independent from a specifc
   ECP or cloud infrastructure.
   R6: Elastic runtime environment
   The DSL must be designed to define applications being able
   to be operated on arbitrary elastic runtime environments.
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems 5
   

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6. Core Language Model
   Requirements R1, R2, R3
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems
   6
   exposes
   

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7. Infrastructure and platform agnostic
   Requirements R4, R5, R6
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems
   7
   A model-to-model transformer
   transforms a universal CNA
   definition (UCAML) into a
   specific ECP format (Kubernetes
   manifests, Swarm compose
   files, etc.).
   • The runtime environment is
   a user decision (other like
   Jolie, platform agnostic).
   • But the runtime specifics
   must not be modeled on the
   application level
   (infrastructure agnostic).
   

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8. Example („Hello World“)
   Elastic webservice for primality checks
   Prof. Dr. rer. nat. Nane Kratzke
   Computer Science and Business Information Systems
   8
   Ucaml::application('prime-service-app',
   services: [
   Ucaml::service('prime-service‘,
   expose: [8888 => 80],
   request: Ucaml::request(cpu: 100, memory: 256, ephemeral_storage: 2),
   scale: Ucaml::scalingrule(min: 1, max: 10, cpu: 66),
   scheduling: Ucaml::constraint(
   'policiy': 'EU-US privacy shield',
   'country': 'ge'
   ),
   ports: [8888],
   container: Ucaml::container('prime-unit', 'transit/primesvc:latest',
   cmd: 'ruby hw-service.rb',
   ports: [80]
   )
   )
   ]
   )
   R1 : Containerized
   deployments (encapsules
   all the logic)
   R2 : Scalable
   services
   R3 : Pragmatic
   description
   R1 : Discoverable
   services
   R4 : Multi-
   Cloud
   contraints
   

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9. All together …
   9
   R1 : Containerized deployments
   R2: Scalable Applications
   R3: Compendiously and pragmatic
   R4 : Multi-Cloud Support
   R5: Infrastructure agnostic
   R6: Elastic runtime environment
   UCAML (this paper)
   PLAIN
   Kratzke, N. (2017). Smuggling Multi-Cloud Support
   into Cloud-native Applications using Elastic Container
   Platforms. In Proceedings of the 7th Int. Conf. on Cloud
   Computing and Services Science (CLOSER 2017)
   

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10. Evaluation
    E1 + E2
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    10
    See: https://microservices-demo.github.io/
    „Sock Shop simulates an e-
    commerce website that sells
    socks. It is intended to aid the
    demonstration and testing of
    microservice and cloud native
    technologies.“
    

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11. Evaluation
    E1 + E2
    (Practicability)
    To evaluate the usability [R3]
    we described a Sock-Shop needing
    [R1, R2]
    deployed the Sock-Shop to Kubernetes,
    and Docker Swarm [R6] in AWS, Azure,
    GCE and OpenStack [R4]
    E3
    (Transferability)
    For demonstrating IaaS
    independence [R4]
    we transfered the deployment at
    runtime between IaaS
    infrastructures of
    Amazon Web Services, Microsoft
    Azure, Google Compute Engine and
    a OpenStack installation.
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    11
    

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12. How to measure language pragmaticism?
    Well, let‘s try it …
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems 12
    * without autoscaling
    650
    500
    300
    170
    60
    K8S Nomad* Mesos/Marathon* Swarm* UCAML
    Lines of code
    (necessary to express the Sock-Shop)
    proposed
    approach
    LoCs taken from the official Sock-Shop repository. Platform-specific deployment files.
    

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13. Results of E3:
    Transfers between AWS, GCE, Azure and OpenStack
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    13
    Transfer of a 1+5 cluster (one master, five workers)
    Only Kubernetes data presented
    (Docker Swarm basically the same)
    

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14. Conclusion
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    14
    • Two independent but complementary engineering problems: platform transferability
    (PLAIN) and platform-agnostic application definition (UCAML).
    • For UCAML we rated DSL pragmatism and practitioner acceptance higher than
    richness of DSL expressions.
    • The DSL is intentionally designed for container and microservice architectures but
    has limitations outside this scope. This enables DSL simplicity but reduces
    possible use cases.
    • The DSL supports currently the following container platforms:
    • Kubernetes
    • Docker Swarm
    • Evaluation on the following IaaS infrastructes (approx. cloud marketshare):
    • AWS, GCE, Azure
    • OpenStack
    • Because it is infrastructure and platform agnostic further infrastructures and
    platforms can be extended.
    70%
    

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15. Acknowledgement
    • Puzzle: Pixabay (CC0 Public Domain, PIRO4D)
    • Definition: Pixabay (CC0 Public Domain, PDPics)
    • Macro/Micro Architecture: isa-principles.org (CC-SA 3.0, innoQ GmbH)
    • Checklist: Pixabay (CC0 Public Domain, Tumiso)
    • Road Ahead: Pixabay (CC0 Public Domain, Nel_NZ)
    • Air Transport: Pixabay (CC0 Public Domain, WikiImages)
    • All cliparts: openclipart.com (CC0 Public Domain)
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    15
    Picture Reference
    Our research is funded by German Federal Ministry of Education
    and Research (13FH021PX4).
    Paper URL
    Presentation URL
    Speaker Deck
    

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16. About
    Prof. Dr. rer. nat. Nane Kratzke
    Computer Science and Business Information Systems
    16
    Nane Kratzke
    CoSA: http://cosa.fh-luebeck.de/en/contact/people/n-kratzke
    Blog: http://www.nkode.io
    Twitter: @NaneKratzke
    GooglePlus: +NaneKratzke
    LinkedIn: https://de.linkedin.com/in/nanekratzke
    GitHub: https://github.com/nkratzke
    ResearchGate: https://www.researchgate.net/profile/Nane_Kratzke
    SlideShare: http://de.slideshare.net/i21aneka
    

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