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Umu seminar 02-2019

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Invited talk at UMU university on service management in fog environment

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Umu seminar 02-2019

  1. 1. Managing Services in Heterogeneous Environments Adaptive Approaches Towards Non-Functional Requirements Satisfaction Monica Vitali - Politecnico di Milano monica.vitali@polimi.it
  2. 2. Once Upon the Time... Applications were designed as monoliths ● Pros: easy to manage, easy to monitor ● Cons: no scalability, no flexibility http://ryanjbaxter.com/2015/07/15/using-microservices-to-build-cloud-native-applications-part-1/
  3. 3. From Monoliths to Microservices Applications are decomposed in smaller specialised units ● Pros: high scalability, improved specialization ● Cons: complex management and monitoring http://ryanjbaxter.com/2015/07/15/using-microservices-to-build-cloud-native-applications-part-1/
  4. 4. From Microservices to Functions Applications are a composition of specialised functions. Execution is event-driven. Payed by execution time of the single function and not by running time of the thread. ● Pros: extremely scalable, no complex maintenance and building of infrastructure (serverless) ● Cons: difficult coordination and monitoring
  5. 5. From Monoliths to Functions https://medium.freecodecamp.org/serverless-is-cheaper-not-simpler-a10c4fc30e49
  6. 6. From Monoliths to Functions https://medium.freecodecamp.org/serverless-is-cheaper-not-simpler-a10c4fc30e49 Management complexity
  7. 7. Fog Computing https://erpinnews.com/fog-computing-vs-edge-computing During the cloud era all the applications moved from local to remote execution Smaller applications and IoT data volume are bringing them back to local
  8. 8. Managing Services An effective management of services depends on (i) the application architectural style and (ii) the infrastructure architecture. GOAL Keep non-functional requirements satisfied during the application life-cycle HOW? Making decisions on ... Where to deploy/move the microservices/functions composing the application -> COMPUTATION MOVEMENT Where to place the data the application is using -> DATA MOVEMENT
  9. 9. Monitoring System The monitoring system is the enabler of the application management It gives insights on the performance of the application It detects violations in SLA SLA is the agreement with the customer indicating the non-functional requirements for the execution of the services: ● QoS, Security & Privacy, Energy Efficiency, Data Quality => UTILITY
  10. 10. DITAS: Data Provisioning in Fog Environments DITAS Cloud Platform allows developers to design data-intensive applications, deploy them on a mixed cloud/edge environment and execute the resulting distributed application in an optimal way by exploiting the data and computation movement strategies
  11. 11. DITAS: Data Provisioning in Fog Environments DESIGN Data administrator Data sources offersregisters Bluprint repository Data source description + Data Utility Application Developer requests Data source description + Data Utility requirements Resolution engine DaaS - the resolution engine selects the best data source according to the application developer’s functional and non-functional requirements
  12. 12. DITAS: Data Provisioning in Fog Environments DEPLOY The VIRTUAL DATA CONTAINER hide the complexity of the data sources and their location and provides a personalised access to the data. TASK VDC query data Ensures SLA satisfaction through monitoring and enactment EXECUTE
  13. 13. DITAS: Data Provisioning in Fog Environments EXECUTE Movement Strategies consists of data and computation movement between resources in the cloud or in the edge and between customer’s resources and data administrator’s facilities Movement Strategies Data Utility requirements DU DQ QoS Security & Privacy + + + + + Decides the location of data and computation optimising the Data Utility
  14. 14. DITAS: e-health scenario Hospitals produce and store a huge amount of data As data administrator Hospitals can decide which data to share, who can access them, and which restrictions (e.g., due to privacy and security) will be applied As data consumer VDCs provide an abstract representation of patients’ data, taking care of movement across environments (edge vs cloud) and data transformations to comply with data protection regulations
  15. 15. DITAS: e-health scenario
  16. 16. P. Plebani, M. Salnitri, and M. Vitali, “Fog Computing and Data as a Service: A Goal-Based Modeling Approach to Enable Effective Data Movements,” in International Conference on Advanced Information Systems Engineering, 2018, pp. 203-219. P. Plebani, D. Garcia-Perez, M. Anderson, D. Bermbach, C. Cappiello, R. I. Kat, A. Marinakis, V. Moulos, F. Pallas, S. Tai, and M. Vitali, “Data and Computation Movement in Fog Environments: the DITAS Approach.” , 2018, vol. 1, pp. 249-266. P. Plebani, D. Garcia-Perez, M. Anderson, D. Bermbach, C. Cappiello, R. I. Kat, A. Marinakis, V. Moulos, F. Pallas, B. Pernici, and others, “DITAS: Unleashing the Potential of Fog Computing to Improve Data-Intensive Applications,” in European Conference on Service-Oriented and Cloud Computing, 2017, pp. 154-158. C. Cappiello, B. Pernici, P. Plebani, and M. Vitali, “Utility-Driven Data Management for Data-Intensive Applications in Fog Environments,” in International Conference on Conceptual Modeling, 2017, pp. 216-226. P. Plebani, D. Garcia-Perez, M. Anderson, D. Bermbach, C. Cappiello, R. Kat, F. Pallas, B. Pernici, S. Tai, and M. Vitali, “Information Logistics and Fog Computing: The DITAS Approach,” in 29th International Conference on Advanced Information Systems Engineering Forum (CAISE Forum), 2017, pp. 129-136. http://ditas-project.eu
  17. 17. Deployment based on Monitoring Capabilities E. Fadda, P. Plebani, and M. Vitali, “Optimizing Monitorability of Multi-cloud Applications,” in 28th International Conference on Advanced Information Systems Engineering (CAISE’16), 2016, pp. 411-426.
  18. 18. Deployment based on Monitoring Capabilities The application owner expresses QoS requirements and monitorability requirements E. Fadda, P. Plebani, and M. Vitali, “Optimizing Monitorability of Multi-cloud Applications,” in 28th International Conference on Advanced Information Systems Engineering (CAISE’16), 2016, pp. 411-426.
  19. 19. Deployment based on Monitoring Capabilities The application owner expresses QoS requirements and monitorability requirements Cloud Providers expresses QoS and monitoring capabilities E. Fadda, P. Plebani, and M. Vitali, “Optimizing Monitorability of Multi-cloud Applications,” in 28th International Conference on Advanced Information Systems Engineering (CAISE’16), 2016, pp. 411-426.
  20. 20. Deployment based on Monitoring Capabilities The application owner expresses QoS requirements and monitorability requirements Cloud Providers expresses QoS and monitoring capabilities Multi-cloud optimal deployment of microservices E. Fadda, P. Plebani, and M. Vitali, “Optimizing Monitorability of Multi-cloud Applications,” in 28th International Conference on Advanced Information Systems Engineering (CAISE’16), 2016, pp. 411-426.
  21. 21. Managing Services in Heterogeneous Environments Adaptive Approaches Towards Non-Functional Requirements Satisfaction Monica Vitali - Politecnico di Milano monica.vitali@polimi.it

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