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CloudBrew 2016 - Building IoT solution with Service Fabric

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When building your IoT solution you face different steps. They normally include Device registration, Data Ingestion, Data processing and Data analysis. So come hear how to model this process on micro services architecture and then hosting whole thing on premise or on a cloud with Azure Service Fabric.

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CloudBrew 2016 - Building IoT solution with Service Fabric

  1. 1. Onsight Building IoT solution with Service Fabric
  2. 2. Onsight Teemu Tapanila  Microsoft Azure MVP  Architect, OnSight Helsinki oy  Microsoft Certified Trainer Teemu@onsight.fi @TapanilaT
  3. 3. Onsight Topics  Why Azure Service Fabric  Device Registration  Data Ingestion  Data processing  Data analysis
  4. 4. Onsight Microsoft Azure Service Fabric A platform for reliable, hyperscale, microservice-based applications Microservices Azure Windows Server Linux Hosted Clouds Windows Server Linux Service Fabric Private Clouds Windows Server Linux High Availability Hyper-Scale Hybrid Operations High Density Rolling Upgrades Stateful services Low Latency Fast startup & shutdown Container Orchestration & lifecycle management Replication & Failover Simple programming models Load balancing Self-healingData Partitioning Automated Rollback Health Monitoring Placement Constraints
  5. 5. Onsight Battle-hardened for over 5 years
  6. 6. Onsight What is a microservice?  Is (logic + state) that is independently versioned, deployed, and scaled  Has a unique name that can be resolved  e.g. fabric:/myapplication/myservice  Interacts with other microservices over well defined interfaces and protocols like REST  Remains always logically consistent in the presence of failures  Hosted inside a “container” (code + config)  Can be written in any language and framework  Developed by a small engineering team
  7. 7. Onsight Types of microservices  Stateless microservice  Has either no state or it can be retrieved from an external store  There can be N instances  e.g. web frontends, protocol gateways etc.  Stateful microservice  Maintain hard, authoritative state  N consistent copies achieved through replication and local persistence  e.g. database, documents, workflow, user profile, shopping cart etc.
  8. 8. Node Node Node Node Node Node
  9. 9. Time = t1 83 76 50 46 64 New Node arrived61 Time = t2 83 61 50 46 Failures Detected cluster reconfigured 83 76 64 50 46 Time = t0 Nodes failed
  10. 10. System Services Failover manager Cluster manager Naming Image store
  11. 11. Queues Storage 3-Tier service pattern Front End (Stateless Web) Stateless Middle-tier Compute Cache      Load Balancer
  12. 12. Stateful Middle-tier Compute Stateful services: Simplify design, reduce latency Front End (Stateless Web) data stores used for analytics and disaster recovery      Load Balancer
  13. 13. Onsight Device Registration  Device needs to be registered when it gets connected to the system.  This includes normally authentication keys and serial number  When device gets registered you should assing it value which you will later use for sharding
  14. 14. Onsight Data Ingestion  Gathered data from 1 data source is not so important normally  Real-time data ingestion vs batch ingestion
  15. 15. Onsight Data Ingestion
  16. 16. Onsight Data processing  Visibility to data averages on grouping level (Machine, Building, Floor or etc)  Logic based on value changes
  17. 17. Stateful Middle-tier Compute Data ingestion & Processing Front End (Stateless Web) data stores used for analytics and disaster recovery Load Balancer
  18. 18. Onsight Data processing Room Stateful Service Floor Stateful Service Building Stateful Service Campus Stateful Service
  19. 19. Onsight Data Analysis  Data is stored outside of service fabric for processing  Most cases makes sense of using other tools to build the analysis platform than Service Fabric
  20. 20. Microsoft Azure Service Fabric A platform for reliable, hyperscale, microservice-based applications Microservices Azure Windows Server Linux Hosted Clouds Windows Server Linux Service Fabric Private Clouds Windows Server Linux High Availability Hyper-Scale Hybrid Operations High Density Rolling Upgrades Stateful services Low Latency Fast startup & shutdown Container Orchestration & lifecycle management Replication & Failover Simple programming models Load balancing Self-healingData Partitioning Automated Rollback Health Monitoring Placement Constraints
  21. 21. Onsight Thank you! Teemu@onsight.fi @TapanilaT

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