Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.

AWS Intelligent at Edge for IoT

841 Aufrufe

Veröffentlicht am



近年來,物聯網(IoT)產業正以驚人的速度成長中,相關的應用與服務也陸續問市,而包含物聯網(IoT)、人工智慧(AI)與機器學習(machine learning)等科技的革新,致使從新創企業乃至傳統產業皆投入這一波新科技的發展,更添產業動能,尤其是在製造業、運輸及物流、公共安全、智慧城市等幾大面向。

據消費及商業企業服務供應商JT Group白皮書預估,到2020年全球物聯網累計裝置量(installed base)將達204.1億台。更多企業也將改變其商業模式,由產品導向轉為服務導向,客戶機構採購的不再只是硬體產品,而是尋求整套完整的解決方案。AWS 即將於3/7 (四) 舉辦『AWS AIoT未來智造高峰論壇』,持續以創新、全球視野帶領您與您的企業一起探索物聯網價值最大化的關鍵。

  • Als Erste(r) kommentieren

AWS Intelligent at Edge for IoT

  1. 1. AWS Intelligent at Edge for IoT Young Yang AWS Solutions Architect beyoung@amazon.com Drive Warehouse Efficiencies with the Same AWS IoT technology That Powers Amazon Fulfillment
  2. 2. 亞馬遜人工智慧應用服務- 以亞馬遜物流為例 Amazon Kindle Reader Revolutionizing the reading experience Amazon Fresh Grocery Delivery Amazon Go Advanced Shopping Amazon Studios Revolutionizing Music and Film Production 尊榮會員服務 雲端服務 (44%全球市佔) 智慧電視智慧語音助理 客戶消費體驗回顧市集 一小時貨物送達服務 新創產品銷售 電子書 一鍵點擊訂購服務 亞馬遜物流 無人機運送 一日生鮮送達服務 無人商店 影音串流服務
  3. 3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  4. 4. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  5. 5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. What you expect in this session The Transformation Path from Monolithic to Microservices in Amazon.com Fulfillment Center
  6. 6. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  7. 7. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Transition period System integrators point of view: From User To Development Collaboration
  8. 8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Big bang or incremental change? Evolution Not revolution
  9. 9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Machine as a service ≠ IIoT Equipment life cycle Cloud connectivity issues Security
  10. 10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  11. 11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  12. 12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  13. 13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  14. 14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  15. 15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  16. 16. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Data from Assets – The Foundation of Digital Twins Unable to link data together 96% of industrial state data is not used Data collected too infrequently 39% of Manufacturers do not regularly collect data Data difficult to access 66% of industrial companies find data is difficult to access Why? SCM World/Cisco “Smart Manufacturing & the Internet of Things 2015”
  17. 17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Decades of this... Source: https://xkcd.com/927/
  18. 18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. ... resulted in this! Operations (OT) Enterprise (IT) IT Systems CRM Asset Management ERP Supply Chain Finance Maintenance Compliance Shopfloor Single machine with multiple components following different standards Complete production line likely to have many machines with different protocols Challenge: Get data from OT to IT and make it usable!
  19. 19. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. ISA-S99, Industrial Automation and Control Systems Security
  20. 20. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Manufacturing networking 101 Internet Enterprise network Manufacturing network VLAN VLAN VLAN VLAN MES/Historian Enterprise apps Shop floor ISA-S99, Industrial Automation and Control Systems Security
  21. 21. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shop Floor to AWS Cloud Connectivity Internet Enterprise DMZ Industrial Machine Tool / PLC ISA-S99, Industrial Automation and Control Systems Security
  22. 22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shop Floor to AWS Cloud Connectivity Internet Enterprise DMZ Industrial Greengrass VPC VPN Connection Direct Connect Machine Tool / PLC ISA-S99, Industrial Automation and Control Systems Security
  23. 23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Greengrass/VPC Internet Corporate DMZ Industrial Greengrass VPC ISA-S99, Industrial Automation and Control Systems Security
  24. 24. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Manufacturing networking - IoT connectivity Internet Enterprise network Manufacturing network VLAN VLAN VLAN VLAN MES/Historian Enterprise apps Shop floor AWS IoT AWS Greengrass
  25. 25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Operations (OT) Solving Industrial Data Extraction Factory Machines Enterprise (IT) IT Systems CRM Asset Management ERP Supply Chain Finance Maintenance Compliance Protocol conversion Modbus conversion OPC UA conversion Gateway Custom / Proprietary Protocol MQTT
  26. 26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. IIoT Design Pattern – ETL @ Edge Load • Buffering • Compression • Gateway  Cloud Transform • Formats (CVS  JSON) • Filtering • Data translation Extract • Protocol conversion • Data rate • Polling vs Events Operations (OT) Gateway Extract Transform Load
  27. 27. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  28. 28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Industrial communication protocols Sends data to PLCs or RTUs Feeds data to SCADA system Supervise and control from an operational terminal programmable logic controllers (PLCs) or remote terminal units (RTUs). IEC 61158 SCADA Protocols
  29. 29. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Communication requirements - Throughput - Scheduled - Low downtime - Hostile environments - Scalable
  30. 30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Fieldbus examples Non-ethernet Ethernet • Modbus RTU/ASCII • Profibus • DeviceNet (CIP) • ControlNet (CIP) • IO-link • AS-i • Modbus/TCP • Profinet • Ethernet/IP (CIP) • CC-Link • PowerLink • EtherCAT
  31. 31. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Supervisory examples Ethernet • Modbus/TCP • S7-Comm • Ethernet/IP • PCCC • SLMP • OPC-UA/OPC-DA
  32. 32. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. SCADA Protocols: The Good, the Bad, and the Ugly Allen-Bradley DF1 Allen-Bradley DH+ Allen-Bradley EN/IP Amocam ARCNet ATS BITbus CANbus CA CCM2 CDCI CDCII Conitel DeviceNet Daniel DL130 DNP 3.0 Elliott Enron Modbus F&M Ferranti MK2A Galveston-Houston GPE GSI Harris 5000/5500/6000 Hansa S002 HART Hayes Honeywell DE Kodata L&J LANDAC Landis & Gyr Micromotion Flowscale MODBUS ASCII MODBUS RTU MODBUS Plus MPS9000 MTS Omron Host Link Optomux PERT 2631 Plessey TC6 RDACSII REDAC 70H RNIM Siemens 3964R Siemens RK512 SLIP SNET -I SNET –II GE SRTP TANO Model 10 TANO Model 100 Tejas Total-Flow Transit Bus TRW 9550 Valmet Series 5 Transmitton MT700 TRW S-70 TRW S-703 Varec Wesdac 4F WISP Wireless HART
  33. 33. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. SCADA Systems have been around for over 40 years now. From an operations point of view, they have been doing their jobs quite well. But we need to re-think SCADA architectures and infrastructures to not only meet the strict requirements of a mission-critical real- time control system, but also provide this business-critical information to other data consumers within the enterprise.
  34. 34. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Operations (OT)Enterprise (IT) Manufacturing environment IT Systems CRM Asset Management ERP Supply Chain Finance Maintenance Compliance SCADA, DCS, etc. Various Protocols
  35. 35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. International standards IEC 61131-3 Programmable Logic Controllers (PLC)
  36. 36. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Hardware Siemens Allen Bradley Mitsubishi CoDeSys SoftPLCsEstablished PLCs
  37. 37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Chosen design Industrial PC—Linux based OS SoftPLC On premises SCADA system, running on Linux hosts.
  38. 38. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Ignition: The Ultimate in Data Acquisition
  39. 39. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Injector This new Injector module easily connects any tag data from the Ignition platform into the Amazon Web Services (AWS) cloud services infrastructure. With a simple configuration, tag data will flow into Amazon Kinesis. • Connects to any TAG Data (including all properties) • Easy to configure • For use on Ignition Gateway or Ignition Edge
  40. 40. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  41. 41. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  42. 42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. From Local Server to AWS Cloud EC2 RDS
  43. 43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Industrial Equipment Manufacturing Execution Systems (MES) Ignition Edge & AWS Greengrass L0 L1 L2 L3 L4 L5 ERP/SAP (financials, etc.) Cloud MQTT-SP-B AWS IoT Telemetry channel (MQTT) File channel (HTTPS) AB CIP Protocol Ignition Gateway PLC AWS Greengrass on Raspberry Pi AB PLC – Micrologix 1100 Machines AB CIP/Modbus/OPC/ other industrial protocols
  44. 44. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. ISA-95 in the context of the AWS Cloud Level 1 Level 2 Line/machine control Animation direct control Level 3 Level 4 Description Line/machine supervision Manufacturing Operations Management Business planning & logistics MES/ Historian ERP/PLP/SCM App/SystemFunction Line/cell execution Business operations SCADA/HMI Supervisory control DCS/PLC/RTU Level 0 Physical values Raw data event signals I/O Sensor AWS Services Enterprise apps in the cloud Data ingestion & analytics AWS Greengrass IoT Device FreeRTOS
  45. 45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Benefits of the transformation
  46. 46. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Cost Saving Business viability
  47. 47. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. When the impact of change is small, release velocity can increase Monolith Does everything Microservices Does one thing
  48. 48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS CodeDeploy
  49. 49. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  50. 50. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Existing designs W M S W C S M a c h i n e s e n s o r s / a c t u a t o r s Rack mount ed in data center Local servers Rigid monolit hi c design
  51. 51. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. New design W M S W C S M a c h i n e s e n s o r s / a c t u a t o r s AWS Local servers and Greengr as s Modul ar design
  52. 52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. International standards ANSI ISA-S88 Batch control Enterprise Site Area Process Cell Amazon Customer Fulfillment Site A Site B . . . Pack Receive . . . Pack Machine Labeler . . . 1:n 1:n 1:n Unit 1:n Glue System . . . Equipment Module 1:n Conveyor Divert . . .
  53. 53. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Modular design
  54. 54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Challenges Monetization mechanism Controller Permission Sensors Actuators Must connect to millions of end points spread out over millions of acres CPU load is highly variable and must be completed in a fixed time window End user engagement needs to assume a very mobile and non-technical customer Multi-system orchestration approach needed to combine all required data in near real-time
  55. 55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS IoT Buttons/Lambda/messaging
  56. 56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS IoT Buttons/Lambda/messaging
  57. 57. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Operator can call assistance from: - Water spider (one click) - Engineer (long click) Results: - Text message to the right person - Message on SCADA AWS IoT Buttons/Lambda/messaging
  58. 58. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  59. 59. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Low Latency Low Volume High Latency High Volume Technique Need Response Applications Cloud Massive datasets for long term analysis Days to Minutes • Deep Learning Fog M2M communication and analysis of batch data from multiple devices Minutes to Milliseconds • Industrial • Wearables – Data Tracking Edge Real-time decision making off of one devices data Milliseconds to Nanoseconds • Real-time traffic Monitoring • Robotics • Streaming Video • VR/AR Edge Fog and Cloud Computing
  60. 60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Examples of learning Classification Prediction & forecasting Route optimization Anomaly detection Object identification Language processing
  61. 61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Key applications Vision, Robotics & Pattern Recognition Source McKinsey
  62. 62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. SP BarCode - Shipping information - Package Contents Carton BarCode - Carton weight - Carton dimensions Shipping Label - Shipping information - Delivery Vendor (UPS 2nd Day Air) - Vendor tracking code
  63. 63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  64. 64. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Greengrass Lambda Function Machine Learning Cameras Scale Sensors Actual weight + tolerance < Expected weight: (weight of package contents + carton weight) Actual Shipping Label <> Expected Shipping Label ML Models: - CV: Segmentation - CV: Text Extraction WMS The intelligent at Edge for IoT
  65. 65. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Shipping label application LPA2 BCR Kinesis Streams 3rd party software SNS Topic S3Storage Lambda LPA 1 S3Storage • Location ID • Item ID • UoM[n] Elastic Beanstalk EC2 Amazon QuickSight Amazon Redshift AWS IoT UoM: Unit of Measures, weight, height, width, length, and etc. BCR: Bar Code Reader
  66. 66. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sortation
  67. 67. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sortation
  68. 68. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sortation
  69. 69. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sortation
  70. 70. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sortation BCR AWS IoT • Location ID • Induct ID • Item ID • UoM[n] A B C D E M XT • Vibration sensors • Motor current • Speed JT Energy consumption • Wh (consumed/generated) • Phase voltages • Phase currents • Active power/phase
  71. 71. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Greengrass on existing machines
  72. 72. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Greengrass on new machines
  73. 73. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  74. 74. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Data from Assets – The Foundation of Digital Twins Unable to link data together 96% of industrial state data is not used Data collected too infrequently 39% of Manufacturers do not regularly collect data Data difficult to access 66% of industrial companies find data is difficult to access Why? SCM World/Cisco “Smart Manufacturing & the Internet of Things 2015” Greengrass/VPC Internet Corporate DMZ Industrial Greengrass VPC ISA-S99, Industrial Automation and Control Systems Security Operations (OT) Solving Industrial Data Extraction Factory Machines Enterprise (IT) IT Systems CRM Asset Management ERP Supply Chain Finance Maintenance Compliance Protocol conversion Modbus conversion OPC UA conversion Gateway Custom / Proprietary Protocol MQTT
  75. 75. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Industrial Equipment Manufacturing Execution Systems (MES) Ignition Edge & AWS Greengrass L0 L1 L2 L3 L4 L5 ERP/SAP (financials, etc.) Cloud MQTT-SP-B AWS IoT Telemetry channel (MQTT) File channel (HTTPS) AB CIP Protocol Ignition Gateway PLC AWS Greengrass on Raspberry Pi AB PLC – Micrologix 1100 Machines AB CIP/Modbus/OPC/ other industrial protocols New design W M S W C S M a c h i n e s e n s o r s / a c t u a t o r s AWS Local servers and Greengrass Modular design AWS Greengrass Lambda Function Machine Learning Cameras Scale Sensors ML Models: - CV: Segmentation - CV: Text Extraction WMS The intelligent at Edge for IoT
  76. 76. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Smart operations Smart products and services Connectivity and internet technology Smart sensors and actuators Cloud processing and storage Big data analytics and artificial intelligence Two predominant outcomes Smart products and services are brought to market with smart operations
  77. 77. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Smart Products and Services Capabilities Machine Connectivity Machine Data Integration Platform Machine as a Service Advanced Machine Optimization • Rapid commissioning • Machine security • Enable template- based machine provisioning • Factory / On-prem • Enable machine OEE monitoring • MTC & OPC offload • Scaled factory data acquisition • Advanced security • Process health • Identity security framework • Machine to cloud framework • Machine tuning • Predictive maintenance • Secure bi-directional data • Secure remote access • Time sensitive networking • High speed, standards based machine I/O and control networking • Advanced control integration with HMI visibility of network • Advanced analytics • Machine Learning Value
  78. 78. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Thank You
  79. 79. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  80. 80. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS industrial IoT reference architecture Amazon SNS AWS Greengrass IoT rule (all data) Amazon S3 Data Lake Kinesis Data Firehose Protocol conversion Email AWS SMS Industrial equipment Industrial equipment Amazon Glacier Kinesis Data AnalyticsProtocol conversion ML inference AWS IoT/AWS Greengrass/ AWS IoT Device Management/ AWS Device Defender Amazon SageMaker ML models Amazon QuickSight Amazon Kinesis Streams Kinesis Data Firehose IoT anomaly data repository Amazon Athena Amazon Athena IoTrule(alerts) Realtimeand historicalvisualization CloudWatch Amazon Cognito CloudTrail AWS Config IoT Cert IAM AWS IoT Analytics
  81. 81. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS manufacturing reference architecture (Brownfield) AWS Greengrass Amazon S3 Data Lake Kinesis Data Firehose MES Factory machines Protocol conversion ML inference AWS IoT Amazon SageMaker Machine Learning Amazon QuickSight Data visualization/reporting Amazon Athena Historian Storage gateway Amazon EMR Amazon EBS Amazon EC2 AWS Batch Amazon AppStream Amazon EBS Amazon EC2 HPC workloads Enterprise workloads (SAP) AWS DMS Amazon RDS Local servers Amazon Redshift Data warehouse Dataingestion API Gateway interfaces N:1 Plant manager Quality manager H&S officer Production planner Plant maintenance Production manager Engineer OSI PI connector AWS Snowball Edge Data migration
  82. 82. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Manufacturing Reference Architecture (Brownfield) Greengrass Edge/GW S3 Data Lake Kinesis MES Factory Machines ML Inference IoT Core Sage Maker ML QuickSight Business Intelligence Athena Historian Storage GW EMR EBS EC2 Batch AppStreamEBS EC2 E&D Workloads (PLM/HPC/CAE) Enterprise Workloads (SAP ERP/CRM)DMS RDS Local Servers RedShift Data Warehouse DataIngestion API N:1 SiteWise Snowball Edge Smart Products DynamoDB Lambda IoT Core Amazon Forecast Plant Maint. Planning Business Functions Greengrass Connectors IoT Analytics Timestream Outpost IoT Events EC2 Lambda Business Logic
  83. 83. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Workshop Architecture Node Red Lambda function VPC Subnet Windows EC2 PLC EC2 Instance
  84. 84. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Ignition AWS Greengrass Lambda Function

×