![interface mongodb compass on gcp instance interface mongodb compass on gcp instance](https://cdn-images-1.medium.com/max/2000/1*SPKof-LyFvx4ruB0AzEHOA.png)
Key features of Cloud Functions include automatic scaling, high-availability, fault-tolerance, no servers to provision, manage, patch or update, only pay while your code runs, and they easily connect and extend other cloud services. Google Cloud FunctionsĪccording to Google, Cloud Functions is Google’s event-driven, serverless compute platform. proto file to generate data access classes. Once you have defined your messages, you run the protocol buffer compiler for your application’s language on your.
![interface mongodb compass on gcp instance interface mongodb compass on gcp instance](https://webassets.mongodb.com/_com_assets/cms/super%20bowl%201-65456502ac.png)
Interface mongodb compass on gcp instance series#
Protocol Buffers are 3 to 10 times smaller and 20 to 100 times faster than XML.Įach protocol buffer message is a small logical record of information, containing a series of strongly-typed name-value pairs. The devices contain a variety of common sensors, including humidity and temperature, motion, and light intensity.Īccording to Google, Protocol Buffers ( aka Protobuf) are a language- and platform-neutral, efficient, extensible, automated mechanism for serializing structured data for use in communications protocols, data storage, and more. Each IoT device is installed in a different physical location. In this demonstration, we will collect environmental sensor data from a number of IoT device sensors and stream that telemetry over the Internet to Google Cloud. They may prefer to transmit telemetry over HTTP using TCP, or securely, using HTTPS (HTTP over TLS). Similarly, depending on the performance requirements and type the application, organizations may not need or want to start out using IoT/IIOT industry standard data and transport protocols, such as MQTT (Message Queue Telemetry Transport) or CoAP (Constrained Application Protocol), over UDP (User Datagram Protocol). Academic institutions, research labs, tech start-ups, and many commercial enterprises want to leverage the Cloud for IoT applications, but may not be ready for a fully-integrated IoT platform or are resistant to Cloud vendor platform lock-in. In reality, not everyone needs a fully integrated IoT solution. They are capable of scaling to tens-of-thousands of IoT devices or more and massive amounts of streaming telemetry. All of these solutions are marketed as industrial-grade, highly-performant, scalable technology stacks. Amazon has AWS IoT, Microsoft Azure has multiple offering including IoT Central, IBM’s offering including IBM Watson IoT Platform, Alibaba Cloud has multiple IoT/IIoT solutions for different vertical markets, and Google offers Google Cloud IoT platform. Most of the dominant Cloud providers offer IoT (Internet of Things) and IIotT (Industrial IoT) integrated services. Aggregate, analyze, and build machine learning models with the data using tools such as MongoDB Compass, Jupyter Notebooks, and Google’s AI Platform Notebooks. Collect IoT sensor telemetry using Google Protocol Buffers’ serialized binary format over HTTPS, serverless Google Cloud Functions, Google Cloud Pub/Sub, and MongoDB Atlas on GCP, as an alternative to integrated Cloud IoT platforms and standard IoT protocols.