at the edge of the network instead of only in the cloud. (Watson IoT Platform recently added an Edge Analytics SDK. Try out this recipe, Getting Started with Edge 
Incremental IoT security for the enterprise: Authenticating user API calls through IAM
The Watson IoT Platform Analytics team has been hard at work on a new feature enabling analytics at the edge of the network. Weannouncedthe forthcoming capabilities back in 2016 with Cisco and several of our joint beta customers. Today, our edge analytics are live in the Watson IoT Platform with anSDK that will allow almost any gateway to host our edge analytics. With these new capabilities, you can configure your analytics in the cloud then push them out to edge-ready gateways (now available from several partners) that sit out in the network close to the source of device and sensor data.
Updated link for our blog announcing the Edge Analytics SDK go live:
With Watson IoT Platform Edge Analytics, we can analyze data where it makes the most sense while filtering out low value data and forwarding high value data to the cloud. We enable customers to leverage the power of the cloudflexibility, ability to scale up and down, and rich services and analyticswith the ability to distribute analytics to the source to monitor more data, respond faster, and still deliver the right data to the cloud for deeper analysis.
WISeKey To Showcase secure IoT solution Integrated with IBMs Watson IoT platform at Hannover Messe 2018
Edge Technical Preview Now Available
Is this service (Edge Analytics) available for public ?
As Harriet Green described it in the announcement:
Modelling Digital Twins in Watson IoT Platform Beta
Program Director, Watson IoT Platform Analytics Twitter: @gtkwahoo
Arm and IBM Simplify IoT and Data Analytics
Why is this important? Because getting access to data can be a challenge, and analyzing data at the right time and place is crucial for making decisions about operations. You need to act on some data in near real-time, close to the source to ensure continuous operations run smoothly, and other data needs deeper analysis to understand broader implications and cross site, cross fleet patterns.
4 comments onIntroducing Edge Analytics!
Charith, it is included as part of the Watson IoT Platform. We just opened our Edge Analytics SDK beta back in Decemberlink follows. If you are interested please let me know. See this blog for the beta announcement:
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Its about analyzing time-critical information on site, in real time. And its about filtering out other data, moving it to the cloud, integrating it with important contextual information, and using it to inform strategic decision-making and long-term investments. Put simply, its about maximizing the time to benefit of all IoT data.
A variety of operations and solutions can benefit from edge analytics. For example, remote operations such as mining, drilling, pipelines, solar and wind farms, and power substations often have constraints on their communication channels including intermittent connectivity, limited bandwidth, and higher cost of transmitting data. In these cases, you need to manage the flow of data while responding locally with low latency and still forward a subset of data to a central location for deeper analysis. In continuous process industries such as manufacturing plants, refineries, chemical plants, and power generation, operations run 24/7 and real-time decisions must be made on site. They need a solution that allows them to tap into new analytics capabilities, such as cognitive and predictive analytics, while maintaining autonomy to process data and make fast, automated decisions locally regardless of network connectivity back to the enterprise or cloud.