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Flogo: Event-Driven Ecosystem with Leon Stigter and Matt Ellis

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Manage episode 219674784 series 1439570
Content provided by Cloud Engineering – Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Cloud Engineering – Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A smart security camera takes in a high volume of video images and processes those images using a set of machine learning models. Those models can be used to identify interesting snippets of movement throughout the day, and decide which of those snippets to keep. Some of the video snippets might contain movement of birds–but other video snippets might contain footage of intruders.

As the video stream is processed on the smart security camera, and machine learning models are used to classify the entities in the video stream, some of the data gets thrown out as useless. Some of the data gets sent to the cloud for additional processing. Some of the data might trigger an alert that there is an intruder on the premises. Each piece of video data is an “event”. These events are processed and acted upon.

Modern applications are highly interactive, and have lots of “events”. Other examples of event data streams are website traffic data, self-driving car data, time-series logging data, and video game session data. Building applications that respond to these high volumes of events requires us to program triggers to react to data streams, actions to take in response to the data streams, and workflows to orchestrate what the overall picture of our application is doing as the application is consuming this large data stream.

Flogo is an event-driven ecosystem for building applications around streams of events. Leon Stigter and Matt Ellis work on Flogo at TIBCO, and they join the show to discuss event-driven application development and their work on Flogo. They also talk about the constraints of machine learning applications at the edge, and how event processing systems like Flogo can be used to handle large data streams on edge devices.

The post Flogo: Event-Driven Ecosystem with Leon Stigter and Matt Ellis appeared first on Software Engineering Daily.

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366 episodes

Artwork
iconShare
 

Archived series ("Inactive feed" status)

When? This feed was archived on February 23, 2023 05:07 (3y ago). Last successful fetch was on January 13, 2023 00:33 (3y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 219674784 series 1439570
Content provided by Cloud Engineering – Software Engineering Daily. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Cloud Engineering – Software Engineering Daily or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A smart security camera takes in a high volume of video images and processes those images using a set of machine learning models. Those models can be used to identify interesting snippets of movement throughout the day, and decide which of those snippets to keep. Some of the video snippets might contain movement of birds–but other video snippets might contain footage of intruders.

As the video stream is processed on the smart security camera, and machine learning models are used to classify the entities in the video stream, some of the data gets thrown out as useless. Some of the data gets sent to the cloud for additional processing. Some of the data might trigger an alert that there is an intruder on the premises. Each piece of video data is an “event”. These events are processed and acted upon.

Modern applications are highly interactive, and have lots of “events”. Other examples of event data streams are website traffic data, self-driving car data, time-series logging data, and video game session data. Building applications that respond to these high volumes of events requires us to program triggers to react to data streams, actions to take in response to the data streams, and workflows to orchestrate what the overall picture of our application is doing as the application is consuming this large data stream.

Flogo is an event-driven ecosystem for building applications around streams of events. Leon Stigter and Matt Ellis work on Flogo at TIBCO, and they join the show to discuss event-driven application development and their work on Flogo. They also talk about the constraints of machine learning applications at the edge, and how event processing systems like Flogo can be used to handle large data streams on edge devices.

The post Flogo: Event-Driven Ecosystem with Leon Stigter and Matt Ellis appeared first on Software Engineering Daily.

  continue reading

366 episodes

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