Monat: Januar 2020

Six things to consider when using Video Indexer at scale

Your large archive of videos to index is ever-expanding, thus you have been evaluating Microsoft Video Indexer and decided that you want to take your relationship with it to the next level by scaling up.
In general, scaling shouldn’t be difficult, but when you first face such process you might not be sure what is the best way to do it. Questions like “are there any technological constraints I need to take into account?”, “Is there a smart and efficient way of doing it?”, and “can I prevent spending excess money in the process?” can cross your mind. So, here are six best practices of how to use Video Indexer at scale.

1. When uploading videos, prefer URL over sending the file as a byte array

Video Indexer does give you the choice to upload videos from URL or directly by sending the file as a byte array, but remember that the latter comes with some constraints.

First, it has file size limitations. The size of the byte array file is limited to 2 GB compared to the 30 GB upload size limitation while using URL.

Second and more importantly for your scaling, sending files using multi-part means high dependency on your network, service reliability, connectivity, upload speed, and lost packets somewhere in the world wide web, are just some of the issues that can affect your performance and hence your ability to scale. 

When you upload videos using URL you just need to give us a path to the location of a media file and we will take care of the rest (see below the field from the upload-video API).

To upload videos using URL via API you can check this short-code sample or you can use AzCopy for a fast and reliable way to get your content to a storage account from which you can submit it to Video Indexer using SAS URL.

2. Increase media reserved units if needed

Usually in the proof of concept stage when you just start using Video Indexer, you don’t need a lot of computing power. Now, when you want to scale up your usage of Video Indexer you have a larger archive of videos you want to index and you want the process to be at a pace that fits your use case. Therefore, you should think about increasing the number of compute resources you use if the current amount of computing power is just not enough.

In Azure Media Services, when talking about computing power and parallelization we talk about media reserved units (RUs), those are the compute units that determine the parameters for your media processing tasks. The number of RUs affects the number of media tasks that can be processed concurrently in each account and their type determines the speed of processing and one video might require more than one RU if its indexing is complex. When your RUs are busy, new tasks will be held in a queue until another resource is available.

We know you want to operate efficiently and you don’t want to have resources that eventually will stay idle part of the time. For that reason, we offer an auto-scale system that spins RUs down when less processing is needed and spin RUs up when you are in your rush hours (up to fully use all of your RUs). You can easily enable this functionality by turning on the autoscale in the account settings or using Update-Paid-Account-Azure-Media-Services API.

To minimize indexing duration and low throughput we recommend you start with 10 RUs of type S3. Later if you scale up to support more content or higher concurrency, and you need more resources to do so, you can contact us using the support system (on paid accounts only) to ask for more RUs allocation.

3. Respect throttling

Video Indexer is built to deal with indexing at scale, and when you want to get the most out of it you should also be aware of the system’s capabilities and design your integration accordingly. You don’t want to send an upload request for a batch of videos just to discover that some of the movies didn’t upload and you are receiving an HTTP 429 response code (too many requests). It can happen due to the fact that you sent more requests than the limit of movies per minute we support. Don’t worry, in the HTTP response, we add a retry-after header. The header we will specify when you should attempt your next retry. Make sure you respect it before trying your next request.

4. Use callback URL

Have you ever called customer service and their response was “I’m now processing your request, it will take a few minutes. You can leave your phone number and we’ll get back to you when it is done”? The cases when you do leave your number and they call you back the second your request was processed are exactly the same concept as using callback URL.

Thus we recommend that instead of polling the status of your request constantly from the second you sent the upload request, you can just add a callback URL, and wait for us to update you. As soon as there is any status change in your upload request, we will send a POST notification to the URL you sent.

You can add a callback URL as one of the parameters of the upload-video API (see below the description from the API). If you are not sure how to do it, you can check the code samples from our GitHub repo. By the way, for callback URL you can also use Azure Functions, a serverless event-driven platform that can be triggered by HTTP and implement a following flow.

5. Use the right indexing parameters for you

Probably the first thing you need to do when using Video Indexer, and specifically when trying to scale, is to think about how to get the most out of it with the right parameters for your needs. Think about your use case, by defining different parameters you can save yourself money and make the indexing process for your videos faster.

We are giving you the option to customize your usage in Video Indexer by choosing those indexing parameters. Don’t set the preset to streaming it if you don’t plan to watch it, don’t index video insights if you only need audio insights, it is that easy.

Before uploading and indexing your video read this short documentation, check the indexingPreset and streamingPreset parts to get a better idea of what your options are.

6. Index in optimal resolution, not highest resolution

Not too long ago, we were in times when HD videos didn't exist. Now, we have videos of varied qualities from HD to 8K. The question is, what video quality do you need for indexing your videos? The higher the quality of the movie you upload means the higher the file size, and this leads to higher computing power and time needed to upload the video.

Our experiences show that, in many cases, indexing performance has almost no difference between HD (720P) videos and 4K videos. Eventually, you’ll get almost the same insights with the same confidence.

For example, for the face detection feature, a higher resolution can help with the scenario where there are many small but contextually important faces. However, this will come with a quadratic increase in runtime (and therefore higher COGS) and an increased risk of false positives.

Therefore, we recommend you to verify that you get the right results for your use case and to first test it locally. Upload the same video in 720P and in 4K and compare the insights you get. Remember, No need to use a cannon to kill a fly.

Have questions or feedback? We would love to hear from you. Use our UserVoice page to help us prioritize features, leave a comment below or email VISupport@Microsoft.com for any questions.

We want to hear about your use case, and we can help you scale.
Quelle: Azure

Fueling intelligent energy with IoT

At Microsoft, building a future that we can all thrive in is at the center of everything we do. On January 16, as part of the announcement that Microsoft will be carbon negative by 2030, we discussed how advances in human prosperity, as measured by GDP growth, are inextricably tied to the use of energy. Microsoft has committed to deploy $1 billion into a new climate innovation fund to accelerate the development of carbon reduction and removal technologies that will help us and the world become carbon negative. The Azure IoT team continues to invest in the platforms and tools that enable solution builders to deliver new energy solutions, customers to empower their workforce, optimize digital operations and build smart, connected, cities, vehicles, and buildings.

Earlier, Microsoft committed $50 Million through Microsoft AI for Earth that provides technology, resources, and expertise into the hands of those working to solve our most complex global environmental challenges. Challenges like helping customers around the world meet their energy and sustainability commitments. Our partnership with Vattenfall illustrates how we will power new Swedish datacenter locations with renewable energy and our partnership with E.ON who manages low-voltage distribution grids is challenging the limits of traditional technology for low-voltage distribution grids through an inhouse IoT platform based on Microsoft Azure IoT Hub.

Over the past few years, our engineers have had the pleasure to connect with and learn from a large ecosystem of energy solution builders and customers that are proactively shifting their consumption priorities. Transmission system operators (TSOs) are focused on transforming grid operations while distribution system operators (DSOs) and utilities are approaching their customers with new solutions, and all participants are requesting better, more accurate, more secure data.

As millions of new electric vehicles are entering our roads, new challenges arise around the transformation of the energy grid that moves us in our daily commutes. At the heart of these transformations are solutions that help energy providers get connected, stay connected, and transform their businesses through devices, insights, and actions.

Late 2019, we announced updates to Azure IoT Central to help solution builders move beyond proof of concept to building business-critical applications they can brand and sell directly or through Microsoft AppSource. Builders can brand, customize, and make their own apps using extensibility via APIs, data connectors to business applications, repeatability, and manageability of their investment through multitenancy and seamless device connectivity. Two IoT Central energy app templates for solar panel and smart meter monitoring already help energy solution builders accelerate development.

Azure IoT Central Energy App Templates.

DistribuTECH 2020

DistribuTECH International is the leading annual transmission and distribution event that addresses technologies used to move electricity from the power plant through the transmission and distribution systems to the meter and inside the home. Held January 28 to January 30 in San Antonio, Texas, we invited 8 leading Energy solution builders to join us at DistribuTECH to demonstrate how they have leveraged Azure IoT to deliver amazing innovation. These partners will join Azure IoT Experts who are available to discuss your business scenarios or get more specific on IoT devices, working with IoT data and delivering a secure solution from the edge to the cloud.

Partners fueling intelligent energy

NXP EdgeVerse™ platform: intelligently manage grid load securely at the edge

The shift to vehicle electrification requires a completely different fueling infrastructure than gas-powered vehicles. Drivers of electric vehicles need to trust they can fuel for every occasion—everywhere, anytime and not get stranded. Every electric utility vehicle in a managed fleet, for example, must be authorized to charge without overloading the grid during peak times.

To manage grid load intelligently, edge computing and security becomes vital. NXP and Microsoft have demonstrated “Demand Side Management” of a smart electric vehicle charging grid and infrastructure running on NXP’s EdgeVerse™ using Azure IoT Central. This solution helps reduced development risk and speed time to market. NXP EdgeVerse includes the NXP Layerscape LS1012 processor and i.MX RT 1060 series, integrated in Scalys TrustBox Edge, to provide best-in-class power efficiency and the most secure (portable) level of communication solution that connects to Azure IOT Central. As the fueling model shifts from petroleum to electric, intelligent management of grid load balancing is key.

OMNIO.net: Danish IoT connectivity startup onboarding devices and unifying data

OMNIO.net, a Danish Industrial IoT connectivity startup, is partnering with Microsoft Azure IoT to solve two of the biggest hurdles in Industrial IoT: onboarding of devices and unification of data.

OMNIO.net is helping companies of all sizes who have outfitted their campuses with solar panels. The OMNIO.net solution connected these panels to Azure IoT Hub to gather real-time data that will help optimize energy production and limit downtime. Companies look to OMNIO.net to overcome challenges connecting industrial devices and getting the most from their data. What may have taken months in the past, with the combination of OMNIO.net’s energy expertise and Azure IoT offers device connection for partners in less than 24 hours, so customers can focus on using their data to solve pressing business challenges rather than on IT.

iGen Technologies: a self-powered heating system for your home

iGen Technologies’ i2 is a self-power heating system for residential homes. With its patented technology, i2 sets a new benchmark in home comfort and efficiency, by generating, storing and using its own electricity, keeping the heat on, even during a grid outage. The system delivers resilience, lower operating costs, efficiency gains, and greenhouse gas emission reductions. The fully integrated solution offers a dispatchable resource with fuel switching capability, providing utilities a valuable tool to manage peak load and surplus generation situations. iGEN has partnered with Microsoft Azure IoT Central to develop a smart IoT interface for the i2 heat and power system. The integration of iGEN’s distributed energy resource (DER) technology with Microsoft’s robust IoT app platform offers an ideal solution for utility Demand Response programs.

The i2 self-powered heating system. 

Agder Energi, NODES: scaling a sustainable and integrated energy marketplace

Distributed energy resources, digitalization, decarbonization, and new consumer behavior introduce challenges and opportunities for grid system operators to maintain reliable operation of the power system and create customer-centric services. The NODES marketplace relies on Azure to scale its flexible marketplace across 15 projects in 10 different European countries. The focus is on the use of flexibility from the distribution grid, transmission and distribution coordination, and integration with current balancing markets. Agder Energi is now piloting a flexible asset register and data hub with device management and analytics built on IoT Central. Rune Hogga, CEO of Agder Energi Flexibility, told us, "In order to have control of the data and be able to verify flexibility trades, Azure IoT Central provides us with a fast and efficient way to set up a system to collect data from a large number of distributed flexible assets."

L&T Technology Services: reducing carbon consumption and emissions

L&T Technology Services (LTTS) has developed low carbon and EV charging grid solutions for global enterprises, buildings, and smart cities. The LTTS Smart City, Campus & Building solutions enable reducing carbon emissions by up to 40 percent through its iBEMS on Azure solution by connecting an entire building's infrastructure to through single unified interface. In collaboration with Microsoft Real Estate & Facilities, LTTS is building breakthrough EV Charging Solutions providing actionable insights and usage patterns, demand forecasting, design and efficiency anomalies for Facility Managers on EV Charger assets while accurately tracking carbon credit. The LTTS solution also enables Facility Managers to optimize EV Charging Grid based on energy sources (geothermal, solar, electric) and grid constraints such as energy capacity, providing consumer EV charging notifications-based drive range preferences.

Telensa: utilities to support the business case for smart street lighting

Telensa makes wireless smart city applications, helping cities and utilities around the world save energy, work smarter, and deliver more cohesive services for their residents. Telensa is demonstrating how utilities can support the business case for smart street lighting, offering a platform to simply and seamlessly add other smart city applications like traffic monitoring, air quality and EV charging with AI-driven data insights. Telensa’s smart city solutions are increasingly built on Microsoft Azure IoT, leveraging the combination of data, devices, and connectivity, making IoT applications a practical proposition for any city.

Telensa is leading the Urban Data Project, with an initial deployment in Cambridge, UK. This new edge-AI technology is generating valuable insights from streetlight-based imaging, creating a trusted infrastructure for urban data to enable cities to collect, protect, and use their data for the benefit of all residents. The first deployment is in Cambridge, UK. Telensa’s Urban IQ, using Microsoft Power BI for data visualization is an open, low-cost platform to add multiple sensor applications.

 

Telensa’s streetlight based multi-sensor pods, which run on Azure IoT Edge and feature real-time AI and machine learning to extract insights.

eSmart Systems: improving powerline inspections and asset optimization by empowering human experts with Collaborative AI

eSmart Systems helps utilities gain insight into their assets by creating a virtuous cycle of collaboration and training between subject matter experts like Distribution or Transmission Engineers and state of the art deep learning artificial intelligence (AI).

A Microsoft finalist for AI energy partner of the year in 2019, eSmart’s Connected Drone software uses the Azure platform for accurate and self-improving power grid asset discovery and analysis. Grid inspectors continuously review results and correct them to feedback more accurate results to the system. Utilities can optimize visual data to improve their asset registries, reduce maintenance costs and improve reliability.

Kongsberg Digital: Grid Logic digital twin services for electrical grids

Increased electrification and introduction of intermittent, distributed, and renewable energy production challenge today’s grid operations. A lack of sufficient data and insights lead to over-investment, capacity challenges, and power quality issues. With Grid Logic digital twin services running on Azure, grid operators get forecasting and insights into hotspots and scenario simulation. With Azure IoT Hub, Grid Logic will make it possible to build a robust operating system for automation of real-time grid operation, optimization, and automation.

Grid Logic capacity heatmap for a part of Norwegian DSO BKK Nett’s grid.

Let’s connect and collaborate to build your energy solutions  

Microsoft Azure IoT is empowering businesses and industries to shape the future with IoT. We’re ready to meet and support you wherever you are in your transformation journey. Pairing a strong portfolio of products and partners will help you accelerate building robust IoT solutions, to achieve your goals. If you are attending DistribuTECH 2020, speak with Azure IoT experts, or connect with one of the partners mentioned above. 

Learn more about Microsoft Azure IoT and IoT for energy

Partner links:

Adger Energi
eSmart Igen
Konsgberg
L&T Technologies Services and L&T Power 
Nodes Market NXP
Omnio
Telensa

Quelle: Azure