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by Aditya Mavlankar , Zhi Li , Lukáš Krasula and Christos Bampis High dynamic range ( HDR ) video brings a wider range of luminance and a wider gamut of colors, paving the way for a stunning viewing experience. HDR was launched at Netflix in 2016 and the number of titles available in HDR has been growing ever since.
We enabled HDR10+ on Netflix using the AV1 video codec that was standardized by the Alliance for Open Media (AOM) in 2018. AV1 is one of the most efficient codecs available today. Title must be available in HDR10+format 3. This consistency allows our members to stay immersed in the content, and better preserves creativeintent.
Gatekeeper is the system at Netflix responsible for evaluating the “liveness” of videos and assets on the site. Gatekeeper accomplishes its prescribed task by aggregating data from multiple upstream systems, applying some business logic, then producing an output detailing the status of each video in each country.
Most of the use cases in these two broad categories benefit from the flexibility that comes from multiple available sources of business data. Log data is then processed accordingly, stored in Dynatrace Grail™ causational data lakehouse, and available for your Business Analytics use cases.
Moorthy and Zhi Li Introduction Measuring video quality at scale is an essential component of the Netflix streaming pipeline. Perceptual quality measurements are used to drive video encoding optimizations , perform video codec comparisons , carry out A/B testing and optimize streaming QoE decisions to mention a few.
Kickstart your creation journey using ready-made dashboards and notebooks Creating dashboards and notebooks from scratch can take time, particularly when figuring out available data and how to best use it. An example of this is shown in the video above, where we incorporated network-related metrics into the Kubernetes cluster dashboard.
When delivering video over-the-top (OTT), the internet is the principal highway for distributing this content. Currently, publicly available wifi hotspots are the preferred networks for video consumption, but poor network infrastructure also leads to unbearable video buffering and latency.
Activate Davis AI to analyze charts within seconds Davis AI can help you expand your dashboards and dive deeper into your available data to extract additional information. This is where Davis AI for exploratory analytics can make all the difference.
Optimizing Video For Size And Quality. Optimizing Video For Size And Quality. Over the last few years, more and more projects are using video as an integral part of the application. However, it all goes sideways when there are issues related to the video playback. Doug Sillars. 2021-02-15T15:00:00+00:00. Real-World Data.
” The talk video is now available on YouTube, linked below. I hope you enjoy it, and thanks again to the organizers of DevAroundTheSun for putting together this global online event.
We could also swap out the implementation of a field from GraphQL Shim to Video API with federation directives. The next phase in the migration was to reimplement our existing Falcor API in a GraphQL-first server (Video API Service). The Replay Testing framework leverages the @override directive available in GraphQL Federation.
i.e. video would play for a very short time, then pause, then start again, then pause. They supplied a video and it looked terrible. I walked upstairs and found the engineer who wrote the audio and video pipeline in Ninja, and he gave me a guided tour of the code. In Ninja, this job is performed by an Android Thread.
Most conversations about streaming quality focus on video. We’re really proud of the improvements we’ve brought to the video experience, but the focus on those makes it easy to overlook the importance of sound , and sound is every bit as important to entertainment as video. is the story nearly as thrilling and emotional?
Understanding these elements and how they relate to each other is crucial for tasks such as video summarization and highlights detection, content-based video retrieval, dubbing quality assessment, and video editing. As a result of DTW, the scene headers have timestamps that can indicate possible scene boundaries in the video.
Problem Netflix’s content catalog is composed of video captured and encoded in one of various frame rates ranging from 23.97 24→60, 25→60, etc…), which manifests as choppy video playback as illustrated below: With Judder Without Judder It is important to note that the severity of the judder depends on the replication pattern.
An example of using Machine Learning to find shots of Eleven in Stranger Things and surfacing the results in studio application for the consumption of Netflix video editors. We must quickly surface the most stand-out highlights from the titles available on our service in the form of images and videos in the member experience.
These UA campaigns typically feature static creatives, launch trailers, and game review videos on platforms like Google, Meta, and TikTok. Ideally, we would have causal estimates from an A/B test to use for validation, but since that is not available, we use another causal inference design as one of our ensemble of validation approaches.
These organizations rely heavily on performance, availability, and user satisfaction to drive sales and retain customers. AvailabilityAvailability SLO quantifies the expected level of service availability over a specific time period. Availability is typically expressed in 9’s, such as 99.9%. or 99.99% of the time.
The team behind Dynatrace University has always pushed themselves to achieve more and provide its users with up to date content.And with that, we’re excited to announce Dynatrace University 2020 is now available! Multi-language certifications and microlearning videos. Now available in your language! What’s changing?
The video is now available — I hope you enjoy it. Back in early July, I did a wide-ranging “ask me anything” Q&A session at C++ Russia. Thanks again to C++ Russia for inviting me to their great online event!
An example for storing both time and space based data would be an ML algorithm that can identify characters in a frame and wants to store the following for a video In a particular frame (time) In some area in image (space) A character name (annotation data) Pic 1 : Editors requesting changes by drawing shapes like the blue circle shown above.
the newly released mobile app available on Android and iOS , uses Davis AIOps to push alert notifications directly to your phone and significantly reduce the incident response times. The Dynatrace mobile app takes the desktop experience you are already familiar with and makes it available on your mobile. Dynatrace 3.0, An issue occurs.
Automatically Transforming And Optimizing Images And Videos On Your WordPress Website. Automatically Transforming And Optimizing Images And Videos On Your WordPress Website. Leonardo Losoviz. 2021-11-09T09:30:00+00:00. 2021-11-09T14:02:28+00:00. Adding Transformations To The Images.
This means we can compare the results for data that was publicly available against the results for data that was private but from the same book. There is clear precedent for training on publicly available data. The remainder of each book is behind a subscription paywall as part of our OReilly online service.
I showed the iPhone to people at Netflix, as it had excellent quality video playback, but they werent interested. At that time YouTube was primarily very short low quality videos, and Netflix average viewing time was over 30 minutes of high qualityvideo. I use mine most days to watch videos. The code is still up on github.
To enhance prediction accuracy in sequential recommendation systems, we organize token features into two categories: Request-Time Features : These are features available at the moment of prediction, such as log-in time, device, or location. These can be directly applied to meet diverse businessneeds.
Leverage synthetic monitoring Synthetic monitoring involves simulating user interactions and transactions to proactively monitor your digital services’ performance and availability. Use synthetic monitoring to conduct regular tests and identify potential issues before they impact real users.
Watch the video here, open it on YouTube or watch it on Dynatrace University (including access to slides): If you want to try this yourself then just follow the guidance from Kristof. As mentioned above I encourage you to watch Kristof’s video closely and also download the slides from Dynatrace University. Step 3: SLOs.
in a video file. As described in the above picture During the first run of the algorithm it identified 500 objects in a particular Video file. Now when we re-ran the algorithm on the same video file it created 600 annotations of schema type Objects and stored them in our service. The Algorithm team improved their algorithm.
What does this example have to do with software development and video encoding? Intel and Netflix announced their collaboration on a software video encoder implementation called SVT-AV1 on April 8, 2019. The first successful digital video standard was MPEG-2, which truly enabled digital transmission of video.
by Liwei Guo , Ashwin Kumar Gopi Valliammal , Raymond Tam , Chris Pham , Agata Opalach , Weibo Ni AV1 is the first high-efficiency video codec format with a royalty-free license from Alliance of Open Media (AOMedia), made possible by wide-ranging industry commitment of expertise and resources. Video encoding is essentially a search problem?—?the
AV1 is a high performance, royalty-free video codec that provides 20% improved compression efficiency over our VP9† encodes. Our support for AV1 represents Netflix’s continued investment in delivering the most efficient and highest quality video streams. AV1-libaom compression efficiency as measured against VP9-libvpx.
AV1 is a high performance, royalty-free video codec that provides 20% improved compression efficiency over our VP9† encodes. Our support for AV1 represents Netflix’s continued investment in delivering the most efficient and highest quality video streams. AV1-libaom compression efficiency as measured against VP9-libvpx.
Below, we discuss how we’ve built upon our previous work of harvesting static images directly from video source files and our computer vision algorithms to produce a set of artwork candidates that covers the major product canvases for the entire content catalog. Broadly speaking, we use two methods to extract movie stills out of video source.
This week my colleague Michael Winkler announced the general availability of Cloud Automation quality gates , a new capability that aims to provide answer-driven release validation as part of your delivery process. Let’s Start: Answer driven automation – your full video tutorial. 01:19 – Introducing Shift-Left SLO Quality Gates.
In recent years, function-as-a-service (FaaS) platforms such as Google Cloud Functions (GCF) have gained popularity as an easy way to run code in a highly available, fault-tolerant serverless environment. On the processing side, GCF functions can interface with Google’s own AI/ML technologies to inspect video and image content.
When Reloaded was designed, we were a small team of developers operating a constrained compute cluster, and focused on one use case: the video/audio processing pipeline. In the diagram below of a typical Cosmos service, clients send requests to a Video encoder service API layer. debian packages).
Every internet user, knowingly or unknowingly, uses a CDN while watching a video, reading a newspaper, or enjoying a TV show. CloudFront CDN and CloudFlare CDN are two popular services available on the market. CDN stands for content delivery network.
David Daly’s presentation at LTB 2020 , How to Waste Time and Money Test ing the Performance of a Software Product, is probably a good introduction [Video] — [Slides]. These two papers provide many more insights: Automated system performance testing at MongoDB , DBTest 2020 [ Video ]. The MongoDB Podcast, Ep.
The video below demonstrates how Dynatrace ’s AI, Davis , enables auto-remediation by identifying a problem’s precise root cause. Availability: Naturally, auto-remediated problems are resolved faster, thereby making digital services more available. Dynatrace news.
Can’t say that it changed much since then industry-wise – but great free MongoDB courses are available to everybody). Some good videos on the topic: Solving MongoDB Performance Riddles with Systems Thinking. Some good videos on the topic: Solving MongoDB Performance Riddles with Systems Thinking. What is MongoDB FTDC (aka.
So e ven when you don’t fully understand the exact cause of a crash, you can still view a video of the end of the crashed session to see the exact steps that the affected user took and the exact data they entered. In such cases, the crash can be analyzed only by using the information that’s available on the session details page.
According to Google’s SRE handbook , best practices, there are “ Four Golden Signals ” we can convert into four SLOs for services: reliability, latency, availability, and saturation. Availability. To measure availability, we can rely on an HTTP monitor from Dynatrace Synthetic Monitoring. Reliability.
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