Microsoft and Isovalent partner to bring next generation eBPF dataplane for cloud-native applications in Azure

This post was co-authored by Narayan Annamalai, Partner PM Manager, Microsoft Azure.

As cloud-native applications are experiencing astronomical growth, customers are constantly demanding to scale their Kubernetes and containerized deployments with rich feature sets for network security and observability and without degrading their network performance. With the above in mind, we are excited about this partnership to enhance our platform to bring the power of eBPF natively in Microsoft Azure that will efficiently meet networking capabilities like container network security, cluster service routing, and network observability at a large scale while maintaining mission-critical uptime and reliability.

Microsoft and Isovalent bring new features with eBPF to Azure Kubernetes Services

Microsoft announces the strategic partnership with Isovalent to bring Cilium's eBPF-powered networking data plane and enhanced features for Kubernetes and cloud-native infrastructure.

Azure Kubernetes Services (AKS) will now be deployed with Cilium open-source data plane and natively integrated with Azure Container Networking Interface (CNI).

Microsoft and Isovalent will enable Isovalent Cilium Enterprise as a Kubernetes container App offering onto Azure Container Marketplace. This will provide a one-click deployment solution to Azure Kubernetes clusters with Isovalent Cilium Enterprise advanced features.

Azure CNI powered by Cilium

Recently, Microsoft announced the preview of Azure CNI powered by Cilium for Azure Kubernetes Services.

Cilium’s expertise in eBPF-enriched features like efficient load-balancing, extensive network security features, and rich monitoring along with industry-leading robust and scalable Azure CNI IP Address Management (IPAM), VNET and Overlay mode, will give the most performant and best-in-class container networking platform for our AKS customers.

As a native offering, customers will find it significantly easier to leverage Cilium open-source features directly on AKS Cluster creations as opposed to multi-step configuration via bring your own CNI (BYOCNI) or custom configurations.

Microsoft will handle first-line support and collaborate with Isovalent on specific support issues to their deep knowledge of the technology. We are thrilled to be expanding our relationship with Isovalent and continuing our collaboration with the Cilium open-source community. Together, we have built an ideal platform for current benefits and future innovations.

Isovalent Cilium Enterprise in Azure Container Marketplace

Microsoft and Isovalent are actively collaborating to bring the Isovalent Cilium Enterprise offering onto Azure Kubernetes Services via Azure Container Marketplace.

With this tight integration, customers who also want advanced Isovalent Cilium Enterprise capabilities, will be offered one-click deployment and upgrade for Cilium Enterprise features to a new or existing AKS cluster with a much simpler and more reliable experience. Cilium Enterprise will be built with native integration with Azure networking platform to offer advanced features and capabilities with best-in-class performance and scale. Microsoft and Isovalent will also collaborate to include joint testing, compatibility, and versioning checks, along with seamline support to ensure Cilium Enterprise runs best on Azure.

Customers will also get a unified billing experience, auto-upgrades of Enterprise version updates, usage, and all the other key features offered by the Azure Marketplace platform. This will eliminate a lot of management overhead, which otherwise customers would have to manage manually.

The preview for this new offering will be available early next year.

Learn more

Find out more about this strategic partnership from Thomas Graf, Co-founder, and CTO of Isovalent.

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Quelle: Azure

Improve speech-to-text accuracy with Azure Custom Speech

With Microsoft Azure Cognitive Services for Speech, customers can build voice-enabled apps confidently and quickly in more than 140 languages. We make it easy for customers to transcribe speech to text (STT) with high accuracy, produce natural-sounding text-to-speech (TTS) voices, and translate spoken audio. In the past few years, we are inspired by the ways customers seek our customization features to fine-tune speech recognition to their use cases.

As our speech technology continues to change and evolve, we want to introduce four custom speech-to-text capabilities and their respective customer use cases. With these features, you can evaluate and improve the speech-to-text accuracy for your applications and products. A custom speech model is trained on top of a base model. With a custom model, you can improve recognition of domain-specific vocabulary by providing text data to train the model. You can also improve recognition based on the specific audio conditions of the application by providing audio data with reference transcriptions.

Custom Speech data types and use cases

Our Custom Speech features will let you customize Microsoft's speech-to-text engine. You will be able to customize the language model by tailoring it to the vocabulary of the application and customize the acoustic model to adapt to the speaking style of your users. By uploading text and/or audio data through Custom Speech, you'll be able to create these custom models, combine them with Microsoft's state-of-the-art speech models, and deploy them to a custom speech-to-text endpoint that can be accessed from any device.

Phrase list: A real-time accuracy enhancement feature that does not need model training. For example, in a meeting or podcast scenario, you can add a list of participant names, products, and uncommon jargon using phrase list to boost their recognition.

Plain text: Our simplest custom speech model can be made using just text data. Customers in the media industry use this in use cases such as commentary of sports events. Because each sporting event’s vocabulary differs significantly from others, building a custom model specific to a sport increases accuracy by biasing to the vocabulary of the event.

Structured text: This is text data that boosts patterns of sentences in speech. These patterns could be utterances that differ only by individual words or phrases, for example, “May I speak with name” where name is a list of possible names of individuals. The pattern can link to this list of entities (name in this case), and you can also provide their unique pronunciations.

Audio: You can train a custom speech model using audio data, with or without human-labeled transcripts. With human-labeled transcripts, you can improve recognition accuracy on speaking styles, accents, or specific background noises. For American English, you can now train without needing a labeled transcript to improve acoustic aspects such as slight accents, speaking styles, and background noises.

Research milestones

Microsoft’s speech and dialog research group achieved a milestone in reaching human parity in 2016 on the Switchboard conversational speech recognition task, meaning we had created technology that recognized words in a conversation as well as professional human transcribers. After further experimentation, we then followed up with a 5.1 percent word error rate, exceeding human parity in 2017. A technical report published outlines the details of our system. Today, Custom Speech helps enterprises and developers improve upon the milestones achieved by Microsoft Research.

Customer inspiration

Peloton: In the past, Peloton provided subtitles only for its on-demand classes. But that meant that the signature live experience so valued by members was not accessible to those who are deaf or hard of hearing. While the decision to introduce live subtitles was clear, executing on that vision proved a bit murkier. A primary challenge was determining how automated speech recognition software could facilitate Peloton’s specific vocabulary, including the numerical phrases used for class countdowns and to set resistance and cadence levels. Latency was another issue—subtitles wouldn’t be very useful, after all, if they lagged behind what instructors were saying. Peloton chose Azure Cognitive Services because it was cost-effective and allowed Peloton to customize its own machine learning model for converting speech to text—and was significantly faster than other solutions on the market. Microsoft also provided a team of engineers that worked alongside Peloton throughout the development process.

Speech Services and Responsible AI

We are excited about the future of Azure Speech with human-like, diverse, and delightful quality under the high-level architecture of the XYZ-code AI framework. Our technology advancements are also guided by Microsoft’s Responsible AI process, and our principles of fairness, inclusiveness, reliability and safety, transparency, privacy and security, and accountability. We put these ethical standards into practice through the Office of Responsible AI (ORA)—which sets our rules and governance processes, the AI Ethics and Effects in Engineering and Research (Aether) Committee—which advises our leadership on the challenges and opportunities presented by AI innovations, and Responsible AI Strategy in Engineering (RAISE)—a team that enables the implementation of Microsoft Responsible AI rules across engineering groups.

Get started with Azure Cognitive Services for Speech

You can use Speech Studio to test how custom speech features would help improve recognition for your audio. In addition, start building new customer experiences with Azure Neural TTS and STT. In addition, the Custom Neural Voice capability enables organizations to create a unique brand voice in multiple languages and styles.

Resources

Try out Speech services in the Studio.
Get started with Custom Speech.
Get started with speech to text.
Get started with text to speech.
Get started with Custom Neural Voice.
Get started with speech translation.

Quelle: Azure