Google to Update GKE

IT giant has added container-native load balancing to Google Kubernetes Engine
15 October 2018   317

Google told about the improvements of the load sharing tool between containers in the Google Kubernetes Engine (GKE). Using the updated balancer, the user independently creates groups of traffic endpoints on the network. The system distributes the load between the containers for greater efficiency.

In GKE, the ability to create an object with external access provided by a dedicated balancer has been added. This allows to configure the routing to the targets at the specified path or host name. The new load distribution system has the following features:

  • Optimal load balancing
    Previously, the Google load balancing system evenly distributed requests to the nodes specified in the backend instance groups, without any knowledge of the backend containers. The request would then get routed to the first randomly chosen healthy pod, resulting in uneven traffic distribution among the actual backends serving the application. With container-native load balancing, traffic is distributed evenly among the available healthy backends in an endpoint group, following a user-defined load balancing algorithm.

  • Native support for health checking
    Being aware of the actual backends allows the Google load balancing system to health-check the pods directly, rather than sending the health check to the nodes and the node forwarding the health check to a random pod (possibly on a different node). As a result, health check results obtained this way more accurately mirror the health of the backends. You can specify a variety of health checks (TCP, HTTP(S) or HTTP/2), which health-check the backend containers (pods), directly  rather than the nodes.

  • Graceful termination
    When a pod is removed, the load balancer natively drains the connections to the endpoint serving traffic to the load balancer according to the connection draining period configured for the load balancer’s backend service.

  • Optimal data path
    With the ability to load balance directly to containers, the traffic hop from the load balancer to the nodes disappears, since load balancing is performed in a single step rather than two.

  • Increased visibility and security
    Container-native load balancing helps you troubleshoot your services at the pod level. It preserves the source IP to make it easier to trace back to the source of the traffic. Since the container sees the packets arrive from the load balancer rather than through a source NAT from another node, you can now create firewall rules using node-level network policy.  

The Cloud Native Computing Foundation updated the GKE container orchestration system at the end of September 2018. According to the developers, in version 1.12, two functions became stable: Kubelet TLS Bootstrap to sign security certificates for TLS connections and support for Azure virtual machines.

Microsoft to Use AI to Create Human Voice

Synthetic voice is nearly indistinguishable from recordings of people
27 September 2018   553

Researchers from Microsoft recorded computer voice, imitating human speech. To overcome the difficulties of the traditional model, they used neural networks for speech synthesis. Microsoft promises to provide support for 49 languages ​​and the ability to create unique voices for the needs of companies in the near future.

Synthesis of speech with the help of neural networks involves comparing the stress and length (so-called prosody) of the speaker's speech units, as well as their synthesis into a computer voice. In systems of traditional speech synthesis, prosody is divided into acoustic and linguistic analysis, controlled by various models. As a result, the speech is noisy and indistinct. Representatives of Microsoft argue that in the model of neural synthesis two stages are combined into one, so the voice sounds like a real one.

The developers are convinced that the synthesis of speech with the help of neural networks will make it more natural to communicate with virtual interlocutors and assistants. Moreover, it will enable you to convert e-books into audiobooks and will allow you to change the scoring of built-in navigators.

Microsoft Neural TTS
Microsoft Neural TTS

Azure computing power is available for real-time use, and Azure Kubernetes is responsible for this. Simultaneous application of neural synthesis of speech together with traditional speaks about expansion and increase of availability of service. At the moment, there are a female voice named Jessa and a man named Guy.

Microsoft is competing in speech recognition and synthesis technologies with Google, which updated its services in late August 2018. Google Cloud announced the release of a stable API for the synthesis of speech Cloud Text-to-Speech with the experimental function of audio profiles and support for several new languages.