Azure Kubernetes Service Case Study

 

Kubernetes

Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications. Kubernetes is an open-source project that has become one of the most popular container orchestration tools around; it allows you to deploy and manage multi-container applications at scale. While in practice Kubernetes is most often used with Docker, the most popular containerization platform, And because Kubernetes is open-source, with relatively few restrictions on how it can be used, it can be used freely by anyone who wants to run containers, most anywhere they want to run them on-premises, in the public cloud, or both.

Kubernetes Features

1. Automated rollouts and rollbacks
2. Horizontal scaling
3. Self-healing
4. Service discovery and load balancing
5. Storage orchestration

Microsoft Azure

Microsoft Azure, formerly known as Windows Azure, is Microsoft’s public cloud computing platform. It provides a range of cloud services, including compute, analytics, storage, and networking. Users can pick and choose from these services to develop and scale new applications, or run existing applications in the public cloud.

Credits to: Azure and Bosch Company

The Azure platform aims to help businesses manage challenges and meet their organizational goals. It offers tools that support all industries including e-commerce, finance, and a variety of Fortune 500 companies, and is compatible with open source technologies. This provides users with the flexibility to use their preferred tools and technologies.

Azure Kubernetes service

Azure Kubernetes Service (AKS) offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver and scale applications with confidence. Deploy and manage containerized applications more easily with a fully-managed Kubernetes service.

Common uses for Azure Kubernetes Service (AKS)

Lift and shift to containers with AKS

Easily migrate existing applications to the container(s) and run within the Azure-managed Kubernetes service (AKS).

Microservices with AKS

Use AKS to simplify the deployment and management of microservices-based architecture. AKS streamlines horizontal scaling, self-healing, load balancing, secret management.

Secure DevOps for AKS

DevOps and Kubernetes are better together. Implementing secure DevOps together with Kubernetes on Azure, you can achieve the balance between speed and security and deliver code faster at scale.

Machine Learning model training with AKS

Training models using large datasets is a complex and resource-intensive task. Use familiar tools such as TensorFlow and Kubeflow to simplify the training of Machine Learning models.

The Bosch Group is a leading global supplier of technology and services. It employs roughly 394,500 associates worldwide (as of December 31, 2020). Its operations are divided into four business sectors: Mobility Solutions, Industrial Technology, Consumer Goods, and Energy and Building Technology. As a leading IoT provider, Bosch offers innovative solutions for smart homes, Industry 4.0, and connected mobility. The Bosch Group’s strategic objective is to facilitate connected living with products and solutions that either contain artificial intelligence (AI) or have been developed or manufactured with its help.

Credits to: Azure and Bosch Company

Technical Story

When Robert Bosch GmbH set out to solve the problem of drivers going the wrong way on highways, the goal was to save lives. Other services like this existed in Germany, but precision and speed cannot be compromised. Could Bosch get precise enough location data in real-time to do this? The company knew it had to try.

The result is the wrong-way driver warning (WDW) service and software development kit (SDK). Designed for use by app developers and original equipment manufacturers (OEMs), the architecture pivots on an innovative map-matching algorithm and the scalability of Microsoft Azure Kubernetes Service (AKS) in tandem with Azure HDInsight tools that integrate with the Apache Kafka streaming platform.

The right way to solve the wrong-way problem

Smartphones or an onboard connectivity unit can anonymously record GPS coordinates and can send that location data to the cloud if the device is in a hotspot area, but GPS satellites broadcast their signals in space with only limited accuracy. What is received depends on many factors, including satellite geometry, signal blockage, atmospheric conditions, and the design and quality of the receiver. For example, GPS-enabled smartphones are typically accurate within a 4.9-meter (16-foot) radius under the open sky.

The Bosch team had to solve two major issues: first, to get the last piece of information out of the noisy sensor data; and second, to develop a highly scalable and ultra-flexible service to process the data in near real-time. The question was how to build real-time data ingestion and processing pipeline capable of returning notifications to drivers within seconds.

The problem was speed. The team assumed that devices emitting location information, such as smartphone apps and automotive head units, could eventually send thousands of data points to the solution per second, from all over Europe and eventually other countries.

The team decided to offload the work of scaling and cluster maintenance to a managed service in a public cloud with a global reach. A team of Microsoft cloud solution architects worked closely with Bosch engineers, who provided valuable feedback to Azure product teams.

The key was orchestration. By orchestrating the deployment of containers using AKS, Bosch would get repeatable, manageable clusters of containers. Bosch already had a continuous integration (CI) and continuous deployment (CD) process to use in producing the container images and orchestration. The result: increased speed and reliability of deployments.

AKS also offered the simplicity of a managed Kubernetes service in the cloud. It provided the elastic provisioning that Bosch wanted, without the need to manage its own infrastructure. In addition, the developers did not have to rethink all their design decisions. Instead, they could take the core business logic developed on-premises using the open-source tools they knew and run the solution virtually as-is, within a faster infrastructure with a worldwide reach. The developers can deploy self-managed AKS clusters as needed, and they get the benefit of running their services within a secured network environment.

In addition, by running their solution on Azure and AKS, the average time to calculate whether a driver is going the wrong way could be improved to approximately 60 milliseconds.

How the solution works

The wrong-way driver warning solution runs as a service on Azure and provides an SDK. Service providers, such as smartphone app developers and OEM partners, can install the WDW SDK to make use of the service within their products. The SDK maintains a list of hotspots within which GPS data is collected anonymously. These hotspots include specific locations, such as segments of divided highways and on-ramps. Every time a driver enters a hotspot, the client generates a new ID, so the service remains anonymous.

Today the solution ingests approximately 6 million requests per day from devices emitting GPS data or from a partner’s back-end system. Anyone can download the SDK and try it out. The APIs grant a free request quota for test accounts. For production use, service providers request permission and then use the WDW SDK to register themselves for their own API authentication keys via the Azure API Management developer portal. Within their application, they configure the service’s endpoints by authenticating with their key for ingress and push notifications. The WDW service on Azure does the rest.

When a driver using a WDW-configured app or in-car system enters a hotspot, the WDW SDK begins to collect GPS signals and sensor events, such as acceleration and rotational data and heading information. These data points are packaged as observations and sent in the frequency of 1 Hertz (Hz) one event per second via HTTP to the WDW service on Azure, either directly or to the service provider’s back end, and then to Azure. The SDK supports both routes so that service providers stay in charge of the data that is sent to the WDW system.

If the WDW service determines that the driver is going the wrong way within a hotspot, it sends a notification to the originating device and to other drivers in the vicinity who are also running an app with the WDW SDK.

Credits to: Azure and Bosch Company 

What we like about AKS is the simplified Kubernetes experience. It clicks and deploys, it’s click and scale. It’s infrastructure as code too, which is quite cool for us.

Christian Jeschke: product owner

Conclusion:

Azure Kubernetes Service is a powerful service for running containers in the cloud. Now we can easily launch a test cluster in a few minutes and see the benefits of AKS by ourselves.

So, we learned that how Company’s like Bosch uses AKS to solve the challenges of real-time traffic-driving problems.

Hope This Blog Helpful to you!!!