So, what are edge apps? Edge applications run on or near data sources, such as . B IoT devices and on-premises Edge Servers, as well as Edge execution. Edge computing enables compute, storage, caching, management, alerting, machine learning, and routing between data centers and the cloud. Companies in various industries such as retail, agriculture, manufacturing, transportation, healthcare, and telecommunications use edge applications to reduce latency, improve bandwidth availability, reduce infrastructure costs, and accelerate decision-making. Because the JSON format does not support object references (even if there is an IETF design), a typical error is triggered when an attempt is made to encode an object with circular references. Next, we need to determine the format of our data. It can be the same as the original format or we can convert it to meet transport, processing or storage requirements. We have to ask ourselves a number of architectural questions. And in many cases, our devices, devices, sensors, operating systems or means of transport require us to choose a specific data format. If you want to learn more about Edge and create your own connectors, check out the following resources: Here, we`ve developed an Edge application that can stream data at event speed and insert thousands of streaming data from other applications into your Apache Pulsar cluster. Then we can add in-depth real-time scans with Flink SQL. This allows us to perform advanced flow processing, connect event streams, and process data at scale.

Let`s test some libraries, languages, and clients on our NVIDIA Jetson Xavier NX to see which one works best for our use case. After prototyping a bunch of libraries that worked on Ubuntu with THE ARM version of NVIDIA Jetson Xavier NX, I found a number of options that generate messages that match what I need for my application. These are not the only ones, but very good options for this edge platform. This blog hasn`t covered the basics of the pulsar you need if you want to build your own edge apps using my methods. If you`re new to Pulsar, I highly recommend taking the self-service Pulsar courses developed by StreamNative Academy or the teacher-led Pulsar training. This will make it easier for you to get started with Pulsar and speed up your streaming instantly. The repository is located on Github github.com/hermitdave/json-formatter-edge with instructions While the decentralized nature of edge computing offers a variety of benefits, it also presents challenges. The main challenges include: the Microsoft Edge extension for JSON and JSONP rendering when you visit it “directly” in a browser tab. To overcome the key challenges of building edge applications, you need an adaptable, hybrid, geo-replicated, extensible, and open source solution.

A widely used open source project offers support for a dedicated community and a rich ecosystem of adapters, connectors, and extensions needed for edge applications. Having worked with various open source technologies and projects over the past two decades, I believe Apache Pulsar meets the requirements of edge applications. Apache Pulsar is an open source, cloud-native distributed messaging and streaming platform. Since Pulsar became a high-profile project of the Apache Software Foundation in 2018, its community engagement, ecosystem growth, and global adoption have skyrocketed. Pulsar is able to solve the many challenges of edge computing because: By default, the JSON code is displayed in the Edge browser. You can download the repository and install the extension after enabling the extension`s developer mode from `about:flags` Can`t wait any longer. I started cloning the Json formatting repository and used the Microsoft Edge Extension Toolkit to port the extension to Edge. When the extension is installed, it is displayed below The explosive growth of connected remote devices poses challenges to the centralized computing paradigm.

Due to network and infrastructure limitations, it is becoming increasingly difficult for organizations to move and process all the data generated by devices in data centers or the cloud without latency or performance issues. As a result, edge applications are on the rise. Gartner estimates that by 2025, 75% of enterprise data will be created and processed outside of data centers or the cloud. For today`s application, we will use JSON, which is ubiquitous and human-readable for virtually any language. . Apache Avro, a binary format, is also a good option, but for these blogs, we`re going to keep it simple. The only reason I install Chrome from time to time is to use extensions like the Json Formatter extension. Recently, Microsoft released the Windows 10 Anniversary Update. The Edge browser in this update supports extensions. This list of extensions in the store is still limited. The team analyzes the performance and publishes it accordingly.

To port another extension, use the Micosoft Edge Extension Toolkit available in the store In this article, you will learn some of the challenges of Edge application development and why Apache Pulsar is the solution. You will also learn how to build edge applications with Pulsar with a step-by-step example. Now that the data format has been selected, we may need to enrich the raw data with additional fields beyond what is generated by sensors, machine learning classification, logs, or other sources. I like to add an IP address, Mac address, hostname, build timestamp, run time, and some fields on device status, such as disk space, memory, and processor. You can add or remove more if you don`t see the need or if your device already transmits the integrity of the device. At the very least, these fields can help with debugging, especially if you get thousands of devices. That`s why I`m always happy to include them, unless strict bandwidth restrictions make it impossible. In today`s examples, we`ll build edge applications on an NVIDIA Jetson Xavier NX that gives us enough power to run a standalone edge Apache pulsar broker, multiple webcams, and deep learning edge applications with HORSE STRENGTH.

My Edge device contains 384 NVIDIA CUDA cores® and 48 tensor cores, six 64-bit ARM cores, and 8 GB of 128-bit LPDDR4x RAM. In my upcoming blogs, I`ll show you that running Pulsar on more discreet devices like Raspberry PI 4s and NVIDIA Jetson Nanos is still enough for fast edge event streams. For IoT applications, you often want to use a time-based primary data store for these events. I recommend Aerospike, InfluxDB or ScyllaDB. .