From toys to heavy-duty excavators, the number of devices that connect to the internet is growing at an amazing pace. The Internet of Things (IoT) ecosystem around us is one of the major focus areas for businesses to design and deploy new revenue streams. It is estimated that there will be over 29 billion IoT devices in use globally by 2030. Irrespective of sectors, the race to accommodate new IoT innovations drives businesses to invest in technologies that help streamline the path to IoT adoption. One of the forerunners in this aspect is edge computing.
Edge computing helps in building a powerful computing backend closer to habitats where connected devices operate. As such, it allows greater flexibility for businesses to build and deploy powerful services that can leverage IoT devices. However, one of the major challenges they face is managing the massive volumes of data generated in such scenarios. IoT data streams are large and complex and often have several dimensions embedded deeper inside them.
Leaders must uncover the true value hidden behind IoT data streams if they are to build a sustainable business model and competitive edge using the connected ecosystem. This mandates a shift from traditional data pipeline tools to a more sophisticated and powerful serverless data pipeline.
What is a serverless data pipeline in an IoT ecosystem?
In simple terms, a serverless data pipeline in the realms of IoT means running IoT data operations on a cloud data platform rather than having to build and operate a native data architecture. It eliminates the need to worry about infrastructure and lets businesses focus on delivering their frontline IoT experiences.
All data streams that are generated within your business are captured and archived on the cloud for further computing, analysis, and processing. Combined with the principles of edge computing, businesses can have their core digital engines running closer to where devices are operating. Connected devices generate billions of data elements mostly as streams. Serverless data pipelines on the edge help in maintaining the right data closer to the nodes where computing logic is executed thereby providing instant outcomes.
What are the benefits of leveraging serverless data pipelines on the edge for IoT data streams?
Let us explore in detail the top 4 benefits that businesses can experience by using serverless data pipelines on the edge for their IoT use cases:
Simplify complex data stream processing
With serverless data pipelines, every computing task can be built as a pipeline in which data is consumed, followed by processing and manipulation of the consumed data and generation of output data. By moving such serverless data pipelines closer to the data source in an edge model, the edge nodes are offered a data management service that produces results instantaneously from the data supplied.
When IoT devices are connected to edge nodes, they can instantly leverage the data pipeline for data-intensive computing workloads and use insights delivered in real-time to drive new customer experiences. In the traditional sense, such a level of real-time IoT operation would require tons of complicated configurations and deployment of data platforms, computing engines, and other supporting environments. With a serverless data pipeline, everything is simplified to a great extent.
Lower cost
IoT data streams have impeccable volume and can scale up dramatically depending on usage patterns. Further challenges occur when the data traffic is unpredictable and may scale up or down depending on a diverse range of factors. Handling such unpredictability with traditional servers for data management can be a very expensive affair. Enterprises will be forced to invest capital in servers and associated physical infrastructure in anticipation of scaled demand. This is not a practical solution when the workloads are as dynamic as in the case of IoT services.
With serverless data pipelines deployed at the edge, enterprises can exercise a great deal of cost efficiency in their operations. It allows for scalable resources with automatic provisioning. This helps the business to tackle dynamic data handling requirements without the need for upfront capital expenditure. Affordable subscription-driven cost agreements can be worked out depending on the usage pattern necessitated by your business's IoT ecosystem.
Easy analytics
By building an effective serverless data pipeline, businesses can tap into the real value of IoT data streams. They can deploy powerful analytical tools on the data pipeline with granular levels of scalability. The data pipeline can adapt to the different needs of analytical and computing tools that the business leverages.
Using the data pipeline, it becomes easier to define standard outputs that need to go into downstream processing or analytical tools. Automated management of the data pipeline eliminates the possibility of bias. As a result, analytical computations and processing happen on the actual data insights and deliver accurate insights that can drive value for the business quickly.
Better modularity in performance
With serverless data pipelines, it becomes easier to deploy individual functions at different locations within a large application. From an edge IoT perspective, serverless data pipelines facilitate the creation and execution of different functions that work with different data from IoT devices. For example, one function can work with telemetric data gathered from IoT devices in an edge node. All processes and sub-processes within the function can work with a data pipeline that supplies it with only telemetric data from the entire operations on demand.
This can help in isolating any issues in performance and quickly address them to ensure that end users never face any hassles.
Serverless data pipelines have immense potential when used as the de-facto data platform for edge IoT assets. It allows enterprises to build and execute data operations closer to the source without worrying about physical infrastructure management for data.
However, achieving a seamless transition from traditional data pipelines to serverless data pipelines requires a strategic approach. It needs expert guidance on building resource provision automation, scalability configurations, choice of tools, and much more. This is where an experienced technology partner like Wissen can make a major mark. Get in touch with us to learn more.
