Speed and agility are the most expected in today’s analytics tools. The quicker you get from idea to insights, the more you can innovate & perform ad-hoc data analysis. I will be talking about how we can use AWS serverless architecture to stream IoT data, managed by python. We can be up and running in minutes―starting small, but able to easily grow to millions of devices and billions of messages.
In this world of IoT, the hardware assembly of the tiny little sensors are just the tip of the iceberg. The real complexity lies in processing the massive amount of data these sensors generate. As I am typing this there are TeraBytes of data being generated every hour by connected things around the globe and the data is predicted to reach 403 ZetaBytes by 2018.
One cannot afford to spend most of the time on building and maintaining a datapipeline server to process this huge stream of data. The quicker you bring the data to the presentation tier, the more you can experiment and drive answers to new business questions. This is where we can leverage the agility of serverless architecture models. I will be talking about how AWS serverless architectures help our case by taking care of the non-differentiated heavy lifting tasks such as managing servers, clusters, and device endpoints – allowing us to focus on assembling the IoT system, analyzing data, and building meaningful reports quickly and efficiently.