
Amazon Web Services (AWS) has been a game-changer in the IT industry, revolutionizing the way we work. From humble beginnings with a small EC2 instance, AWS has evolved to offer powerful solutions like AWS IoT Greengrass for building IoT solutions. Throughout this incredible journey, AWS has consistently been the best friend of Computer Science Engineers,
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With the rise of automation, everyone is shifting from monolithic architecture to microservice architecture. Microservice architectures are more flexible and robust when it comes to security, development and deployment cycles. [Do check out our previous blog on Microservices to understand more about microservices] For establishing a microservice architecture, one needs to automate the
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Enterprises using monolithic systems to support large applications find it increasingly difficult to respond to evolving business priorities and rising customer expectations. Each functionality is built together as one single block, and it’s almost impossible to change or update a portion of it, without overhauling the complete monolith. Due to this, enterprises are rapidly exploring
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At a time where information and insights from data are the most significant assets that any business has, implementing data warehouse solutions has been more critical than it has been at any other time in the past. So, what exactly does a data warehouse mean? In a nutshell, a Data Warehouse is a basic data
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Handling IoT devices and doing computations on their readings is always a tedious process as it requires both Hardware and Software handling expertise. Furthermore, It becomes even more complex when you need to transfer data using traditional MQTT protocols and design your own servers and infrastructure for handling the flow of data from IoT devices
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