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As far as modern architectures go, there are few more complicated than an IoT pipeline. You’ve got to consider an ingestion layer (typically streaming) that may undergo manic load. You’ve got to think of data tagging, storage (probably across multiple engines), archival and access—both internal and external. And all of it has to scale like crazy, be as cost effective as possible, and use automation wherever it can. Oh, and your boss needs the IoT pipeline built by tomorrow. Short timelines? Tight budget? Unrealistic expectations? Unfortunately, these asks are realities for many cloud professionals. AWS knows this and is here to help.
Learn how Docker makes it easy to update, test and debug software with this white paper and gain foundational knowledge about Dockerfile, Docker images and containers.
Like it or not, Internet of Things (IoT) is upon us. There are a number of factors that will impact its adoption rate, and the inevitable privacy (or lack of) discussions will likely happen sooner than later. This is going to change the world as we know it, in many cases for the better. But we will need to keep an eye on the extent to which it invades our personal lives if it is going to be the positive force it has the potential to be.
Amazon Web Services (AWS) offers increased agility, developer productivity, pay-as-you-go pricing and overall cost savings. But you might wonder where to start, what pitfalls exist and how can you avoid them? How can you best save time and money? Learn what you need to know and where to start before launching an AWS-hosted service.
Database Management Systems (DBMS) have been monolithic structures with their own dedicated hardware, storage arrays, and consoles. Amazon Web Services (AWS) realized that while each company can use unique methods of collecting and using data, the actual processes of building the management infrastructure are almost always the same. AWS remedies DBMS problems with its Amazon Relational Database Service (Amazon RDS).