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Examine the evolution from physical servers to VMs to containers and the driving factors behind this change. Also review the available container management solutions on AWS, Google Cloud Platform and Microsoft Azure.
Cloud computing is a big force in IT today, and it isn't going away. In fact, cloud adoption is going up geometrically, both for end users (think apps on your phone or tablet) as well as for organizations of all sizes. In fact, many smaller organizations may not have any on-premises infrastructure at all, other than networking infrastructure to get connected to the cloud. With this transformation in IT, it behooves all of us in the industry to understand it and adapt or risk being out of a job, like punch card operators.
A range of factors can influence the data center you choose. You should consider all of the factors listed in this white paper before deciding where to place your servers.
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.
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.
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).
AWS has introduced Auto Scaling so that you can take advantage of cloud computing without having to incur the costs of adding more personnel or building your own software. You can use Auto Scaling to scale for high availability, to meet increasing system demand, or to control costs by eliminating unneeded capacity. You can also use Auto Scaling to quickly deploy software for massive systems, using testable, scriptable processes to minimize risk and cost of deployment.
Discover how the enhanced performance and reliability of Amazon Aurora will help AWS customers reduce performance bottlenecks in their applications. The relatively low cost of Aurora will tempt many customers to migrate workloads to this implementation of RDS.
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.
The definition of cloud computing depends largely on whether you are a consumer or producer. The public cloud is geared more for the individual consumer or small company, while the private cloud is geared more for a medium-to-large company. In addition, the private cloud is branching out to incorporate the ability to have some data and applications serviced from the public cloud. This white paper examines the different types of cloud computing and shows what cloud computing can offer you.