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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.
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.
Building upon the IT best practices of Lean, Agile Scrum and IT Service Management, DevOps adds that “missing” layer to tie together the service lifecycle workflow across Development and Operations, while leveraging the latest in automation technology. Demand for skilled, open-minded, and collaborative professionals with DevOps knowledge is rapidly increasing. Are you ready for change?
This white paper explores the native AWS storage solutions, enabling you to deliver applications in the cloud in the most efficient, cost-effective, and secure manner. In terms of storage, it's important to understand the characteristics of each AWS storage option so that you can implement one or more AWS storage services to meet your needs. Often, you'll find that utilizing multiple storage options together will give you the best outcomes.
AWS is an incredibly rich ecosystem of services and tools, some of which have security aspects baked in (like S3 SSE), and others that provide overarching security capabilities (like IAM and VPC) that apply to many services. With regard to data storage, operating system, and applications, security functions largely the same in the cloud or on-premises software. Customers can and should continue to follow best practices that have served them well in their own data centers.