These five companies are using cloud computing in production settings to achieve five common cloud-oriented goals:
- Perform load balancing and performance testing.
- Determine appropriate cloud adoption strategies for web and mobile applications.
- Use data and predictive analytics to create a "perfect" environment for consumers.
- Meet storage security and compliance requirements.
- Integrate development tools into the cloud environment.
These basic resources will introduce you to cloud computing.
- A main cloud primer
- Determining what application should and shouldn't run in the cloud
- Cloud computing at developerWorks
Cloud computing is designed to provide on demand resources or services over the Internet, usually at the scale and with the reliability level of a data center; to achieve this reliability, you need to keep the performance level of your cloud at its best. Load balancing — spreading the workload around in a timely fashion — and performance testing — being able to determine your cloud's performance level for all components both before and during transactions — are critical to performing this task.
Load balancing and performance testing: SOASTA
- 8 Common Myths About Performance Testing in Production (registration required)
- Stop Cheating: Adequate Website Performance Testing (registration required)
- Strategies for Seasonal Readiness (registration required)
- Five Strategies for Performance Testing Mobile Applications (registration required)
- Cloud Testing Production Applications (registration required)
Load balancing and performance testing: developerWorks
- Using MapReduce and load balancing on the cloud
- Enable application-centric cloud management
- Load balancing a chat server
- Analyze and optimize cloud cluster performance
- Craft a cloud performance metrics policy
- Develop and deploy cloud-optimized 4GL applications
- Grid and P2P add to automated testing on the cloud
- Configure a complex cloud app test system
Cloud computing and mobile device access go hand in hand; you'll rarely find a cloud environment that doesn't make use of mobile applications. In business's rush to the cloud, there are many questions to answer in order to determine whether the cloud is right for you, what model your business should be following (and to what extent), and just how mobile your cloud needs to be to satisfy the requirements of your customers.
Mobile and cloud adoption strategies: Sogeti
- Seize The Cloud: From Utility Computing to a Cloud Revolution (ebook)
- Collaboration in The Cloud: Effectively Crossing Conversational Boundaries (ebook)
- Top 5 mobile apps revealed
- Best practices for IT departments on mobile app development and integration
Mobile and cloud adoption strategies: developerWorks
- Change app behavior: From in house to the cloud
- Considerations for migrating to the cloud
- Migrate your Linux application to the cloud
- Build a more secure, mobile cloud environment
- Mobile cloud computing
- Understanding the four variables that shape a cloud mobile security policy
- Develop mobile cloud applications using a collaborative, user-centric model
It is now, officially, the era of Big Data. Thanks to faster processing, better bandwidth, and cloud-oriented infrastructure strategies, businesses can capture more and more of the transactional data that occurs between and among users and systems. But capturing and storing that data would just be a waste of effort; so would culling through it by "hand" to try to gain some insights. Thanks to smarter software, you're not limited to those options. Now it is possible to span the enormous volumes of captured data and allow "containerized" best practice and expert knowledge to automatically analyze what the information means; you can even perform these actions on data in transition. Plus, you're no longer limited to looking backwards at what the data means — you can also use this data to predict what will happen next.
Data and predictive analytics: Flagship Solutions Group
- Transforming professional football into a customer-oriented entertainment systems via data analytics
Data and predictive analytics: developerWorks
- Hadoop-based data analytics on IBM SmartCloud Enterprise
- Agile predictive analytics on IBM SmartCloud Enterprise
- Cloud business analytics
- Solve cloud-related big data problems with MapReduce
- Rob Thomas and Dan Gisolfi on Big Data and cloud computing
- IBM Intelligent Operations Center
Two things that you always have to have with a technology system are a way to secure your data and a way to store your data. With cloud computing, you start with the traditional IT systems forms of security and storage, then expand those envelopes to include features, methods, and technique that are unique to the structure of a cloud — ensuring transaction speed, reliability, protection and effective access control, and recoverability.
Cloud storage and security: Compsat Technology
Cloud storage and security: developerWorks
- Dat a protection in the cloud
- Cloud governance and security
- Build a regulatory compliant web application
- Recover data in IBM SmartCloud Enterprise
- Understanding ephemeral storage
- Cloud security scenarios
- Anatomy of a cloud storage infrastructure
- Build an effective cloud policy
If you're going to move some or all operations to a cloud environment, you need to be able to take your application development and deployment tools and infrastructure management tools with you. Always be aware of the tools that travel well and those that don't.
On-boarding development tools to the cloud: CloudOne
On-boarding development tools to the cloud: developerWorks
- Develop cloud applications with Rational tools
- Best practices for cloud-based asset-centric collaboration
Scott Laningham, host of developerWorks podcasts, was previously editor of developerWorks newsletters. Prior to IBM, he was an award-winning reporter and director for news programming featured on Public Radio International, a freelance writer for the American Communications Foundation and CBS Radio, and a songwriter/musician.
Kane Scarlett is a technology journalist/analyst with 20 years in the business, working for such publishers as National Geographic, Population Reference Bureau, Miller Freeman, and IDG, and managing, editing, and writing for such august journals as JavaWorld, LinuxWorld, and of course, developerWorks.
Robin Langford, developerWorks managing editor, divides her time between rich media production and IBM product trials. Before developerWorks, she wrote for, edited, and managed information for IBM software and hardware in development. Her degrees are in English from Auburn University in Auburn, AL, and Technical writing from Rensselaer Polytechnic Institute in Troy, NY.