7 steps to Enterprise PaaS
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Move from Web Era to PaaS requires careful planning. This presentation simplifies the process by outlining 7 basic steps an Enterprise has to consider as it moves to PaaS
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7 steps to Enterprise PaaS
- 1. 7 Best Practice when moving to Enterprise PaaS
- 3. Other people must have do this before?
- 5. Every enterprise is unique however there are common requirements
- 7. Discover The Current State
- 8. The Current State Discover System People Requirements Projects
- 10. Understand the dependency between applications
- 14. The application should operate in an elastic environment
- 16. Move to modern elastic middleware
- 18. Frameworks can improve developer productivity and innovation by 50%
- 22. No machines or middleware to manage
- 23. Latest high productivity frameworks
- 24. Choice of application services
- 26. More responsive to developers
- 27. Elastic and dynamically scalable
- 29. Digest future cloud advances
- 31. Reference Architecture Demonstration 17
- 33. Evolve YOUR business and IT at your pace
- 36. Building application for the cloud
- 37. Cloud first policy for new applications
- 38. Cloud based application development
- 42. Monitor for application failures
- 43. Identity application load trends
- 45. Tracing available in production minimizes need to reproduce problems in the lab
- 46. Common view between developers and operations simplifies escalations
- 47. Transparently instrument Spring applications at the code level
- 48. Roll up data from multiple application nodes with filters and drill down
- 49. Hyperic integration for unified operational view and robust alertingBenefits
- 50. Application Visibility Answers Important Questions Monitor How is my Hotel Booking app performing? Are the response times within expected SLAs? Is there an issue with finding and displaying available hotel rooms? Is the database a bottleneck?
- 53. Horizontal scaling requires module application
- 54. Vertical Scaling has it limits.
- 55. Cloud Scaling requires application portability.Vertical Cloud
- 56. Virtualizing Monolithic Applications – a good start 70% 105% Scale App C 35% App B App B Avg CPU Utilization Avg CPU Utilization 35% App A App A Avg CPU Utilization
- 57. Virtualizing Monolithic Applications – the goal Scale App B App B App A 35% App B App B App B App B App B App B Avg CPU Utilization 35% App A App A App A App A App A App A Avg CPU Utilization
- 58. Virtualizing Monolithic Applications – the goal App B App B App A 35% App B App B App B App B App B Avg CPU Utilization App A App A App A App A 35% App A Avg CPU Utilization Scale
- 60. Ensure OPEN agreement both technical and legally.
- 62. Cloud ROI model
- 63. Flexibility
- 64. Response to Peak DemandScale App A App B App B App A App B App B App B App B App A App A App B App A App B App A App A App A App A
- 65. Avoiding Bottlenecks at the Data Layer Scale How to scale the data tier?
- 67. Data distribution, replication, partitioning and colocation
- 68. Pools memory and disk across many nodes
- 70. Move functionality to the data for peak performance
- 71. Active/Continuous Querying and Event Notification
- 72. Changes are propagated to one or more "active" copiesApplication Data Lives Here Application Data Sleeps Here Other Data Systems File Systems Databases
- 75. Ensure your new cloud application can be integrated into your existing application .
- 77. Modern messaging for the cloud... Integrate Your [Java Spring] App Hyperic & Spring Insight Trace, Monitor, Alert, Manage Built with SpringSource Tool Suite Cloud scale message bus AMQP, SMTP, XMPP, Stomp, … Point –to-point and pub-sub Virtual hosts, dynamic config RabbitMQ Message Brokers Other clouds devices applications
- 79. Summary
- 80. Enterprise PaaS – 7 Best Practices
- 82. No machines or middleware to manage
- 83. Latest high productivity frameworks
- 84. Choice of application services
- 86. More responsive to developers
- 87. Elastic and dynamically scalable
- 89. Digest future cloud advances
Notes de l'éditeur
- As we think about it from an enterprise perspective, Cloud Foundry is an opportunity to boost application velocity through systemic productivity improvements across the entire dev and ops pipeline. Developers can focus on the app while IT delivers the platform as a service. PaaS speeds up prototyping, trial, testing, scale testing, production, updating, cloud-scaling apps.
- Although Spring is famous for its openness and portability, we can take advantage of our deep understanding of Spring to add unique value for applications running on the vFabric platform. Spring Insight is a technology that provides code level tracing – tracking the time a transaction spends in each method and JDBC (database) call – transparently for Spring Applications. Basically, users get very deep information on the operation of a running Spring application just as a benefit for running in on vFabric. No code modifications or setup is required. Spring Insight has been available for developers for almost a year as part of the tc Server Developer Edition. This is a single-user, development-time solution that integrates helps developers find performance bottlenecks in their applications while running it on their local machines, typically inside our Eclipse-based IDE, SpringSource Tool Suite. Next year we will roll out Spring Insight Enterprise, which leverages the same code-level tracing technology but pulls together information from multiple application servers into a single console with roll-up views, drill downs, and historical comparisons. This solution has been designed to minimize the overhead of the monitoring so it is suitable for both test and production environments. While the Spring Insight Enterprise console is useful for both administrators and developers who may need to troubleshoot problems in production, it is also important that administrators and operations have a single place to go for vFabric monitoring. Therefore, Spring Insight Enterprise monitoring will be available not only as a stand-alone console but also through a plug-in to the Hyperic monitoring solution, enabling a single view across data from multiple sources and integrated alerting and control actions.
- Over the past year, we have invested a lot of effort in providing automatic visibility into Spring applications so that our customers can answer important questions about the behavior of their applications.In this particular example, we have a Hotel Booking application. By using the Spring Insight technology baked into our application platform, our customers can interact with a chart that illustrates how their application is performing and whether or not the response times are within the expected SLAs.If there is an issue, they are able to drill into the application further. Let’s say that certain response times for finding and displaying available hotel rooms look out of band…well, you can selectively drill into that request and see if the database is the bottleneck, for example. This level of visibility helps developers create high performing applications, but as we will cover in a moment, this information combined with visibility across the application infrastructure stack is also critical for delivering the proactive performance management required of today’s modern platforms.
- As we think about it from an enterprise perspective, Cloud Foundry is an opportunity to boost application velocity through systemic productivity improvements across the entire dev and ops pipeline. Developers can focus on the app while IT delivers the platform as a service. PaaS speeds up prototyping, trial, testing, scale testing, production, updating, cloud-scaling apps.