it process automation

Application-to-Cloud Migration

Leveraging its unique AppsOne product and technology, Appnomic provides a performance monitoring and benchmarking solution to mitigate the risk of migration of enterprise applications from on-premise IT environments to Clouds, or to external data centers.  Appnomic’s AppsOne enables pre- and post-migration performance benchmarking assurance for service providers and their enterprise customers.  As a result, application owners are assured that their applications will perform as well or better after migration as they did before.  The AppsOne Application-to-Cloud Migration solution also helps reduce cap-ex by eliminating over-provisioning of application infrastructure in the Cloud.

Customers may purchase the application migration solution directly from Appnomic, or alternatively, can engage a select group of system integrators who have incorporated AppsOne into their Cloud migration practice. This growing group of world-class integrators is working with end-customers to help them assess, plan, benchmark and execute migration to the Cloud.

Questions You Need to Answer Before You Migrate Applications to the Cloud.

  • How will performance of an application be impacted with migration to the Cloud?
  • What should be the baseline target for performance of an application in the Cloud?
  • How do I avoid over provisioning in the Cloud?
  • Can I optimize my application performance once in the Cloud?
  • How can I get continuous visibility into my Cloud provider’s SLA delivery?
  • How do I plan for growth in my application usage in the Cloud?

The Appnomic Approach

The AppsOne Application-to-Cloud Migration solution answers these key questions delivering:

  • Detailed measurements and analytics on application usage patterns.
  • Identification of application optimization opportunities.
  • Pre- and post-migration management of performance SLAs.

Detailed Measurements and Analytics on application usage patterns

Old-fashioned capacity planning focuses on the peak usage of the application.  Appnomic delivers a new way to look at capacity planning within the Cloud - elasticity planning. You have to factor peak usage, moderate usage and low-level usage as well. If you are going to maximize the benefits of your Cloud infrastructure, you need to understand how you're going to be provisioned to respond to the varying performance demands of your application.

AppsOne uses Appnomic’s patented Application Behavior Learning (ABL) technology to identify unique usage patterns and measuring performance for many varieties of enterprise-grade applications.  Illustrations 1 and 2 show examples of usage patterns. These patterns identify different combinations of concurrent transaction types and load. These usage patterns correlate to different infrastructure behavior patterns.

AppsOne customers can apply application usage patterns to manage the elasticity of their Cloud infrastructure. Example usages patterns include steady state, on and off, or burst scenarios. By understanding the nature of these usage patterns and the correlation to underlying infrastructure component performance as well as response times of the most important transactions in an application, you can tune your application and right-size it.

Application usage patterns also provide guidance for application test scripts that reflect real user usage patterns for running load and functional tests - testing will never be the same.

Identification of Application Optimization Opportunities

As illustrated in Tables 1 and 2, AppsOne provides insights into ‘hotspots’; over- and under-provisioned infrastructure resources (along with variability in transaction response times as described above).  This information can then be utilized by system administrators and application development teams to optimize application code or system configurations.  For example, if the SAN storage standard deviation for Disk I/O during peak load patterns is consistently high as compared to during other load patterns and the CPU and memory are low then it gives an indication that top write/update peak load transaction types are likely suffering because of sub-optimal configuration at the storage level. This may be addressed by reviewing and changing the LUN configuration.


 Illustration 1: Application Usage Patterns


 Illustration 2: Application Usage Pattern Details

AppsOne customers can apply application usage patterns to manage the elasticity of their Cloud infrastructure. Example usages patterns include steady state, on and off, or burst scenarios. By understanding the nature of these usage patterns and the correlation to underlying infrastructure component performance as well as response times of the most important transactions in an application, you can tune your application and right-size it.

Application usage patterns also provide guidance for application test scripts that reflect real user usage patterns for running load and functional tests - testing will never be the same.

Identification of Application Optimization Opportunities

As illustrated in Tables 1 and 2, AppsOne provides insights into ‘hotspots’; over- and under-provisioned infrastructure resources (along with variability in transaction response times as described above).  This information can then be utilized by system administrators and application development teams to optimize application code or system configurations.  For example, if the SAN storage standard deviation for Disk I/O during peak load patterns is consistently high as compared to during other load patterns and the CPU and memory are low then it gives an indication that top write/update peak load transaction types are likely suffering because of sub-optimal configuration at the storage level. This may be addressed by reviewing and changing the LUN configuration.

“We are now able to gain much deeper insights into real user experience, underlying infrastructure, component performance and application usage patterns which is strategic to both Persistent and our clients. Appnomic’s AppsOne complements our own Cloud Assessment Tool and enables us to better assess the optimal target Cloud architecture for applications we are migrating to the Cloud on behalf of our clients as well as ensure the ideal service agreement for each unique situation.”

- Shreekanth Joshi, Vice President – Cloud Computing Practice, Persistent Systems

Pre- and Post-Migration Management of Performance SLAs

With AppsOne, customers can collect performance data on real user transactions (Table 1) as well as infrastructure performance & utilization (Table 2) prior to migration to the Cloud.  This performance data is available for business critical transactions during multiple periods of application usage like peak business use and off-peak hours.  Customers use this data to establish SLAs that should be met or improved upon after migration to the Cloud.  Additionally, customers can also monitor and manage these SLAs in production by deploying AppsOne for their Cloud-hosted application once the migration is complete.

Benefits of the Application-to-Cloud Migration Solution

  • Eliminate the risk of degradation in user experience for applications post migration to the Cloud.
  • Hold Cloud providers accountable for application performance post migration to the Cloud.
  • Avoid the costs associated with over provisioning in the Cloud during and post migration.
  • Proactively manage the costs associated with expansion of your application Cloud.

Appnomic Application-to-Cloud Migration Partners

Appnomic has partnered with multiple service providers who integrate Appnomic technologies into their Cloud migration and Cloud management practices. One of those partners is Persistent Systems. Persistent Systems (www.persistentsys.com) is a leading systems integrator with more than 700 engineering resources in their Cloud practice who are enabling customers to migrate their applications from on-premise to the Cloud.

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SAP Application Performance Management
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Application-to-Cloud Migration