Cloud Computing

Russell Rothstein (U.S) Service Performance and Availability Issues in the Cloud - Part 1

With all of the hype around the benefits of private clouds, many IT teams are feeling the pressure to race ahead with their cloud strategy. I've noticed that with all of the pressure and excitement, many organizations are focusing entirely on building out the infrastructure and on migrating their applications and services.

If you are working on your cloud strategy or implementation now, it's important to look ahead and think about how you are going to manage it when it goes live. As with any production environment, there are going to be performance and availability issues. And because of the high expectations from the cloud, you are going to need a way monitor, communicate and control service levels right out of the gate.

I've put together a list of the top service delivery issues that you need to handle in a private or hybrid cloud. In this blog entry, I'll review the first three hurdles, and talk about ways you can address them. In part two, I'll follow up with the rest of the list.


Challenge 1: Performance - If you don't know which physical servers your application is running on in the cloud, how do you find server-related root causes when performance issues arise?

In fully-dedicated environments, we sometimes use infrastructure metrics and events to diagnose performance issues. But silo-centric metrics don't show service-centric performance in the cloud. Inferring application performance from tier-based statistics becomes challenging - if not impossible - when applications share dynamically allocated physical resources. To manage application performance in the cloud, you need a real-time topological map of service delivery across all tiers. Since the landscape is always changing, it's essential that the dependency map is dynamically generated and automatically updated for every single transaction and service instance. With the map in hand, you can then take advantage of tier-specific metrics for diagnostics.


Challenge 2: Chargeback - How do you know how much CPU your application is consuming in order to choose an appropriate chargeback model or verify your chargeback bills?

IT needs a new paradigm for assessing resource consumption in order to transition from a resource-focused cost-center to a business-service-focused profit-center. But traditional chargeback and APM tools do not collect resource utilization per transaction to enable business-aligned costing and chargeback paradigms. For the cloud, you need a solution that monitors consumption for every service across multiple applications and tiers, so you can accurately cost services, decide on appropriate chargeback schemes, and tune applications and infrastructure for better resource utilization and lower cost.


Challenge 3: Not aligned with the business - How do you ensure that services are allocated according to business priority?

Clouds offer us new levels of dynamic resource allocation. However, to ensure that SLAs in the cloud are met, you must be able to prioritize the allocation of resources based on measurements of real end user performance and an accurate view of where additional resources can truly alleviate SLA risks. To make that possible, you need a clear picture of resource consumption at the transaction level and business intelligence about the impact of each infrastructure tier on performance. Provisioning based on business priorities becomes even more critical as cloud architectures transition to a dynamic auto-provisioning model.


  • Part 2 will be published on Tuesday 19th April

Russell Rothstein is Vice President of Product Marketing at OpTier, a supplier of software for cloud performance management, application performance management and business transaction management. Follow him on twitter at russrothsteinit and



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