Challenges in SLA Translation
Service-Oriented Architecture (SOA) represents an architectural shift for building business applications based on loosely coupled services. In a multi-layered SOA environment the exact conditions under which services are to be delivered can be formally specified by Service Level Agreements (SLAs). However, typical SLAs are just specified at the top-level and do not allow service providers to manage their IT stack accordingly as they have no insight on how top-level SLAs translate to metrics or parameters at the various layers of the IT stack. SLA@SOI has recently proposed a conceptual framework for the precise definition and classification of SLA translations in SOA.
The full details are presented in an accompanying technical paper, Challenges in SLA Translation, but the overall framework is illustrated here in Figure 1.
Figure 1: Observables (metrics) and configurables (parameters) in SOA layers, with different types of translations.
The framework distinguishes four main translation types:
- C2C (Configuration to Configuration): this type of translation mostly relates to the dependencies within a layer or between layers. Such dependency graphs are useful in configuration management and problem diagnosis.
- M2C (Metric to Configuration): this type of translation translates higher-level objectives to lower-level system parameters. It can also be referred as “top-down” translation or SLA decomposition. It is useful for sizing and capacity planning, mostly at design time.
- C2M (Configuration to Metric): this type of translation predicts higher-level objectives from lower-level system parameters. It can also be referred as “bottom-up” translation or performance prediction. It is useful both what-if analysis at design time and predictive management at run time.
- M2M (Metric to Metric): this type of translation correlates a high-level metric with lower-level metrics. The translation can go both directions, namely decomposition or prediction, depending on the usage scenario. It is useful for forecasting and problem diagnosis at run time.
Additionally, we have also identified and described the fundamental research challenges that need to be addressed to turn the vision of holistic and transparent SLA translation into reality. These research challenges are
- Realistic workloads and usage patterns
- Tradeoff-analysis for scalable approaches
- Innovation and integration of methodologies
- Model integration and transformation
- The definition of layers and layer interfaces
- Business values and reference benchmarks
To found out more about this proposed conceptual framework and these research challenges, please see the accompanying technical paper, Challenges in SLA Translation.
Hui Li, SAP Research
Tags: Conceptual Architecture, Research Challenges, sla, Translation
December 21st, 2009 at 22:30
Good evening,
Is there some form of hierarchy between the layers? If so why is service not on top?
What I could not find in the challenges bullet list was the configuration of a transformation table in which causality between the layers is hard wired for a specific service.
Regards Nick
December 22nd, 2009 at 17:27
Dear Nick,
There is certainly a hierarchy… the one we display here is taken from OMG and its Model-Driven Architecture. For them the process layer is clearly on top.
On the other hand you could also give an even more service-oriened view on all these layers by considering that all or many of them expose their functionality as service and are managed accordingly.
Causality is definitly an important issue, which we subsumed so far in the model integration aspect.
Best regards, Wolfgang