I've always considered Oracle's Dave Chappell a thought leader in advancing the case for SOA across complex environments, and his latest article on application grids didn't disappoint.
As Dave points out, SOA adoption is outpacing Moore's Law, meaning that all this new messaging that's taking place between applications and systems is greatly taxig our existing systems. "The potential to overwhelm your systems has become very real, and may happen at times when you least expect it," he writes.
Latency can add up pretty quickly, he notes. Data files grow larger and larger, especially as multimedia becomes part of the data mix. In addition, XML payloads are expanding. In one instance, Dave observes that each of 15 service calls to an application was spending 1-2 seconds in an open source Web service toolkit doing parsing and marshaling of the XML payload. With thousands of users, this can slow things down pretty quickly.
Dave proposes harnessing the power of grid, which essentially dynamically spreads processing loads and storage requirements across machines. As he puts it:
By spreading workloads across application grids, a range of operations, including parallel processing of queries, events, and transactions, can be supported. "For large datasets, an entire collection of data may be put to the grid as a single operation, and the grid can disperse the contents of the collection across multiple primary and backup nodes in order to scale," Dave says.
As Dave points out, SOA adoption is outpacing Moore's Law, meaning that all this new messaging that's taking place between applications and systems is greatly taxig our existing systems. "The potential to overwhelm your systems has become very real, and may happen at times when you least expect it," he writes.
Latency can add up pretty quickly, he notes. Data files grow larger and larger, especially as multimedia becomes part of the data mix. In addition, XML payloads are expanding. In one instance, Dave observes that each of 15 service calls to an application was spending 1-2 seconds in an open source Web service toolkit doing parsing and marshaling of the XML payload. With thousands of users, this can slow things down pretty quickly.
Dave proposes harnessing the power of grid, which essentially dynamically spreads processing loads and storage requirements across machines. As he puts it:
"Using a combination of complementary technologies, we spread compute operations across a distributed network of machines, and lessen the processing and memory requirements of our data consumers - SOA services, application servers, and client applications. We also remove the need to use a database for intermediate storage of data while it is (or simply so it can be) processed. By using an application grid we can also implement patterns where we pass around references to data, rather than the data, resulting in huge efficiency gains in the communications layer, and dramatically reducing or eliminating the boundary cost."By "boundary costs," Dave refers to the handling or processing of services from multiple domains.
By spreading workloads across application grids, a range of operations, including parallel processing of queries, events, and transactions, can be supported. "For large datasets, an entire collection of data may be put to the grid as a single operation, and the grid can disperse the contents of the collection across multiple primary and backup nodes in order to scale," Dave says.
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