Filtering Authenticated Synthetic Transactions in Cloud Monitoring
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Solution Overview
Problem
Conventional synthetic transaction monitoring in cloud computing environments inflates usage statistics and incurs unnecessary costs by counting synthetic transactions as actual usage, leading to inaccurate monitoring and potential financial burdens.
Innovation Solution
A method and system that filter authenticated synthetic transactions by analyzing request headers for synthetic tokens, verifying their correspondence to specific web services, and bypassing usage monitoring for authorized synthetic transactions, thereby excluding them from usage metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic synthetic transactions are performed to monitor service performance and availability, then service monitoring capability is improved, but usage statistics become inflated and accuracy deteriorates
Solution Approach 1:
The system segments transactions into two distinct categories: synthetic transactions (for monitoring) and actual user transactions (for usage measurement). This is achieved by introducing a synthetic token in the request header that allows the server to identify and separate synthetic transactions from genuine user transactions, enabling independent handling of each type.
Solution Approach 2:
The invention extracts synthetic transactions from the general transaction stream by analyzing request headers for synthetic tokens. Once identified, these synthetic transactions are removed from usage monitoring calculations through bypass instructions, ensuring they do not contaminate the usage statistics while still serving their monitoring purpose.
2Reliability
If synthetic transactions are counted in usage monitoring, then monitoring coverage is improved, but unnecessary costs are incurred
Solution Approach 1:
The system extracts synthetic transactions from the monitored transaction flow by detecting synthetic tokens in request headers. These identified synthetic transactions are then excluded from usage monitoring and billing calculations through bypass instructions, eliminating unnecessary costs while preserving complete monitoring coverage.
Solution Approach 2:
The synthetic token acts as an intermediary marker that enables the server to distinguish between synthetic and actual transactions. This intermediary mechanism allows the system to maintain comprehensive monitoring coverage while selectively excluding synthetic transactions from cost-incuring usage statistics.
3Ease of operation
If all transactions are monitored uniformly, then monitoring simplicity is improved, but ability to distinguish transaction types deteriorates
Solution Approach 1:
The system applies different handling rules to different parts of the transaction stream based on local characteristics. By examining the request header for synthetic tokens, the server identifies synthetic transactions and applies a different processing path (bypass monitoring) compared to actual user transactions (normal monitoring), enabling differentiated treatment while maintaining operational simplicity.
Data Source
AI summary
A method of filtering authenticated synthetic transactions comprises receiving over a network, at a server providing a first networked application, a plurality of requests for the first networked application, wherein the plurality of requests includes a first synthetic transaction. The method further comprises analyzing a respective header of each of the plurality of requests; identifying a synthetic token in the respective header of the first synthetic transaction in response to analyzing the respective header of each of the plurality of requests; determining that the identified synthetic token corresponds to the first networked application; and bypassing usage monitoring for the first synthetic transaction in response to determining that the identified synthetic token corresponds to the first networked application.