Multi-tenant Database Operations Analyzer for Error Tracing
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Solution Overview
Problem
In multi-tenant database systems, debugging errors and tracing side-effects during CRUD operations can be challenging due to shared application code and data, making it difficult to identify the cause of issues affecting customer-developed applications.
Innovation Solution
An operations analyzer is implemented within the multi-tenant data processing system to analyze objects, evaluate validation, assignment, workflow, and escalation rules, and generate reports detailing the impact of CRUD operations, thereby facilitating error identification and performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a multi-tenant database system is implemented to provide cloud-based processing, then cost savings and resource sharing are improved, but debugging errors and tracing side-effects become more difficult
Solution Approach 1:
The patent segments the execution trace into distinct components: tenant-specific code execution traces and system-wide code execution traces. This segmentation allows the system to track operations at different levels of abstraction, making it easier to identify whether an error originates from tenant-specific code or shared system code, thereby resolving the difficulty of error tracing in multi-tenant environments.
Solution Approach 2:
The patent introduces an intermediary analysis mechanism that processes and correlates execution traces from multiple tenants. This intermediary layer aggregates trace information, applies filtering and correlation rules, and presents simplified error reports to users. The intermediary mechanism transforms the complexity of multi-tenant trace data into manageable, actionable insights without requiring users to manually analyze raw trace data.
2Device complexity
If shared application code is used across all tenants, then system complexity is reduced and maintenance is easier, but it becomes difficult to determine the cause of side-effects affecting customer applications
Solution Approach 1:
The patent applies local quality by differentiating between tenant-specific code execution and system-wide code execution. The trace analysis mechanism treats these two types of code differently, generating specialized trace information for each. This allows the system to maintain a unified codebase while providing tenant-specific debugging capabilities, effectively applying local quality analysis to shared code.
Solution Approach 2:
The patent implements feedback mechanisms that provide real-time information about code execution paths and potential errors. The system analyzes execution traces and provides feedback to users about the likely causes of errors, including which specific lines of shared code may be responsible. This feedback loop enables users to quickly identify the source of side_effects without manually analyzing the entire codebase.
3Measurement precision
If comprehensive trace analysis is performed to identify all CRUD operations, then error identification accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by selectively analyzing only the portions of execution traces that are most likely to contain errors. The system uses heuristics and rules to identify critical operation paths and focuses trace analysis on those segments rather than uniformly analyzing all CRUD operations. This selective approach maintains high error identification accuracy while significantly reducing the time and computational resources required for analysis.
Solution Approach 2:
The patent changes parameters of the trace analysis process dynamically based on the specific error conditions and tenant configurations. The system adjusts analysis depth, trace collection scope, and correlation rules according to the situation at hand. This parameter adaptation allows the system to maintain high measurement precision for error identification while optimizing processing time by avoiding unnecessary analysis of irrelevant operations.
Data Source
AI summary
A system and method for analyzing operations in a multi-tenant database system environment is provided. The system may include a database storing tenant application data and common application data, the tenant application data and common application data controlling a creation, read, update, deletion or undeletion of an object in the multi-tenant database system environment. The system may further include a processor to analyze the tenant application data and common application data to identify therein where the object is being modified, and generate a report identifying potential errors or side effects which may affect the object based upon the analyzed tenant application data and common application data.