Dynamic Event Log Management for SaaS Tenants
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Solution Overview
Problem
In multi-tenant Software-as-a-Service (SaaS) environments, the varying event log rates from different tenants lead to inefficient use of computing resources, as existing systems often require frequent generation and deletion of data structures, causing performance delays in log queries and reporting.
Innovation Solution
A system that determines the event rate for each tenant and generates data structures based on a calculated rotation interval, allowing for dynamic storage of event logs within a time window, thereby optimizing resource utilization and reducing the need for frequent data structure changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single-sized data structure is used for storing event logs, then device complexity is reduced, but productivity decreases due to frequent generation and deletion of data structures
Solution Approach 1:
The patent implements dynamic data structures that automatically adjust their size and retention period based on the event rate of each tenant. The system monitors event rates and modifies data structure parameters (such as time window duration and storage capacity) in real-time, allowing the data structure to adapt to varying log volumes without manual intervention or frequent recreation.
Solution Approach 2:
The system changes key parameters of the data structure based on event rate measurements. When event rates increase, the system extends the time window and increases storage capacity; when event rates decrease, it reduces these parameters. This dynamic parameter adjustment optimizes both storage efficiency and query performance without requiring system recreation.
2Adaptability or versatility
If data structures are frequently generated and deleted to accommodate varying event rates, then adaptability improves, but loss of time increases due to performance delays
Solution Approach 1:
The system performs preliminary actions by proactively adjusting data structure parameters based on predicted event rates. Instead of waiting for event rates to change and then reacting, the system monitors trends and pre-adjusts storage capacity and time windows before peak event rates occur, preventing performance delays during high-volume periods.
Solution Approach 2:
The patent ensures continuous operation of data structures by maintaining them throughout their lifecycle without deletion and recreation. The system continuously monitors event rates and makes incremental adjustments to data structure parameters, ensuring uninterrupted log storage and query capabilities while adapting to changing conditions.
3Reliability
If storage capacity is increased to accommodate high event rates, then reliability improves, but use of energy increases
Solution Approach 1:
The system applies local quality by customizing data structure parameters for each tenant based on their specific event rates. Instead of allocating maximum storage capacity to all tenants uniformly, the system assigns storage resources proportional to each tenant's actual needs, optimizing the balance between reliability and energy consumption on a per-tenant basis.
Solution Approach 2:
The system implements periodic monitoring and adjustment of data structure parameters. Rather than continuously allocating maximum resources, the system periodically evaluates event rates and adjusts storage capacity accordingly, reducing energy consumption during low-event periods while maintaining adequate storage during high-event periods.
Data Source
AI summary
Some implementations described herein relate to a system that is configured to obtain one or more event logs associated with a tenant of the system. The system may be configured to determine, based on the one or more event logs, an event rate associated with the tenant and thereby determine, based on the event rate, a rotation interval. The system may be configured to cause, based on the rotation interval, a data structure to be generated for storing event logs associated with the tenant that are obtained during a time window. The system may be configured to obtain, within the time window, one or more additional event logs associated with the tenant and to cause, based on obtaining the one or more additional event logs within the time window, the one or more additional event logs to be stored in the data structure.