Cellular Observability Architecture with Tiered Storage
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Solution Overview
Problem
Telecommunications companies face challenges in cost-effectively expanding their network infrastructure while improving user experience due to the complexity of monitoring and managing radio access networks (RANs), which require extensive observability and specialized hardware/software.
Innovation Solution
A system and method for collecting and storing observability data using a short-term data storage layer and a long-term data storage layer, integrated with Kubernetes clusters and network functions virtualization (NFV) infrastructure, allowing for efficient data management and network optimization across 5G cellular networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If data is stored indefinitely in a single storage layer, then data retention is improved, but data retrieval efficiency deteriorates
Solution Approach 1:
The storage system is segmented into multiple storage layers (hot, warm, cold storage) with different retention periods and access speeds. Frequently accessed data is kept in hot storage for rapid retrieval, while less frequently accessed data is moved to cold storage for long-term retention, thereby resolving the contradiction between retention duration and retrieval efficiency
Solution Approach 2:
The system dynamically transitions data between storage layers based on access patterns and age. Data automatically moves from hot to warm to cold storage as it ages and becomes less frequently accessed, optimizing both retention and retrieval performance at different time points
2Ease of operation
If all data is kept in short term storage, then data accessibility is improved, but storage costs deteriorate
Solution Approach 1:
The storage system segments data into different accessibility tiers (hot, warm, cold) with corresponding storage resources. Only data requiring frequent access occupies expensive high-performance storage, while less accessible data resides in cheaper storage media, reducing overall storage resource consumption while maintaining necessary accessibility
Solution Approach 2:
The system changes storage parameters (access speed, retention period, storage media type) based on data characteristics and access patterns. By adjusting these parameters dynamically, the system optimizes the balance between data accessibility and storage resource consumption
3Quantity of substance
If data is archived in long term storage, then storage costs are reduced, but data retrieval speed deteriorates
Solution Approach 1:
The system dynamically manages data location based on access patterns. When data in long-term storage is accessed, it is automatically promoted to shorter-term storage layers, ensuring that frequently accessed data moves to faster storage media while maintaining cost efficiency for infrequently accessed data
Data Source
AI summary
A system for cellular system observability data collection includes systems generating data; an observability (OBF) layer configured to collect the data and store the data for a maximum threshold amount of time; and a long term storage layer. The long term storage layer is in communication with the OBF layer to store the data for a term greater than the maximum threshold amount of time. Use applications requiring data to be not older than the maximum threshold amount of time retrieve data directly from the OBF layer, while other use applications retrieve data from the long term storage layer.