Serverless Data Pipelines for Flexible Endpoint Delivery
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Solution Overview
Problem
Conventional computing systems and architectures for data processing and delivery in service provider systems are costly, difficult to scale, and inefficient, particularly during downtimes or updates, and require specific server configurations that are hard to change.
Innovation Solution
Implementing a serverless computing environment with computing code and microservices to ingest, transform, and load data using applications and data processing pipelines, allowing dynamic resource allocation and flexible system configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If specifically configured and designated servers are used for data processing and delivery, then data processing can be performed with dedicated infrastructure, but the system becomes costly, difficult to change, and hard to scale
Solution Approach 1:
The patent implements dynamic server selection where the system automatically chooses between first and second servers based on real-time conditions. The first server handles data processing under normal conditions, while the second server takes over during maintenance or failures. This dynamic switching mechanism provides both reliability through dedicated infrastructure and adaptability through automatic reconfiguration, resolving the contradiction between system stability and flexibility.
2Productivity
If conventional server architectures are used for data ingestion and delivery, then data processing can be performed, but the system slows down and becomes unusable during system downtimes, servicing, or updates
Solution Approach 1:
The patent implements preliminary action by pre-configuring a second server specifically for handling data processing during maintenance periods. Before the first server undergoes servicing or updates, the system is already prepared with an alternative server ready to take over. This eliminates service interruptions because the transition to the second server is instantaneous, preventing any loss of productivity during maintenance activities.
3Reliability
If server computing machines are used for data processing, then data can be processed and delivered, but resource allocation becomes specific and scalability is limited
Solution Approach 1:
The patent implements universality by designing the second server with multi-functional capabilities. The second server can handle both backup data processing functions and serve as the primary processing server when needed. This universal design allows the system to scale flexibly, as either server can assume any role based on demand, eliminating the limitation of specific resource allocation while maintaining reliable data delivery through dedicated infrastructure.
Data Source
AI summary
There are provided systems and methods for serverless data ingestion for transforming and delivering data in system endpoints. An entity, such as company or business, may utilize computing services provided by a service provider. When providing these services, one or more computing services, processors, or the like of the service provider's computing architecture may be used. This may include use of serverless computing environment to delivery data to internal and/or external endpoints. To automate data delivery in a serverless environment, computing code for data processing and delivery pipelines may be configured and deployed in the serverless environment. This allows applications and microservices to be executed in the serverless environment to provide a computing architecture for without requiring servers and designation of server clusters. The data pipeline may provide operations for ingesting, transforming, and loading data when received for delivery to endpoints.