How to Automatically Deploy Database Containers Based on Workload Patterns
This patent describes a method for automatically deploying optimized database containers by analyzing storage system data to identify workload "fingerprints" and matching them to specific container configurations.
Original patent title: “Fingerprint-based database container deployment”
This patent describes a method for automatically deploying optimized database containers by analyzing storage system data to identify workload "fingerprints" and matching them to specific container configurations. Granted in 2026.
Coverage
What does this patent actually cover?
The patent describes a system for smart deployment of database containers. It starts by gathering information from one or more storage systems in a storage environment to identify "characteristics of a plurality of database workloads." For example, it might analyze data access patterns or I/O demands. Based on these characteristics, the system then identifies "fingerprint information for a plurality of database workload types." This fingerprint acts like a unique profile for how a database is used. Finally, when a new database container is needed, the system uses this "fingerprint information for a particular database workload type" to deploy a database container specifically configured for that workload, aiming for better performance and resource use.
The gap
What does this patent NOT cover?
- Does not cover deploying database containers without first identifying workload characteristics from storage system data.
- Does not cover deploying containers based solely on manual configuration or generic templates without generating "fingerprint information."
- Does not cover general container deployment for applications that are not databases.
- Does not cover systems that identify workload types without specifically collecting data from "one or more storage systems."
- Does not cover identifying database workload types without creating specific "fingerprint information" for them.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → lies in creating specific "fingerprint information" from observed database workload characteristics on storage systems to automatically guide the deployment of optimized database containers. This moves beyond generic container deployment to intelligent, data-driven optimization.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Cloud database services like AWS RDS or Google Cloud SQL
Kubernetes deployments for stateful database applications
Database-as-a-Service (DBaaS) platforms
Data centers managing large numbers of virtualized databases
Why it matters
The bigger picture
This technology aims to make database operations more efficient by automating the optimization of container deployments. In large cloud environments or data centers, manually tuning database containers for every workload is complex and time-consuming. By automatically matching container configurations to specific workload patterns, this patent could lead to better performance, reduced resource consumption, and lower operational costs for companies managing many databases.
Filed
July 29, 2022
Granted
September 15, 2026
Market context
Who's building on this
Companies in this space
Major cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure are continuously optimizing their managed database services and container orchestration platforms. Companies specializing in database management and automation, such as MongoDB, Oracle, and Red Hat, also focus on efficient deployment and scaling of database workloads in containerized environments. This patent's concepts align with efforts to automate and optimize resource allocation for databases.
Market impact
This patent, once granted, could influence how database-as-a-service offerings and container orchestration platforms manage stateful workloads. It aims to reduce the manual effort and expertise required for database tuning, potentially leading to more efficient cloud resource utilization and lower operational costs for businesses. The focus on automated, data-driven deployment could become a standard feature in future database management systems.
Claim 1 — Plain English
What this patent covers
The patent describes a system for smart deployment of database containers. It starts by gathering information from one or more storage systems in a storage environment to identify "characteristics of a plurality of database workloads." For example, it might analyze data access patterns or I/O demands. Based on these characteristics, the system then identifies "fingerprint information for a plurality of database workload types." This fingerprint acts like a unique profile for how a database is used. Finally, when a new database container is needed, the system uses this "fingerprint information for a particular database workload type" to deploy a database container specifically configured for that workload, aiming for better performance and resource use.
The clever bit
The novelty lies in creating specific "fingerprint information" from observed database workload characteristics on storage systems to automatically guide the deployment of optimized database containers. This moves beyond generic container deployment to intelligent, data-driven optimization.
What it does not cover
- Does not cover deploying database containers without first identifying workload characteristics from storage system data.
- Does not cover deploying containers based solely on manual configuration or generic templates without generating "fingerprint information."
- Does not cover general container deployment for applications that are not databases.
- Does not cover systems that identify workload types without specifically collecting data from "one or more storage systems."
- Does not cover identifying database workload types without creating specific "fingerprint information" for them.
Patent timeline
Application submitted to the patent office
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
0/20
Narrow claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$19K – $61K
Midpoint $38K · 15.8 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
Concepts involved
Cite this patent
(2026). How to Automatically Deploy Database Containers Based on Workload Patterns (U.S. Patent No. 12,737,226). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12737226/fingerprint-based-database-container-deployment
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How to Automatically Deploy Database Containers Based on Workload Patterns cover?
This patent describes a method for automatically deploying optimized database containers by analyzing storage system data to identify workload "fingerprints" and matching them to specific container configurations.
When does this patent expire?
This patent is expected to expire on September 15, 2046, when the invention enters the public domain.
What problem does this patent solve?
This technology aims to make database operations more efficient by automating the optimization of container deployments. In large cloud environments or data centers, manually tuning database containers for every workload is complex and time-consuming. By automatically matching container configurations to specific workload patterns, this patent could lead to better performance, reduced resource consumption, and lower operational costs for companies managing many databases.
What does this patent NOT cover?
Does not cover deploying database containers without first identifying workload characteristics from storage system data.
Patent monitoring