DCT

8:25-cv-02182

Corent Technology Inc v. Microsoft Corp

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I. Executive Summary and Procedural Information

  • Parties & Counsel:
  • Case Identification: 8:25-cv-02182, C.D. Cal., 09/26/2025
  • Venue Allegations: Plaintiff alleges venue is proper in the Central District of California because Defendant Microsoft maintains regular and established places of business in the district, including in Irvine and Playa Vista, and has committed acts of infringement there.
  • Core Dispute: Plaintiff alleges that Defendant’s cloud computing products and services, including Azure Migrate, Azure Kubernetes Service, Azure Marketplace, and Azure SQL Database, infringe four patents related to cloud application migration, orchestration, multi-tenant database architecture, and usage metering.
  • Technical Context: The technology concerns foundational tools for the software-as-a-service (SaaS) industry, specifically addressing the challenges of efficiently migrating legacy applications to the cloud, managing them in a multi-tenant environment, and billing for their usage.
  • Key Procedural History: The complaint alleges that Plaintiff Corent had multiple meetings with Microsoft's product team, including the Chief Product Officer and CVP of Azure Core, dating back approximately four years prior to the complaint, where Corent's patents and product line were discussed. This history may be central to the allegations of pre-suit knowledge and willful infringement.

Case Timeline

Date Event
2010-01-01 Microsoft Azure launched (approximate date)
2011-09-23 Earliest Priority Date for U.S. Patent No. 9,495,372
2014-07-31 Earliest Priority Date for U.S. Patent Nos. 11,019,136; 10,320,893; and 10,305,761
2016-11-15 U.S. Patent No. 9,495,372 Issued
2017-10-01 Microsoft Azure Kubernetes Service (AKS) first deployed (approximate date)
2017-01-01 Microsoft Azure Migrate announced; Azure SQL Database multi-tenant patterns released (approximate dates)
2018-01-01 Microsoft Azure Migrate became generally available (approximate date)
2019-05-28 U.S. Patent No. 10,305,761 Issued
2019-06-11 U.S. Patent No. 10,320,893 Issued
2021-05-25 U.S. Patent No. 11,019,136 Issued
2025-09-26 Complaint Filed

II. Technology and Patent(s)-in-Suit Analysis

U.S. Patent No. 11,019,136 - "PARTITIONING AND MAPPING WORKLOADS FOR SCALABLE SAAS APPLICATIONS ON CLOUD"

  • Patent Identification: U.S. Patent No. 11,019,136, “PARTITIONING AND MAPPING WORKLOADS FOR SCALABLE SAAS APPLICATIONS ON CLOUD,” issued May 25, 2021 (the “’136 Patent”). (Compl. ¶62).

The Invention Explained

  • Problem Addressed: The patent addresses the technical challenges of migrating traditional, non-cloud-native ("non-tenant-aware") software applications to a cloud environment. Such migrations are often inefficient because legacy applications may not be configured to leverage cloud resources effectively, and there is a "wide variety of configurations" that may not pair well with an application's requirements. (Compl. ¶66; ’136 Patent, col. 1:42-51).
  • The Patented Solution: The patent discloses a method for systematically planning such a migration. The method involves identifying an application's constituent functional units, or "workloads," grouping them into "partitions" and "sub-partitions" based on common characteristics, and then creating multiple potential "workload assignment maps" to assign these partitions to specific cloud resources. These maps are then ranked based on rules such as cost or performance to find an optimal migration strategy before deployment. (Compl. ¶¶65, 68; ’136 Patent, col. 2:5-23).
  • Technical Importance: This approach provides a structured, automated method for analyzing and optimizing cloud migration, replacing ad-hoc processes and allowing for better decision-making regarding cost, scalability, and performance. (Compl. ¶66).

Key Claims at a Glance

  • The complaint asserts at least independent claim 1. (Compl. ¶139).
  • Claim 1 is a method claim with the essential elements:
    • identifying workloads of a non-tenant-aware application and a set of application characteristics for each;
    • creating a partition of the workloads in reference to a partition application characteristic;
    • grouping the created partition into a plurality of workload sub-partitions as a function of a common workload characteristic;
    • assigning each partition of the workloads to a set of cloud resources;
    • constructing a plurality of workload assignment maps to assign workloads; and
    • ranking each one of the plurality of workload assignment maps based on a set of rules. (Compl. ¶68).
  • The complaint reserves the right to assert additional claims. (Compl. ¶139).

U.S. Patent No. 10,320,893 - "PARTITIONING AND MAPPING WORKLOADS FOR SCALABLE SAAS APPLICATIONS ON CLOUD"

  • Patent Identification: U.S. Patent No. 10,320,893, “PARTITIONING AND MAPPING WORKLOADS FOR SCALABLE SAAS APPLICATIONS ON CLOUD,” issued June 11, 2019 (the “’893 Patent”). (Compl. ¶69).

The Invention Explained

  • Problem Addressed: Like its family member the ’136 Patent, the ’893 Patent addresses the problem that legacy applications "may fail to take advantage of the additional resources offered by a cloud environment" and can "run inefficiently in a cloud." (Compl. ¶73; ’893 Patent, col. 1:45-51).
  • The Patented Solution: The patent claims a system for implementing the migration planning process. This system comprises a series of distinct engines: a "scanning engine" to identify workloads based on defined rules, a "partitioning engine" to group them, a "mapping engine" to assign partitions to cloud resources based on user-defined rules, and a "rendering engine" that constructs a final migration plan. (’893 Patent, col. 8:16-41; Compl. ¶75). The system is designed to use various databases containing rules for partitioning and mapping. (’893 Patent, Fig. 2).
  • Technical Importance: This claimed system provides a concrete architecture for automating the complex task of workload analysis and migration planning for cloud environments. (Compl. ¶73).

Key Claims at a Glance

  • The complaint asserts at least independent claim 1. (Compl. ¶146).
  • Claim 1 is a system claim with the essential elements:
    • a scanning engine configured to identify workloads of a non-tenant-aware application;
    • a partitioning engine configured to group the workloads to a smaller set of partitions;
    • a mapping engine configured to assign each partition to a set of cloud resources;
    • a rendering engine that constructs a migration plan to migrate the workloads; and
    • wherein the engines comprise stored program instructions embedded in a non-transitory computer readable storage medium, executed by a processor. (Compl. ¶75).
  • The complaint reserves the right to assert additional claims. (Compl. ¶146).

U.S. Patent No. 9,495,372 - "MULT-TENANT AGILE DATABASE CONNECTOR"

  • Patent Identification: U.S. Patent No. 9,495,372, “MULT-TENANT AGILE DATABASE CONNECTOR,” issued November 15, 2016 (the “’372 Patent”). (Compl. ¶76).
  • Technology Synopsis: The patent addresses the technical problem of enabling a single-tenant application to operate in a multi-tenant environment without requiring significant and costly reprogramming. The invention is an "agile database connector" that functions as an intermediary, intercepting data access commands from the application and transparently translating them into tenant-specific commands for the multi-tenant database by inferring tenant identity from an external source. (Compl. ¶¶79-81; ’372 Patent, Abstract).
  • Asserted Claims: At least independent claim 1. (Compl. ¶153).
  • Accused Features: The complaint alleges that Microsoft's Azure SQL Database, particularly its "database-per-tenant" and "sharded multi-tenant" models, infringes by offering the same benefits of scalable, lower-cost multi-tenant use through a similar connector-based architecture. (Compl. ¶¶123-124).

U.S. Patent No. 10,305,761 - "MULTI - APPLICATION SAAS METERING ENGINE"

  • Patent Identification: U.S. Patent No. 10,305,761, “MULTI - APPLICATION SAAS METERING ENGINE,” issued May 28, 2019 (the “’761 Patent”). (Compl. ¶83).
  • Technology Synopsis: The patent addresses the difficulty of accurately monitoring and billing for resource consumption on a per-tenant basis in a multi-tenant system. The invention is a system comprising a "metering engine" to monitor data streams, an "identity engine" to identify the specific user, and a "bucket aggregator" to aggregate that user's activity. This enables granular, usage-based billing rather than less precise "block billing." (Compl. ¶¶86-87; ’761 Patent, col. 4:3-15).
  • Asserted Claims: At least independent claim 1. (Compl. ¶160).
  • Accused Features: The complaint alleges infringement by Microsoft's Azure Marketplace and Azure Monitor services, which provide metering capabilities that allow for "individual attribution of usage of Azure resources" and the tracking and metering of multi-tenant systems like AKS. (Compl. ¶¶109, 114, 116).

III. The Accused Instrumentality

Product Identification

  • The "Accused Products" are identified as a suite of Microsoft's cloud services: Microsoft Azure, Microsoft Azure Migrate, Microsoft Azure Kubernetes Service (AKS), Azure Marketplace, Azure Monitoring, and Azure SQL Database. (Compl. ¶90).

Functionality and Market Context

  • The complaint describes these services as an integrated ecosystem designed to attract and retain cloud customers. (Compl. ¶20). Azure Migrate is a service that facilitates the discovery, assessment, and migration of customers' on-premises applications to the Azure cloud. (Compl. ¶95). The complaint includes a diagram from Microsoft illustrating Azure Migrate's phased process of "Decide, Plan, Execute," which includes discovery, dependency analysis, and wave planning. (Compl. p. 25, ¶¶96-98). AKS is a managed container orchestration service that uses the Kubernetes platform to automatically deploy and manage containerized applications, assigning workloads to virtual machines via a scheduler. (Compl. ¶¶103-104). The complaint provides a diagram showing the Kubernetes architecture, highlighting the role of the scheduler. (Compl. p. 27, ¶103). Azure SQL Database provides scalable database services for SaaS applications, offering both "database-per-tenant" and "sharded multi-tenant" architectures to balance cost and tenant isolation. (Compl. ¶¶119-121). A Microsoft diagram comparing these two models is included in the complaint. (Compl. p. 33, ¶120). Finally, Azure Marketplace and Azure Monitoring provide tools for metering and billing cloud resource usage on a granular level. (Compl. ¶¶109, 111-112).
  • The complaint alleges that Microsoft leverages free offerings for Azure Migrate and AKS to "lure customers" into its ecosystem, where they are then monetized through paid services like Azure Marketplace and Azure SQL Database, thereby undercutting competitors like Corent. (Compl. ¶¶101, 106, 129).

IV. Analysis of Infringement Allegations

’136 Patent Infringement Allegations

Claim Element (from Independent Claim 1) Alleged Infringing Functionality Complaint Citation Patent Citation
identifying workloads of a non-tenant-aware application and a set of application characteristics... Azure Migrate's "decision phase" inventories the on-premises architecture, and its tools allow for the discovery and assessment of virtual machines and applications. ¶¶95, 97 col. 2:5-8
creating a partition of the workloads in reference to a partition application characteristic... In the "planning phase," Azure Migrate identifies and groups application workloads into partitions, analyzing dependencies between them. AKS groups containerized workloads via a "partitioning process." ¶¶98, 103 col. 2:9-11
grouping the created partition of the workloads into a plurality of workload sub-partitions... Azure Migrate's "inbuilt dependency mapping for high-confidence discovery of multi-tier applications" performs this sub-grouping function. ¶95 col. 2:12-14
assigning each partition of the workloads to a set of cloud resources... AKS automatically assigns workloads and partitions to cloud resources using its Kube Scheduler. Azure Migrate performs "intelligent rightsizing [of] Azure virtual machines." ¶¶95, 104 col. 2:15-18
constructing a plurality of workload assignment maps... During planning, Azure Migrate creates a "series of targeted mappings" for analysis. AKS uses "filtering, scoring, and mapping functionality" to determine assignments. ¶¶99, 104 col. 2:19-21
ranking each one of plurality of workload assignment maps based on a set of rules. Azure Migrate determines a "most favorable mapping" before execution, which is alleged to be a ranking process. The "scoring" functionality of the AKS scheduler is also alleged to perform this ranking. ¶¶99, 104 col. 2:21-23

’893 Patent Infringement Allegations

Claim Element (from Independent Claim 1) Alleged Infringing Functionality Complaint Citation Patent Citation
a scanning engine configured to identify workloads of a non-tenant-aware application... The "Discovery" tools within Azure Migrate are alleged to function as a scanning engine to identify and assess on-premises virtual machines and their workloads. ¶95 col. 8:16-21
a partitioning engine configured to group the workloads to a smaller set of partitions... The "Dependency Analysis" functionality in Azure Migrate groups workloads based on their interdependencies. AKS uses containerization to group application components. ¶¶95, 98, 103 col. 8:22-27
a mapping engine configured to assign each partition of the workloads to a set of cloud resources... The Kube Scheduler in AKS, which uses filtering, scoring, and mapping to assign workloads to nodes, is alleged to be the mapping engine. Azure Migrate’s "Wave Planning" functionality also performs mapping. ¶¶98, 104 col. 8:28-38
a rendering engine that constructs a migration plan to migrate each of the workloads... The "Execute" phase of Azure Migrate, which involves replication, testing, and activation based on the prior analysis, is alleged to be the function of a rendering engine constructing a migration plan. ¶99 col. 8:39-44

Identified Points of Contention

  • Scope Questions: A central question may be whether the distributed tools within the broad Azure Migrate and AKS platforms (e.g., discovery agents, dependency mappers, a Kubernetes scheduler) collectively constitute the specific, integrated "engines" ("scanning", "partitioning", "mapping", "rendering") as recited in the system claim of the ’893 Patent.
  • Technical Questions: What evidence does the complaint provide that Azure Migrate or AKS explicitly constructs a plurality of distinct workload assignment maps and then performs a comparative ranking of those maps, as required by the ’136 Patent? The complaint alleges a "most favorable mapping is determined" (Compl. ¶99), which suggests a selection, but the process of creating and ranking multiple discrete options may be a point of dispute.

V. Key Claim Terms for Construction

"workload"

Context and Importance

  • This term defines the fundamental unit being partitioned and mapped in the ’136 and ’893 Patents. Its construction is critical because the infringement theory depends on mapping this term to Microsoft's concepts like virtual machines, multi-tier applications, and containers. (Compl. ¶¶95, 98, 103).

Intrinsic Evidence for Interpretation

  • Evidence for a Broader Interpretation: The ’893 Patent specification defines a "workload" as "one or more modules of a software application... that can be independently executed separately from other modules of the software application on any computer unit of a cloud." (’893 Patent, col. 6:18-22). This broad, functional definition may support reading the term on various software components.
  • Evidence for a Narrower Interpretation: A defendant could argue that specific embodiments or context within the specification limit a "workload" to a particular type of application component distinct from a fully containerized microservice or a monolithic virtual machine, creating a potential mismatch with the accused technologies.

"ranking each one of plurality of workload assignment maps"

Context and Importance

  • This limitation from claim 1 of the ’136 Patent requires not just selecting an assignment, but performing a specific process of creating multiple options ("plurality of... maps") and ordering them ("ranking"). The infringement allegation hinges on equating the "scoring" in AKS or the determination of a "most favorable mapping" in Azure Migrate with this claimed process. (Compl. ¶¶99, 104).

Intrinsic Evidence for Interpretation

  • Evidence for a Broader Interpretation: The specification of the related ’893 Patent mentions systems that "rank desirability of the permutations of workload assignment maps by some user or administrator provided rules, such as cost, efficiency, and/or scalability." (’893 Patent, col. 1:60-63). This suggests that any rule-based evaluation and selection process could be considered "ranking."
  • Evidence for a Narrower Interpretation: A defendant may argue that the claim language requires the explicit generation of multiple, complete, and distinct "maps," which are then formally ordered. It may be argued that a real-time scheduling algorithm that scores and selects nodes without creating discrete, alternative end-to-end plans does not meet this limitation.

VI. Other Allegations

Indirect Infringement

  • The complaint alleges both induced and contributory infringement for all four asserted patents. Inducement allegations are based on Microsoft allegedly encouraging its customers to use the Accused Products in an infringing manner through "promotional materials, product manuals, brochures, videos, demonstrations, and website materials." (Compl. ¶¶141, 148, 155, 162). Contributory infringement is alleged on the basis that Microsoft supplies software that is a material part of the claimed inventions and is not a staple article of commerce. (Compl. ¶¶142, 149, 156, 163).

Willful Infringement

  • Willfulness is alleged for all four patents. The allegations are based on pre-suit knowledge, stemming from Microsoft allegedly acting as a broker for Corent's products on its Azure platform and, more specifically, from direct meetings between Corent's and Microsoft's leadership where the patents and related products were discussed years before the suit was filed. (Compl. ¶¶100, 138, 145).

VII. Analyst’s Conclusion: Key Questions for the Case

  • A core issue will be one of definitional scope: can the term "workload", as defined in the patents, be construed to cover the diverse and evolving units of cloud computing in the accused products, such as containerized microservices in AKS and entire virtual machines in Azure Migrate?
  • A key evidentiary question will be one of functional infringement: does the operational logic of Microsoft's accused services—particularly the real-time "scoring" algorithm of the Kubernetes scheduler in AKS and the "dependency analysis" in Azure Migrate—perform the specific, multi-step method of creating and "ranking" a "plurality" of distinct migration "maps" as required by the claims, or is there a fundamental mismatch in the technical process?
  • A central question for willfulness and damages will be one of knowledge and intent: what specific information regarding the asserted patents and their alleged applicability to Azure services was exchanged during the alleged meetings between Corent and senior Microsoft executives, and how does that information bear on Microsoft's subsequent conduct?