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: Venue is alleged to be proper based on Microsoft maintaining regular and established places of business within the Central District of California.
  • Core Dispute: Plaintiff alleges that Defendant's Azure cloud services, including Azure Migrate and Azure Kubernetes Service, infringe four patents related to the automated migration, orchestration, multi-tenant database connectivity, and usage metering of software applications in the cloud.
  • Technical Context: The technology concerns systems and methods for analyzing and adapting software for cloud computing environments, a critical process for enterprises seeking to modernize their IT infrastructure and adopt Software-as-a-Service (SaaS) models.
  • Key Procedural History: The complaint alleges that Plaintiff, Corent, discussed the Asserted Patents and the functionality of its related products with Microsoft's product team in meetings dating back approximately four years before the complaint's filing, which may be used to support allegations of pre-suit knowledge.

Case Timeline

Date Event
2010 Microsoft Azure Launched
2011-09-23 '372 Patent Priority Date
2014-07-31 '136, '893, and '761 Patents Priority Date
2016-11-15 '372 Patent Issue Date
2017 Azure Migrate Announced
2017 Azure SQL Database Released
2017-10 Azure Kubernetes Service (AKS) Deployed
2018 Azure Migrate Became Generally Available
2019-05-28 '761 Patent Issue Date
2019-06-11 '893 Patent Issue Date
2021-05-25 '136 Patent Issue Date
2025-09-26 Complaint Filing Date

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"

Issued: May 25, 2021

The Invention Explained

  • Problem Addressed: The patent's background describes the difficulty of migrating traditional, non-tenant-aware software applications to the cloud Compl. ¶66 This is because cloud environments have a "wide variety of configurations" that may not align with an application's requirements, and "legacy applications may fail to take advantage of the additional resources offered by a cloud environment" or may "run inefficiently" Compl. ¶66 '136 Patent, col. 1:45-51
  • The Patented Solution: The invention proposes a method to automate the planning of cloud migrations. It involves systematically identifying an application's "workloads" (constituent computing tasks), partitioning them based on their characteristics, grouping them into sub-partitions, and then constructing and ranking multiple "workload assignment maps" to find the optimal deployment configuration across available cloud resources '136 Patent, abstract '136 Patent, col. 2:24-41 This allows for the effective consideration of factors like "cost, scalability, performance, and security" before deployment Compl. ¶66 '136 Patent, col. 1:60-2:2
  • Technical Importance: The technology aims to provide a structured, automated, and data-driven approach to planning cloud migrations, replacing manual and potentially error-prone analysis Compl. ¶¶47-48

Key Claims at a Glance

  • The complaint asserts at least independent claim 1 Compl. ¶139
  • Independent claim 1 is a method claim comprising the following essential elements:
    • identifying workloads of a non-tenant-aware application and their characteristics;
    • creating a partition of the workloads in reference to a partition application characteristic;
    • grouping the created partition into a plurality of workload sub-partitions based on a common workload characteristic;
    • assigning each partition to a set of cloud resources based on application and resource characteristics;
    • constructing a plurality of workload assignment maps for the workloads; and
    • ranking the 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"

Issued: June 11, 2019

The Invention Explained

  • Problem Addressed: Similar to its sibling '136 patent, this patent addresses the challenges of migrating non-tenant-aware applications and orchestrating them effectively in a cloud environment where resource configurations vary widely Compl. ¶73 '893 Patent, col. 1:38-44
  • The Patented Solution: The patent describes a system for configuring workloads, comprised of distinct functional engines. A "scanning engine" identifies workloads and their characteristics; a "partitioning engine" groups them; a "mapping engine" assigns the partitions to cloud resources based on user-defined rules; and a "rendering engine" constructs a migration plan from the resulting assignments '893 Patent, abstract '893 Patent, col. 2:4-22 The system is implemented with program instructions on a non-transitory computer-readable storage medium Compl. ¶75
  • Technical Importance: This patent provides a concrete system architecture for implementing the automated migration-planning method described in the '136 patent, defining the specific software engines required to perform the analysis and mapping Compl. ¶¶72-74

Key Claims at a Glance

  • The complaint asserts at least independent claim 1 Compl. ¶146
  • Independent claim 1 is a system claim comprising the following essential elements:
    • a scanning engine to identify workloads and characteristics using rules;
    • a partitioning engine to group workloads into partitions using rules;
    • a mapping engine to assign partitions to discrete cloud resources using rules;
    • a rendering engine to construct a migration plan based on the assignments;
    • wherein the engines comprise stored program instructions on a non-transitory medium; and
    • wherein the instructions are executed by a computer processor Compl. ¶75
  • The complaint reserves the right to assert additional claims Compl. ¶146

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

Issued: November 15, 2016

  • Technology Synopsis: The patent addresses the problem of enabling a traditional single-tenant application to operate in a multi-tenant environment without requiring significant reprogramming of the application itself Compl. ¶80 The invention is an "agile database connector" system that sits between the application and the database, transparently intercepting generic data access commands, inferring the correct tenant ID, and translating the command into a tenant-specific one for the multi-tenant database Compl. ¶79 Compl. ¶81
  • Asserted Claims: At least independent claim 1 is asserted Compl. ¶82 Compl. ¶153
  • Accused Features: Microsoft's Azure SQL Database, particularly its "database-per-tenant" and "sharded multi-tenant" database models, are accused of infringing by using an agile database connector to manage multi-tenant access Compl. ¶119 Compl. ¶¶123-124 A diagram in the complaint illustrates the database-per-tenant architecture, showing a shared application instance connecting to separate tenant databases via a catalog Compl. p. 33

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

Issued: May 28, 2019

  • Technology Synopsis: The patent addresses the technical problem of accurately measuring and billing for cloud resource consumption on a per-tenant basis in a multi-tenant system, which was previously "unmeasurable by conventional systems" Compl. ¶¶86-87 The patented solution is a system comprising a "metering engine" to monitor data streams, an "identity engine" to identify the user, a "bucket aggregator" to collect usage data, and a "subscription engine" to generate summaries for granular, consumption-based billing rather than fixed "block billing" Compl. ¶86 '761 Patent, abstract
  • Asserted Claims: At least independent claim 1 is asserted Compl. ¶88 Compl. ¶160
  • Accused Features: Microsoft's Azure Marketplace, Azure Monitoring, and Traffic Analytics services are accused of infringement for providing metering systems that track and enable billing for individual customer usage of cloud services and applications Compl. ¶109 Compl. ¶112 Compl. ¶116

III. The Accused Instrumentality

Product Identification

  • The accused products and services are Microsoft Azure, Microsoft Azure Migrate, Microsoft Azure Kubernetes Service (AKS), Azure Marketplace, Azure Monitoring, and Azure SQL Database (collectively, "Accused Products") Compl. ¶90

Functionality and Market Context

  • The complaint alleges that these products form an integrated cloud ecosystem. Azure Migrate is presented as a tool for discovering, assessing, and planning the migration of on-premises workloads to the Azure cloud Compl. ¶95 A provided diagram illustrates the migration process in three phases: "Decide," "Plan," and "Execute" Compl. p. 25 AKS is described as a container orchestration system that automates the assignment of workloads to cloud resources Compl. ¶¶103-104 Azure SQL Database is alleged to provide scalable multi-tenant database architectures Compl. ¶¶119-121, while Azure Marketplace and Azure Monitoring are alleged to provide the ability to meter and bill for individual usage of cloud resources Compl. ¶109 Compl. ¶113 The complaint alleges Microsoft offers key services like Azure Migrate and AKS for free to "lure customers" into its ecosystem, where they then purchase other paid services, thereby undercutting competitors like Corent Compl. ¶101 Compl. ¶106 Compl. ¶134 A screenshot from Microsoft's website shows "Azure Migrate" listed as "Free," while third-party tools like Corent's require a license Compl. p. 27

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 for each of the identified workloads Azure Migrate identifies on-premises workloads and gathers information about them, including software components, hardware dependencies, and performance metrics, to prepare for migration. ¶139; Ex. 5 p. 3 col. 1:28-34
creating a partition of the workloads in reference to a partition application characteristic Azure Migrate performs dependency analysis to identify cross-server/workload dependencies, and based on these dependencies or similarities, different workloads are partitioned. ¶139; Ex. 5 p. 5 col. 2:29-32
grouping the created partition of the workloads into a plurality of workload sub-partitions as a function of a common workload characteristic Azure Migrate enables grouping of discovered on-premises workloads based on a common workload characteristic, such as security, data sensitivity, or mission criticality. The created partition of workloads is grouped into sub-partitions. ¶139; Ex. 5 p. 11 col. 7:42-49
assigning each partition of the workloads to a set of cloud resources as a function of the partition application characteristic and a characteristic of the set of cloud resources Azure Migrate assigns partitions of workloads to different deployment targets (cloud resources). For example, out of 54 workload instances, 28 are assigned to Azure SQL VM, 24 to Azure SQL MI, and 2 to Azure SQL DB based on workload and resource characteristics. ¶139; Ex. 5 p. 19 col. 8:7-13
constructing a plurality of workload assignment maps to assign to each of the workloads in accordance with the created partition Azure Migrate creates detailed migration plans (workload assignment maps) for each identified workload, ensuring each is mapped to the appropriate Azure resources for efficient deployment. ¶139; Ex. 5 p. 20 col. 2:36-41
and ranking each one of plurality of workload assignment maps based on a set of rules Each workload assessment in Azure Migrate is associated with a "confidence rating" (from one to five stars) based on a set of rules, which depends on the percentage of available data points for the migration. ¶139; Ex. 5 p. 23 col. 2:67-3:2

'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 and a set of application characteristics for each of the identified workloads using workload rules in a workload partitioner rules database defined by an administrator user Azure Migrate is alleged to be a scanning engine that identifies workloads of a non-tenant-aware application and a set of their characteristics using workload rules defined by an administrator user. ¶146; Ex. 6 p. 3 col. 2:5-13
a partitioning engine configured to group the workloads to a smaller set of partitions as a function of common characteristics of workloads in a partition using partition rules in a partition mapper rules database defined by an administrator user Azure Migrate is alleged to be a partitioning engine that groups workloads into smaller sets of partitions based on common characteristics, using rules defined by an administrator. ¶146; Ex. 6 p. 5 col. 2:14-22
a mapping engine configured to assign each partition of the workloads to a set of cloud resources...wherein each partition is assigned to a discrete cloud resource using partition rules...defined by an administrator user Azure Migrate is alleged to be a mapping engine that assigns each partition of workloads to a set of cloud resources, with each partition being assigned to a discrete resource using administrator-defined rules. ¶146; Ex. 6 p. 11 col. 2:30-40
and a rendering engine that constructs a migration plan to migrate each of the workloads to the set of cloud resources in accordance with the assigned partitions from the mapping engine Azure Migrate is alleged to be a rendering engine that constructs a migration plan to migrate each workload to the cloud resources according to the assigned partitions from the mapping engine. ¶146; Ex. 6 p. 30 col. 2:41-45
wherein the scanning engine, the partitioning engine, the mapping engine, and the rendering engine comprise stored program instructions embedded in a non-transitory computer readable storage medium, and wherein the stored program instructions are executed by a computer processor to execute a function Azure Migrate is alleged to be a system where the engines' functions are performed by a computer processor executing stored program instructions. ¶146; Ex. 6 p. 36 col. 2:46-52

Identified Points of Contention

  • Scope Questions: A central dispute may arise over whether Microsoft's "dependency analysis" and creation of "move groups" in Azure Migrate Compl. ¶¶98-99 correspond to the more formally structured "partitioning," "grouping into...sub-partitions," and "constructing a plurality of workload assignment maps" as required by claim 1 of the '136 patent. The court may need to determine if Microsoft's higher-level planning phases perform the specific, sequential steps recited in the claim.
  • Technical Questions: For the '893 patent's system claim, a key question will be whether Azure Migrate is an integrated system of the claimed "engines" or a looser collection of tools. The claim requires a "scanning engine," "partitioning engine," "mapping engine," and "rendering engine," and infringement will depend on evidence that the accused product contains these structurally and functionally distinct components operating as claimed.

V. Key Claim Terms for Construction

  • The Term: "workload"

    • Context and Importance: This term defines the fundamental unit being analyzed, partitioned, and mapped by the claimed inventions. The breadth of this term is critical, as it dictates the nature of what Microsoft's Azure Migrate must be shown to "identify" and "group" to infringe the '136 and '893 patents.
    • Intrinsic Evidence for Interpretation:
      • Evidence for a Broader Interpretation: The '893 patent specification defines a workload as an "independently executable software sub-unit on a computing hardware," which "can therefore be comprised of one or more modules" '893 Patent, col. 7:2-6 This language may support a broad interpretation covering various granularities of software components.
      • Evidence for a Narrower Interpretation: The claims tie workloads to a "non-tenant-aware application" (e.g.,'136 Patent, claim 1). A defendant may argue this context limits "workloads" to components of a monolithic, legacy application, raising the question of whether the term applies to modern, microservice-based architectures that Azure Migrate also assesses.

  • The Term: "partition"

    • Context and Importance: This term is central to the core inventive concept of grouping workloads for analysis and migration in both the '136 and '893 patents. The infringement analysis will likely focus on whether the "groups" created by Azure Migrate Compl. p. 25 meet the specific definition of a "partition" as used in the claims. Practitioners may focus on this term because the claims require creating a partition "in reference to a partition application characteristic" ('136 patent, claim 1b), suggesting a structured, rule-based grouping rather than an arbitrary one.
    • Intrinsic Evidence for Interpretation:
      • Evidence for a Broader Interpretation: The '893 patent specification describes grouping workloads into partitions based on "one or more module characteristics and/or dependencies with other modules," which could be interpreted broadly ('893 Patent, col. 6:33-36). The complaint alleges Microsoft's "dependency analysis" creates such groupings Compl. ¶98
      • Evidence for a Narrower Interpretation: The claims of the '136 patent introduce a hierarchy of "partition" and "sub-partitions" ('136 Patent, claim 1c). A defendant may argue that this implies a specific nested structure that must be found in the accused product, and that a simple "move group" in Azure does not meet this structural requirement.

VI. Other Allegations

  • Indirect Infringement: The complaint alleges that Microsoft induces infringement by providing customers with promotional materials, product manuals, and technical support that instruct them on how to use the Accused Products in ways that practice the patented methods Compl. ¶141 Compl. ¶148 It also alleges contributory infringement, asserting Microsoft supplies software (the Accused Products) that is a material part of the claimed inventions, is not a staple article of commerce, and is known to be especially made for use in an infringing manner Compl. ¶142 Compl. ¶149
  • Willful Infringement: Willfulness is alleged based on Microsoft's purported pre-suit knowledge of the Asserted Patents. The complaint claims that Corent's leadership met with Microsoft's product team "dating back approximately four years ago" to discuss the patents and Corent's competing product line, and that Microsoft continued its allegedly infringing conduct despite this notice Compl. ¶100 Compl. ¶138

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

  • A central issue for the '136 and '893 patents will be one of definitional scope: does the functionality of Microsoft's Azure Migrate, which is described in terms of "dependency analysis," "assessments," and "move groups," satisfy the specific, structured claim requirements for "identifying workloads," "creating a partition," "grouping... into... sub-partitions," and "ranking... workload assignment maps"? The case may turn on whether Microsoft's more generalized migration planning tools can be mapped onto the granular, multi-step process claimed in the patents.
  • A key architectural question for all asserted patents will be one of functional identity: do the accused Azure services, which are presented as a suite of distinct tools (e.g., Azure Migrate, Azure SQL Database, Azure Marketplace), constitute the specific, integrated "engines" recited in the system claims (e.g., the '893 patent's "scanning engine" and "partitioning engine"; the '372 patent's "agile database connector"; the '761 patent's "metering engine")? The court will need to consider whether Microsoft's combination of services operates as the specific, purpose-built systems claimed by Corent.
  • An important evidentiary question will concern pre-suit knowledge and intent: what was the specific content of the alleged meetings between Corent and Microsoft, and does that evidence establish that Microsoft had actual knowledge of the patents-in-suit and the allegedly infringing nature of its products? The answer will be critical for Corent's claims of willful and indirect infringement.
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