List of Microsoft Azure Container Instances Customers
Redmond, 98052-6399, WA,
United States
Since 2010, our global team of researchers has been studying Microsoft Azure Container Instances customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Microsoft Azure Container Instances for Container Service from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Microsoft Azure Container Instances for Container Service include: icertis, a United States based Professional Services organisation with 2200 employees and revenues of $327.0 million, Cloud 9, a United States based Professional Services organisation with 200 employees and revenues of $30.0 million, Gluwa, a United States based Banking and Financial Services organisation with 30 employees and revenues of $5.0 million and many others.
Contact us if you need a completed and verified list of companies using Microsoft Azure Container Instances, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Cloud 9 | Professional Services | 200 | $30M | United States | Microsoft | Microsoft Azure Container Instances | Container Service | 2020 | n/a |
In 2020, Cloud 9 implemented Microsoft Azure Container Instances as its Container Service to support the Game Insights Platform for esports analytics in the United States. Cloud 9 uses Microsoft Azure Container Instances to run model-runner and replay processing workloads, leveraging on-demand container execution and per-second billing to align compute costs with processing demand.
The deployment places ephemeral container instances into pipeline-driven processing for game telemetry and replay ingestion, enabling automated provisioning and scale-out for batch analytics. Microsoft Azure Container Instances is integrated into the Game Insights Platform workflow, providing the execution tier that allowed Cloud 9 to scale from hundreds to thousands of games per day, reduce infrastructure complexity, and improve processing agility for esports analytics operations.
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Gluwa | Banking and Financial Services | 30 | $5M | United States | Microsoft | Microsoft Azure Container Instances | Container Service | 2023 | n/a |
In 2023, Gluwa implemented Microsoft Azure Container Instances to host blockchain-related services and public endpoints that power lending and investor-matching services for emerging-market financial inclusion. Microsoft Azure Container Instances was used as a Container Service alongside Azure Kubernetes Service to isolate public traffic and streamline containerized endpoint delivery.
Architecturally Gluwa leveraged Microsoft Azure Container Instances for public endpoints and AKS for bootstrap and RPC nodes, creating a split-plane deployment that separates external API surface from node orchestration and stateful workloads. The implementation covered blockchain-related services including RPC provisioning, node bootstrap workflows, and public API endpoints for lending and investor-matching functions. This configuration enabled container-level scaling of stateless endpoints while retaining Kubernetes orchestration for node lifecycle and networking.
Operational scope remained focused in the United States where Gluwa runs its lending and investor-matching operations, and the environment was integrated between Microsoft Azure Container Instances and AKS for communications and service routing. The use of Microsoft Azure Container Instances alongside AKS provided reliable, scalable communications and supported millions of loan transactions while improving uptime and operational efficiency. Governance centered on separating public endpoint deployment from node orchestration to reduce blast radius and simplify operational runbooks.
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icertis | Professional Services | 2200 | $327M | United States | Microsoft | Microsoft Azure Container Instances | Container Service | 2023 | n/a |
In 2023, icertis deployed Microsoft Azure Container Instances to support contract digitization and analytics within its Contract Lifecycle Management legal and contract management offering in the United States. The implementation pairs Microsoft Azure Container Instances with Azure Machine Learning to run large scale containerized workloads for document extraction, ML inference, and analytics across enterprise CLM customers, aligning the application to the Container Service category.
The deployment configures containerized processing pipelines for automated contract ingestion, OCR and natural language processing model scoring, and analytics aggregation. Microsoft Azure Container Instances is used to provision short lived compute for batch and streaming tasks, enabling elastic execution of contract processing jobs and reducing manual orchestration overhead in the CLM application stack.
Integrations are explicit with Azure Machine Learning for model hosting and inference, and with the icertis CLM platform for end to end contract lifecycle workflows. Operational scope is focused on enterprise customer deployments in the United States, with container service workloads embedded into contract onboarding, clause extraction, and analytics workflows that serve legal and contract management functions.
Rollout activities emphasized embedding container execution into CLM deployment pipelines and operationalizing model-driven automation for contract processing. The implementation lets icertis automate and scale contract processing for enterprise customers, improving throughput and accelerating deployments across its CLM platform, while maintaining containerized compute boundaries and ML integration points for governance and operational control.
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