Multi-tenant web applications with ASP.NET Core

Jun 18, 2018Download as PPTX, PDF0 likes15,773 views

It’s a dawn on cloud era and many systems around the world are moving to cloud. Every new day brings new cloud based services to market. This presentation helps attendees to jump to SaaS systems band wagon and focuses on design, architecture and implementation of multi-tenant ASP.NET Core applications. The goal is to provide the audience with elegant real-world knowledge they can apply already next day at work. Demos show how different techniques work in practice, also how to deploy and run multi-tenant web applications on Microsoft Azure.

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Multitenant web applications with
ASP.NET Core
Gunnar Peipman
ASP.NET/IIS MVP
gunnarpeipman.com

@ITCAMPRO #ITCAMP18Community Conference for IT Professionals
Many thanks to our sponsors & partners!
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• What is multitenancy?
• Hosting models
• Concepts
• Demos
• Q&A
Agenda

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• Presentation page: bit.ly/aspnetcoremultitenant
• Source code: bit.ly/aspnetcoremultitenantsrc
• My blog: gunnarpeipman.com
Support materials

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WHAT IS MULTITENANCY?

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The term "software multitenancy" refers to a software architecture in
which a single instance of software runs on a server and serves multiple
tenants.
A tenant is a group of users who share a common access with specific
privileges to the software instance.
With a multitenant architecture, a software application is designed to
provide every tenant a dedicated share of the instance - including its
data, configuration, user management, tenant individual functionality
and non-functional properties.
„Multitenancy“, Wikipedia
What is multitenancy?

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HOSTING MODELS

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All resources are shared between tenants
Shared model
Tenant 1 Tenant 2
App
hosting
Storage
Tenant 3 Tenant 4
App
hosting
Storage

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Some resources are shared between tenants
Hybrid model
Tenant 1 Tenant 2
App
hosting
StorageStorage
SQL
database
CDN Cache

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No shared resources
Dedicated model
App
hosting
Storage
Data
Tenant 1
App
hosting
Storage
Data
Tenant 2

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• Customer provided environment
• Multi-instance, not multitenant hosting
• Usually special case
On-premises

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CONCEPTS

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• Tenant definition
• Tenant provider
• Missing tenant middleware
• Multitenant DbContext
Concepts

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• Data structure that defines tenant technically
• Used by multitenant application
• Provided to application externally
Tenant definition

@ITCAMPRO #ITCAMP18Community Conference for IT Professionals
• Detects current tenant
• Provides other parts of
application with tenant
information
• Multiple
implementations
Tenant provider
ITenantProvider
DbTenantProvider FileTenantProvider
BlobTenantProvider HttpTenantProvider

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• Request middleware
• Handles missing tenants
• Usually redirects to some page
• Don’t throw nasty errors
Missing tenant middleware

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• Provides correct cache key for model caching
• Defensive CRUD operations
• Checks for cross-tenant operations
• Database provider agnostic
Multitenant DbContext

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DEMO

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Q & A

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Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.

How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik

This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements. Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows. We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure. The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.

Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev

If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic? Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search. Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval. GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.

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Exploring Code Comprehension in Scientific Programming: Preliminary Insight...University of Hawai‘i at Mānoa

This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software. Presented at: The 33rd International Conference on Program Comprehension (ICPC '25) Date of Conference: April 2025 Conference Location: Ottawa, Ontario, Canada Preprint: https://arxiv.org/abs/2501.10037

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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers

Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach. Read More:- https://www.esofttools.com/nsf-to-pst-converter.html

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