DDD North 2020

DDD North 2020

This article was originally published 1st March 2020 on Linkedin

The Monolith of Microservices - Ian Johnson

What is a Monolith?

A tightly coupled architecture where each component and its associated components must be present to be executed. How we got here? We started with big machines, then desktops were low power and single core and there is then the internet with server-based computation and rendering on the desktop with networked computers - does the monolith still work here? People have fast internet and multiple CPUs and there's huge demand and ever more complex demands.

Monolith Advantages

Easier to refactor, plenty of tools to help, compiles will tell you what's wrong, all the code is co-located the refactored code is deployed in a single unit, centralised logging, reduced distance between components with faster per operation and reliability compared to inter-process. Debugging allowing complex processing is traceable live and capture the “global” app state and they have fewer moving parts and layers of complexity. Don't have to worry about many network hops, and there's no chance of an individual component being available or worry about things like eventual consistency.

Monolith Disadvantages

Easier to make highlight coupled codebases DRY overuse and refactoring can suggest the wrong thing. Can be hard to scale onto multiple boxes but this depends on what the monolith is doing, hard to share useful features between monoliths, limits the effectiveness of multiple teams including conflicts, dependencies, cadence and lack of ownership and slow release cycles if it is highly coupled. DRY makes you put many things in an object even if only used by one part of the service. Dependencies being different can make it difficult to share functionality.

The Monolithic Database

Every component is bound to multiple tables in the database - coupling with data and application bound so must be deployed together. One model to rule them all - data driven design tells us there never one true model, multiple reasons to change data increases chances of locking, acts as a “source of truth” and a “view model”. Not just relational databases you can have monolithic document databases too where they're used like tables with relationships. Services require multiple documents to function. Data is slow to change, can take you whole system down until a schema change is complete. Once schema of an entire application can be a major problem. Need to know how our code relates to the database.


Building a large app from a suite of modular components, each service owns its own data, use public APIs with each service is a bounded context with their own database, they only talk by publishing and receiving events with a shared messaging infrastructure. You could even use multiple languages to implement different microservices.

Microservices Advantages

Easier for teams to work independently, smaller more isolated code and a loosely coupled architecture. Deployed & scaled independently. You don't have to fit the whole world in your head. Technology agnostic - the right tech for the right job. You could just receive and send events and makes it easy to test. Easier to compose new workflows and functionality and testing is easier.

Microservices Disadvantages

They are way more complex operationally than a monolith with many moving parts. Observability is an issue - what services are running and how many services are there, centralised logging. Issues like eventual consistency become a problem, versioning and fault tolerance can be an issue - should services depend on each other this way? Security can be an issue with zero trust or trust external services like external user trust. Services should not call each other they should communicate via event; it should be that if part of the system goes down users don't notice otherwise it is just a distributed monolith. If you can't build a well structured monolith what makes you think that microservices are the answer, can have shared data with hidden coupling or breaking changes to message formats plus fault tolerance could make multiple things go down if done wrong.

A monolith of microservices

Shared infrastructure bringing logging and routing with entry points brings loosely coupled services together, micro services are loosely coupled and cannot talk directly to each other - you could force messages to be serialised to aid interoperation. Just do a shared database with a schema per microservice and use permissions to hide other data. No cross-schema structures and if services need to duplicate data then duplicate it! Normalise only within the schema. Even if doing reporting follow the same patterns.

Monolith of Microservices Advantages

Multiple teams can still work quite easily in the monolith - like a monorepo, working on one vertical slice at a time, the compiles finds issues early and versioning can be unnecessary as all events are internal. Can ship more frequently if services are loosely coupled as soon as they're ready. New ideas or services can be easily supported by the infrastructure and by messaging design. Fewer moving parts allow fewer things to go wrong and is operationally easier and is easier to debug.

Disadvantages of Microservices Advantages

Is still might not scale well - individual services don't scale. It is still a distributed workflow, requires discipline as it is easy to directly couple microservices to expose code that should be internal. Microservices enforce boundaries that a monolith cannot.

Technology Ideas

Use the actor model - the universal primitive of concurrent computation, communicate via messages only, can modify internal state, process one message at a time aka akka.net.

Mediator/message bus using MediatR or Brighter Command - internal message bus within program to pass decoupled messages between multiple parts of the system

Becoming structured from legacy code

You have a lot of understanding about the domain from a successful, if evil, system. Pull each service into assemblies and modules, no messaging yet but assemblies may reference each other. Refactor to break these dependencies between the services and introduce share infrastructure such as messaging, routing etc. Messaging becomes the primary means of communication and can take one service at a time.

Moving to microservices

Switch internal message bus onto an external message bus, you solve one problem at a time. Start listening to these external events then you deploy this service as an independent thing. Once at a point you've solved a lot of the operational problems - you solve them as and when you need to, then you split the database out and deploy the service independently as this makes sense, so you can reduce the monolith down but it doesn't have to be all microservices.

Secure by Design: How to Harden Your Applications Using Threat Modelling - Mike Goodwin

Why do I think it's so awesome? The basics - what is it, SRIDE and Beyond the Basics. It is one of the most effective and important things you can do to help you harden your applications.

What is it and why?

It's great for defence in depth, avoid a hard perimeter - the aim the game is to limit damage or prevent anyone getting further. It forces/encourages you to think hard about your security. It works best when done as a team with different perspectives in play.

Decompose your application

Usually done with some form of diagram, even on a piece of paper or a whiteboard but can be difficult to iterate unless using a tool. External Actor - anything that is at the boundary of the application you're modelling e.g. client app, a person or another system. Process - simply a process within the system. Data Store - any kind of persistent data storage e.g. database, file or parameter/secret store. Data Flow - any transmission of data from one model element to another, is directional e.g. web request and response, read/write to file system and an inter process communication. Trust Boundary - a transition between model elements that is associated with a change of trust level e.g. internet, network boundary, process-to-process boundary or storage access where how do you know the data is valid or hasn't been changed or intercepted.

Identify Threats

Try to put yourself in the mindset of an attacker - ask question about what bad stuff you could do in the different elements of the diagram with the answer giving you the threats. Remember to question your assumptions and expectations, need to get into the mindset of how someone would subvert the system and what bad things could happen to this. What assumptions could one make about a web application with incoming requests, what if they are wrong. An attacker could send a request pretending to be another person and access their data. What could an attacker do if they got access to a message queue - an attacker could place a poison message on the queue causing the receiving process to crash. What could an attacker do if they were able to change the data in the database - they could modify a bank account number to divert payments into their own account. Helpful to think of specifics to design the correct mitigations.

Design Mitigations

Find ways to block, avoid or minimise the threats, some of these mitigations might change the design, might have to accept some low risk unmitigated threats. To mitigate web application requests, you could identify the requestor using a session cookie and apply authorisation logic. For the message queue you could digitally sign messages and validate the signature or maintain a retry count on messages and discard them after 3 failures. To mitigate changes to the database you could restrict access to the database using a firewall and log changes to bank account numbers and audit these, potentially validate these changes.


Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service and Elevation of Privilege. These are Pretending you're someone you're not, changing something, doing something and denying you did it, giving information to an unauthorised person, degrading/preventing access to a service and doing something you're not authorised to do. These could be Cross site request forgery, inject malware or backdoor into code, exploit lack of logging, man in the middle attack, flooding a service with more requests than it can handle and exploiting a direct object reference vulnerability.

Top Tips

Aiming to address - don't have time, doing a lot of repeat work, talking about model semantics, don't know how to mitigate, how do you start threat modelling?

  1. Focus on trust boundaries - get this right first then justify the trust yourself and determine how the trust is established? Across a trust boundary how is the flow authenticated, how is it authorised, what validation is needed, opportunities for denial of service and automated threats and don't forget to look at responses too!
  2. Don't stress about model grammar - ENISA thread taxonomy, SRIDE, SWE etc. You don't need to classify the threat accurately, more important to know it exists than to attach to correct element, model doesn't have to be 100% complete to be useful, if part of the model confuses then can just remove it and if need to add extra things for it to make sense then do it! You can model the parts of your system that are security critical or feel most nervous about if have limited time.
  3. Do incremental threat modelling - can do it a bit of at a time, if not feasible to unpick a system, you can think about the new web application layer and deal with the interface between this and the legacy system and make new features more secure if can't do the whole thing.
  4. Detection can be a mitigation too - if you detect a threat, log it even if you can't mitigate it, exploits of known vulnerabilities, digital signature check fails, invalid input, unauthorised access attempts and “unusual” activity. Document your application log events and decide which events need to generate alarms and what the run-book is - when it happens what do you do?
  5. Not all mitigations need to be in your code - DDoS mitigation services, multi-factor authentication, FIM or similar e.g. OSSEC, rotate encryption keys, access control audits and segregation of duties and least privilege. To be most effective think holistically about the service, your processes and even your organisation design.

Azure App Services: Containers - Andrew Westgarth

Azure App Service

High productivity framework to allow developers to add value to their applications without worrying about the underlying platform. Is Fully Managed where everything is taken care of including scaling, load balancing and patching. It is enterprise grade with high level security compliance. Languages and Operating Systems are ASP.NET, PHP, Node.JS, .NET Core, Python and Ruby on Windows and Linux. You can host any custom container however, but those languages are first class images with the runtime already available.

Build and deploy options

CLI support for deployment, have built in build capabilities on Azure App Service to create a Runnable web app, Git deployment directly from local or even GitHub deployment plus support for Bitbucket and Mercurial & Git compatible (on Windows only).

You can Deploy directly from Visual Studio, you can publish a zip file for Azure Pipelines, the application is run directly from the zip and not unpacked at runtime. OneDrive, Dropbox and FTP available for content sync/regular file copying.

Deploying containers can be deployed from docker hub or the Azure or Private Container Registry. You can docker push to those and the container image will be pulled in.

Windows Container Support Public Preview

Windows Server 2029 Host Support for smaller containers, higher density of apps, faster pull and start times. Support lift and shift to PaaS, don't allow applications which have dependencies but can package all dependencies inside containers. Low-level libraries such as GDI, PDF generation are blocked so these can't be exploited and are disabled by default.

TDD and the Terminator: An introduction to Test Driven Development - Layla Porter

TDD Successes

Acceptance criteria - hard to write tests with woolly requirements.

Interfaces - you can write the single focused piece of information as a coding contract and allows you to get on with stuff.

Asynchronous Development - when someone implements your stuff, nothing is going to break. Cleaner Code - only writing enough code to fulfil your test.

Safe refactoring - don't have to worry as unit tests will fail if you break anything and fewer bug.

Increasing returns - allow new features to be implemented without undoing previous development work and living documentation as unit tests allow someone to see what your code should be doing.

Process of programming our Terminator

Gather the requirements - scan subjects and determine if they require further investigation. Scan subjects and determine if they fail the requirements.

Start with failing tests - if you don't you've written code. You need to make sure your tests aren't fitted to the code.

Red/green refactor pattern - start with failing test, write just enough code to get the test to pass and refactor (as a cycle).

When writing tests - clearly label your class as an “sut” or subject under testing and can name tests like “SubjectShould_”. Then have arrange, act and assert - can use fluentassertions e.g. result.Should().BeTrue(). Can also use TestCases to cover many eventualities in the same test if the outcomes are being asserted is the same.

Change of Requirements

Once this is done you can continue to refactor but may get new requirements such as with the terminator which is to protect from threats and learn. You need to design your application to be more robust to requirement changes by using design patterns like SOLID principles.

  • Single responsibility principle - Every class or module in a programme should have responsibility for just a single piece of that programme's functionality.
  • Open/close principle - software entities (classes, modules, functions etc) should be open for extension but closed for modification
  • Liskov substitution principle - objects of their subtype should be replaceable.
  • Interface Segregation Principle - split interfaces that are very large into smaller and more specific ones so that implementation will only have to know about the methods that are relevant to them.

Ideally need to make something extensible without having to be modified internally, you could add a rule for the example, so you can create a rule to match a subject as the implementation of a new interface with this functionality. You could implement a list of rule implementations and could check over all of those. If you need to make a private method in order to test it, it's time to refactor - if you have these then this is a code smell!

With good practices, code management becomes infinitely easier. How to write more robust code, if find yourself going to the same code then you can write it in a robust maintainable way.

TDD Failures

Underestimating the learning curve - is a complete culture shift and doesn't come naturally but if change mindset you can more productive. Confusing TDD with unit testing. Thinking TDD is enough testing - you need those integration tests as well. Not starting with failing tests is a warning you've written too much code. Not refactoring enough - want the least amount of code to fix it but also make sure developing the interfaces needed and not actually doing TDD!

Implementation with your organisation

Can be controversial and is a significant culture change and need to think how to make it easy for you and your teammates - let people find their way. Initial drop in productivity can be disconcerting - slowing down to begin with. Productivity will go up and reworks are reduced - don't have those regression bugs. Increased understanding of requirements and their acceptance criteria - you have things clear and precise as were able to write tests and if not good enough you need more details to write tests and can push back and take more control.

Zero to Mobile Hero - Intro to Xamarin and Cognitive Services - Luce Carter

Mobile Development with Xamarin

Thin C# wrapper around the native APIs for Android, iOS and Windows UI with a shared C# backend. You can use Xamarin.Forms to share the UI between iOS, Android and UWP, it is not the same as XAML but there was talk of XAML standard but there hasn't been any movement on this. Apps on each platform support the native features and UI so don't need to know about the UI.

How do you get started?

You can use Visual Studio with the Xamarin Workloads - however you need the XCode build tools on a Mac to develop Xamarin apps on iOS. You could use MacInCloud.com to rent space or you can use Visual Studio for Mac (formally MonoDevelop and Xamarin Studio) but you won't be able to build and run UWP applications on a Mac either. You can develop also with F# and can use Fabulous for the layout and can use MVU (Model, View & Update) pattern.

Cognitive Services

Set of APIs and SDKs to make apps more intelligent, you can create Machine Learning based experiences, there are services for making Q&As or Immersive Reader, Speech to Text, Speech Recognition and services for Vision for recognition of images. Some examples include their own sentiment nalysis and emotion analysis app, plus there is an X-ray analysis app to look at images and decide what is wrong in the image, also a skin cancer prediction app with Azure Machine Learning.