While Deptrac is commonly used to enforce horizontal boundaries within PHP projects, it can also help define and maintain vertical boundaries (such as bounded contexts in DDD speak, or quanta) in PHP monoliths.
This capability is especially valuable when implementing the Ports and Adapters architecture, ensuring clear separation of concerns and robust modularity in your PHP applications.

This three-part series will cover:

• Part 1: Setting up a basic Deptrac configuration for a PHP monolith (this post)
• Part 2: Refactoring spaghetti code into bounded contexts using Ports and Adapters
• Part 3: Enforcing architectural boundaries in your CI pipeline

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The Lost Update Problem is a common issue in concurrent systems, where two transactions read the same data, modify it, and write it back to the database. The second transaction will overwrite the changes made by the first transaction, causing the first transaction’s changes to be lost.

This is especially problematic in cases where money in a bank account is involved, as it can lead to inconsistencies in the account balance. A rather dramatic example of this is the Flexcoin bankruptcy.

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Let’s have a look at the React Function as Children Pattern.

The simple component

Usually, JSX/TSX code looks like this:

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<SomeComponent>
  <SomeChild someProp={something}/>
</SomeComponent>

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In the world of software development, ensuring the quality and reliability of code is paramount. One popular approach to achieving this goal is Test-Driven Development (TDD), where developers write tests before writing the actual code. TDD is also my default way of approaching software development.

However, I’ve started in many environments situations where code changes are made without accompanying automated tests. In such cases, I am using a method I call “Review-Driven Testing”, which helps not only to improve code quality and upskill developers, but also to promote a testing culture within development teams.

What is Review-Driven Testing?

Review-Driven Testing is a practical approach to adding automated tests to code changes that were initially developed without them. While traditional TDD focuses on writing tests before writing code, Review-Driven Testing involves writing tests after the code has been developed and submitted for review. It can be seamlessly used in teams that are not used to writing automated tests by default (yet).

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Code reviews can be very time-consuming. Especially if you are reviewing a lot of code changes. Often, code changes are simple refactorings, such as extracting code into methods/functions or moving code around. These changes are more or less irrelevant for the review, since they usually don’t change the behavior of the code. As a reviewer, one still wants to make sure that code hasn’t been changed during the code move.

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Since AWS is going to sunset / auto-upgrade Aurora Serverless v1 in December 2024, it’s time to upgrade to Aurora Serverless v2. Upgrading to Serverless v2 MySQL instances also means upgrading from MySQL 5.7 to MySQL 8.0 under the hood.

This article describes how to adapt the AWS provided upgrade path to work with a CDK / CloudFormation infrastructure-as-code project, which requires a few more steps which I call the “CDK/CloudFormation retain-and-import dance“.

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This article demonstrates how to upgrade an CDK (or Cloudformation)-managed AWS Aurora cluster from MySQL 5.7 compatible AWS Aurora 2 to MySQL compatible Aurora 3 engine without any - ok, I lied - one minute of downtime. The process utilizes the blue/green deployment feature of Aurora. It also shows how CDK/CloudFormation stacks are brought back in sync with the upgraded Aurora clusters.

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When managing RDS parameter groups with CloudFormation, you might have noticed that changes to a DB cluster or instance parameter group will always cause a reboot of the RDS instance. This happens when the RDS cluster or instance parameter group and the RDS instance are managed by the same CloudFormation stack.

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A recurring task when provisioning databases is to initialize them with initial users, stored procedures, and/or tables.

In the CDK world, there is currently no native support for this, but there are some workarounds. AWS has a blog post about this, but it’s using a Lambda function, and a bunch of custom code which seemed like too much operational overhead for me.

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Having defined what is serverless and what not in the last article, this time let’s have a look at one particular characteristic of serverless systems: they can scale to zero also known as: you don’t pay for idling resources. So let’s discuss why this is actually very important.

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