Architecture Artifacts Cross-Checker

Last time we looked at architecture metrics. We stated then that the data required for calculating these metrics could come from a variety of sources. However, we all know that information about architectures is often not kept up-to-date…

So how do you keep your metrics reliable by keeping their inputs fresh?

In order to answer a question like that it’s always good to understand the reasons diagrams and other artifacts go stale. It’s not because people are deliberately making them rot, it’s more that they have many things to do and either simply forget to update artifacts or prioritize some other activity.

To solve the first problem, a simple reminder could be all it takes. But here we run the risk of crying wolf. So we need to make sure there is something to update before we send out a reminder.

Enter the architecture artifacts cross-checker. This is a tool that compares different inputs to verify they are consistent. Let’s look at some examples of inputs such a tool could verify.

External systems in a context diagram should also appear in the corresponding container diagram. If you have a tech radar, it should list at least the technologies that are in the container diagram. Containers in a container diagram should have a corresponding process in a data flow diagram. Threat models should calculate the risk of security threats against each of those. Etc. Etc.

We may even be able to tie some of the architecture artifacts to source code.

For instance, in a micro services architecture, each service may have its own source code repository or its own directory in a monorepo. And if you have coding standards for cross-service calls, you may be able to derive at compile time which containers call which at runtime. Alternatively, this information could come from runtime call patterns collected by a service mesh. Finally, running a tool like cloc gives technologies used in the service, which should be listed in the container diagram and in the tech radar.

By combining these diverse sources of information about your system, you can detect inconsistencies automatically and send out reminders for updates. Or even fail the build, if you want to go that far.

What do you think? Would a little bit of coding effort to write an architecture artifacts cross-checker be worth it in your situation? Please leave a comment below.

XACML In The Cloud

The eXtensible Access Control Markup Language (XACML) is the de facto standard for authorization.

The specification defines an architecture (see image on the right) that relates the different components that make up an XACML-based system.

This post explores a variation on the standard architecture that is better suitable for use in the cloud.

Authorization in the Cloud

In cloud computing, multiple tenants share the same resources that they reach over a network. The entry point into the cloud must, of course, be protected using a Policy Enforcement Point (PEP).

Since XACML implements Attribute-Based Access Control (ABAC), we can use an attribute to indicate the tenant, and use that attribute in our policies.

We could, for instance, use the following standard attribute, which is defined in the core XACML specification: urn:oasis:names:tc:xacml:1.0:subject:subject-id-qualifier.

This identifier indicates the security domain of the subject. It identifies the administrator and policy that manages the name-space in which the subject id is administered.

Using this attribute, we can target policies to the right tenant.

Keeping Policies For Different Tenants Separate

We don’t want to mix policies for different tenants.

First of all, we don’t want a change in policy for one tenant to ever be able to affect a different tenant. Keeping those policies separate is one way to ensure that can never happen.

We can achieve the same goal by keeping all policies together and carefully writing top-level policy sets. But we are better off employing the security best practice of segmentation and keeping policies for different tenants separate in case there was a problem with those top-level policies or with the Policy Decision Point (PDP) evaluating them (defense in depth).

Multi-tenant XACML Architecture

We can use the composite pattern to implement a PDP that our cloud PEP can call.

This composite PDP will extract the tenant attribute from the request, and forward the request to a tenant-specific Context Handler/PDP/PIP/PAP system based on the value of the tenant attribute.

In the figure on the right, the composite PDP is called Multi-tenant PDP. It uses a component called Tenant-PDP Provider that is responsible for looking up the correct PDP based on the tenant attribute.