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Design Principles

The design of Airy Core heavily relies on a few core ideas. The goal of this document is to provide context about these ideas and how they affected the way the platform is built.

One source of truth, no shared state#

The most central idea behind the Airy Core design is composed of two connected principles. Here's the first one:

There's one source of truth for data and that place is a Apache Kafka.

We mean all of the data of an Airy Core instance lives in Kafka. One way of thinking about it: as a strongly typed (via Avro) data pipeline. The HTTP endpoints the platform provide also solely rely on Kafka via a feature called interactive queries.

And here's the second principle:

Every service in the system builds their version of reality.

What we mean is that we do not allow services to talk to each other and share state via internal HTTP calls. Let's use an example to clarify: imagine we have a service dealing with conversations data that needs channels data (see our glossary for more information) to build a JSON response. Many systems would work like this:

  • A client asks for conversations
  • the service in charge makes an HTTP internal call to the channels service
  • Once it obtains a response, it merges the data with the conversations
  • It returns the data to the client

In Airy Core, it works like this:

  • A client asks for conversations
  • the service in charge has both conversations and channels data
  • It returns the data to the client

As each service has their own version of reality (aka it maintains their own state of everything they need), there is no communication between services. The trade-off is that, at the cost of more disk space (traditionally pretty cheap), we avoid any dependencies between services.

Test the real thing#

Our default choice for testing is high-level integration tests. As "integration tests" may mean different things to different people, we explain in the following what it means for us.

Most components of Airy Core have multiple dependencies. For example, our HTTP endpoints are Kafka Streams applications that expose data via interactive queries. These endpoints depend on:

  • Apache Kafka
  • Apache Zookeeper (indirectly as Kafka depends on it)
  • The confluent schema registry (almost all our topics are Avro encoded)

To us, "testing the real thing" in this context means:

  • spinning up a test Kafka cluster (and a zookeeper one)
  • spinning up a test schema registry server
  • Run the tests against these test servers

The idea is that we test code in conditions that resemble as closely as possible the production environments. In a way, this approach is also made possible by the principle "Every service in the system builds their version of reality" as most of our endpoints effectively only depend on the storage system and have no other dependencies.

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