Reactive Microservices

I came across CQRS and attended a talk by James Roper on Lagom for micro services called “Rethinking REST” this week. The idea put forth in the talk was that REST services being synchronous are not ideal for microservices. Microservices should not be blocking , so something that emphasizes this async aspect would be preferable to REST.

How is this notion of async services different from a pub-sub model ? One way it goes beyond that is by proposing polyglot persistence. Different microservices should use their own persistence layer that is optimal – relational, nosql, timeseries, event log.

Lagom architecture is based on the book Reactive Services Architecture and that also suggests CQRS. The book proposes service isolation and that composition of systems with microservices should be done asynchronously via message passing.

A quote from the book on why bulkheads failed to save the Titanic:

“The Titanic did use bulkheads, but the walls that were supposed to isolate the compartments did not reach all the way up to the ceiling. So when 6 out of its 16 compartments were ripped open by the iceberg, the ship started to tilt and water spilled over from one compartment to the next, until all of the compartments were filled with water and the Titanic sank, killing 1500 people.”

The suggestion is that for higher availability there should be stricter isolation. The individual (micro)services may fail but the overall system should not be affected. Looking at it this way I think requires one to examine more closely the system design and its invariants.

Take CQRS as an example. In a query system, data is being read and not being modified; a query is a search operation on accumulated data – potentially a very large set with speed (availability) demands. Whereas in a command system, there is more real-time,  perhaps collaborative aspect which leaves most of the data untouched, but creates some new data which needs to be recorded (upload this image, send this message). Why should these two very different operations be served by the same backend ?

One of the systems that has done separation of concerns remarkably well is  AWS. Let’s take the separation of S3 and the database (say Dynamodb). Neither filesystem vendors nor database vendors came up with simple services to solve the problem of an app trying to upload an object and update a database that the object has been uploaded. The failure modes of each service are exposed to the client and the client is not forced to upload files to S3 via a server (bottleneck). S3 offers a read-write consistency for new uploads and eventually consistency for updates. Here the storage object, its universally addressable name, and its properties (backup, encryption, access, versioning, retention policies) are an invariant -a client does not need to fiddle with them apart from being assured of a certain level of service. One can call it an ingestion system.  More on that here.

The takeaway is that microservices should do one thing and do it very well, in a highly available, non-blocking manner. REST services can certainly be non-blocking, but they can also be blocking as described here, which is a problem.

A cornerstone of asynchronous services is messaging. Here’s a talk on Riak, a masterless database and messaging system, running on CloudFoundry, at GE – . It is followed by talks on microservices.

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