The source code for this post can be found on Github.
Intermittent network flapping, or any one downstream host of several clones responding slowly, is a not uncommon thing that happens in a microservices architecture, especially if you’re using java applications, where the JIT compiler can often make initial requests slower than they ought to be.
The source code for this post is available on Github.
Things break. When you start adding more and more microservices, things will break a lot more. This post is about how to provide a degraded experience to your users when things break.
The source code for this post can be found on Github.
Following up on the last post, which was making sequential calls to downstream services, sometimes you are in a position where you can make calls in parallel and merge the results. In this case, we want to use zip.
The source code for this article can be found on Github.
In reactive programming, it’s a game of callbacks. In the vast majority of cases, you will want to defer all of your I/O operations to the library you are using [typically, netty, under the hood], and stay focused on setting up the flow so that the right functions are invoked in the right order. Sometimes you will want to make calls in parallel, sometimes you need data from a previous call or operation available in order to invoke that right function.
The source code for this post can be found on Github.
Following up on the previous post where we showed how to send SQS messages to Localstack using the AWS SDK for Java 2.0, we will now demonstrate how to write code that continuously polls for SQS messages, processes them, then deletes them off the queue.
The source code for this post is available on GitHub.
One of the nice things about a reactive programming model is there is a significantly lower risk of doomsday when things start getting latent all at once. You don’t have threads upstream blocking and waiting for a response, therefore they won’t all seize up and stop serving requests [or they won’t short circuit if you’re using a resiliency library like hystrix].
The source code for this post can be found on Github.
Mock Server is a really simple and straightforward way to actually let your application make downstream calls and intercept them. That level of abstraction is really nice to have, and gives at least me much more confidence that my code is actually working in a microservices environment.
The source code for this post can be found on Github.
The most straightforward way to write unit tests in spring boot webflux is to leverage project reactor’s StepVerifier. StepVerifier allows you to pull each item in a Flux or the only potential item in a Mono and make assertions about each item as it’s pulled through the chain, or make assertions about certain errors that should be thrown in the process. I’m going to quickly walk you through an example integrating mockito with it and webflux.
The OpenAPI Specification is an “industry standard” way of declaring the API interface. As REST APIs using JSON have dominated the way we move data around in most organizations and on the internet, particularly in service oriented architectures, and as documentation at almost every company has been written once, read a couple of times, then lost to the wind, smart people have figured out that they can put the documentation for their services living with the code–better yet, displayed while the app is running.
The source code for this post can be found on Github.
When you make the switch to a reactive codebase, ThreadLocal becomes effectively off limits to you, because you aren’t guaranteed that the thread that starts the request processing remains the same, even if it’s the same HTTP request. This has caused pain in many places: the original implementation of spring security, for example, relied very heavily on ThreadLocal variables to store state that happened in the start of the request, and then reuse the information stored in those variables later on to make access control decisions. Neflix spoke of their pain migrating to a reactive stack, when they had relied so heavily on ThreadLocal variables in most of their shared libraries.
In my last post on getting started with spring boot webflux and AWS DynamoDB, I mentioned that it wasn’t immediately obvious to find a way to customize the response code in a spring boot RestController, so I opted to use handlers instead.
The source code for this post can be found on Github.
The latest AWS SDK for java uses a reactive client to send requests to various AWS services, including DynamoDB. Reactive programming is ultimately more robust at the edges–once you start experiencing latency anywhere in your stack, if your tech is not reactive, you’re going to have a significantly worse time than if it were.
