Month: June 2018

  • Four Spring Cloud Projects That You Should Be Using

    Since I’ve moved up to the Seattle-area three years ago, there’s been a hole in my life. No longer. The Habit just opened up around the corner from me. I missed that place! While most of the attention (including my own) is on the Charburger, they actually have a pretty deep menu. I thought about that this week when looking at the latest Spring Cloud portfolio. While it’s used millions of times per month by Java developers —and usage grew 137% over the past year alone—Spring Cloud is best known for its Config Server and packaging of NetflixOSS tech. You know, things for service discovery, load balancing, circuit breakers, etc. THEY DESERVE THE GLORY. But there are four other interesting packages that you shouldn’t overlook.

    Spring Cloud Stream

    It’s no secret that I’m a big fan of this library. It abstracts away all the complexity of dealing with message brokers like RabbitMQ and Apache Kafka. Spring Cloud Stream has a straightforward programming model that makes it simple to do complex things. Content-based routing? Dead letter queuing? Content-type conversions? Partitioned processing, even on brokers that don’t natively support it? You get all that.

    I’ve seen more and more companies move away from the heavy, centralized ESB and towards a federated messaging model. With Stream, you can use your choice of message broker, but make it a late-binding decision for developers. And if you’re doing event processing and want to chain a series of action together, Spring Cloud Stream works great with Spring Cloud Data Flow.

    If you want to dig in, check out my Pluralsight course that has a whole module on Spring Cloud Stream. Or just go build something!

    Spring Cloud Contract

    Consumer-driven contracts are a fresh take on testing APIs. You know the classic way we share API info: create an API and expose operations and payloads for teams to model and test against. With consumer-driven contracts, the API creator builds and tests their service against a set of consumer expectations. But this has traditionally been a bit difficult to pull off. Enter Spring Cloud Contract.

    It’s described in the docs as moving “TDD to the level of software architecture.” It does this by “covering a range of options for writing tests, publishing them as assets, and asserting that a contract is kept by producers and consumers.”

    You write contracts in Groovy or YAML, and testing stubs get generated and used by both producers and consumers. This enables fast feedback for both side. What’s cool about these generated testing stubs (and the associated “stub runner”) is that you can mock complex distributed systems with a few code annotations. This includes the messaging layer as well. Powerful stuff, and a big deal for today’s software developers.

    Read this insightful interview with Spring Cloud Contract’s creator, Marcin Grzejszczak. And check out the docs for all the gory details.

    Spring Cloud Gateway

    This one’s pretty new, so I’ll excuse you if you haven’t heard of it. BUT ONLY THIS ONCE! Spring Cloud Gateway gives you a powerful API gateway based on Spring components.

    Use (built-in or custom) route predicates to determine how requests are handled. Built-in ones include datetime (before, after, or between), cookies, headers, host, method, path, query, and more. Combine them to get whatever behavior you need. You can also modify incoming or outgoing traffic. Add headers, integrate with Hystrix for circuit breaker behavior, check a rate limiter, do directors, among other things. As you’d expect, this is quite extensible and scalable.

    API gateways form an important part of your architecture, and having a bunch of mini-gateways deployed (instead of a single, monolithic one) might give you extra flexibility. Check out the docs and try it out.

    Spring Cloud Function

    Unless you’ve awoken from a three-year slumber, you’re probably familiar with “serverless” tech. Spring Cloud Function is a pretty wicked (generally available) framework that does a few things you might not expect.

    It’s not just about making Spring Boot friendly to function platforms like AWS Lambda or Azure Functions. That’s there (see AWS and Azure adapter guidance). But besides providing a consistent programming model across clouds, it also has stuff you need to run it standalone.

    Decorate your code with annotations that result in HTTP or stream-processing endpoints getting attached to your function. Your function can take part in messaging as a source, processor (takes data in, publishes data out), or sink. Or it can get be a standalone web app that gets activated upon HTTP request. Neato. Read the docs and see how easy it is to get started.

    Spring Cloud is a pretty unique collection of projects, and the Spring team is constantly upgrading and improving them. The whole point is to make it simple to incorporate proven distributed systems pattern in your apps. From what I can tell, it’s achieving that mission.

  • Creating a continuous integration pipeline in Concourse for a test-infused ASP.NET Core app

    Creating a continuous integration pipeline in Concourse for a test-infused ASP.NET Core app

    Trying to significantly improve your company’s ability to build and run good software? Forget Docker, public cloud, Kubernetes, service meshes, Cloud Foundry, serverless, and the rest of it. Over the years, I’ve learned the most important place you should start: continuous integration and delivery pipelines. Arguably, “apps on pipeline” is the most important “transformation” metric to track. Not “deploys per day” or “number of microservices.” It’s about how many apps you’ve lit up for repeatable, automated deployment. That’s a legit measure of how serious you are about being responsive and secure.

    All this means I needed to get smarter with Concourse, one of my favorite tools for CI (and a little CD). I decided to build an ASP.NET Core app, and continuously integrate and deliver it to a Cloud Foundry environment running in AWS. Let’s go!

    First off, I needed an app. I spun up a new ASP.NET Core Web API project with a couple REST endpoints. You can grab the source code here. Most of my code demos don’t include tests because I’m in marketing now, so YOLO, but a trustworthy pipeline needs testable code. If you’re a .NET dev, xUnit is your friend. It’s maintained by my friend Brad, so I basically chose it because of peer pressure. My .csproj file included a few references to bring xUnit into my project:

    • “Microsoft.NET.Test.Sdk” Version=”15.7.0″
    • “xunit” Version=”2.3.1″
    • “xunit.runner.visualstudio” Version=”2.3.1″

    Then, I created a class to hold the tests for my web controller. I included one test with a basic assertion, and another “theory” with an input data set. These are comically simple, but prove the point!

       public class TestClass {
            private ValuesController _vc;
    public TestClass() {
                _vc = new ValuesController();
            }
    
            [Fact]
            public void Test1(){
                Assert.Equal("pivotal", _vc.Get(1));
            }
    
            [Theory]
            [InlineData(1)]
            [InlineData(3)]
            [InlineData(20)]
            public void Test2(int value) {
                Assert.Equal("public", _vc.GetPublicStatus(value));
            }
        }
    

    When I ran dotnet test against the above app, I got an expected error because the third inline data source led to a test failure, since my controller only returns “public” companies when the input value is between 1 and 10. Commenting the offending inline data source led to a successful test run.

    2018.06.06-concourse-02

    Ok, the app was done. Now, to put it on a pipeline. If you’ve ever used shameful swear words when wrangling your CI server, maybe it’s worth joining all the folks who switched to Concourse. It’s a pretty straightforward OSS tool that uses a declarative model and containers for defining and running pipelines, respectively. Getting started is super simple. If you’re running Docker on your desktop, that’s your easiest route. Just grab this Docker Compose file from the Concourse GitHub repo. I renamed mine to docker-compose.yml, jumped into a Terminal session, switched to the folder holding this YAML file, and ran docker-compose up -d. After a second or two, I had a PostgreSQL server (for state) and a Concourse server. PROVE IT, you say. Hit localhost:8080, and you’ll see the Concourse dashboard.

    2018.06.06-concourse-01

    Besides this UX, we interface with Concourse via a CLI tool called fly. I downloaded it from here. I then used fly to add my local environment as a “target” to manage. Instead of plugging in the whole URL every time I interacted with Concourse, I created an alias (“rs”) using fly -t rs login -c http://localhost:8080. If you get a warning to sync your version of fly with your version of Concourse, just enter fly -t rs sync and it gets updated. Neato.

    Next up? The pipeline. Pipelines are defined in YAML and are made up of resources and jobs. One of the great things about a declarative model, is that I can run my CI tests against any Concourse by just passing in this (source-controlled) pipeline definition. No point-and-ciick configurations, no prerequisite components to install. Love it. First up, I defined a couple resources. One was my GitHub repo, the second was my target Cloud Foundry environment. In the real world, you’d externalize the Cloud Foundry credentials, and call out to files to build the app, etc. For your benefit, I compressed to a single YAML file.

    resources:
    - name: seroter-source
      type: git
      source:
        uri: https://github.com/rseroter/xunit-tested-dotnetcore
        branch: master
    - name: pcf-on-aws
      type: cf
      source:
        api: https://api.run.pivotal.io
        skip_cert_check: false
        username: XXXXX
        password: XXXXX
        organization: seroter-dev
        space: development
    

    Those resources tell Concourse where to get the stuff it needs to run the jobs. The first job used the GitHub resource to grab the source code. Then it used the Microsoft-provided Docker image to run the dotnet test command.

    jobs:
    - name: aspnetcore-unit-tests
      plan:
        - get: seroter-source
          trigger: true
        - task: run-tests
          privileged: true
          config:
            platform: linux
            inputs:
            - name: seroter-source
            image_resource:
                type: docker-image
                source:
                  repository: microsoft/aspnetcore-build
            run:
                path: sh
                args:
                - -exc
                - |
                    cd ./seroter-source
                    dotnet restore
                    dotnet test
    

    Concourse isn’t really a CD tool, but it does a nice basic job of getting code to a defined destination. The second job deploys the code to Cloud Foundry. It also uses the source code resource and only fires if the test job succeeds. This ensures that only fully-tested code makes its way to the hosting environment. If I were being more responsible, I’d take the results of the test job, drop it into an artifact repo, and then use that artifact for deployment. But hey, you get the idea!

    jobs:
    - name: aspnetcore-unit-tests
      [...]
    - name: deploy-to-prod
      plan:
        - get: seroter-source
          trigger: true
          passed: [aspnetcore-unit-tests]
        - put: pcf-on-aws
          params:
            manifest: seroter-source/manifest.yml
    

    That was it! I was ready to deploy the pipeline (pipeline.yml) to Concourse. From the Terminal, I executed fly -t rs set-pipeline -p test-pipeline -c pipeline.yml. Immediately, I saw my pipeline show up in the Concourse Dashboard.

    2018.06.06-concourse-03

    After I unpaused my pipeline, it fired up automatically.

    2018.06.06-concourse-05

    Remember, my job specified a Microsoft-provided container for building the app. Concourse started this job by downloading the Docker image.

    2018.06.06-concourse-04

    After downloading the image, the job kicked off the dotnet test command and confirmed that all my tests passed.

    2018.06.06-concourse-06

    Terrific. Since my next job was set to trigger when the first one succeeded, I immediately saw the “deploy” job spin up.

    2018.06.06-concourse-07

    This job knew how to publish content to Cloud Foundry, and used the provided parameters to deploy the app in a few seconds. Note that there are other resource types if you’re not a Cloud Foundry user. Nobody’s perfect!

    2018.06.06-concourse-08

    The pipeline run was finished, and I confirmed that the app was actually deployed.

    2018.06.06-concourse-09

    Finished? Yes, but I wanted to see a failure in my pipeline! So, I changed my xUnit tests and defined inline data that wouldn’t pass. After committing code to GitHub, my pipeline kicked off automatically. Once again it was tested in the pipeline, and this time, failed. Because it failed, the next step (deployment) didn’t happen. Perfect.

    2018.06.06-concourse-10

    If you’re looking for a CI tool that people actually like using, check out Concourse. Regardless of what you use, focus your energy on getting (all?) apps on pipelines. You don’t do it because you have to ship software every hour, as most apps don’t need it. It’s about shipping whenever you need to, with no drama. Whether you’re adding features or patching vulnerabilities, having pipelines for your apps means you’re actually becoming a customer-centric, software-driven company.

  • Here’s where you’ll find me over the Summer

    I mean, you’ll mainly find me in Seattle, where I actually live. But, I’m also speaking on a variety of topics at a few shows over the next few months, and thought I’d point those out.

    Architecting Highly Available Cloud Integrations” at Integrate 2018 (June 4-6, London)

    If the thing that connects your other things together isn’t resilient, you’re in trouble. In this talk, I’ll take a look at some core availability patterns for application/data integration, and then review how to configure Azure’s integration services for high availability. This is always a terrific show with compelling speakers, and the hosts at BizTalk360 always do a bang-up job putting it on.

    Product Ownership, Explained” at Agile 2018 (August 6-10, San Diego)

    I know a few things about product ownership, such as how to be a good product owner, and a bad one. Primarily because I’ve been both. In this talk at the “big Agile” show, I’ll look at the role and what a product owner should do. I’m starting to work on this presentation now, and will likely list 10+ things that you should do, and a few things to avoid. This will be my second time speaking at this conference, and I enjoy hearing from so many folks focused on software teams and getting code to production.

    What NASA’s Voyager Mission Teaches Us About Building Distributed Systems” at Pluralsight LIVE (August 28-30, Salt Lake City)

    I’ve been geeking out on space exploration books and movies lately, and thought it’d be fun to translate the lessons from an iconic NASA mission to the everyday challenges faced by software engineers. Here, I’ll show how some of the key ideas applied by NASA engineers reinforce some of the best practices when designing complex software systems. I didn’t attend the inaugural edition of this conference last year, but I’m jazzed to be part of it this time around.

    I hope I’ll see you at some of these! If you’ll be at any one of them (or all three, if you’re my stalker!), do let me know.