Dropwizard vs Spring Boot

wizard photo

Photo by seanmcgrath

I just rolled off a project where I chose to use Spring Boot to create a number of microservices.  I have also written a number of Dropwizard services, and wanted to compare the two while they were fresh in my mind.

They have a number of similarities, of course.  Both Spring Boot and Dropwizard create standalone jarfiles that can be deployed without needing a container.  Both favor convention over configuration and want to help you do the right thing out of the box.  Both are java based.  Both have monitoring, health checks, logging and other production nicitiies buit-in.  Both are opinionated–making a lot of choices for the developer, rather than forcing the developer to choose.  Both make it easy to leverage existing libraries.  Both have a focus on performance.

However, there were a number of reasons I choose Spring Boot over Dropwizard for the recent project, and these highlight the differences.  The first is that dependency injection is built into Spring Boot in a way that it simply isn’t with Dropwizard.  Of course, there are third party solutions for bolting DI onto Dropwizard, but we also needed a java DI framework that would handle lifecycle events, which pretty much means Spring.  Finally, this project wasn’t all about REST services, and while Dropwizard has some support for other types of services, it really is designed as a performant HTTP/REST layer, and certainly almost all the questions about Dropwizard online are about REST and APIs.  Spring Boot, on the other hand, aims to provide support for a plethora of different types of services.  Plus, you can leverage the rest of the large Spring codebase.

There are some other differences as well.  Dropwizard uses shading to build fat jars while Spring Boot uses nested jars.  As far as support, Spring, as usual, wins on the documentation front, with loads of accurate docs.  But Dropwizard definitely has a larger community around it (compare the activity of the DW google group to the Spring Boot forums).

If you are writing a REST API in Java, Dropwizard is a great choice (here’s a review of other options I did a few months ago).  If you want to build microservices that integrate with other types of components (queues, nosql, etc), Spring Boot is what I’d recommend.

Update 12/8: Per this tweet, the spring forums aren’t used because of spam, but you can find plenty of support on StackOverflow with questions tagged ‘spring-boot’.

Thoughts on Amazon CloudFormation

cloud formation photo

Photo by eschipul

I recently set up Amazon CloudFormation for a fairly complicated application in AWS.  For those unfamiliar with this service, it allows you specify a number of AWS resources in a declarative way in a JSON document, create them all at once (it’s called a ‘stack’), manage them as one entity, and destroy them.  You are billed just as you would be if you created the resources by hand.  But it’s a versionable, replicable way to create resources.

The distributed application for which I was creating the stack had the following components:

  • queues (SQS)
  • databases (dynamodb, including secondary indices)
  • compute (EC2)
  • alarms (Cloudwatch)
  • storage (S3)
  • a VPC and Subnets
  • event logging (kinesis)
  • hadoop (Elastic Map Reduce)

The last four items were not configured by the CloudFormation template I wrote.  S3, VPC and subnets because I leveraged existing resources, and Kinesis and EMR because they are not supported by CloudFormation.  (Kinesis has some support, but CloudFormation doesn’t allow you to specify a name of a stream, which makes it pretty useless when you want to post or read from a specific stream.)  However, while it would be preferable to have everything specified in CloudFormation, partial stack creation was useful–I just documented the other requirements in the CloudFormation template–because:

  • resource configuration like queue timeouts, names, read throughput, etc can be applied uniformly–consistency is enforced.
  • the infrastructure is defined and documented in one place, allowing a new developer to get up to speed quickly.
  • tags can be applied uniformly.
  • CloudFormation supports parameters, so that you can preface every resource with a deployment environment specific variable (‘stage’, ‘dan-dev’, etc), or have different DynamoDB throughput for different deployments.
  • if different configuration needs to be tested, you can stand up a new stack in minutes and test it.
  • the template can be stored in your version control system, allowing someone to see how things changed over time.  Yay, commit logs!

There were some other possible benefits I just didn’t have time to explore fully before the project wound down.

  • autoscaling groups seemed like they’d be extremely useful.  These aren’t a CloudFormation only tool, but CloudFormation seems an ideal way to define and use them.
  • the ability to create and delete stacks opened up the possibility of creating developer specific environments for debugging issues.

If you are going to start with CloudFormation, I highly recommend setting up an initial environment by hand, and then running CloudFormer, a small application written by Amazon which reads from your existing AWS infrastructure and generates a CloudFormation template.  I used CloudFormer to create a template for everything in our AWS account, and then picked and chose what was pulled over to the new template.  There were a few issues with this though:

  • There was a bug in the CloudFormation documentation for DynamoDB schemas.  You want to use this syntax: "KeySchema": { "HashKeyElement": { "AttributeName": "attrname", "AttributeType": "S" }, ... }.  CloudFormer generated them correctly, however.
  • CloudFormer coerces names of some resources resources including VPCs and subnets to strings, and I had to back those out when I wanted to use existing resources.

Other than not being able to fully define an application (because of dependencies on unsupported AWS tools like Kinesis and EMR), what other downsides does CloudFormation have?

  • it locks you into AWS.  Openstack Heat is an alternative that works across clouds, or so I read.  And, really, once you decide on AWS, is a infrastructure creation script going to be the one thing that keeps you from moving?
  • it is tied to infrastructure creation (though there is resource by resource support for in place updates).  If you want to modify one queue setting, you have to tear down and create anew the entire stack.  I found this to be relatively quick (15 min or so).
  • you are still writing scripts in the UserData section of the EC2 definition to set up your server environment.

After this experience, and reviewing my thoughts above, I believe the sweet spot of CloudFormation is setting up dev and QA environments quickly, and documenting infrastructure choices when you are committed to AWS.

My Experiences with a Digital Sabbath

I’ve tried a digital sabbath a few times in the past year.  If you aren’t familiar with the concept, it means taking one day a week and putting away all your digital devices.  No smartphones, tablets, laptops or desktop computers (do people still use those?  I do!).  For one day, I even skipped making phone calls.  Focus on the here and now.  Read a book.  Play with your kids.  Go outside.  Do that home improvement project you’ve been meaning to get to.  Look, there’s even a website about the digital sabbath!

I’ve done this a few times and it is tough.  Why?  If I have any questions about anything, I reach for my phone or tablet–when does Home Depot open?  How do I cook sunchokes?  That is relatively easy to counter–just prepare ahead of time, or accept not knowing.  I’ve even been known to pull out a copy of the white pages (yes, they still distribute that).

I also feel I am ‘maximizing’ my time–when I can read about Clojure or respond to tweets while brushing my teeth, I feel like I’m doubling my time.  It’s the same feeling I have when I run the washing machine and the dishwasher–I can sit on the couch and read because I’m ‘doing’ two jobs already!  So, a sabbath removes a major source of attention fragmentation.

The harder part of a digital sabbath is the non informational uses of my phone.  Frankly, I use my phone to escape boredom and frustration.  Of course, it is still entirely possible to ‘check out’ with a book or even daydreaming, but using a phone makes it so dang easy.  I think it is because it feels like you are accomplishing something worthwhile easily–gaining new knowledge, interacting with someone across the world.  Maybe because those use to be hard hard tasks–you had to check a book out of the library, or write someone a letter or make an expensive phone call.  Now the effort/reward has a radically decreased numerator, but my brain is still in the 1980s and doesn’t recognize it.


While I can learn plenty and make plenty of friends through your phone/tablet/internet connected whatzit, a digital sabbath forces you to ive in the now and the here.  Escapism is fine in small doses, but a digital sabbath forced me to confront how often I use my phone for that purpose.

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