I think enormous sprawling enterprises who&#x27;s infrastructure has evolved over decades really need something like docker in order to consolidate what used to feel like a tangled mass of different tech.  For that use case docker probably saves top firms a ton of money by reducing overall complexity in their operations.<p>However for early stage web startups especially ones that use the JVM there are only really likely to be a handful of diverse technologies in play.  A typical example: nginx, jruby, redis, kafka, &lt;primary persistence tech goes here&gt;.  Now at first glance you might look at this and see 5 diverse systems and think &quot;these guys could probably benefit from docker&quot;, and perhaps some could, but I personally think that a growing number of shops feel like it&#x27;s a waste of time and resources, and here is why:<p>Although there are five separate systems in the example above the truth is that developers are not sitting around writing nginx config files all day, nor kafka config, nor redis config, nor Mysql config files.  Those are things that you only have to setup correctly once and then you only change gradually, a few lines here and there over the lifetime of the business until you settle in on the most optimized configuration for your workload.<p>99.9% of your team&#x27;s changes will only touch the &quot;application layer&quot; which in this example resides on a single runtime environment (the JVM).  Teams who utilize the JVM in this way usually don&#x27;t feel &quot;pinned in&quot; by it since after all the performance is there, the mature profiling tools are there, the library ecosystem is there, and there are diverse programming languages, frameworks, and multiple programming paradigms all of which ride atop the JVM.  examples:  (Java, JRuby, Scala, Clojure, Vertx.io (non-blocking io&#x2F;javascript), Lift, Akka, spray.io, Play, Immutant, Wildfly, etc)<p>What I&#x27;m getting at is there&#x27;s really no good excuse for a team who standardizes on the JVM to ever need to go outside of that paradigm unless perhaps they&#x27;re writing a C extension to optimize some tight loop, but these days the JVM&#x27;s optimizing bytecode compiler is getting pretty decent at doing that for you.<p>If 99% of your application code (the code that is updated continually) runs on the JVM then even if you have a micro-services architecture with several different programming languages in use you don&#x27;t really need to lean on a containerization technology to standardize deployment because all of it is already under the same runtime environment roof anyways.  From an operations standpoint all your build&#x2F;deploy step really needs to do is ship jar files around over the network irregardless whether it&#x27;s a clojure service, or a scala, or ruby app.  And all of it can be monitored in a clean way thanks to the monitoring support built into the JVM called JMX.<p>To use docker in such a situation is to just waste system resources and to increase network IO (moving heavy disk images around) for no reason.  Instead you can just use shell scripts or Ansible to provision an instance and then rely on the JVM&#x27;s own venerable mini-containerization primitive (the jar file) as the standard way to deploy apps across your fleet.<p>To each his own though..