Much of the interest in dynamic languages like Groovy, JRuby, and Scala comes from running on the JVM. That lets them leverage the tremendous R&D that’s gone into JVM performance and stability. It also opens up the universe of Java libraries and frameworks.
And yet, much of my work deals with the 80% of cost that comes after the development project is done. I deal with the rest of the software’s lifetime. The end of development is the beginning of the software’s life. Throughout that life, many of the biggest, toughest problems exist around and between the JVM’s: Scalability, stability, interoperability, and adaptability.
As I previously showed in this graphic, the easiest thing for a Java developer to create is a slow, unscalable, and unstable web application. Making high-performance, robust, scalable applications still requires serious expertise. This is a big problem, and I don’t see it getting better. Scala might help here in terms of stability, but I’m not yet convinced it’s suitable for the largest masses of Java developers. Normal attrition means that the largest population of developers will always be the youngest and least experienced. This is not a training problem: in the post-commoditization world, the majority of code will always be written by undertrained, least-cost coders. That means we need platforms where the easiest thing to do is also the right thing to do.
Scaling distributed systems has gotten better over the last few years. Distributed memory caching has reached the mainstream. Terracotta and Coherence are both mature products, and they both let you try them out for free. In the open source crowd, as usual, you lose some manageability and some time-to-implement, but the projects work when you use them right. All of these do the job of connecting individual JVMs to a caching layer. On the other hand, I can’t help but feel that the need for these products points to a gap in the platform itself.
OSGi is finally reaching the mainstream. It’s been needed for a long time, for a couple of reasons. First, it’s still too common to see gigantic classpaths containing multiple versions of JAR files, leading to the perennial joy of finding obscure, it-works-fine-in-QA bugs. So, keeping individual projects in their own bundles, with no classpath pollution will be a big help. Versioning application bundles is also important for application management and deployment. OSGi is what we should have had since the beginning, instead of having the classpath inflicted on us.
I predict that we’ll see more production operations moving to hot deployment on OSGi containers. For enterprise services that require 100% uptime, it’s just no longer acceptable to bring down the whole cluster in order to do deployments. Even taking an entire server down to deploy a new revision may become a thing of the past. In the Erlang world, it’s common to see containers running continuously for months or years. In Programming Erlang, Joe Armstrong talks about sending an Erlang process a message to “become” a new package. It works without disrupting any current requests and it happens atomically between one service request and the next. (In fact, Joe says that one of the first things he does on a new system is deploy the container processes, at the very beginning of the project. Later, once he knows what the system is supposed to do, he deploys new packages into those containers.) Hot deployment can be safe, if the code being deployed is sufficiently decoupled from the container itself. OSGi does that.
OSGi also enables strong versioning of the bundles and their dependencies. This is an all-around good thing, since it will let developers and operations agree on exactly versions of which components belong in production at a given time.