Environment Portability

I've talked about this a lot before and we have done a lot of work in this area but it cannot be stressed how important it is. In fact I think portability is the key success factor to building a good Continuous Delivery Implementation. Without portability there is no scalability.

There are two things that need to be built with portability in mind the build pipe itself and our dev, test and prod environments. If the build pipe isn't portable then it will become a bottleneck. Infact if the build pipe can run on each individual developer machine without the use of a build server then it is portable enough to scale in a build server environment.

Though in this post I will focus on Environment Portability from Desktop to Production.

Why do we need Portable Production Environments?

For years we have accepted the fact that the Test Environment isn´t really like the Prod Environment. We know that there are differences but we live with it because its too hard and too expensive to do anything about it. When doing Continuous Delivery it becomes very hard to live with it and accept it.

"If its hard do it more often" applies here as well.

The type of problems we run into as a result of non Portable Production Environments are problems that are hard by nature its scalability, clustering, failover, ect, ect. Its non functional requirements that need to be designed in early. By exposing the complexity of the production environment late in the pipe we create a very long feedback loop for the developers. It can be days or weeks depending on how often you hit prod with your deployments.

By increasing the portability of the production environment we increase the productivity of our developers and the quality of our application. This is obvious but there is another very important issue to deal with as well. Every time a deployment in UAT or Prod fails it undermines the credibility of Continuous Delivery. Each time a something that worked in UAT fails in Prod the person responsible for UAT will call for more manual tests before production. Obviously increasing the lead time even further making the problem worse but we need to constantly improve in order to manage fear.

If we have Portable Production Environments then the issues that stem from Environment Complexity will never hit production as they get caught much earlier in the pipe.

Who owns the definition of our Environments?

The different environments that we have in an organization who defines the and who owns them? There are a lot of variations to this as there are a lot of  variation to environment definitions and organizations. In most normally defunct organizations out there the Ops team owns the Production environments and often the machines in the earlier environments. How the earlier environments are set up and used is often the responsibility of the Dev team and if the organization is even more defunct then there is often a Delivery Team involved which defines how its environments are used.

This presents us with the problem that developers quite often have no clue how the production environment looks and implements the system based on assumption or ignorance. In the few cases where they actually have to implement something that has to do with scaling, clustering or failover its often just guess work as they don´t have a way to reproduce it.

Going into production this most often creates late requests on infrastructural changes and often even cases where solutions where based on assumptions that cannot be realized in a production environment.

What is portability?

When we talk about Portable Production Environments what do we really mean? Does it mean that we have to move all our development to online servers and all dev teams get their own servers that are identical to production but in smaller scale? Well not really. It is doable especially with the use of Cloud providers but I find it highly inconvenient to force the developer to be online and on a corporate network in order to develop. Having the ability to create a server environment for a developer on a need to have basis is great because it does cover for the gap where local environments cannot fully be portable.

Assuming one cloud provider to solve all your needs for portability across all environments is not short term realistic in most enterprise organizations unless you are already fully committed and fully rolled out to a cloud provider. There is always these legacy environments that need to be dealt with.

I think the key is to have portability on the topology of the environment. A environment built in AWS with ELBs will never be portable since you will never have an ELB locally. But having A load balancer in your dev environment and having multiple application nodes forces you to build for horizontal scalability and it will capture a whole lot more than just running on one local node.

Running a Oracle XE isnt really the same as running Enterprise Oracle but it provides a good enough portability. Firing it up on a Virtual Box of its own will force the DB away from local host.

In our production environment we monitor our applications using things like Graphite, Logstash+Kibana, ect, ect. These tools should be part of the development environment as well to increase the awareness of runtime and enable "design for runtime".

Creating the Development Environment described here with Vagrant is super easy. It can be built using other tools as well such as Docker or a combo of Vagrant and Docker. But if you use Docker then it needs to be used all the way. My example here with just Vagrant and VBox is to show that portability can be achieved without introducing new elements to your production environment.

Individual Environment Specifications and One Specification to rule them all.

To create a portable topology we need one way to describe our environments and then a way to scale them. A common human and machine readable Topology Specification that defines what clusters, stores, gateways and integrations there are in the topology of our production environment gives us the ability to share the definition of our environments. Then a environment specific specification that defines the scale of the environment and any possible mocks for integrations in development and test environments.

In an enterprise organisation we will always have our legacy environments. Over time these might migrate over to a cloud solution but some will most likely outlive their existence in a legacy environment. For these solutions we still benefit hugely from portable production environments and one way to define them. In a cloud environment we can recreate their topology and leverage the benefits of portability even if we cannot really benefit from the cloud in the production environment it self.

For these solutions the Topology Specification and Environment Specification can be used to generate documentation, little bit of graphviz can do wonders here. This documentation can be used for change request contracts and for documentation purposes.

We like Groovy scripts for our Infrastructure as Code. Here is an example of how the above example with the Cluster and the Oracle database could be defined using the Topology Specification. This example covers just clusters, storages and network rules but more can be added such as HTTP Gateways Fronts as 'gateways'  and pure network integrations with partners as 'integrations'.

def topologySpec = [name:'SomeService'
   ,clusters:[[name:'SomeServiceCluster'
           ,image_prefix:'some-service'
           ,cluster_port:80
           ,node_port:8080
           ,health_check_uri:'/ping/me'
           ,networks:[[
                   name:'SomeServiceInternal'
                   ,allow_inbound:[
                       [from:'0.0.0.0',ports:'80',protocol:'TCP']
                       ,[from:'192.168.16.0/24',ports:'22',protocol:'SSH']
                   ],allow_outbound:[
                       [from:'0.0.0.0',ports:'80',protocol:'TCP']
                       ,[to:'OracleInternal',ports:'1521',protocol:'TCP']
                   ]
               ]
           ]
       ]
   ],storages:[[name:'Rdbms'
           ,type:'oracle'
           ,network:[
               name:'OracleInternal'
               ,allow:[
                   [from:'SomeServiceInternal',ports:'1521',protocol:'TCP']
                   ,[from:'192.168.16.0/24',ports:'22',protocol:'SSH']
               ]
           ]
       ]
   ]
]

Environment Specifications contain scaling of the Topology but can also contain integration Mocks as 'clusters' defined just for that environment.

def devEnvSpec = [name:'SomeService'

   , clusters:[[name:'SomeServiceCluster'

           ,cluster_size:2

           ,node_size:nodeSize.SMALL

       ]

   ]

   ,storages:[

       [name:'Rdbms'

           ,cluster_size:1

           ,node_size:nodeSize.SMALL

       ]

   ]

]

def prodEnvSpec = [name:'SomeService'

   , clusters:[[name:'SomeServiceCluster'

           ,cluster_size:3

           ,node_size:nodeSize.MEDIUM

       ]

   ]

   ,storages:[

       [name:'Rdbms'

           ,cluster_size:1

           ,node_size:nodeSize.LARGE

       ]

   ]

]

Then the definitions are pushed to the Provisioner implementaiton with the input argument of which environment to Provision.

def envSpecs = ['DEV':devEnvSpec

              ,'PROD':prodEnvSpec

              ,'LEGACY':prodEnvSpec]

//args[0] is env name 'DEV', 'PROD' or 'LEGACY'

//Provisioner pics the right implementation (Vagrant, AWS or PDF) for the right environment

new Provisioner().provision(topologySpec, envSpecs, args)

Test Environments should be non persistent environments that are provisioned and decommissioned when the test execution is finished.

Development environments should be provisioned in the morning and decommissioned at the end of the day. This also solves the issue of building the Dev Environment which can be a tedious manual process in many organisations.

Production environments on the other hand need to support provision, update and decommission as its not always convenient to build a new environment for each topological change.

Also understand that Provisioning an environment is not the same as deploying the application. There can be many deployments into a provisioned environment. The Topology Specification doesn't specify what version of the application is deployed just what the base name of the artefact is. I find that convenient as that can be used to identify which image should be used to build the cluster.

One Specification, One Team Ownership

The Topology Specification should be owned by one team, the team that is responsible for developing and putting the system into runtime. Yes I do assume that some sort of DevOps like organisation is in place at this stage. If it isn't then I would say that the specification should be owned by the Dev team and the generated documentation should be contract between Dev and Ops. Consolidating ownership of as many environments as possible into one team should be the aim.

Summary

I think using these mechanisms to provision environments in a Continuous Delivery pipe will increase the quality of the software that goes through the pipe immensely. Not only will feedback be faster but we will also be able to start tailoring environments for specific test scenarios. The possibilities of quality increase are enormous.