Archive for the ‘Release Engineering’ Category
Source: Flickr; Chrice‘s Photostream
The following recommendation was given in the post How to Initiate a Devops Project:
For a DevOps project, start by establishing the technical debt of the software to be released to operations. By so doing you build the foundations for collaboration between development and operations through shared data. In the devops context, the technical debt data form the basis for the creation and grooming of a unified backlog which includes various user stories from operations.
I would like to augment this recommendation with a suggestion with respect to the mindset during the initiation phase. Chances are the IT folks feel outnumbered by the dev folks. It might or might not be a matter of optics, but recognizing and appreciating this mindset is will help a lot in getting the devops project on track.
Here is a simple example I heard from a participant in the June 25 devops day in Mountain View, CA. The participant with whom I talked is an IT ops person who tries to get ops aligned with fairly proficient Agile development teams. She is, however, constrained with respect to the IT ops resources available to her. She simply does not have the resources required to attend each and every Scrum meeting as 25 such meetings take place every day. She strongly feels “outnumbered.”
Various schemes could be devised to enable meaningful participation of ops in the Agile process. The more important thing though is to be fully sensitized to the “outnumbered” feeling. The extension of Agile principles to ops will not succeed at the face of such a feeling.
Boundary objects are objects which are both plastic enough to adapt to local needs and constraints of the several parties employing them, yet robust enough to maintain a common identity across sites. They are weakly structured in common use, and become strongly structured in individual-site use. They may be abstract or concrete. They have different meanings in different social worlds but their structure is common enough to more than one world to make them recognizable means of translation. The creation and management of boundary objects is key in developing and maintaining coherence across intersecting social worlds. [Source: Wikipedia].
As an example, the boundary object for the situation described in this post could be a set of technical debt criteria that make the code eligible for deployment from a product life cycle perspective. By so doing, it shifts the dialog from the process to the outcome of the process. Instead of working on generating IT resources in an “outnumbered” mode, the energy shifts toward developing a working agreement on the intrinsic quality of the code to be deployed.
Some technical debt criteria that could form the core of a devops boundary object are mentioned in the post Technical Debt Meets Continuous Deployment. Corresponding criteria could be used in the boundary object to satisfy operational requirements which are critical to the proper functioning of the code. For example, a ceiling on configuration drift in IT could be established to ensure an adequate operating environment for the code. A boundary object that contains both technical debt criteria and configuration drift criteria satisfies different concerns – those of dev and those of ops – simultaneously.
Scrum set the flywheel in motion and caused the rest of the IT process life cycle to respond. ITIL’s processes still form the solid core of service support and we’ve improved the processes’ capability to handle intense work velocity. The organization adapted by developing unprecedented speed in the ability to deliver production fixes and to solve root cause problems with agility.
From what I gleaned yesterday in the O’Reilly Velocity conference I believe the tables are turning. Ops, or at least web ops, will soon drive development.
The reason for my saying so is quite simple: the breadth and depth of forthcoming web analytics unveiled in the conference. This is not “just” about Google making website performance part of their ranking algorithm. Everything related to web performance will soon be analyzed mercilessly under the “make the web faster” mantra. Dev will need to respond to analytics from operations with an unprecedented speed. For most practical purposes analytics run in ops will dictate the speed for dev.
The phenomenon actually goes beyond performance aspects. To be able to implement changes quickly, dev will need to be very good in ensuring the quality of fast changes. While quality has many dimensions to it, the most applicable one is test coverage. There is no way to change the code quickly without a comprehensive automated test suite.
The first step toward dev meeting the required speed is described in the post How to Initiate a Devops Project:
For a devops project, start by establishing the technical debt of the software to be released to operations. By so doing you build the foundations for collaboration between development and operations through shared data. In the devops context, the technical debt data form the basis for the creation and grooming of a unified backlog which includes various user stories from operations.
I would actually go one step further and suggest including technical debt criteria in the release process. The code is not accepted unless the technical debt per line of code is below a certain pre-set level such as $2. The criteria, of course, can be refined to include specific criteria for the various components of technical debt such as coverage, complexity or duplication. For example, unit test coverage in excess of 70% could be established as a technical debt criterion.
Once such release criteria are established, the metaphorical flywheel starts turning in an opposite direction to that described in The Agile Flywheel. With technical debt criteria embedded in the release process, the most straightforward way for dev to meet these criteria is to use the very same criteria as integral part of the build process. The scheme for so doing in given in the following chart:
One last recommendation: don’t wait till Velocity 2011 to start on the path described above. Velocity 2010 already provides plenty of actionable insights to warrant starting now. Just take a look at the web site.
Source: 17th/21st Lancers c. 1922-1929 “THE FIGHTING SPIRIT!”
Agile consultants on a development project often start by helping the team construct a backlog. The task is sufficiently concrete to get all stakeholders (product management, project management, development, test, any others) on a collaborative track through the creation of a key artifact. The backlog establishes a base line for the tasks to be carried out in the project.
For a DevOps project, start by establishing the technical debt of the software to be released to operations. By so doing you build the foundations for collaboration between development and operations through shared data. In the DevOps context, the technical debt data form the basis for the creation and grooming of a unified backlog which includes various user stories from operations.
Apply the same approach when you are fortunate to be able to include folks from operations in the Agile team from the very beginning. You start with zero technical debt, but you track it on an ongoing basis and include the corresponding “fix-it” stories in the backlog as you accrue the debt. Running technical debt analytics on the source code every two weeks is a good practice to follow.
As the head of development, you might not be comfortable sharing technical debt data. This being the case, you are not ready for DevOps.
The traditional way of examining software from a life-cycle perspective is phase-by-phase. The software is developed; deployed; monitored; maintained; changed; and, eventually retired.
True though this description is, more and more executives these days actually view it all as one continuum. An application is developed, and then deployed and maintained as part of some business process. At a certain level it might not really matter to a business executive what the software life-cycle is and which party carries out what phase. The thing that matters is that some service is performed to customer satisfaction. One could actually do complete Business Process Outsourcing, chartering a third party to take care of all the “headaches” in the continuum – from coding a critical software component to repairing a delivery truck to answering calls like, “My shipment has not arrived on the promised date.”
This post looks inside the continuum to comments on the implications of increasing the number of releases. Aspects related to, IT operations, IT service management and the customer as a strategic partner will be discussed in subsequent posts.
Number of Active Releases
The delivery of value to the customer is a fundamental tenet of Agile. The whole Agile development process is geared to that end. Customer value, however, is realized when the customer is able to start using the product . As deployment cycles for enterprise software can be quite long, time gained through Agile development is not necessarily of immediate value to the customer. For customer value to materialize, the deployment cycle needs to be fast as well.
Companies that use Agile successfully can be quite different with respect to deployment practices. Here is a quick comparison of BMC Software, PatientKeeper and Google:
- The successful implementation of Scrum at BMC Software led to producing 3-4 releases of the BMC Performance Manager per year. However, time to deployment by various customers varied greatly. Hence, a relatively small number of releases was active at any point in time.
- With PatientKeeper, Sutherland exploited the hyper-productivity of his Agile teams to produce a relatively large number of releases. When a customer needed a “release” it was downloaded via VPN and installed in fairly short order. Some 45 active releases of the software existed at any point in time.
- Companies such as Google expedite deployment by using Software as a Service (SaaS) as the delivery mechanism. Google has only one actively deployed release at a time, but produces many fast releases.
As one increases the number of releases, a reasonable balance between velocity of development versus velocity of deployment in the continuum must be struck. To streamline end-to-end operations, velocity gains in one should be matched by gains in the other.
It does not Really Matter if you can Tell the Egg from the Chicken
One can speculate on how things evolve between development and deployment. Whether Agile software development leads to improvement in deployment, or Software as a Service “deployment” induces faster development processes. The Agile philosophy is well expressed in either case. In either direction, the slowere speed area is considered an opportunity, not a barrier. A Software as a Service Operations person who pushes for faster development speed lives the Agile philosophy even if he knows nothing about Agile methods.