Archive for the ‘IT Operations’ Category
What 108M Lines of Code do not Tell Us
Source: Nemo
Coming on the heels of Gartner’s research note projecting $1 trillion in IT Debt by 2015, CAST’s study provided a more granular view of the debt, estimating an average of over $1 million in technical debt per application in a sample of 288 applications. Between these two studies, the situation examined at the micro-level seems to be quite consistent with the state of affairs estimated and projected at the macro-level.
My hunch is that the gravity of the situation from a software quality and maintenance perspective is actually masked by efforts of IT staffs to compensate for programming problems through operational excellence. For example, carefully staged deployment and quick rollback often enable coping with defects that could/should have been handled through higher test coverage, lesser complexity or a more acceptable level of code duplication.
Part of the reason that the masking effects of IT staffs are not always fully appreciated is that they are embedded in the business design of IT Outsourcing companies. The company to which you outsourced your IT is ‘making a bet’ it can run your IT better than you can. It often succeeds in so doing. The unresolved defects in your old code plus those that evolved over time through software decay have not necessarily been fixed. Rather, the manifestations of these defects are handled operationally in a more efficient manner.
Think again if your visceral reaction to the technical debt situation described in the Gartner research note and the CAST study is of the “This can’t possibly be true” variety. It is what it is – just take a quick look at Nemo to see representative technical debt data with your own eyes. And, as indicated in this post, it might even be worse than what it looks. As Gartner puts it:
The results of such [IT Debt] an assessment will be, at best, unsettling and, at worst, truly shocking.
As If Another Proof Point Was Needed
Annie Shum’s interview earlier this week gave readers of this blog a multi-dimensional view of imminent changes in IT. If you needed independent validation, it came yesterday through EMC’s Chuck Hollis words in the national solution provider GreenPages Technology Solutions’ 14th annual summit:
Vice President Global Marketing CTO Chuck Hollis Monday said the changes resulting from the storage giant’s own no-holds barred journey to the private cloud led to a decline in IT employee job satisfaction…
Hollis said the internal IT satisfaction drop came in the second phase of the EMC cloud revolution focused squarely on mission critical applications. That second phase — which EMC is in the midst of now — has sparked major changes in IT jobs as the company has replaced IT management, security staff and backend IT staff.
“During this phase, this is where org (organizational) chart issues started to come in,” Hollis said. “People’s jobs started to change. Younger people in the organization were being promoted over older people.”
As if another proof point to add to Annie‘s rigorous data was needed…
Boundary Objects in DevOps
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.
Discussing the subject with my friend Andrew Shafer, he mentioned the effectiveness of boundary objects in such cross-organizational situations:
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.
Technical Debt Meets Continuous Deployment
As you would expect in a conference entitled velocity, and in a follow-on devops day, speeding up things was an overarching theme. In the context of devops, the theme primarily manifested itself in lively discussions about the number of deploys per day. Comments such as the following reply to my post Ops Driven Dev were typical:
Conceptually, I move the whole business application configuration into the source code…
The theme that was missing for me in many of the presentations and discussions on the subject was the striking of a balance between velocity and quality. The classical trade-off in process control is between production rate and product quality (and safety, but that aspect [safety] is beyond the scope of this post). IMHO this trade-off applies to software just as it applies to mechanical or chemical processes.
The heart of the “deploy early and often” strategy hailed by advocates of continuous deployment is known deployment state to known deployment state. You don’t let the deployment evolve from one state to another before it has stabilized to a robust state. The power of this incremental deployment is in dealing with single-piece (or as small number of pieces as possible) flow rather than dealing with the effects of multiple-piece flow. When the deployment increments are small enough, rollback, root cause analysis and recovery are relatively straightforward if a deployment turns sour. It is a similar concept to Agile development, extending continuous integration to continuous deployment.
While I am wholeheartedly behind this devops strategy, I believe it needs to be reinforced through rigorous quality criteria the code must satisfy prior to deployment. The most straightforward way for so doing is through embedding technical debt criteria in the release/deploy process. For example:
- The code will not be deployed unless the overall technical debt per line of code is lower than $2.
- To qualify for deployment, code duplication levels must be kept under 8%.
- Code whose Cyclomatic complexity per Java class is higher than 15 will not be accepted for deployment.
- 50% unit test coverage is the minimal level required for deployment.
- Many others…
I have no doubt whatsoever that code which does not satisfy these criteria might be successfully deployed in a short-term manner. The problem, however, is the accumulative effect over the long haul of successive deployments of code increments of inadequate quality. As Figure 1 demonstrates, a Java file with Cyclomatic complexity of 38 has a probability of 50% to be error-prone. If you do not stop it prior to deployment through technical debt criteria, it is likely to affect your customers and play havoc with your deployment quite a few times in the future. The fact that it did not do so during the first hour of deployment does not guarantee that such a file will be “well-behaved” in the future.
Figure 1: Error-proneness as a Function of Cyclomatic Complexity (Source: http://www.enerjy.com/blog/?p=198)
To attain satisfactory long-term quality and stability, you need both the right process and the right code. Continuous deployment is the “right process” if you have developed the deployment infrastructure to support it. The “right code” in this context is code whose technical debt levels are quantified and governed prior to deployment.
Devops: It is Not About ITIL, It is About Proficiency
As you would expect, the Information Technology Infrastructure Library (ITIL) topic was brought up in the devops day held last Friday in a LinkedIn facility in Mountain View, CA. We, of course, had the expected spectrum of opinions about ITIL in the context of devops – from “ITIL will never work for a true continuous development shop” to “well, you can make ITIL work under such circumstances.” Needless to say, a noticeable level of passion accompanied these two statements…
IMHO the heart of the issue is not ITIL per se but system management proficiency. If your system management proficiency is high, you are likely to be able to effectively respond to 10, 20 or 50 deploys per day. Conversely, if your system management proficiency is low, ops is not likely to be able to cope with high velocity in dev. The critical piece is alignment of velocities between dev and ops, not the method used to manage IT systems and services. Whether you use ITIL, COBIT or your own home-grown set of best practices is irrelevant. Achieving alignment of velocities between dev and ops is a matter of proficiency in system management.
How to Initiate a DevOps Project
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 Agile Flywheel
Readers of The Agile Executive have been exposed to the “All In!” strategy used by Erik Huddleston to transform the software engineering process at Inovis and make it uniquely streamlined. In this post we follow up on the original discussion of the subject to explore the effect of Agile on IT Operations. As the title implies, Agile at Inovis served as a flywheel which created the momentum required to transform IT Operations and blend the best of Agile with the best of ITIL.
This guest post was written by Ray Riescher – a Six Sigma Black Belt, Agile evangelist and a business process change agent. Ray is currently responsible for business process management and IT governance at Inovis, a leading provider of business-to-business (B2B) e-commerce services, in Alpharetta, GA
Here is Ray:
When we converted to an Agile Scrum software methodology some 24 months ago, I never imagined the lessons I’d learn and the organizational change that would be driven by the adoption of Scrum.
I’ve lived by the philosophy that managing a business is managing its processes and that all of those processes, especially the operational processes, are interconnected. However, I don’t think I was fully prepared for effect Agile Scrum would have on our company operations.
We dove head first into Agile Scrum and adapted to it very quickly. However, it wasn’t until we landed a very large and demanding customer that Scrum was really put to the test. New enhancements, new features, and new configurations were all needed ASAP. Scrum delivered with rapid development and deployment in the form of releases that were moving into production with amazing velocity. Our release cadence hit warp drive and at one point we experienced several months where multiple teams’ production releases were deploying at the end of every two week sprint.
We’ve subscribed to the ITIL service support processes for Release, Change, Incident, Problem and Configuration Management. ITIL has served us well, giving us a common language and a clear understanding of process boundaries.
As the Scrum release cadence kicked in, the downstream ITIL processes had to keep up, adapt, and support the dynamics of rapid production changes. What happened was enlightening and maybe a bit ground breaking.
The Release Management process had to reassess its reliance on artifacts for gate keeping. The levels of sign offs had to be streamlined, the heavyweight deployment documentation had to be lightened, yet the process still had to control the production release to ensure deployment success. The rapidity of the release cycles meant that maintenance window downtime would be experienced too frequently by customers, so “rolling bounce” deployment strategies were devised and implemented.
Change requests could no longer wait for a weekly Change Management review board to approve and schedule the changes. Change management risk models had to be relied on for accurate detection of risky changes.
Early on in this dynamic environment, we weren’t quite as good as we needed to be and our Incident Management process was put to the test. Faster releases meant more opportunity for problems with service degradation and outages. This reality manifested itself more frequently than we’d ever experienced. Monitoring, detecting and repairing became paramount for environment stability and customer satisfaction.
What we found out was that we became very agile at this break/fix game. We developed a small team approach to managing incidents and leveraged the ITIL Problem Management process to rapidly perform root cause analysis. Once the true root cause was determined, a fix would be defined and deployed. Sometimes the fix was software related and went through the Scrum process, sometimes the fix was hardware related and went through the Configuration Management process, other times it was more operational and the fix took the form of training or corrections to procedural documentation.
The point is we’ve become agile across the entire IT spectrum. Whether it’s development via Scrum, the velocity with which we now operate our ITIL processes, or the integrated break/fix operational support processes, we are performing all of these with an agile mindset and discipline. We have small teams, working on priorities, and completing what needs to be completed now.
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.
What I think we are witnessing is a manifestation of Agile Business Service Management; a holistic agile methodology running across the IT process spectrum that’s delivering eye popping change and tremendous results.