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Tag: Productivity

  • REP SPOTLIGHT: getITright

    REP SPOTLIGHT: getITright

    DevOps Institute: Tell us a little about your organization.

    getITright: With offices in Australia, South Africa, The Netherlands, Nigeria and Malta and a network of partners operating in 31 countries, we offer a bouquet of services to help organizations to:

    • Manage better
    • Lower risk
    • Perform better
    • Make better business and IT decisions

    Our service offering includes:

    • Training courses – Learning best-practice through our Partner Academy courses or network of training providers
    • Accredited IT Best practice course material – License our training material
    • Consulting – We use an agile approach for projects and a lean approach for operations when consulting and coaching.

    DevOps Institute: What other topics do you teach or consult on?

    getITright:

    • Service Management: ITIL®, ISO/IEC20000, Lean IT, Service Desk Institute
    • Governance of Enterprise IT: COBIT® 5
    • Project Management: PRINCE2®, PRINCE2® Agile, DSDM AgilePM®, Scrum
    • Information & Cyber Security Management: ISO/IEC27001, NIST Cybersecurity using COBIT5
    • Quality Management & Business Improvement: ISO9001, LEAN SIX-SIGMA
    • Risk & Continuity Management: ISO31000, ISO/IEC27005, ISO22301
    • Cloud Computing

    DevOps Institute: What type of interest in DevOps are you seeing in your region?

    getITright: DevOps awareness in the region is still low, but we see a steady increase in the level of interest in the topic.

    DevOps Institute: How do you think that DevOps contributes to the business’ value stream?

    getITright: It makes projects and business as usual faster, more stable, with less risk.

    DevOps Institute: What topic area in DevOps excites you the most?

    getITright: DevOps enables organizations to improve productivity and respond to change with less risk. It’s easy to adopt by organizations with mature ITSM practices in place.

    DevOps Institute: Why should enterprises and individuals consider formal DevOps training?

    getITright: Training ensures that all resources in the organization are in sync when implementing new practices like DevOps in an organization and ensures a cohesive approach that facilitates proper organizational buy-in and adoption.

  • The Art of DevOps

    The Art of DevOps

    This is the third in a series of posts on DevOps. The first written by my colleague Lee Reid was titled The Simple Math of DevOps. The second The Calculus of DevOps was written by IBM client, and my friend Carmen DeArdo of Nationwide. Lee introduced mathematically improving delivery throughput by leveraging DevOps to improve Trust. And Carmen used Calculus to imply that the business value of IT can be improved by adopting DevOps to increase the frequency of releases. In my post I would like to visit the art of DevOps , or the art of adopting DevOps by picking up right where Carmen left off – by looking at the culture side of adopting DevOps.

    Lee and Carmen have already alluded to some basic premises behind DevOps as an approach – reducing batch sizeand improving collaboration. These result in reducing complexity, increasing throughput, and improving trust. Let’s talk about how to get there.

    As I have worked with customers adopting DevOps, across company sizes, across industries and countries, there are four common threads that make DevOps adoption successful, leveraging all three aspects of DevOps adoption – culture, process and automation. These are:

    1. Reduce batch size: The most effective way to manage risk and quality, while increasing speed is to reduce the batch size in each iteration or ‘sprint’. This is a mind shift to release smaller, more frequent new versions. Where it is not possible to release new versions that frequently to customers, release small batches to a pre-production area. The deliverable in pre-production is tested and made customer-ready, and then released to the customer at formal release dates. As Lee and Carmen have both discussed, reducing batch size is a pre-requisite to improving both trust and business value.
    2. Shift-left Operational engagement: Get operations engaged right from the beginning of a project/initiative. This has been a core principle of DevOps. Do not leave Ops in a silo that one throws code over the wall to, but have them engaged in the development process, right from requirement inception stage. This allows Ops to have visibility into what is coming from Dev; allowing them to deliver the right production-like environments, as and when needed to Dev and Test teams. It also allows Ops to shift operational concerns left, left into the minds of developers, making them more Ops conscious and engaged in what happens after they hand-off to Ops.
    3. Continuous funding: This is a significant change in an organizations funding model to enable continuous availability and engagement of SMEs and business functions, previously not engaged on a continuous basis – like security, legal, marketing, etc. Carmen in his post mentioned several examples of ‘waiting for…’ work, someone else to do something and environments. Another ‘waiting for’ in enterprises is for funding. Funding is typically provided in a waterfall manner, with specific hard dates (Months, quarters, fiscal year) and gates, not suitable for a Continuous Delivery model. Funding too should be continuous.
    4. Create a ‘Product Management’ team: This team includes a Designer, Development lead, operations lead and an Architect at the minimum (4-in-box). They own the ‘product’ through its entire lifecycle, and beyond transient projects. They are responsible for long-term thinking, design thinking, evolutionary architectural thinking, and overall ownership of the product, from concept to end-of-life.
    5. Setting up a DevOps Center of Excellence (CoE): This center of excellence is not an administrative organization or a ‘tools/enablement group’, but a place where DevOps adoptees come to learn from each other and share expertise and lessons learnt. As organizations adopt and scale DevOps adoption, this CoE also becomes a source of DevOps coaches, helping teams and programs adopt DevOps, and own the organizations DevOps framework – their own flavor of DevOps.

    Adopting DevOps is an art. It is not as simple as hiring a consultant who can show how to improve processes; it is not just buying and adopting tools to automate manual tasks; and it is not going through ‘fall-back-into-the-arms-of-the-person-behind-you’ exercises to build trust. It is a combination of all three – process improvement, organizational and cultural change, and automation with tools to replace manual processes. Adopting these in any enterprise, outside of startups, requires overcoming organizational inertia. By changing culture not by edict, but by showing the need and value of change. By building trust, not through meetings, but with improved communication and transparency. By improving business value, not by measuring mandated KPIs, but by improving organizational agility and throughput. Overcoming organizational inertia, by delivering towards a common goal for the business, irrespective of where in the organization one is, and what role one has. By developing a culture where everyone takes responsibility of delivering value to the business.

    Watch the webcast series hosted by devopsy.kinsta.cloud in partnership with IBM or download a copy of DevOps for Dummies book for more information.

    About the Author/ Sanjeev Sharma

    SanjeevSanjeev Sharma, CTO and Distinguished Engineer – DevOps Technical Sales and Adoption, IBM Cloud Unit, is a 20-year veteran of the software industry with expertise in DevOps, Mobile Development and UX, Lean and Agile Transformation, Application Lifecycle Management and Software Supply Chains. He is a DevOps Thought Leader at IBM and speaks regularly at conferences. He has written several papers and is the author of the DevOps for Dummies book.

     

    Contact Sanjeev on linkedintwitter

  • The Calculus of DevOps

    The Calculus of DevOps

    This is the second in a series of blogs, partnering with Lee Reid, who wrote the first installment “The Simple Math of DevOps” and Sanjeev Sharma both of who are outstanding DevOps Thought Leaders from IBM.

    I am picking up on Lee’s mathematical DevOps model to apply a calculus perspective, a “calculus of DevOps” if you will, (OK, not quite core Big Bang Theory Calculus but rather approaching it from the aspects of engineering queuing theory).

    One of the cultural challenges that DevOps poses is, that some aspects of it run counter to engineering principles that many of us learned with respect to capacity and response time.   When I worked at Bell Labs, we would apply queuing theory to determine how to best package information to be sent across the network. A basic premise revolved around a tradeoff between throughput and response time. On one hand, the more messages that were packed into the packet, the more the payload would improve capacity because the overhead of processing the packet of information would be spread across the messages.   However, waiting to accumulate enough call processing information meant that the packets would be transmitted less frequently, increasing the response time.

    A simple example of this would be making trips to the grocery store. If one wanted to spend the least amount of resources (time, gas, car wear, etc.) on shopping, then one would make less frequent trips and then buy a larger amount of food. So if the Smith family made one trip a month and spent 2 hours, then their average time per week spent on shopping would be 30 minutes.   If the Jones family went every week and spent an hour, then they would be spending twice the time and four times the gas on grocery shopping. However if the Smith family run out of an item (say cereal), they would have to wait, on average 2 weeks before this was replenished. The Jones family average on any item that they ran out of would be 3.5 days in comparison.

    So when the 2014 DevOps report was published[1] which states that areas that deploy more frequently get customer feedback more quickly, that is to be expected. But what’s not expected is that these organizations also have higher productivity.   So exactly what is happening here that seems to be in a basic conflict to the principles of throughput and response time?

    Keeping up with the JONESES

    If we think of a pre- DevOps state for a medium to large enterprise, it may be typical for applications to only be released (deployed into production) a few times a year to provide business functionality. (I assume there are more frequent releases for “unplanned work” like defects and other changes or operational work). For the sake of this discussion, let’s call this the Smith Application. So from a business perspective, the business wants to pack as much work into the Smith releases as possible given they only have a few cracks a year at getting new business functionality into production.

    SMITH APPLICATION CHARACTERISTICS:

    • Deliver Business Value 3 times a year (every 4 months)
    • Cost is C1
    • Business Value (BV) delivered is V1
    • Average time from concept (e.g. Story) being ready to be pulled from the backlog to the time it is delivered to the customer is 2 months plus any additional wait times (e.g. prioritization)
    • BV delivered per year is 3*V1
    • Cost per year is 3*C1

    Now let’s transport over to the Jones Planet where the application is released into production with new business capabilities at the end of every 2 week iteration.   In this case the business is more concerned with providing a constant demand flow into IT than they are with debating over whether a given feature/story is going to be included in this particular release.   Instead there is a constant prioritization (or continuous planning) process that ensures the highest value work is being fed into the IT pipeline.

    JONES APPLICATION CHARACTERISTICS:

    • Deliver Business Value 26 times a year (every 2 weeks)
    • Cost is C2
    • BV delivered is V2
    • Average time from concept (e.g. Story) being ready to be pulled from the backlog to the time it is delivered to the customer is 1 week plus any additional wait times
    • BV delivered per year is 26*V2
    • Cost per year is 26*C2

    Based on the previous engineering analysis, we would expect the following:

    1. SMITH annual cost (3C1) < JONES Annual Cost (26C2)
    2. SMITH annual BV (3V1) > JONES annual BV (26V2)

    So the tradeoff (we would believe) JONES is making by delivering more frequently is that they are spending more money and are delivering less business value on an annual basis.

    However the data from the previously referenced DevOps report is just the opposite. In fact the findings are that enterprises that deploy smaller units of work more frequently have much higher quality and much higher productivity (Capacity). So what’s going on here?

    A NEW PARADIGM

    If you go up to any IT team (even an agile one) and ask them why they don’t deploy business value more frequently, they will generally refer to the following types of wait states of waste that they encounter:

    • Waiting for work (lack of consistent flow)
    • Waiting for somebody else to do something (dependencies from other teams)
    • Waiting for environments (contention)

    One major root cause of this is the dependencies that arise from large enterprises packing a lot of work into infrequent releases. From a planning perspective, the process is elongated due to prioritization discussions because being on the wrong side of the line can mean delay amounting to months, in delivering a product to a customer.   Ask a business portfolio leader what their highest priority is for IT and I am guessing they can tell you in a matter of seconds. However, most large organizations can spend several months a year planning their annual portfolio of work for IT. Some organizations spend more than 50% of their new project build time prior to a single story entering an agile development team’s backlog!

    From a development perspective, packing a lot of work into releases means many more dependencies that have to be managed across initiatives and impacted applications. From a testing perspective, downstream environments (ST, UAT) have to manage much more information in terms of application versions and especially test data that complicate and slow down the process. The complexity of test data increase is proportional to the number of pairwise relationships that exist within the datasets required for testing.   As such, the testing complexity will increase non-linearly (perhaps proportional to the square of the dependent systems) and from a release and change perspective; there is a lot of coordination necessary given how much is being changed at one time.

    All of this work to manage all of the dependencies found in medium to large enterprises completely eliminates any potential savings one might get from batching work into a single delivery. In addition, the possibility of having to pull some work out of a release (due to quality or business readiness or some other reason) sometimes leads to complicated source code management (feature branches in some cases) that further complicate the process of merging frequently into the trunk. These types of practices also serve to drive up technical debt. So looking at the problem from this angle shows why results we are seeing make perfect sense.

    Productivity is inversely proportional to the number of dependencies in a release

    As Lee related to in the initial blog, a lot of an organization’s success depends on trust. And one factor of trust is clarity which speaks to understanding the changes that each release is bringing to the IT and customer environments. So a factor that is working against trust is the notion of delivering more things less frequently and better controlling change somehow, is a good notion.

    Trust is inversely proportional to the number of dependencies in a release

    There is another hidden component of waste associated with “big bang” initiatives. Go back to our grocery example for a moment. Chances are that the Smith monthly excursion results in buying some stuff they end up not using. Perishable items are not spread out very well when they aren’t purchased more frequently. Likewise in IT planning, we tend to put a bunch of stuff in our IT Delivery basket that we don’t know for sure that we will need and we end up with a lot of wasted effort for features that are hardly used or not needed at all. Some enterprise estimates are that 50-65% of what they put into large releases does not actually result in true value to the business. Doing more frequent releases allows a constant discovery process to better guide the usage of IT resources on what is truly of value.

    Waste is proportional to the size of a release.  

    In other words:

    Yield (Value per IT investment) is proportional to the frequency of releases.

    REVISTING THE MATH OF DELIVERY TIME

    So if we revisit Lee’s model

    Lee Reid Blog equationand apply the “Calculus of Release” as we stated above, there are increased costs associated with having larger and less frequent releases in medium/large enterprises.

    • Planning cost TPLAN
    • Development complexity TDESIGN + TDEVELOP + TBUILD
    • Testing Complexity TTEST
    • Release and Change Management Complexity TRELEASE + TDEPLOY + TEVALUATE

    TRUST % – Even if everything was proportional between the JONES and SMITH models, the component of trust that impacts clarity, consistency and collaboration, is much lower for large (SMITH) releases.  Given that TRUST has a multiplicative impact, this alone can account for the results found in the studies.

    CULTURAL CHALLENGE

    While clearly one needs to be sensitive to the changes being introduced into the business, having the ability for the business stakeholders to pull capability when they want it and having it available more frequently is not only good for customers but also has extreme benefits from an IT perspective in terms of increased productivity and reduction of technical debt. The challenge is to convince leaders in both the business and IT areas on the merits of doing more continuous planning and frequent deliveries.   Unicorns may have led the way in this type of thinking but it is actually the horses that will benefit most from this type of culture shift because it is the horses[2] that have the most to gain in mitigating the dependency factor which can undermine quality, productivity and cycle times.

    Read more about the topic in the next blog of this series The Art of DevOps by Sanjeev Sharma.

    [1] “2014 State of DevOps Reports”, Puppet Labs, IT Revolution, https://puppetlabs.com/sites/default/files/2014-state-of-devops-report.pdf

    [2] “The Phoenix Project”, Gene Kim, Kevin Behr, George Spafford, http://www.amazon.com/The-Phoenix-Project-Helping-Business/dp/0988262592

     

    About the Author

    CarmenCarmen DeArdo is the Director of Application Development Tools and Technologies at Nationwide Insurance. Carmen is responsible for driving continuous delivery utilizing DevOps, Lean and Agile techniques across Mobile, Distributed and Mainframe and other technologies. This includes recommendations and implementation of technologies used across the development life cycle (e.g. IBM Rational tool suite, open source technologies).

  • DevOps Sometimes Means Kill It Before Fixing It

    DevOps Sometimes Means Kill It Before Fixing It

    The public attention for DevOps is having a very positive effect on many areas of IT with regard to improving their ability to deliver for the business. Yet, I see little attention being paid to an integral part of this desire to change, which is to assess and baseline the current approach and then strategically select those areas where attention needs to be paid. Alternatively stated, many DevOps efforts are focused on improving current approaches without even determining if the current approach is appropriate for the business.

    In their book, “The Lean Mindset: Ask the Right Questions,” the authors question the focus on productivity as an aspect of implementing lean or agile methods. This comes up quite often in discussion with customers regarding DevOps adoption. There’s a misconception that becoming more productive is the way to fulfill demand from the business. But productivity is not the right question or answer. Regardless how you approach the problem domain lack of infinite resources—money, time and people—the demand will typically exceed the ability to fulfill.

    The way for IT to help the business achieve agility is to deliver the right set of features at the right time, which means the first step has to be looking at what you’re doing today and being willing to stop spending time and effort where there is minimal value or gain. The authors of “The Lean Mindset” have some interesting anecdotes around the realities surrounding this in enterprise settings.

    • Politics – one company decided to financially incent development management to deliver agreed upon features on a behind schedule project even though it meant that testing would suffer and the final product would be unreliable. When later asked if they could have reduced the feature set and delivered fewer high-quality features, the team stated that it could have been done as less than 50% of the features were being used in the final deliverable anyway. The politics of delivering what was agreed upon was more important than delivering fewer high-quality features.
    • Can’t Say No! – many IT executives find it difficult to push back on the business and, hence, end up attempting to deliver all that is already on their plate plus new requests that arise during the year. In many cases, much of what is already on their plate is no longer needed or provides minimal value to the business. Without a system of measurement around cost to deliver versus value delivered, IT cannot justify to the business the need to shift resources elsewhere to ensure optimal value.

    For these reasons, among others, any attempt at DevOps needs to start with an understanding for where resources are being applied today and where they should be applied in the future. Doing useless stuff faster doesn’t help IT and it doesn’t help the business. It’s also why IT/Business alignment is a critical part of any DevOps adoption strategy. IT needs to work with the business in an open manner to select the most important features, capabilities, systems, etc. that will deliver value for the business. This also means IT is responsible for instituting the necessary systems to measure resource consumption and provide the business with the necessary data for them to make intelligent choices about where they want to spend their IT capital.

    There’s a great Peter Drucker quote in the book, “There is nothing quite so useless as doing with great efficiency something that should not be done at all.” So, if your IT Operations team spends six weeks automating deployment for a system that really should have been sunset, that’s six weeks lost that could have been better spent on a more business critical function. Of note, this is not the IT Operations’ fault. If that system is not going to be sunset and has been the bane of their existence consuming time due to outages, then they have driven improvement. The failure is on IT management and the business having not taken the necessary steps to allow these resources to be focused on more important initiatives once again illustrating the importance of executive sponsorship for DevOps initiatives prior to tooling, automation, process improvement or organizational shifts.