How DevOps oils the Value Chain

DevOps ? a clipped compound of development and operations – is a way of working whereby software developers are in a team with project beneficiaries. A client centred approach extends the project plan to include the life cycle of the product or service, for which the software is developed.

We can then no longer speak of a software project for say Joe?s Accounting App. The software has no intrinsic value of its own. It follows that the software engineers are building an accounting app product. This is a small, crucially important distinction, because they are no longer in a silo with different business interests.

To take the analogy further, the developers are no longer contractors possibly trying to stretch out the process. They are members of Joe?s accounting company, and they are just as keen to get to market fast as Joe is to start earning income. DevOps uses this synergy to achieve the overarching business goal.

A Brief Introduction to OpsDev

You can skip this section if you already read this article. If not then you need to know that DevOps is a culture, not a working method. The three ?members? are the software developers, the beneficiaries, and a quality control mechanism. The developers break their task into smaller chunks instead of releasing the code to quality control as a single batch. As a result, the review process happens contiguously along these simplified lines.

Code QC Test ? ? ?
? Code QC Test ? ?
? ? Code QC Test ?
? ? ? Code QC Test
Colour Key Developers Quality Control Beneficiary

This is a marked improvement over the previously cumbersome method below.

Write the Code ? Test the Code ? Use the Code
? Evaluate, Schedule for Next Review ?

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

The Key Role that Application Program Interfaces Play

Application Program Interfaces, or API?s for short, are building blocks for software applications. Using proprietary software-bridges speeds this process up. A good example would be the PayPal applications that we find on so many websites today. API?s are not just for commercial sites, and they can reduce costs and improve efficiency considerably.

The following diagram courtesy of TIBCO illustrates how second-party applications integrate with PayPal architecture via an API fa?ade.

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

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The DevOps Revolution Continues ?

We close with some important insights from an interview with Jim Stoneham. He was general manager of the Yahoo Communities business unit, at the time Flickr became a part. ?Flickr was a codebase,? Jim recalls, ?that evolved to operate at high scale over 7 years – and continuing to scale while adding and refining features was no small challenge. During this transition, it was a huge advantage that there was such an integrated dev and ops team?

The ?maturity model? as engineers refer to DevOps status currently, enables developers to learn faster, and deploy upgrades ahead of their competitors. This means the client reaches and exceeds break-even sooner. DevOps lubricates the value chain so companies add value to a product faster. One reason it worked so well with Flickr, was the immense trust between Dev and Ops, and that is a lesson we should learn.

?We transformed from a team of employees to a team of owners. When you move at that speed, and are looking at the numbers and the results daily, your investment level radically changes. This just can’t happen in teams that release quarterly, and it’s difficult even with monthly cycles.? (Jim Stoneham)

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Why Executives Fail & How to Avoid It

The ?Peter Principle? concerning why managers fail derives from a broader theory that anything that works under progressively more demanding circumstances will eventually reach its breaking point and fail. The Spanish philosopher Jos? Ortega y Gasset, who was decidedly anti-establishment added, “All public employees should be demoted to their immediately lower level, as they have been promoted until turning incompetent”.

The Peter Principle is an observation, not a panacea for avoiding it. In his book The Peter Principle Laurence J. Peter observes, “In a hierarchy every employee tends to rise to his level of incompetence … in time every post tends to be occupied by an employee who is incompetent to carry out its duties … Work is accomplished by those employees who have not yet reached their level of incompetence.”

Let’s find out what the drivers are behind a phenomenon that may be costing the economy grievously, what the warning signs are and how to try to avoid getting into the mess in the first place.

Drivers Supporting the Peter Principle

As early as 2009 Eva Rykrsmith made a valuable contribution in her blog 10 Reasons for Executive Failure when she observed that ?derailed executives? often find themselves facing similar problems following promotion to the next level:

The Two Precursors

  • They fail to establish effective relationships with their new peer group. This could be because the new member, the existing group, or both, are unable to adapt to the new arrangement.
  • They fail to build, and lead their own team. This could again be because they or their subordinates are unable to adapt to the new situation. There may be people in the team who thought the promotion was theirs.

The Two Outcomes

  • They are unable to adapt to the transition. They find themselves isolated from support groups that would otherwise have sustained them in their new role. Stress may cause errors of judgement and ineffective collaboration.
  • They fail to meet business objectives,?but blame their mediocre performance on critical touch points in the organization. They are unable to face reality. Either they resign, or they face constructive dismissal.

The Warning Signs of Failure

Eva Rykrsmith suggests a number of indicators that an individual is not coping with their demanding new role. Early signs may include:

  • Lagging energy and enthusiasm as if something deflated their ego
  • No clear vision to give to subordinates, a hands-off management style
  • Poor decision-making due to isolation from their teams? ideas and knowledge
  • A state akin to depression and acceptance of own mediocre performance

How to Avoid a ?Peter? in Your Organization

  • Use succession planning to identify and nurture people to fill key leadership roles in the future. Allocate them challenging projects, put them in think tanks with senior employees, find mentors for them, and provide management training early on. When their own manager is away, appoint them in an acting role. Ask for feedback from all concerned. If this is not positive, perhaps you are looking at an exceptional specialist, and not a manager, after all.
  • Consider the future, and not the past when interviewing for a senior management position. Ask about their vision for their part of the organization. How would they go about achieving it? What would the roles be of their subordinates in this? Ask yourself one very simple question; do they look like an executive, or are you thinking of rewarding loyalty.
  • How to Avoid Becoming a ?Peter??Perhaps you are considering an offer of promotion, or applying for an executive job. Becoming a ?Peter? at a senior level is an uncomfortable experience. It has cost the careers of many senior executives dearly. We all have our level of competence where we enjoy performing well. It would be pity to let blind ambition rob us of this, without asking thoughtful questions first. Executives fail when they over-reach themselves, it is not a matter of bad luck.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

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