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?.

imgd2.jpg

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)

Contact Us

  • (+353)(0)1-443-3807 – IRL
  • (+44)(0)20-7193-9751 – UK

Check our similar posts

Saving Energy Step 2 ? More Practical Ideas

In my previous blog, we wrote about implementing a management system. This boils down to sharing a common vision up and down and across the organisation, measuring progress, and pinning accountability on individuals. This time, we would like to talk about simple things that organisations can do to shrink their carbon footprints. But first let’s talk about the things that hold us back.

When we take on new clients we sometimes find that they are baffled by what I call energy industry-speak. We blame this partly on government. We understand they need clear definitions in their regulations. It’s just a pity they don’t use ordinary English when they put their ideas across in public forums.

Consultants sometimes seem to take advantage of these terms, when they roll words like audit, assessment, diagnostic, examination, survey and review across their pages. Dare we suggest they are trying to confuse with jargon? We created ecoVaro to demystify the energy business. Our goal is to convert data into formats business people understand. As promised, here are five easy things your staff could do without even going off on training.

  1. Right-size equipment? outsource peak production in busy periods, rather than wasting energy on a system that is running at half capacity mostly.
  2. Re-Install equipment to OEM specifications ? individual pieces of equipment need accurate interfacing with larger systems, to ensure that every ounce of energy delivers on its promise.
  3. Maintain to specification ? make sure machine tools are within limits, and that equipment is well-lubricated, optimally adjusted and running smoothly.
  4. Adjust HVAC to demand ? Engineers design heating and ventilation systems to cope with maximum requirements, and not all are set up to adapt to quieter periods. Try turning off a few units and see what happens.
  5. Recover Heat ? Heat around machines is energy wasted. Find creative ways to recycle it. If you can’t, then insulate the equipment from the rest of the work space, and spend less money cooling the place down.

Well that wasn’t rocket science, was it? There are many more things that we can do to streamline energy use, and coax our profits up. This is as true in a factory as in the office and at home. The power we use is largely non-renewable. Small savings help, and banknotes pile up quickly.

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.

Contact Us

  • (+353)(0)1-443-3807 – IRL
  • (+44)(0)20-7193-9751 – UK
Failure Mode and Effects Analysis

 

Any business in the manufacturing industry would know that anything can happen in the development stages of the product. And while you can certainly learn from each of these failures and improve the process the next time around, doing so would entail a lot of time and money.
A widely-used procedure in operations management utilised to identify and analyse potential reliability problems while still in the early stages of production is the Failure Mode and Effects Analysis (FMEA).

FMEAs help us focus on and understand the impact of possible process or product risks.

The FMEA method for quality is based largely on the traditional practice of achieving product reliability through comprehensive testing and using techniques such as probabilistic reliability modelling. To give us a better understanding of the process, let’s break it down to its two basic components ? the failure mode and the effects analysis.

Failure mode is defined as the means by which something may fail. It essentially answers the question “What could go wrong?” Failure modes are the potential flaws in a process or product that could have an impact on the end user – the customer.

Effects analysis, on the other hand, is the process by which the consequences of these failures are studied.

With the two aspects taken together, the FMEA can help:

  • Discover the possible risks that can come with a product or process;
  • Plan out courses of action to counter these risks, particularly, those with the highest potential impact; and
  • Monitor the action plan results, with emphasis on how risk was reduced.

Find out more about our Quality Assurance services in the following pages:

Ready to work with Denizon?

Contact Us Today