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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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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9 Cloud Security Questions you need to ask Service Providers

Companies in Ireland and the UK who are considering cloud adoption might already have a general idea of the security risks inherent in cloud computing. However, since different providers may not offer the same levels of risk mitigation, it is important to know which providers can give sufficient assurance on cloud security.

Here are 10 cloud security questions to ask service providers vying for your attention.

1. Where will my data be located?

There are a variety of reasons why you will want to ask this question. One big reason is that there are certain countries that don’t have strict legislation (or any legislation at all) pertaining to cloud computing. In that case, the provider won’t be as motivated to apply high levels of risk mitigation.

So if your data is hosted off shore, then you might want to reconsider or at least conduct a deeper study regarding the security conditions there.

2. Do you have provisions for regulatory compliance?

Certain standards and regulations (e.g. PCI DSS and possibly the EU Data Protection Directive) have specific guidelines pertaining to data stored in the cloud. If your organisation is covered by any of these legislation, then you need to know whether your provider can help you meet requirements for compliance.

3. Who will have access to my data?

In a cloud environment, where your data is going to be managed by people who aren’t under your direct supervision, you’ll have to worry as much about internal threats as you would with external threats.

Therefore, you need to know how many individuals will have access to your data. You also need to know relevant information such as how admins and technicians with data access rights are screened prior to getting hired. You also need to determine what access controls are being implemented.

4. How is data segregated?

Since there will be other clients, you will want to know how your data is going to be segregated from theirs. Is there any possibility of an accidental or intentional data breach due to poor data segregation? Find out if your data is going to be encrypted and how strong the encryption algorithm is.

5. How will you support investigative activities?

Sometimes, even if strong cloud security measures are in place, a data breach can still happen. If it does happen, the provider should have ways to track each user/administrator’s activity that can sufficiently support a detailed data forensics investigation.

Find out whether logs are being kept and how detailed they are.

6. Are we protected by a Disaster Recovery/Business Continuity plan? How?

Don’t be fooled by sales talk of 100% up-time. Even the most robust cloud infrastructures can suffer outages too. But the important thing is that, when they do fail, they should be able to get up and running in the soonest time possible.

Don’t just ask about their guaranteed RPOs and RTOs. Find out whether your data and applications will be replicated across multiple sites. Unless the provider says they will be, you need to find a provider with a better infrastructure.

7. Can I get copies of my VMs?

In a cloud infrastructure, your servers are actually in the form of files known as virtual machines (VMs). Because VMs are just files, they should be easily copied. There may be issues though, like the VMs might be stored in a not-so-popular proprietary format. Another possible issue is that the provider may simply not allow copying.

Having copies of your VMs can be useful should you later on decide to transfer to another provider or even duplicate your cloud infrastructure on your own.

8. What will happen to my data when I scale down?

One outstanding benefit of cloud computing is that when your business demands drop, you can easily scale down computing resources and reduce your cloud spending. ?But what will happen to your data when you decommission virtual servers? Will they be discarded?

You might want your data to be retained up to a certain period. On the other hand, you might also want them to be deleted immediately. Ask about the provider’s data deletion/data retention policies and see if they are in line with yours.

9. What will happen to my data if I decide to close my account?

There might come a time when you’ll want to terminate your contract with your cloud provider. Just like in issue #8, you’ll want to find out more about data deletion/data retention policies.

Although some providers can give you detailed answers, many of these answers can include a lot of technical jargon that can leave you totally confused. If you want someone you can trust to:

  • simplify those answers;
  • help you pick the right cloud service provider, and
  • even make sure cloud security is really upheld once your cloud engagement is ?under way

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How to be cleaner and greener indoors

The supply of water on planet earth is finite hence the need to conserve this precious resource. Water is a utility that is often used in and outdoors and for that reason, water conservation activities should be undertaken everywhere.

Get greener everywhere
Water saving can be achieved through various ways. Of utmost importance, fixing leaks should be undertaken in all areas. Small household leaks can add up to gallons of water lost every day. It is therefore important to check all water system fixtures and ensure that there are no leakages.

Greener bathroom habits
Turning off taps- this should be practised in the bathroom especially while shaving and brushing teeth. One could also consider using showers instead of baths since showers use less water and get into the habit of taking shorter showers.

Clean and green dishes
The kitchen is one of the areas where a lot of water is used. Some of the ways through which water can be conserved in the kitchen are:

  • Use of basins when washing dishes by hand
  • Using a dishwasher – when using the dish washer, it is important to make sure it’s fully loaded. Scraping plates instead of rinsing before loading it into the dishwasher will also go a long way in the conservation of the valuable commodity called water

Green your laundry and earn green bucks
The other area where water saving can be made is the laundry room. Washing only full loads of laundry will ensure that your washing machine is running at full efficiency hence you will be able to maximise your washer for energy efficiency. Always ensure you use the appropriate water level or load size selection on the washing machine. All these will not only save water but energy too and since savings are earnings you can smile all the way to the bank where some green bucks will be credited to your account.

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