Testing Your DevOps Is Just as Important as Testing Your Software

ALAN CROUCH | June 18, 2018

article image
Long gone are the days of waterfall software development. The agile movement has brought common-sense software development principles to nearly every corner of the world and changed the way we look at software. This philosophy left marks on how we look at our infrastructure, too. With agile came DevOps and the idea to bring together infrastructure engineers and developers, which has lead to the broad use of infrastructure-as-code tools such as Chef, Puppet, and Ansible as key enablers to making DevOps a reality.

Spotlight

DiCentral

"DiCentral’s services and solutions are singularly focused on B2B integration and used by many of the Fortune 1000, processing over $500 million in transactions for over 30,000 organizations worldwide. The company’s vertical expertise transcends Automotive, Retail, Distribution, Manufacturing, Pharmaceutical, Health Care, Energy and Financial Services. "

OTHER ARTICLES

The Future of Digital Advertising: AI & Advertising

Article | June 24, 2021

The world of digital advertising is witnessing a great change, all thanks to Artificial Intelligence (AI). As AI keeps on advancing, we will see more and more improvements in digital advertising strategies for the companies to get profitable customer insights. The automobile giant, Lexus, is the first company to release an AI-scripted advertisement. According to the report from Variety, IBM Watson was used by Lexus to analyse car and luxury brand campaigns that have received the Cannes Lions award in the category of creativity. However, it was not the only motive of IBM Watson. A wide range of other external information was also analysed with the help of it. This turned out to be a great move as Watson was successful in identifying dataset elements that would relate to customers on emotional levels. What was behind this achievement? Of course, AI. But there was even a bigger message — AI is the future of advertising. Today, there are multiple commercially available platforms that can generate advertisements without the involvement of humans. But, AI is not just about creating ads. It has the power to transform every single possible thing in the advertising industry in 2021 and beyond, be it ad buying or even audience targeting. Don't be surprised to read every content throughout your day that is written by AI in the coming years. Luckily for writers like me, our industry is not there yet. As we have just stepped into a whole new decade, it’s a good moment to think about the future of advertising where AI will play a vital role. So without further ado, let’s get into it! The Future Of Advertising Has Already Begun Just like any other marketers or businesses, we always try to predict or guess what the future of advertising holds for us. Yes, there certainly are some known things and some unknown ones. However, we still can discuss how it can be considering all the potential changes and variables. The major reason behind this is, the future of advertising has already begun a few years back. How? Well, most of the futuristic trends of the advertising world have already kicked off. Especially those trends that are going to be the hot buzz in the coming decade. But here lies one important question, which of these trends will impact the future of advertising the most? And, what does AI have to do with this? Well…if you closely look at the current advertising trends, AI-powered sophisticated delivery systems are behind most online ads. Such systems are capable of placing ads in front of millions of internet users at the same time. The best thing — the coordination between the ads and the internet users occurs in real-time. And, it is ridiculously automatic. The theoretical term for this kind of advertising is programmatic advertising. With this tech, artificial intelligence is used to profile visitors to apps or websites. Using this information, the targets are fixed and then ads are delivered. This becomes possible because of a modern ad supply chain that involves a complex network of services and platforms that have a different role to play at each stage. Nowadays, the ad industry is being dominated by this type of AI-powered programmatic advertising. If we look at the predictions forwarded by eMarketer, more than 86 per cent of the display ads in the United States will be in front of the people because of automated channels. In fact, programmatic advertising is used in every 8 out of 10 mobile display ads. Furthermore, we all see recommended products on Google and Facebook, don't we? How are these ads powered? Yes, you guessed it right, that’s AI. The stats are even more surprising — these firms captured around 90% of the advertising business back in 2017. AI has made it extremely simple for brands to advertise online at scale. And, this is just the beginning. AI goes much further than just scaling when it comes to the future of advertising. The current cut-throat competition has made it difficult for brands to create and deliver more relevant, more personalised, and more contextual ads to specific customer preferences. As a result, AI is the only way to fulfil this need. And ultimately, this fact holds a lot of implications for the future of advertising. How AI Can Improve The Digital Advertising Trends It is human psychology to personalize messages in face-to-face or one-on-one contexts. This happens with the people we already know. For example, we communicate with a family member, a friend, or a coworker keeping their possible response in mind. We know them and eventually have an idea about their preferences, desires, and behaviours. But when it is about tailoring and personalizing messages at scale, there is a need for contextual data on thousands of consumers. In such a case, we need to have the customer information so that we can analyse it and then develop the right communication of each of them. Humans do not have the required intellectual bandwidth, resources, and time for this enormous task. But thankfully, AI has that all. No wonder that more and more businesses are counting on AI for ad creation at scale. Even though this is just the beginning of the AI era, it has already started impacting many advertisers out there. For instance, AI can overrule all the advertising decisions made by your corporate team even if they have spent a significant amount of time and money to create them. To know this better, suppose you have created an ad on Facebook. The algorithm powered by AI analyses your ad and determines its relevance score. The delivery of your ad depends on the relevance score and it decides how effectively your ad is displayed in front of more and more customers. if your ad is less relevant to user needs or they don't just like your ad, the relevance score will be less. A machine is responsible for deciding the relevance score of your ad and it has nothing to do with any creative and strategic decisions your team has made. What does this mean? Your business may not have to depend solely on humans to develop creative and strategic advertising decisions. You can imagine how AI can reduce the time and costs of advertising by effectively advertising on social media. In essence, it reduces your advertising budget to nearly half with effective email advertising and mobile advertising strategies. To summarise this all, AI is going to change the entire advertising industry including all the elements in advertising processes. It is about to bring infinite opportunities for businesses in terms of precise analytics, content creation, semantic targeting, user experience improvement, and much much more. Conclusion As advertisers want to optimize huge amounts of data to create better ad campaigns and drive more impact, the popularity of Artificial Intelligence continues to increase. Before AI, businesses struggled to measure the effectiveness of their ad campaigns and determine where to allocate the budget. AI-powered advertising affects not only the media spend but also creativity, analytics, and planning. Therefore, the future of advertising with AI is inevitable to target the right audience, offer more personalised experiences, make better decisions faster, and ultimately improve the returns of your investment. The future of advertising will show us how the automation mechanism can dominate the marketing and sales domains, and help companies to save more resources while driving more value to their consumers in the long run. FAQs How Is AI Used in Advertising? Currently, there are a few main use cases of AI in advertising. Marketers and businesses are deploying AI-powered systems across channels and platforms. They include the following: ● Budget optimization and targeting ● Ad creation ● Ad management ● Ad platforms Programmatic advertisements use AI and Machine Learning (ML) to regulate both sales and purchase using real-time factors. It includes almost all the ad exchange, party networks, and even platforms such as Instagram, Facebook, and Snapchat. What Role Will Artificial Intelligence Play in The Advertising World? AI is all about developing intelligent machines that can solve questions. As businesses continue to add newer customer touchpoints, the amount of data they are collecting from their consumers is going to be unimaginably huge in the future. Managing this amount of data is not humanly possible. And that’s where AI comes into play. How Does AI Affect Marketing? AI is certainly reshaping customer-facing services for businesses, advertisers, and marketers. It does so by improving efficiency and optimizing user experience. By reducing the resources, AI is eventually causing improved ROI and affecting businesses in terms of every aspect such as ad creations, ad management, advertising budgets, planning, implementations, and whatnot. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How Is AI Used in Advertising?", "acceptedAnswer": { "@type": "Answer", "text": "Currently, there are a few main use cases of AI in advertising. Marketers and businesses are deploying AI-powered systems across channels and platforms. They include the following: Budget optimization and targeting Ad creation Ad management Ad platforms Programmatic advertisements use AI and Machine Learning (ML) to regulate both sales and purchase using real-time factors. It includes almost all the ad exchange, party networks, and even platforms such as Instagram, Facebook, and Snapchat." } },{ "@type": "Question", "name": "What Role Will Artificial Intelligence Play in The Advertising World?", "acceptedAnswer": { "@type": "Answer", "text": "AI is all about developing intelligent machines that can solve questions. As businesses continue to add newer customer touchpoints, the amount of data they are collecting from their consumers is going to be unimaginably huge in the future. Managing this amount of data is not humanly possible. And that’s where AI comes into play." } },{ "@type": "Question", "name": "How Does AI Affect Marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI is certainly reshaping customer-facing services for businesses, advertisers, and marketers. It does so by improving efficiency and optimizing user experience. By reducing the resources, AI is eventually causing improved ROI and affecting businesses in terms of every aspect such as ad creations, ad management, advertising budgets, planning, implementations, and what not." } }] }

Read More

TOP 10 EMERGING PROGRAMMING LANGUAGES IN 2020

Article | February 15, 2020

Programming languages such as C, C++, Java and PHP have been used by programmers for many years now, and software companies are often on the lookout for programmers who are well versed with these programming languages. However, with time as the demand has increased for high-level programming languages, a number of new languages have emerged to make it big in the programming languages space. In this article, we have listed down the top ten emerging programming languages of 2020 that can come handy for programmers.

Read More

A Guide to Technical Debt Management

Article | July 27, 2021

In the ‘new normal’ world, digitalization is the core reason to drive businesses to success. As a result, these emerging technologies have given rise to technical debt. Of course, technical debt has always been a part of every IT and non-IT organization. But the evolution of the IT world has made companies invest more time to think about reducing tech debt. As the term consists of the word- debt, it gives a picture of being negative. Thus, technical debt is more or less like financial debt, but it also has good aspects. In this article, we will talk all about technical debt management and ways to deal with it. What Is Technical Debt? When a code design is not neat, has disjointed data structures, and is of poor quality, it gives rise to technical debt. If a code is designed in a hurry to meet strict deadlines, it may be written clumsily. For that particular period, the software may work perfectly well, but it starts bugging and stops working with time. And it becomes a difficult task to decode the coding and understand the problem as the code was not written neatly. The accumulation of work due to short-term decisions, unrealistic deadlines, shortage of resources, or just ‘lazy work’ leads to technical debt. Every organization has technical debt. Take note that this debt can never be zero. But the important part is to deal with technical debt management. It cannot be ‘paid off’ entirely but can be minimized and managed. Types of Technical Debt Various reasons lead to technical debt. Some are deliberate, and some are accidental. Whatever is the reason, if you notice any of the below actions implemented in your organization, consider it as a red flag. Then, identify the reasons for technical debt for precise technical debt management. Complex Architecture This is one primary reason that leads to technical debt. Of course, the coding should be precise and straightforward. But sometimes, due to limited time and resources, a complex architecture is created even for the simplest code. And if not mended with time, this leads to various problems along with technical debt. Thus complexity in products, processes, and applications should be simplified with time. Software Entropy This is also known as bit-rot. Software entropy occurs when developers write codes for the updates of the same software. As a result, the coding gains maximum complexity. And after a point, it gets unsolvable. Thus the software quality deteriorates, leading to errors and reduced usability. The solution to this is refactoring, which we will discuss later in the article. Accidental Tech Debt This type of tech debt occurs when there is sudden evolution in technology. For example, if the code was simple and precise but not meant to be adapted or updated with the changing scenario, accidental technical debt occurs. It leads to a wastage of time and resources in the future. Thus, this debt is resolved by dedicating time to update the code and system quickly. Ways to Handle Technical Debt Management When the engineering or developer’s team takes shortcuts to meet deadlines or finish the project early, it leads to more work in the long run. We understand that sometimes these demands are unavoidable, but the team needs to come back and resolve the issues to save the organization from technical debt. For starters, an organization must identify the causes of technical debt and deal with them accordingly. Here are some of the ways of technical debt management and how to manage them in the future. Identify the Source The best way to avoid and tackle technical debt is to identify the source. This can be done by having a conversation with the team as to why this debt occurred? For example, if the IT team was asked to design healthcare software within two months due to the project's urgency, the team will say that the reason for complex coding was the time constraints. As a result, you are identifying technical debt sources. They may have occurred due to time, resources, or system constraints. Once you identify the root cause, there is always a way to go back and solve the issue to avoid getting buried in technical debt. This is the first step towards technical debt management. Track Technical Debt You will be appalled to know that 7% of organizations track technical debt to minimize them. And they are a significant success. Tracking technical debt is as important as identifying it. When a team keeps track of technical debt, it is easy for them to forecast the time and resources required to pay it off. Digital Documentation This is building a roadmap while writing code. It makes sure that the entire team is on the same page while developing the software. The benefit of this documentation is that whenever there is an update or an error wherein the entire code requires to be reworked, it gets easier for any developer to work on it. This is a precise way to prevent the tech-debt burden. Maintain Agility & Testing This technique is paving the way for technical debt management. However, developing agile software and maintaining its agility through time are two different things. To reduce the technical debt, you need to maintain software agility by updating it on a timely basis. But be sure to make this update process clean and qualitative. Try not to skip testing of the software for whatsoever reasons. Testing of the software is essential to stop the build-up of technical debt. However, do not substitute manual testing for automated testing. It can prove to be a significant hurdle in the team’s agile process. Refactoring Dedicate time to understand and pay off technical debt. Even when you avoid errors and follow all the suitable approaches, there are chances of technical debt. Sometimes these may happen due to the client’s urgent demands or limited bandwidth to perform tasks. Whenever this happens, take out time and treat technical debt as a business problem and not a technical one. This is an intelligent way of handling technical debt management. Refactoring means going back to the developed codes in haste for many reasons and cleansing them. This does not affect the external working of the code but cleans the code and makes it future-ready. Furthermore, such timely cleaning of codes reduces technical debt significantly. How Is Technical Debt Good? Technical debt is not always bad. Sometimes the code building is done in haste and works precisely the way it should. The updating of codes is also seamless. At such times technical debt is regarded as a good thing. This usually happens in applications that have simple processes. Technical debt is also good in software that requires timely development and not bug fixes. The Conclusion Technical debt is required to stay ahead in the competition. But see to it that it is tackled and minimized in the best possible way. Procrastination is the enemy of success. And this is highly true in the case of technical debt. It will get more expensive the longer you hold it. So ensure that your team takes out regular time from their schedule for minimizing technical debt. Technical debt management will help your team to perform better, improve agility and deliver exceptional results. Frequently Asked Questions What drives tech debt? Tech debt occurs when the team cannot write a clean code due to deadlines or limited resources. The tech debt worsens if the team does not go back and dedicate time to clean the code. How do you handle tech debt? There are specific ways to handle technical debt. These include: Identifying the reasons that led to technical debt Integrate metrics in your strategy Digital documentation Refactoring Knowing that tech debt is not always bad What are the types of technical debt? There are majorly three main types of technical debt. Deliberate creation of complex software Software entropy Accidental tech debt { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What drives tech debt?", "acceptedAnswer": { "@type": "Answer", "text": "Tech debt occurs when the team cannot write a clean code due to deadlines or limited resources. The tech debt worsens if the team does not go back and dedicate time to clean the code." } },{ "@type": "Question", "name": "How do you handle tech debt?", "acceptedAnswer": { "@type": "Answer", "text": "There are specific ways to handle technical debt. These include: Identifying the reasons that led to technical debt Integrate metrics in your strategy Digital documentation Refactoring Knowing that tech debt is not always bad" } },{ "@type": "Question", "name": "What are the types of technical debt?", "acceptedAnswer": { "@type": "Answer", "text": "There are majorly three main types of technical debt. Deliberate creation of complex software Software entropy Accidental tech debt" } }] }

Read More

Create a Cloud Migration Strategy with IT Infrastructure Monitoring

Article | July 23, 2020

The rapid pivot towards a remote workforce is forcing organizations to adopt a cloud-first approach faster than ever. We recently surveyed 500 IT decision-makers around the globe to ascertain their views on IT automation, cloud migration, and business continuity in the face of unexpected crises. The survey found that 87% of IT professionals agree that the current COVID-19 pandemic will cause organizations to accelerate their migration to the cloud.

Read More

Spotlight

DiCentral

"DiCentral’s services and solutions are singularly focused on B2B integration and used by many of the Fortune 1000, processing over $500 million in transactions for over 30,000 organizations worldwide. The company’s vertical expertise transcends Automotive, Retail, Distribution, Manufacturing, Pharmaceutical, Health Care, Energy and Financial Services. "

Events