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Difference between Agile and DevOps

DevOps is a hot topic that has been circulating in the industry for a long period. Despite its popularity, there is mounting concern about how it differs from Agile. What could be worse? The Agile and DevOps discussion is a never-ending one in the information technology industry.

Are you an ambitious engineer interested in learning all about DevOps and Agile?. If you want to learn how they differ and preferable, then stick around until the end of this ‘Agile vs. DevOps’ article, where I will share detailed information about both methodologies.

We will discuss the two methodologies in this article, as well as the differences between these two.

Agile Vs DevOps in Software Development
Agile Vs DevOps

What is Agile?

Agile is a project management style that emphasizes the continuous delivery of small, manageable project increments. It is done through iterative development and testing. It was created to replace the conventional waterfall technique, which is recognized for its organized, linear, and sequential life cycle.

Agile facilitates the day-to-day management of complex projects by enhancing communication and cooperation between team members and clients.

What is DevOps?

DevOps is a methodology of software development in which the development team collaborates with the operations team to increase cooperation and efficiency. Additionally, the process requires integrating DevOps ideas and strategies and testing using a set of DevOps tools.

Site Reliability Engineering is the next phase of DevOps implementation. DevOps is a concept that may be implemented in a variety of ways. SRE is much more rigid in terms of the way of doing things and what the team’s clear goals are; particularly, the objective is to maintain the site’s reliability and availability, and to prioritize the activities that contribute to achieve the goal.

The key aspect to remember is that DevOps is not a substitute for Agile! Does it sound incorrect? No, Agile is not on the verge of extinction. However, is DevOps superior? Yes, this is an advancement.

Agile vs. DevOps

Let’s begin by learning about the similarities and differences between the two methodologies. They are not the same, despite their similarities, and some may claim that one is better than other. Therefore, it is critical to know the exact details to clear this uncertainty.

How Agile and DevOps are similar?

How are both methodologies similar if they follow the different methods? Doesn’t it sound wrong? The answer is yes they have some similarities.

Both methodologies depend upon rapid software development. Moreover, their ideas support rapid growth without compromising the client or the processes.

Both emphasize efficiency, effectiveness, and quality across the software development lifecycle. Additionally, they prioritize shorter release cycles.

Both techniques place a greater emphasis on automation and cooperation. When you use Agile or DevOps methodologies, risk tends to decrease with time. On the other hand, risk tends to grow when other techniques, such as Waterfall, are used.

What are the differences between Agile and DevOps?

How Agile differ from DevOps? While both systems promote cooperation to increase speed and efficiency, they vary significantly regarding achieving the target. Before I talk about the technical differences, I want to set the context straight. Hence, I will be talking about a few technical differences which you should be aware of.  The following are some crucial differences in the Agile vs. DevOps debate.

Procedure

The difference between DevOps and Agile methodologies is how specific tasks are completed. Agile ensures regular communication between teams and clients while DevOps emphasizes testing and delivery. Communication between developers and IT operations is predominantly between programmers and IT operators. Additionally, the Agile approach is a better fit for complex projects, while the DevOps technique is more adapted for end-to-end procedures.

Teams 

The organizational structure of the teams is one of the major differences between DevOps and Agile. For instance, bigger teams often use DevOps, with the skill set shared across operations and development team members. It implies that each team member will be responsible for completing a particular job or task at each step of the process. On the other hand, agile is better suited for smaller teams that need to accomplish work quickly. Typically, the Agile methodology does not assign particular tasks to team members but instead encourages everyone to share responsibility equally. As a result, all Agile team members should be capable of managing or delegating any aspect of a project at any point in time.

Tools 

Agile and DevOps methodologies also use a variety of tools, depending on the nature of the project. Kanboard and Jira project management software and Bugzilla server software are popular Agile project management solutions. While DevOps utilizes Amazon Web Services cloud computing, Puppet automation software, TeamCity servers, OpenStack software, and Chef infrastructure.

Attention and Feedback

Agile and DevOps also have significant differences in terms of focus and feedback. While DevOps initiatives prioritize operational and business readiness and get feedback from internal team members, an Agile approach often receives input directly from customers.

In addition, agile teams often use sprints to keep focus, with each sprint lasting shorter than a month. Agile teams design sprints to ensure that available tasks are accomplished in manageable chunks, with the next sprint beginning just after the previous sprint is made.

With DevOps, specific deadlines and standards must be met, some of which might occur daily.

DevOpsAgile
Self EvaluationCustomer Feedback
Shorter release cycles, instant feedbackSmaller release cycles
Emphasis on efficiency and automationEmphasis on speed
Business-friendlyNot optimal for business

Conclusion

To conclude, both methodologies strive to provide high-quality software on schedule. The contrast between agile and DevOps is that agile emphasizes the optimization of the development lifecycle, while DevOps unifies development and operations in a continuous integration/continuous delivery environment.

Agile and DevOps do not have to be mutually independent. Any firm undergoing a DevOps transformation should not quit its current agile operations. DevOps is an extension of agile that focuses on techniques that are not central to agile. Hence, these methods enhance software development and result in higher-quality products.

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AI Powering Advertising

AI for Advertising or Marketing Content Intelligence

AI Powering Advertising Content Insights

Curse of Bad Decision-Making?

Decision-making is a part of our existence. Every day we need to make decisions that may have good or bad results. Moreover, people have different ways of coming up with their decisions. Some base their decisions on emotions while others apply critical thinking. Interestingly, you can use AI to automate and optimize decision-making.

Bad decisions prevail in the business world. Do you know MySpace.? It was the most popular social networking platform around the year 2000. Today, however, we’re just living in the shadow of its past. Dagogo Altraide explained in his YouTube channel ColdFusion the reasons why MySpace.com failed and declined as once a growing social networking site. Altraide said that MySpace executives made the wrong decisions. This involves ineffective content strategy, bad user experience, and outdated technology.

The case of MySpace perhaps confirms the fact that humans are prone to errors. Even intelligent people tend to make the wrong decisions. For example, advertisers and marketers may commit mistakes in their campaigns. Let’s say those simple errors in calculating ad costs can have the worst consequences. They may end up investing money in ad content that only drain their budget. So, does this mean we’re under the curse of bad decision-making? Is it difficult for us to make the right decisions due to our limitations as human beings? 

AI as a Valuable Solution

Our limited knowledge, skills, and experiences can cause lapses in our judgment. That’s a reality we have to deal with. Yet, we have gifts that enable us to make the right decisions and solve our problems in smart ways. One of them is the capability to create technological advances. This is where AI comes in. AI is a data science discipline that blurs the line between humans and machines. 

With AI, experts build machines that mimic how humans process data and perform tasks. Thus, they create machines that think and function like ordinary humans. Such technologies act on information and function with little or no intervention from humans. This is done using machine learning algorithms, which are sets of procedures and computations used to guide machines on what to do and how to do them. In addition, the machines can learn and improve on their own as they gain new experiences and face different situations. 

What’s the relationship between AI and decision-making? It means we can make the best decisions without being mentally and physically exhausted. AI allows brand owners, marketers, and advertisers to pass data management to AI machines and tools. In particular, they can come up with ideas from information about their ad content. 

AI-Powered Ad Insights

Leading cloud providers like Amazon added AI to some of their services and apps. In fact, it provides AI solutions that help users enhance their ad campaigns. Amazon Web Services offers a service called Amazon Comprehend. This service applies NLP or Natural Language Processing to understand the meanings hidden in texts.  

With Natural Language Processing, AI tools let you know how your ad content affects people. For instance, if you serve ad content on social media, you’ll know what users think and feel about the content. The AI technologies extract information found in posts and comments. They analyze the information to reveal the true meanings of the words used by users. Thus, you’ll see whether or not people on social media are happy with your ad content and the business as a whole.

These AI technologies also enable you to measure user engagement. Thus, you can monitor and assess all important metrics you need about how users are interacting with your ad content. That depends on the specific goals of your campaigns. You’ll determine the exact number of views, likes, mentions, shares, clicks, conversions, sales, and revenues for a certain ad content at any time

Unlocked Customer Behavior

AI technologies allow you to deliver ad content suitable for your audiences. They let you keep track of the complete customer journey. You can discover key information about your customers. Their needs, interests, and preferences are all unlocked. One great thing with AI is that it can be used to make accurate predictions out of previous and current data.

Known as predictive analytics, this AI feature lets you have an idea of how well customers will engage with your ad content. Based on historical data on customer behavior, you’ll find out what possible decisions and actions they’ll make. Let’s say you know that some of them are interested in certain types of ad content. 

Furthermore, they might have visited particular marketing channels or searched for products using certain keywords. As a result, you’ll serve the right ad content to the right customers on the right channels. Other than this, you can personalize your content to suit customers’ needs. Therefore. this increases the chance that people will convert or buy your products.

Intelligent Ad Spending

For obvious reasons, money is a primary consideration in making important business decisions. In other words., if you want to grow your business, you need to reduce your expenses and increase your profits. Let’s go back to the case of MySpace. The company actually tried to save itself from its demise. Along the way, the new shareholders and executives of the company used a new content strategy. They allowed music and news to be published on the social networking site, but that didn’t work. They failed to get traffic back, as Facebook began to attract more users. The budget for the new strategy, therefore, was spent in vain. 

Through AI, you can avoid suffering the same fate as MySpace. AI is used in programmatic ad buying as well. If you run ads on ad platforms, you can bid for ad spaces and contents based on specific factors. These can be the location of prospects, intentions, and personas of buyers. and past product/service purchases. You’ll prevent wasting money while ensuring that you can reach your target audiences. 

Moreover, AI allows you to adjust your marketing budgets and spends depending on performance. In an automated manner, you can increase the amount of money you allocate to ad channels and contents that deliver better results. When the ad content doesn’t hit your engagement, conversion, and sales goals, you can cut down your budget for it.

Making Smarter Decisions on Ad Content Through AI”

AI is an invention that extends humans’ thinking abilities to machines. Indeed, it gives us the opportunity to make the right decisions in our business or personal lives, in spite of our susceptibility to mistakes. Through AI, we can obtain valuable insights into advertising content. We can discover and explore underlying social sentiments, customer behaviors, and spending patterns as we serve ad content on various channels.

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