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How intelligent software delivery can accelerate digital success

How intelligent software delivery can accelerate digital success

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According to Fernando Mellone, Sales Director at Dynatrace Brazil, as consumers start to seek seamless digital experiences, organizations need to evolve their operations.

According to Fernando Mellone, Sales Director at Dynatrace Brazil

From government to industries, the truth is that demand for digital services is undeniably increasing in all markets, closely linked to changing user expectations. After all, as consumers seek seamless digital experiences, more organizations need to evolve their operations to keep up with this new scenario.

It is not by chance that researchers indicate that the larger global companies expect to invest about US$1.78 trillion in Digital Transformation in 2022, an increase compared to the US$1.31 trillion recorded in 2020.

However, this rapid pace of transformation has increasingly put pressure on development and operations (DevOps) teams to move faster without compromising the quality of service delivered to customers. In this current environment, it is expected from these teams to create and release minor incremental updates to their applications, sometimes with releases several times a day. It is worth remembering that, a few years ago, teams would likely deliver one major update per trimester.

As a result of this growing pressure, we have seen that even large global corporations, including those organizations recognized for the highest standards of digital experiences, are being challenged daily to fight against possible pauses and incidents in systems performance.

Disrupting the delivery of an application today can leave users and entire corporations without access to critical data to deliver value to businesses and end-users.

Therefore, for organizations to innovate without harming the user experience, companies in the digital age must adopt modern and intelligent development practices and solutions that help to mitigate threats, ensuring observability of application performance. With this stance, leaders can reduce risk and unexpected errors, improve code quality and ease the burden on DevOps teams. It is necessary as innovation cycles have become faster and demands have become more urgent.

Recent Dynatrace research indicated that organizations expect the frequency of their software releases to increase by 58% by 2023. But many of these companies will struggle to keep up with this planned pace as DevOps teams are experiencing existing workloads.

As IT complexity increases, the time demands on DevOps teams increase even more. Writing code is only part of the daily battle these professionals face.

On top of this, there is time-consuming manual testing, increasingly fragmented tool configuration and integration chains, and the explosion of data resulting from the move to the cloud. This entire set of tasks certainly adds friction to the development process.

With so much work and no additional resources, the pressure on DevOps teams can force them to sacrifice code quality. As a result, encoding errors are more likely to pass through the network, harming digital services and user experiences. It is a crucial challenge because even the slightest applied changes can bring risks to the performance of the software and the operation as a whole.

It is necessary to find ways to measure the impacts and changes brought by each update and preferably in real-time. It sounds simple, but the truth is that it can be hard to understand the true impact of a new software version until it is released. Worse still, it is often difficult to revert the change when it creates a problem and reverts to a previous, stable version of the application.

Much of this challenge is due to the complexity of multi-cloud environments. Digital services are composed of hundreds of millions of lines of code and billions of dependencies, spanning multiple platforms and different types of infrastructure. This interconnectivity makes it difficult for DevOps teams to understand the consequences of the changes – however small they may seem.

There is also the overhead of alerting, with cloud monitoring tools capturing a volume, velocity and variety of data beyond human ability to manage. It is often impossible for DevOps teams to quickly find the single line of code that triggered an issue.

To prevent low-quality code from reaching production and to ensure seamless user experiences, organizations need a more intelligent approach to software development. It starts with continuous automation to repeatable tasks, which frees DevOps teams to work on higher-value activities.

Combining this observability with AIOps (the use of AI in operations) can take these insights a step further by automatically prioritizing issues according to their business impact. This way, DevOps teams can quickly identify urgent alerts and resolve them before users experience problems.

Improving development practices through AIOps, automation and observability can significantly relieve pressure on DevOps teams and help them keep pace with Digital Transformation. As organizations are releasing software faster, it is increasingly essential to integrate intelligence with continuous, automatic insights across the entire digital services environment. Only then will it be possible to accelerate the transformation and deliver seamless software experiences as customers want.

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