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The Power of Deep Code Insights

Jina Na
AppDynamics

The rise of technologies like cloud computing and automated delivery pipelines has enabled teams to deliver software at breakneck speed. In fact, top tech companies deploy software hundreds, even thousands of times per day, raising the bar for digital services. To stay competitive, organizations in every industry must match the pace of innovation set by these digital-native companies.

However, it's challenging to maintain heterogeneous applications and ensure that service is not only available, but also delighting users and driving business outcomes. From the front-end experience to back-end architecture, a web of third-party services, legacy data centers and a distributed, multi cloud infrastructure are supporting the application.

If you're unable to effectively manage these complex application environments, your business is impacted — an outage leads to poor user experience which leads to lost business and impact to your organizational productivity and resources. Take for instance what recently happened with the Iowa caucus app. Coding issues led to significant delays in counting and reporting important primary results, which led other states, such as Nevada, to pull two previously developed apps for their own primary elections, losing out on tens of thousands of dollars.

This example shows that while deployment velocity has increased exponentially, traditional approaches to troubleshooting fall short when it comes to equipping developers (and IT teams) with enough information to pinpoint the root cause of application code issues.

In fact, according to Stripe Research, developers spend roughly 17.3 hours each week debugging, refactoring and modifying bad code — valuable time that could be spent writing more code, shipping better products and innovating. The bottom line? Nearly $300B (US) in lost developer productivity every year.

What happened in Iowa is just one example of how developers are often blamed for code level issues, issues that with the right level of insight could reveal what's causing a bug in production before impacting the digital experience for customers.

So what's the solution and what opportunities would developers suddenly benefit from if they spent more time writing code and less time debugging?

The Aha Moments — What Code Level Insights Bring to Life

The job of a developer is never ending given business priorities and product roadmaps. For those battling issues in monolithic environments or in highly distributed, microservices-based applications, code level insights greatly improve software delivery efficiency by enabling developers to spend less time debugging and more time delivering world-class software.

Specifically, today, once developers ship their code, access to the application and data is restricted. This means that most dev teams are forced to rely on time and resource intensive logging to collect the critical data needed to understand the cause of any performance impact.

Instead of this time intensive, often manual process, by leveraging code-level insights, developers are able to capture critical data and context, on-demand. This level of insight, means, developers have access to data and can collect the necessary information when they need to in order to pinpoint what's causing an issue. As a result, developers have witnessed a decrease in MTTR, improving the overall IT efficiency of their teams, a tighter alignment between Operations and Development teams and according to recent studies, a 25 percent improvement in developer productivity, freeing up valuable time to focus on releasing new features.

Armed with time back, developers can focus on building market-differentiating products that drive user experience, customer satisfaction, and business priorities. This is especially key for organizations competing with younger, digital-native companies.

Jina Na is Associate Product Marketing Manager at AppDynamics

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The Power of Deep Code Insights

Jina Na
AppDynamics

The rise of technologies like cloud computing and automated delivery pipelines has enabled teams to deliver software at breakneck speed. In fact, top tech companies deploy software hundreds, even thousands of times per day, raising the bar for digital services. To stay competitive, organizations in every industry must match the pace of innovation set by these digital-native companies.

However, it's challenging to maintain heterogeneous applications and ensure that service is not only available, but also delighting users and driving business outcomes. From the front-end experience to back-end architecture, a web of third-party services, legacy data centers and a distributed, multi cloud infrastructure are supporting the application.

If you're unable to effectively manage these complex application environments, your business is impacted — an outage leads to poor user experience which leads to lost business and impact to your organizational productivity and resources. Take for instance what recently happened with the Iowa caucus app. Coding issues led to significant delays in counting and reporting important primary results, which led other states, such as Nevada, to pull two previously developed apps for their own primary elections, losing out on tens of thousands of dollars.

This example shows that while deployment velocity has increased exponentially, traditional approaches to troubleshooting fall short when it comes to equipping developers (and IT teams) with enough information to pinpoint the root cause of application code issues.

In fact, according to Stripe Research, developers spend roughly 17.3 hours each week debugging, refactoring and modifying bad code — valuable time that could be spent writing more code, shipping better products and innovating. The bottom line? Nearly $300B (US) in lost developer productivity every year.

What happened in Iowa is just one example of how developers are often blamed for code level issues, issues that with the right level of insight could reveal what's causing a bug in production before impacting the digital experience for customers.

So what's the solution and what opportunities would developers suddenly benefit from if they spent more time writing code and less time debugging?

The Aha Moments — What Code Level Insights Bring to Life

The job of a developer is never ending given business priorities and product roadmaps. For those battling issues in monolithic environments or in highly distributed, microservices-based applications, code level insights greatly improve software delivery efficiency by enabling developers to spend less time debugging and more time delivering world-class software.

Specifically, today, once developers ship their code, access to the application and data is restricted. This means that most dev teams are forced to rely on time and resource intensive logging to collect the critical data needed to understand the cause of any performance impact.

Instead of this time intensive, often manual process, by leveraging code-level insights, developers are able to capture critical data and context, on-demand. This level of insight, means, developers have access to data and can collect the necessary information when they need to in order to pinpoint what's causing an issue. As a result, developers have witnessed a decrease in MTTR, improving the overall IT efficiency of their teams, a tighter alignment between Operations and Development teams and according to recent studies, a 25 percent improvement in developer productivity, freeing up valuable time to focus on releasing new features.

Armed with time back, developers can focus on building market-differentiating products that drive user experience, customer satisfaction, and business priorities. This is especially key for organizations competing with younger, digital-native companies.

Jina Na is Associate Product Marketing Manager at AppDynamics

The Latest

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...

As enterprises accelerate their cloud adoption strategies, CIOs are routinely exceeding their cloud budgets — a concern that's about to face additional pressure from an unexpected direction: uncertainty over semiconductor tariffs. The CIO Cloud Trends Survey & Report from Azul reveals the extent continued cloud investment despite cost overruns, and how organizations are attempting to bring spending under control ...

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