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How to Shift Left with Code Profiling

Madeline Horton
Stackify

What is "Shifting Left?"

Development teams who utilize shift left practices typically employ frequent testing to speed up project deliverability and allow for better adherence to project timelines.

In Agile, development and testing work in tandem, with testing being performed at each stage of the software delivery lifecycle, also known as the SDLC. This combination of development and testing is known as "shifting left." Shift left is a software development testing practice intended to resolve any errors or performance bottlenecks as early in the software development lifecycle (SDLC) as possible.

Before Agile, software testing was performed using the waterfall methodology. When using the waterfall methodology, all testing occurs prior to deployment — from the non-production environments to the production environments. Through waterfall pre-deployment testing, issues are found in the code far too late and the release is inevitably delayed until all bottlenecks are fixed. Then, the code re-enters a testing period, which continues until all bugs are resolved and the code is deployed into the production environment. Waterfall methodology often negatively impacts the project’s deliverability and timeline. Increased time to market directly correlates with business revenue.

How Can I "Shift Left?"

In order to properly shift left, continuous testing must begin as soon as a developer starts to write code. A code profiler is one way of receiving immediate feedback and implementing a continuous testing loop in the preliminary stages of development.

Code profiling is one tool developers use to shift left and utilize frequent testing throughout the SDLC. Why? Fixing code directly while writing it on the developer’s workstation is essentially shifting as far left as possible. By shifting this far left, issues are found even before committing the code to a QA or non-production environment.

Traditionally, developers have used code profilers to identify performance bottlenecks without having to constantly touch their code. Code profilers are useful in answering questions such as "How many times is each method being called in my code" or "How long are these methods taking?" Additionally, code profilers track useful information such as memory allocation, garbage collection, web requests, and key methods in your code.

There are two types of code profilers: server-side profilers and desktop profilers. Server-side profilers track key performance methods in both pre-production and production environments to measure transaction timing and increased visibility into errors and logs. Another term for server-side profiling is Application Performance Management, or APM.

A desktop code profiler tracks the performance of every line of code within an individual method as well as tracking memory allocations and garbage collection to aid with memory leaks. Unfortunately, desktop profiling often causes applications to run slower than usual. In return, most developers utilize desktop profilers as a situational tool and not for daily use. Usually, developers only use code profilers when investigating a CPU or memory problem.

In order to provide both the granularity of a desktop code profiler and the light-weight nature of a server-side profiler, there are hybrid profilers. In a sense, hybrid profilers serve as the best of both worlds — merging key data from the server-side profiler with code-level details from the desktop profiler. Their light-weight nature is perfect for everyday use with server level insights and the ability to track key methods, transactions, dependency calls, errors, and logs.

What Code Profiler Should I Pick?

After evaluating the importance of a code profiler when implementing shift left methodology, it is important to keep in mind a few things. Often, profilers need to be built into the code itself. This is the reason why most desktop code profilers cause applications to run slow and are only utilized in specific circumstances. When looking at application performance management tools, note that most APMs require code or multiple configuration changes.

Whether you implement shift left methodology via a server-side, desktop, or hybrid code profiler, profilers are imperative for finding the hot path in your code. For example, a code profiler can be used to find what is using the 20% of the total CPU usage within your code. Then, your code profiler can help determine what you can do to improve your code.

Additionally, you can utilize a code profiler for proactively finding memory leaks as well as dependency call and transaction performance.

Code profilers are a necessary tool for constantly testing and improving your code throughout the SDLC as profilers can help look for the methods that can lead to the greatest improvement over time.

Madeline Horton is a Campaign Marketing Strategist at Stackify

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How to Shift Left with Code Profiling

Madeline Horton
Stackify

What is "Shifting Left?"

Development teams who utilize shift left practices typically employ frequent testing to speed up project deliverability and allow for better adherence to project timelines.

In Agile, development and testing work in tandem, with testing being performed at each stage of the software delivery lifecycle, also known as the SDLC. This combination of development and testing is known as "shifting left." Shift left is a software development testing practice intended to resolve any errors or performance bottlenecks as early in the software development lifecycle (SDLC) as possible.

Before Agile, software testing was performed using the waterfall methodology. When using the waterfall methodology, all testing occurs prior to deployment — from the non-production environments to the production environments. Through waterfall pre-deployment testing, issues are found in the code far too late and the release is inevitably delayed until all bottlenecks are fixed. Then, the code re-enters a testing period, which continues until all bugs are resolved and the code is deployed into the production environment. Waterfall methodology often negatively impacts the project’s deliverability and timeline. Increased time to market directly correlates with business revenue.

How Can I "Shift Left?"

In order to properly shift left, continuous testing must begin as soon as a developer starts to write code. A code profiler is one way of receiving immediate feedback and implementing a continuous testing loop in the preliminary stages of development.

Code profiling is one tool developers use to shift left and utilize frequent testing throughout the SDLC. Why? Fixing code directly while writing it on the developer’s workstation is essentially shifting as far left as possible. By shifting this far left, issues are found even before committing the code to a QA or non-production environment.

Traditionally, developers have used code profilers to identify performance bottlenecks without having to constantly touch their code. Code profilers are useful in answering questions such as "How many times is each method being called in my code" or "How long are these methods taking?" Additionally, code profilers track useful information such as memory allocation, garbage collection, web requests, and key methods in your code.

There are two types of code profilers: server-side profilers and desktop profilers. Server-side profilers track key performance methods in both pre-production and production environments to measure transaction timing and increased visibility into errors and logs. Another term for server-side profiling is Application Performance Management, or APM.

A desktop code profiler tracks the performance of every line of code within an individual method as well as tracking memory allocations and garbage collection to aid with memory leaks. Unfortunately, desktop profiling often causes applications to run slower than usual. In return, most developers utilize desktop profilers as a situational tool and not for daily use. Usually, developers only use code profilers when investigating a CPU or memory problem.

In order to provide both the granularity of a desktop code profiler and the light-weight nature of a server-side profiler, there are hybrid profilers. In a sense, hybrid profilers serve as the best of both worlds — merging key data from the server-side profiler with code-level details from the desktop profiler. Their light-weight nature is perfect for everyday use with server level insights and the ability to track key methods, transactions, dependency calls, errors, and logs.

What Code Profiler Should I Pick?

After evaluating the importance of a code profiler when implementing shift left methodology, it is important to keep in mind a few things. Often, profilers need to be built into the code itself. This is the reason why most desktop code profilers cause applications to run slow and are only utilized in specific circumstances. When looking at application performance management tools, note that most APMs require code or multiple configuration changes.

Whether you implement shift left methodology via a server-side, desktop, or hybrid code profiler, profilers are imperative for finding the hot path in your code. For example, a code profiler can be used to find what is using the 20% of the total CPU usage within your code. Then, your code profiler can help determine what you can do to improve your code.

Additionally, you can utilize a code profiler for proactively finding memory leaks as well as dependency call and transaction performance.

Code profilers are a necessary tool for constantly testing and improving your code throughout the SDLC as profilers can help look for the methods that can lead to the greatest improvement over time.

Madeline Horton is a Campaign Marketing Strategist at Stackify

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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