Category: Uncategorized

Architectural Observability Accelerates App Modernization

Posted on January 8, 2024 by - Uncategorized

Following best practices for continuous modernization minimizes technical debt. Monitoring tools such as logs and traces highlight accumulating application debt. Once identified, the weaknesses are added to the list of iterative changes in the development pipeline. Little by little, companies pay down their debt.

Unfortunately, not all debt appears as bugs or coding inefficiencies. Sometimes, it represents deviations from the original architecture. This architectural debt happens when infrastructure and design decisions are made as the software evolves.

No one wants to weaken the architecture, but development teams are often faced with adding functionality under time constraints. They may be asked to change features in older frameworks. Each decision moves the software a little further away from its original design. This architectural drift, if left unmanaged, can result in catastrophic failures. 

Related: Technical Debt Risk: A Look into SWA, the FAA, and Twitter Outages

By shifting left, continuous application modernization can bring a level of architectural observability to the process. With this added observability, engineers can identify design aspects that no longer serve their purpose. They can recognize redundant classes and intra-service dependencies that other tools may not. Without architectural observability, organizations will struggle to modernize applications at the speed needed to remain competitive.

How Architectural Drift Slows Continuous Modernization

A  recent survey found that 87% of decision-makers said application modernization is essential to gain and maintain a competitive edge. That said, they must accelerate the process to remain ahead of their competitors. This push for speed can contribute to architectural drift.

It’s the reality of software development. Few projects have the time and resources to deliver the perfect application. Developers and designers are constantly looking at trade-offs as they try to balance delivery times with best practices, resulting in architectural technical debt.

Declining Productivity

When left to grow unchecked, architectural drift hampers productivity. Developers are unable to incorporate updates quickly. They spend more time trying to make the changes work with a lopsided infrastructure. Before they know it, their application architecture looks like Jack’s house in The Nightmare Before Christmas. The entire structure is just moments away from collapse.

Teams struggle to resolve issues quickly. When the production application differs from the original design, developers take longer to identify and correct problems. Less time is available for writing new code, and their competitive edge shrinks in size.

Increasing Risk

A recent exposé on Twitter outages underscored the risk associated with architectural drift. Long before Elon Musk took control, Twitter had reliability issues. Frequent site failures led to the infamous “fail whale” label that mocked the site’s error screen.

Since 2000, Twitter has consistently added engineers to strengthen the site’s infrastructure. When ownership changed in 2022, layoffs began, threatening the site’s stability. In February 2023, four widespread outages were reported, which is almost half of the nine reported in all of 2022.

Massive layoffs meant a loss of undocumented knowledge. The remaining staff learned the infrastructure through a very public trial and error. Not only does increasing architectural technical debt make it harder to achieve productivity goals, but it also adds to the risk of a catastrophic failure. 

Escalating Costs

Architectural drift slows modernization efforts as applications become burdened with growing technical debt. Eventually, the mismatch of architecture and operating environment requires a reassessment of the application, which can result in expensive restructuring.

Testing can take longer as developers struggle to understand the architectural deviations, adding to delivery costs. The process of onboarding engineers slows as they try to unravel architectural intent to become productive. All these factors add to development costs.

Growing technical debt can waste as much as 25% to 45% of a development budget as more resources are needed to maintain and update applications. That doesn’t include the opportunity costs that result from the inability to capitalize on new technologies.

Minimizing the impact of architectural drift requires architectural observability, the ability to analyze an application statically and dynamically to understand its architecture, observe drift, and find and fix architectural technical debt. Software architects need tools to help them see what is happening statically and dynamically. With the right tools, they can baseline the architecture, collect data to detect drift, identify significant events, and correct architectural anomalies before they degrade an application’s business value.

How Architectural Observability Accelerates Continuous Application Modernization

Tradition has architects defining the infrastructure and setting the standards for application development, but they are rarely consulted as the project progresses—opening the door to a design that is loosely tied to the actual application. Today’s continuous modernization approach does little to change that perspective. 

Many self-organizing teams see little need for a design engineer. Why worry about maintaining an architectural design that only faintly resembles what operates in the wild? Incorporating architectural concerns only complicates the process with minimal value. 

While that assessment may have merit in organizations that lack architectural observability, it no longer reflects the visibility and context that architectural observability tools can provide. With the proper tools, engineers can see how the code operates, define standards, and identify anomalies that allow companies to make informed decisions about how to reduce architectural technical debt.

Architectural observability can accelerate continuous modernization processes by establishing a baseline, deploying AI-empowered tools, and creating internal platforms for increased productivity and business value.

Identify Architectural Drift Faster with a Baseline

Evaluating architectural drift means knowing how an application has deviated from its original design. That process requires a baseline that shows sources of architectural technical debt such as complexity, modularity, and scalability. Depending on system complexity, establishing a baseline may require multiple iterations. The goal is to create a comprehensive representation of an application. 

Without an accurate baseline, architects cannot assess the impact of deviations over time. They are forced to evaluate behaviors from a subset of data that reduces the validity of their decisions. However, a baseline in a continuous application modernization process is not static. As fixes are fed into the pipeline, baselines can change.

The cyclical nature of agile methodology and continuous improvement means analyzing the application and its architecture to avoid adding complexity and increasing technical debt. A comprehensive analysis requires data on static and dynamic behaviors. 

From application analysis, architects gain observability that allows them to monitor architectural drift and identify problems. Early detection helps minimize drift as the application and its architecture remain in sync. This enables architects to manage their systems effectively. Not only do they understand the application’s current state, but they can also assess future trajectories.

Architects must ensure they are using tools that support dynamic baselines. From an established baseline, engineers can observe behaviors and analyze changes to reduce architectural drift and avoid application disruptions. 

Use AI-Based Tools to Improve Productivity

Gartner sees AI-assisted software engineering taking on a more significant role in the software lifecycle. Their analysts envision relegating mundane development tasks to AI. They see AI performing the following:

  • Creating systems that operate autonomously
  • Developing model-building tools
  • Managing the end-to-end governance of applications
  • Enabling automation, orchestration, and scaling of products
  • Generating classes of test data

Incorporating these capabilities into architectural observability tools allows software engineers to spend less time writing code. AI-augmented tools can accelerate and facilitate modernization and reduce technical debt. 

Deploying AI-infused architectural observability tools removes time-consuming tasks from an architect’s workload. They allow developers to address architectural technical debt incrementally with fewer disruptions. The tools can evaluate changes in architecture and alert staff when thresholds have been reached, freeing developers to work on tasks with higher business value.

Create Internal Platforms for Accelerated Delivery

Setting up environments for development, testing, or support can be time-consuming. If solutions are vendor-agnostic, they may require multiple environments. Platform engineering tasks a dedicated team, building and operating self-service internal development platforms. These platforms are designed to optimize productivity and accelerate delivery. 

For example, an architectural observability platform would provide internal teams with a set of tools and processes to statically and dynamically evaluate the behavior of an application’s architecture. The platform would ensure consistency in data acquisition and results. With ownership established, changes to the platform configuration would be restricted, ensuring the integrity of the environment. 

In today’s development and release environments, changes happen quickly. No longer do months go by without an update. That creates a challenge for developers. How can they ensure they are working with the latest release? A dedicated team would be responsible for using architectural observability to ensure software architecture is current. Less time preparing an environment means more time available for other tasks.

Deploy an Architectural Observability Platform for an AI-Infused Platform

Architectural drift can sabotage a company’s efforts to modernize its applications. While IT departments may track application technical debt, they often dismiss the impact of architectural technical debt. They believe self-organized teams can address design issues. However, recent very public meltdowns at Southwest and the FAA have demonstrated what happens when architectural drift is ignored. Productivity declines, costs escalate, and potential risk increases.

Adding modern architectural observability tools allows development teams to assess architectural drift in parallel with technical debt. Parallel assessments ensure that architectural anomalies can be incorporated into the continuous application modernization queue for timely correction. Explore how vFunction’s architectural observability platform can accelerate your continuous modernization process by starting a free trial or requesting a demo.

The Transformative Influence of Observability on Software Architecture

Posted on December 19, 2023 by - Uncategorized

Technical Debt. If those two words send you running from the room, you are not alone. A recent survey found that 70% of respondents said technical debt inhibited their ability to innovate. Even though 79% of organizations had defined goals, only 54% could outline a strategy for reducing debt. Without continuous architectural observability, it is common to deploy new code only to have unexpected problems pop up.

Nothing is more frustrating than refactoring code only to discover issues that set a project back months. When setbacks happen, pipelines can become clogged and releases delayed. Project costs may go up, increasing everyone’s stress level. It’s no wonder that 79% of software modernization projects fail.

Many have presented reasons for why projects fail. These reasons have included everything from a lack of executive support to the elimination of in-person collaboration. What they haven’t talked about is focus.

Most teams assess technical debt by looking at code quality, defect ratios, or technical debt ratios of an application. They rarely assess an application’s architecture, assuming it will take care of itself as modernization progresses. Couple this attitude with continuous delivery demands, and architectural drift increases with each release cycle.

Rather than ignore architectural concerns, development teams should champion continuous architectural observability. They need to shift left architect involvement to lessen the impact of application complexity and continuous delivery on application architecture.

Why Focus on Application Architecture?

If you’ve been involved in constructing a building, you know there are original and as-built plans. As-builts document the changes made to the original design during construction and should include the exact dimensions and locations of all work elements. The plans are invaluable when remodeling or renovating an existing structure.

Related: Unlocking Excellence: Navigating the Path of Continuous Modernization

Building and maintaining software applications works in much the same way. Specifications may outline what the code should do, but actual coding rarely matches the specification when deployed. As with construction projects, someone needs to monitor the deviation from the original architecture to ensure project integrity.

Application Complexity

While microservices architecture has many advantages, its web of microservices increases application complexity. Every service is self-contained. If a microservice needs an external resource, it makes a request. Sometimes, developers write extra code to maintain service independence, which can contribute to architectural drift.

The distributed nature of microservices applications makes testing and troubleshooting challenging. Tracing a request through multiple services means looking at the data each service provides. Stringing the information together still lacks context despite the hours of analysis.

Integrating third-party application programming interfaces (APIs) adds to application complexity. Developers have no control over changes in third-party APIs that happen over time. Instead, they must modify their code to address changes. Even if the API remains unchanged, developers may need to add application functionality that requires a workaround to accommodate the API.

Cloud computing adds a third component to application complexity. The top priority for businesses in the next three years is modernizing and integrating applications with cloud services. While most companies operate in a public cloud, 55% still use on-premise systems.

This hybrid operating environment requires modernization processes to consider current implementation that may involve cloud and on-premises operations with future cloud-only capabilities. Developers must assess the sustainability of their applications as they migrate to a cloud-first enterprise.

Microservices, third-party integrations, and cloud migration create a complex environment for managing application architecture. Add continuous delivery to the mix, and the potential for unconstrained architectural drift grows with each release.

Related: Unlocking Excellence: Navigating the Path of Continuous Modernization

Continuous Delivery

As more organizations adopt an agile methodology, speed adds another dimension to software delivery. Applications are rarely once and done, requiring regular updates, new features and functionality and a modern user experience—all of which depend upon incremental improvements as quickly as possible.

This demand for continuous delivery often forces development teams to evaluate the tradeoffs between speed and quality. For example, a company has promised new functionality in the upcoming release. However, the optimal implementation would delay the release by two weeks. The developers opt for a less-than-optimal approach to ensure the software meets its release date. 

Theoretically, developers should add a task to their backlog to optimize the new functionality. However, the priority assigned to the task depends on what else is in the backlog. It could take months before the issue is addressed.

If the optimization involves application architecture, the assigned priority may be lowered in favor of more revenue-generating features. Unfortunately, ignoring the task only adds to the application’s technical debt.

Without architectural observability, development teams lack the resources to prioritize architectural technical debt. Deviations accumulate with each release cycle until catastrophe strikes. With architectural observability, engineers can see behaviors in context and address them before a disruption in service occurs.

Related: How Continuous Modernization Can Address Architectural Drift

How Observability Helps Architectural Focus

Technical debt can be intentional or unintentional. Intentional technical debt happens when architects and developers evaluate the tradeoffs among several design options. No matter the decision, they know that some technical debt will accrue. 

In the past, development teams lacked the tools needed to assess the architectural impact of those decisions. They made educated guesses based on traces and logs produced by each microservice. The sheer volume of data from hundreds of microservices was difficult to analyze and place in context.

Architectural observability changes how engineers look at technical debt. It lets them see structural deviations before they threaten application stability. With observability tools, architects can establish baselines, set thresholds, and monitor drift to address architectural technical debt proactively.

Establish a Baseline

Odds are the original architectural plan for an application is not what is operating in the wild. How far the architecture has drifted requires a baseline. Establishing a baseline identifies an application’s behaviors and interactions. It quantifies the deviation from the original design and measures the drift going forward.

Baselining an application’s architecture means looking at complexity, modularity, and risk. It requires data on areas of architectural debt, such as service exclusivity, cross-domain contamination, and interoperability. Without a baseline, architects struggle to set thresholds and assess accumulating architectural technical debt.

Set Thresholds

Organizations need to set thresholds for technical debt, whether application or architectural. When software reaches or exceeds those values, development teams need a plan to lower the values and the corresponding technical debt.

Automated architectural observability tools can monitor applications and alert architects when thresholds are reached. They can help visualize the drift for a clearer picture of what is actually happening during runtime. With advanced notice, engineers can develop a plan for fixing the anomalies before they result in service disruption.

Monitor Drift

Capturing data on evolving software applications is challenging. Development teams not only need a process that incorporates observability into each iteration of continuous delivery, but they also need to identify what to monitor to minimize technical debt. 

Service Creep

Adding or deleting services can alter an application’s architecture. Architects should audit an application’s structure to ensure the service changes are necessary for technical or business reasons. In complex applications, maintaining control of service creep decreases the potential impact of architecture deviation.

Service Exclusivity

Fundamental to a microservices architecture is service exclusivity. However, avoiding dependencies can be challenging when moving a monolithic application to a microservices structure. Monoliths share resources and classes. Modules are often tightly coupled. Unless architects monitor service exclusivity, architectural technical debt can grow undetected.

Dead Code

Dead code can be revived. Unlike unreachable code, dead code can technically be reached. It may no longer be used, but there’s always the possibility it could triggered accidentally. Dead code increases as software evolves and functionality changes. If left untouched, dead code can complicate an application’s architecture. 

Developers are hesitant to touch unused but reachable code for fear of a zombie apocalypse. Using architectural observability tools, engineers can watch what happens to ensure that touching the dead code will not have catastrophic results.

Common Classes

Common classes should function as a shared common library of core platform services. If not placed into common services, an application’s architecture can develop dependencies and duplicate code. Duplicate code increases an application’s size unnecessarily, and dependencies violate service exclusivity.

Architectural observability allows architects to identify dependencies and duplicate code for proactive correction. They can provide fixes that re-establish the architecture before technical debt is allowed to accumulate.

Maintain Focus

Architectural observability moves architects into the mainstream of software development. They are no longer relegated to the start of a project. Instead, they are part of each iteration, ensuring that development teams keep architectural technical debt in focus.

Addressing architectural drift incrementally with automated tools allows engineers and architects to minimize deviations through early detection. They can integrate fixes into development schedules to reduce the impact on delivery. Development teams can keep architectural drift in focus.

vFunction’s Architectural Observability Manager enables technical teams to create architectural baselines, set thresholds, and receive alerts when software architecture changes may result in architectural drift and technical debt. The tool enables architects and engineers to proactively address architectural anomalies.

With its AI capabilities, the vFunction Architectural Observability Manager can quantify improvements and confirm fixes. If you’re ready to transform your modernization process, request a demo to learn how architectural observability can help.

Five 2024 Predictions for Software Architects

Posted on December 8, 2023 by - Uncategorized

Post originally featured on VMblog.

There’s no doubt that 2024 will usher in an exciting era of new Generative AI solutions across a range of business and personal use cases. Under that noise, there are some serious issues across IT and software engineering organizations that need serious attention and are on the brink of big changes in 2024. Here are five 2024 predictions to track and keep an eye on.

Software Architects Get Some Long Needed AI-Love

Getting software architecture right is hard. Keeping your software architecture right over time is even harder. And modernizing an architecture you inherited from previous architects is nearly impossible. The good news for software teams is that generative AI holds a tremendous amount of potential to reduce the drudgery of everyday software development and maintenance. In particular, the dreaded task of framework and language upgrades and migrations can be greatly simplified with the latest round of AI-assisted developer tooling.

But unfortunately, software architecture – and the inevitable architectural technical debt that comes with it – needs something more than an AI-assistant magic button (sorry to say). In 2024 though, help is on the way in the form of AI-Augmented tools that focus on software architecture. This requires the ability to identify domains, peel away dependencies, and help architects extract clean services with well-defined boundaries and APIs. The focus is to support the expert, who in this case is the software architect, and give them the iterative tooling to rearchitect, refactor, or rewrite given their understanding of value streams and business processes.

Learn more >

Developer Productivity Turns a Corner, Finally

The state of developer productivity makes me sad. With all the investments and advancements in automation, shifting left, full stack development, the plethora of plug-n-play cloud services and XaaS options, the latest and greatest generative AI tools, and so on – developer productivity continues to plummet year after year. Perhaps we finally reached the cognitive load limits of developers and teams.

Having spent a considerable amount of time with organizations understanding and evaluating how they manage technical debt, I’ve come to the conclusion that until teams start proactively managing technical debt – not just simple source code tech debt but deeper architectural technical debt – then we’ll never turn the corner on improving developer productivity. That’s because technical debt is actually the root of the problem – while these other solutions have been merely chasing symptoms. In 2024, architectural observability and analysis solutions will provide a lifeline for teams that want to reverse their developer productivity woes. Reducing architectural technical debt will be the secret to unlocking developer productivity in 2024.

Learn more >

Governance Turns Its Focus on Software Architecture

Software governance, audit, and compliance tools have come a long way. Maybe not long enough yet, but automated governance and governance-as-a-service solutions are viable options for organizations today. Automated analytics can measure source code quality, check for security issues, detect composition problems, SBOM analysis, and more. Plug these into your CI/CD pipeline and compliance automation is looking pretty sweet.

But wait, what about software architecture and architectural compliance and governance? Architectural technical debt has a much greater effect on business velocity, cost efficiency, and productivity than any of this existing compliance and policy telemetry. To manage architectural drift, organizations in 2024 will start to turn to architectural governance tools that measure technical debt in the same cycles that they are tracking security, composition, and source code quality. Plug-in architectural observability baselining and drift detection directly in line with development pipelines, and teams will truly automate architectural policy and enact technical debt standards.

Learn more >

Look! Platform Engineering for Architects

Platform engineering is a pretty cool concept. The idea of building and managing self-service internal developer platforms (IDPs) for software delivery and life cycle management has kept SRE and DevOps teams busy in 2023. In 2024, software engineering leaders will leverage this experience and extend the concept to address their modernization backlog. The modernization experience for architects and developers is terrible: it’s complex, tedious, risky, and slow.

Enterprise architects looking to extend a broader and more consistent modernization approach across their architect teams will deploy modernization platform engineering to set enterprise-wide technical debt measurement and management standards. In 2024, enterprise architects will gain organizational visibility, tracking, and governance while line-of-business software architects will leverage reusable architectural observability tools and self-service capabilities to improve their modernization experience and productivity. A win, win for sure.

Learn more>

Observability Makes Inroads Into Software Architecture

Observability, AIOps, and OpenTelemetry are on a roll. They have truly made massive progress over the last three years, so why stop in 2024? While Application Performance Management (APM) tools have tried to scratch the surface of application modernization, they’ve mostly applied old monitoring and correlation technologies to technical debt and app modernization use cases. When all you have is a hammer then everything looks like a nail. Architects have tried to use APM and existing observability tools to solve their problems, but mostly because their DevOps teams have already paid for them. They need new tools and hardware (really software), not hammers and nails.

Learn more >

Summary

In 2024, enterprise and software architects will seek out observability solutions that are specifically designed for their app modernization, technical debt management, and architectural analysis needs. Architectural observability solutions will emerge that look deeply into software architecture to unearth domains, tease out dependencies, and surgically extract new services, microservices, and serverless functions. Think of these as new tools for the software architect’s toolbox. Instead of borrowing tools from their DevOps neighbors, in 2024 architects will use purpose-built solutions designed especially for their needs. And finally, they can return their borrowed but unused tools to their friends down the street.

Empower a Software Evolution with Continuous Modernization

Posted on November 27, 2023 by - Uncategorized

Continuous software modernization is the key to scalability, security, and minimizing both technical debt and architectural drift. Technical debt is a major issue for today’s organizations, costing companies a significant percentage of their tech budgets and limiting growth. According to a survey by McKinsey, 3 out of 10 CIOs dedicate more than 20% of their tech budget to resolving tech debt issues that would otherwise be used for new value-generating products.

Architectural drift can contribute to technical debt and is an equally challenging issue for organizations to overcome. A continuous approach to modernization using the architectural observability life cycle ensures drift and tech debt are identified and resolved. As a CIO or software architect, you can modernize your organization’s monolithic architecture with the help of a continuous modernization platform. 

The right platform allows you to analyze architecture and incrementally modernize to address technical debt. It provides observability to ensure you can identify and resolve issues between releases with the architectural observability life cycle.

What Is Continuous Software Modernization, and Why Is It Critical for Businesses?

Continuous software modernization involves the progressive and continuous evolution of a legacy software architecture. Software architecture problems are incrementally addressed and updated with frequent releases, monitored, and refined during the software development life cycle. It can help organizations spread out modernization, making the process more manageable while reducing risks, future architectural drift, and architectural tech debt. 

Modernization evolves software architecture and delivers new features incrementally, focusing on balancing required architectural improvements with priority features and higher quality. It improves scalability and reduces costs by replacing or refactoring monolith software into more modular architectures, microservices, or serverless functions that offer horizontal scalability at a lower cost and fewer dependencies. 

Architects can extract domains depending on priority and refactor them into microservices. The new services or microservices can be scaled based on performance needs and demand to meet the organization’s objectives.

Ignoring modernization results in more architectural drift and snowballing technical debt. Architectural drift is when software is no longer able to evolve to serve its intended purpose, resulting in an implementation that does not meet changing business requirements. Architectural drift factors into technical debt, adding additional interest to the debt which must be eventually resolved.

Related: Unlocking Excellence: Navigating the Path of Continuous Modernization

Organizations can reduce architectural drift and technical debt with continuous modernization. The architectural observability life cycle is one way that organizations can ensure continuous modernization. It involves five phases that play out continuously to provide a holistic solution to drift and tech debt.

What Is the Architectural Observability Life Cycle?

Architectural observability enables an architect to monitor and detect architectural drift, allowing them to pinpoint and resolve issues during each agile sprint or version release. Architects can address drift incrementally to manage tech debt from past decisions, eliminating dead code and unmanageable dependencies.

There are five main phases in the architectural observability life cycle: analyze, baseline, observe, inform, and fix. A software architect can use this life cycle to effectively modernize monolithic architectures, address architectural drift, and reduce tech debt.

Analyze

Analyzing your existing software architecture is the first critical step in the life cycle. During the analysis phase, the architect is able to identify and visualize domains and identify current tech debt sources that require immediate action to address.

Baseline

After analyzing, identifying, and visualizing domains and tech debt sources, the architect is alerted to the key issues and to-do’s to address them. Creating a baseline allows an architect to watch for future drift. Baselining also helps the architect create a to-do list to address cross-domain database relationships, high debt classes, and cross-domain pollution while discovering and refining domains.

Observe

With an established baseline, the architect can continuously observe the architecture as it changes. Observation allows architects to identify architectural drift, dead code, new domains, new database dependencies, and the introduction of code with high-tech debt.

Inform

As an architectural observability solution detects the architectural changes to the software architecture, the inform phase alerts the architect of significant architectural events. Architectural events can be added to the modernization to-do list, allowing the architect to pinpoint database table interdependencies, dead code, high debt code, and classes to create stories in the next phase.

Fix

With the significant architectural events identified, the architect is able to pinpoint fixes and create modernization stories and to-do list backlogs. Using the baseline, observe, and inform phases, the architect can resolve issues in dead code, common libraries, exclusivity thresholds, and domain identification.

Architects should evaluate fixes to ensure incremental remediation of architectural drift and reduction of tech debt. One report in McKinsey found that paying off tech debt can result in as much as a 50% increase in a software engineer’s time to work on profitable new features and software. Fixing can also include extracting new microservices, refactoring, decomposition, upgrading frameworks, and building new libraries.

It is critical to remember that fixing is not the final phase in the architectural observability life cycle. The life cycle is continuous, and the architect will go through each of the five phases indefinitely to ensure continuous software modernization.

Software Modernization Use Cases

Organizations use software modernization to meet several use cases. While a full transformation, where companies completely replace the legacy architecture with a new solution, is often considered, an incremental, continuous approach is preferred due to its reduced risk and more controlled process, along with its lower upfront time and resource investment.

Related: Why Mastering Architectural Observability is Pivotal to Managing Technical Debt

Modernization can improve the scalability, security, and performance of the architecture by extracting domains from the monolith and refactoring them into microservices, modules, or serverless functions. Companies can modernize without transformation to manage tech debt and prevent architectural drift by creating to-do’s and resolving issues.

Full Transformation

Architects can carry out software modernization with a full transformation. In this use case, the monolithic architecture is completely replaced with new microservices extracted and refactored from the original application in a full transformation. It is an ideal choice when the application needs a complete overhaul, or when it is outdated and difficult to maintain. Businesses often choose continuous incremental refactoring as an investment in a more sustainable best practice, due to the amount of time and resources it can take to create new microservices from scratch.

Incremental Transformation

Incremental transformation is a continuous software modernization technique that is preferred by modern businesses. Instead of approaching modernization all at once, the organization breaks the monolith into pieces and incrementally refactors functions into more modular components such as microservices. It allows the company to invest time and resources into modernization over a longer period, spreading out the process in agile sprints. The architect can also prioritize the functions that require modernization most and leave less necessary functions for later.

An incremental transformation offers a much less risky approach to modernization, reducing interruptions in service considerably compared to full transformation. According to Venture Beat, 51% of respondents to the Infosys Modernization Radar 2022 report cited major interruptions during a full transformation approach, compared to just 21% using an incremental approach. Incremental modernization gives architects time to identify issues between releases and focus on extracting and refactoring a single function at a time.

Architectural Tech Debt Management

As mentioned above, technical debt comes from decisions that delay fundamental improvements, resulting in the need for future reworking that can come at a higher cost later. Continuous software modernization helps architects identify issues in the software architecture early and often. Architects can create itemized to-do’s, identifying what needs to be addressed and how it can be resolved. Modernization allows architects to reduce tech debt and improve architecture without extracting services or transforming them, instead allowing them to manage, contain, and remediate issues.

Prevent Architectural Drift

Architectural drift happens when the description of the architecture drifts from the implementation. Continuous software modernization can prevent architectural drift and mitigate drift in the future. When the architecture worsens and further impacts developer productivity, scalability, and velocity,  architects can identify that drift and resolve it. 

Leverage Architectural Observability for Continuous Software Modernization

Modernization is a continuous process that requires architectural observability to identify and resolve issues between sprints or releases. It can involve a full or incremental transformation to replace or refactor the monolith into scalable microservices. Companies can also modernize without incremental or full transformation using the architectural observability life cycle to identify and resolve technical debt and architectural drift.

Architectural observability is essential on your continuous modernization journey, and a continuous application modernization platform that offers analytics to provide the observability and automation features you need to assist in successful modernization can make all the difference. vFunction helps you reduce technical debt by incrementally iterating large backlogs into several releases. Request a demo to improve your continuous modernization efforts with architectural observability.

Architectural Technical Debt and Its Role in the Enterprise

Posted on November 21, 2023 by - Uncategorized

For over 400 years, people have used the adage, “can’t see the forest for the trees,” to indicate that individuals are so focused on parts of a situation that they lose sight of the bigger picture. The same sentiment is often applied to development teams who appear to ignore or deprioritize more significant issues when maintaining and updating applications.

This myopic focus can lead to the accumulation of architectural technical debt, a hidden cost that can impede innovation, compromise system reliability, and increase the likelihood of critical failures. Unchecked technical debt not only hampers the overall health of software applications but can also result in significant financial and reputational losses for organizations.

Understanding the intricate balance between architecture, code quality, scalability, and functionality is crucial. Leveraging tools that prioritize these aspects can help developers maintain a healthy software architecture, prevent technical debt, and ensure the long-term success of their software projects.

What Happens When Technical Debt Grows Unrestrained

In many ways, the forest analogy is an unfair one. Just as a forest can’t exist without trees, software can’t operate efficiently today without modern architecture. Similarly, a thriving forest cannot grow unconstrained without the risk of a devastating forest fire. Software architectures need to be managed, maintained, and modernized, or tech debt accumulates and the software can implode. Take Southwest as an example.

Southwest’s 2022 holiday failure was only the beginning of its technical “glitches” as it tried to compensate for technical debt that grew uncontrolled. In April 2023, Southwest asked the FAA to pause all flights until they could address another glitch that delayed 1,700 flights. The airline’s woes illustrate the challenges of balancing maintaining the forest while addressing the trees. Southwest chose to ignore its growing tech debt in favor of selling more trees.

How can organizations avoid becoming the next Southwest? How do they control architectural and application technical debt? They must incorporate architectural observability and testing tools at every stage of their development and DevOps process to ensure their applications operate smoothly across their enterprises. This includes

  • Static source code analysis tools
  • Software composition analysis tools
  • Static and dynamic application security testing tools (SAST, DAST)
  • Architectural observability tools

Ground-Level Coding Tools

Many programmers dislike testing their code. They believe unit testing is a poor use of their time. When teams are pressured to deliver updates, taking time away from development seems counterproductive. However, static code analysis can help identify technical debt at a foundational level. Tailoring these tools can establish rules for consistent coding within an application or across an enterprise.

Related: Why Mastering Architectural Observability is Pivotal to Managing Technical Debt

Static code analysis tools detect bugs and weak coding methods. They can highlight spaghetti, dead, and zombie code. Some even calculate technical debt and help build more comprehensive unit testing. Encouraging developers to use tools improves code quality and reduces costly rework because of errors found later in the delivery pipeline. 

Paying Attention to the Environment 

Forests begin with a single tree. Saplings planted in the appropriate environment thrive, building a robust forest. Attempting to create a forest in an area that meets the minimal requirements increases the effort needed to sustain growth. Land management spends more time monitoring the environment and compensating for poor growing conditions.

To effectively manage an evolving application, software developers need to evaluate the components used to build an application. Programming languages, frameworks, and third-party libraries impact the final solution. Picking the most appropriate building blocks improves an application’s stability. However, yesterday’s solution may not meet today’s needs.

For example, open-source components may contain security vulnerabilities and lack the support to address them. Programming languages may not have the flexibility to deliver new capabilities efficiently and frameworks may demonstrate weaknesses over time. Unless developers routinely reassess their choices, they may discover an increase in their software’s technical debt.

Monitoring the environment of a growing forest requires automation. Modern technology places sensors among the trees to report changes in the environment. Development teams can deploy automation to evaluate application building blocks.

Software composition analysis tools can detect outdated frameworks or known vulnerabilities in open-source components. They can recommend remediation solutions to continuously reduce technical debt. By automating the process, organizations can focus on new development, knowing that tools are in place to monitor the environment.

Secure by Design

Secure by Design is an initiative to design and develop software that incorporates cybersecurity measures to protect against malicious attacks as early in the process as possible. To help guide developers around the globe, the Cybersecurity and Infrastructure Security Agency and its international partners released a Secure-by-Design publication in April 2023. The document outlines core principles to protect technology, including

  • Shifting security responsibilities from the end user to designers and developers.
  • Building an organizational structure that prioritizes security as an essential design element.
  • Embracing transparency and accountability to ensure vulnerabilities are addressed.

The difficulty with such an approach is developers are not cybersecurity professionals. When companies struggle to fill cybersecurity positions, allocating those limited resources to design and development may not be possible. Their skills are better applied to protecting the enterprise. 

Deploying security and vulnerability analysis tools (e.g., SAST and DAST tools) throughout the development life cycle can make secure-by-design feasible. Instead of waiting until the end of a development cycle to run the software through a security expert, have team members use analysis tools early. It’s less costly to address vulnerabilities at the design stage than to rework code once in production. 

Managing Growth

Managing a forest means managing growth. Pine trees and Douglas fir saplings grow at different rates. Comparing real-time growth metrics with established benchmarks helps the Forest Service plan. Perhaps the saplings aren’t receiving enough sunlight, or brush is accumulating on the forest floor. Determining the best approach requires visibility. 

No one expects that trees will grow according to benchmarks. They plan on viewing the site to understand how the trees are performing. From the data, forest managers make adjustments to their plans. They may rely on monitoring data for information between site visits to decide if an unscheduled look is needed, but nothing can replace onsite visibility.

Although developers can’t make onsite visits to their code, they can deploy tools that can record activity during testing and at runtime. These records may be logs and traces. Performance records can generate a historical log of changes. Observability tools make it possible to digest the volume of recorded data to help DevOps understand deviations quickly.

Architectural observability tools can help measure architectural technical debt that accrues as software architectures drift and evolve. Incorporating architectural observability into the continuous integration and delivery process helps minimize architectural debt introduced sprint by sprint, release by release. Best practices suggest that these tools should be used before and after each software change.

Observing the Architecture

Suppose forest managers followed all the best practices only to discover their forest is three feet over the property line, and the owner wants the trees removed. That’s a significant effort for a mile-long boundary. Unfortunately, the land managers lost sight of the forest while building thriving trees.

For software developers, it’s easy to focus on individual snippets of code or an application, without considering how they impact the entire architecture. For example, the original architecture used a data lake for storage. When adding several new features, developers found the data lake architecture was not responding fast enough to meet their needs. Reporting jobs took hours to complete. They decided to extract the necessary data from the data lake to build a smaller dataset without regard to the myriad of inter dependencies and cross-domain issues for the rest of the application.

Related: Shift Left to Avoid Technical Debt Disasters: The Need for Continuous Modernization

While the application continued to perform, the problem was that other domains and services were also using the data services due to cross-domain pollution and contamination. This created further testing issues, new bugs, release delays, data integrity and security problems. 

While the data lake controlled access to its data, other domains that tried to access the new data lake did not. The developers assumed the application authentication was enough. What they failed to realize was some of the extracted data fell under HIPAA and PCI standards. 

Without fully understanding the architecture and related dependencies, the developers took a localized view without a more global architectural perspective and were forced to back out their fixes. The resulting product release delays and potential compliance violations demonstrated the need for architectural observability as a guidepost for future updates. 

Understanding Software Architecture

Just as trees make a forest, applications make an enterprise. Applications carrying heavy technical debt weaken an enterprise and expose it to vulnerabilities. When a tree is damaged or diseased, it is removed to secure the forest. Yet, many organizations fail to look at the technical debt that accumulates at the architectural level, letting it grow unchecked.

In order to address architectural technical debt, development teams have a range of tools to help manage source code, security, or software composition but need architectural observability tools for their software architecture. Individual programmers already can access existing tools to find bugs, eliminate smelly code, and conduct unit testing. These tools can reduce technical debt before it leaves a developer’s desk but do not address architectural technical debt.

Automated tools can help development teams look for outdated or unsupported components and check for security vulnerabilities throughout the development life cycle. Adding architectural observability capabilities before and after software changes lets teams find, fix, and manage architectural technical debt as part of a continuous modernization process.vFunction’s Architectural Observability Manager allows engineers and architects to view, manage, and track application architecture in both a static and runtime context. It lets organizations manage their software architecture to minimize architectural drift. To avoid being the next Southwest, let us help you see the forest without ignoring the trees.

Is Refactoring to Microservices the Key to Scalability?

Posted on October 23, 2023 by - Uncategorized

As the speed of technology continues to increase, an outdated monolithic architecture limits your organization’s ability to scale and run effectively. Modernizing your software by refactoring to microservices offers increased scalability, allowing your company to optimize the value it gets from the cloud. For many business leaders, modernization is now a priority. According to a survey featured in DevOps, over 5 out of 10 decision-makers in IT are currently migrating to the cloud or plan to within the year. For good reason, business leaders are motivated to move to the cloud for improved scalability, reliability, and security.

Learn how vFunction supports and accelerates your monolith-to-microservices journey.
Learn More

There are various options to help your organization modernize and migrate to the cloud by refactoring your monolithic architecture to microservices. Using a platform that facilitates continuous modernization will ensure you can modernize your legacy applications iteratively and complete your migration to the cloud successfully. It will help you break your monolithic architecture into containerized microservices to scale horizontally, add more capacity, and optimize the value of the cloud for your company.

A monolithic architecture can be challenging to scale, and many organizations fail at the task. But when they take the right steps and successfully refactor to microservices with a continuous modernization approach, they can unlock the scalability of the cloud with cloud-native applications that overcome the limitations of legacy software.

Monolithic vs. Microservices Scalability

While monolithic architectures are less scalable than microservices, many organizations still use monolithic architectures in legacy implementations due to their simplicity. A few factors make scaling microservices preferable to monolithic software:

  • Monolithic architecture contains all components and functions in a single, large codebase. Microservices are containerized based on their components or functions into separate codebases.
  • Increased traffic can cause a reduction in performance when using monolithic architecture. Microservices are optimized for the cloud, with each containerized function receiving dedicated computing resources, resulting in higher throughput and performance.
  • Monolithic architecture can only scale vertically to meet demands. Microservices offer independent and horizontal scalability, allowing you to plan for increased demand and allocate resources accordingly.

When you inevitably switch to microservices at a later date, your postponement can result in technical debt. Architectural observability will help you identify architectural debt and drift so you can refactor as you go, minimizing downstream effects. 

The Challenges of Monolithic Architectures That Refactoring to Microservices Can Overcome

Monolithic software architectures consist of self-contained applications with various functions and components tightly coupled together. Their codebases are large to ensure each function can be executed. When one component or function is executed, the entire application must be compiled and run.

Related: Shift Left to Avoid Technical Debt Disasters: The Need for Continuous Modernization

The size and tight coupling of components and functions in monolithic software design make scaling a very complex process. Monolithic software can only scale vertically, and improving performance and adding new features can be costly. Some challenges developers face when scaling monolithic architecture include the following.

Challenge #1: Individual Units Are Difficult to Scale

Monolithic code consists of a large codebase with various application components and dependencies, including configuration files, frontend, and backend code. The complexity and size of the code can be difficult to maintain, update, and scale. Scaling monolithic software will require extensive coding for each application function and expensive hardware with significant CPU, memory, and data capacity. It is resource-heavy and requires large-scale testing, debugging, and deployment, which can result in a significant investment of time and resources.

Challenge #2: Vertical Scaling Requires Increased Computing Resources

Monolithic software can typically only scale vertically. Scaling up requires significant increases in CPU, memory, disk, and network resources. It can deliver increased performance and serve a larger user base, but it can be costly, and server hardware is limited to a set amount of CPU, memory, and disk upgrades. Organizations prefer horizontal scaling to vertical scaling, due to its lower cost and increased benefits. However, monolithic software cannot readily scale horizontally.

Investment in higher-end computing resources could instead be used to refactor the monolith to microservices. Eventually, the server will reach its limitations, and refactoring will need to be completed at a later date anyway, resulting in technical debt that can be devastating to your company. 

Technical debt is the cost of solving problems in the future due to postponements and fixes that do not address the underlying problem. It could be lost opportunities, decreased productivity, or increased expenses. According to McKinsey, technical debt accounts for up to 40% of the average company’s tech expenses. Making decisions that facilitate modernization can help your business avoid devastating technical debt when it needs to modernize the monolith at a later time.

Challenge #3: Monolithic Applications Require Maximum Cloud Services without Scalability

While monolithic software can be migrated to the cloud using lift and shift methods, it comes with limitations. The lift and shift method does not include any optimization for the cloud, resulting in poor optimization for cost and performance.

Lifting and shifting can cause security, availability, efficiency, and scalability issues. It often results in organizations paying significantly more for maximum cloud service without the scalability and elasticity benefits the cloud provides. Refactoring to microservices is an ideal way to modernize your code and optimize cloud performance, costs, and scalability.

What Is the Role of Refactoring?

Refactoring is a method of restructuring and modernizing software while maintaining its expected behavior. Software teams can use new, more scalable architectures and automation tools to revamp the capabilities and performance of legacy software. Refactoring to microservices containerizes the code, reducing dependencies and making the code easier to maintain and secure. It can improve the lifespan of the software and compatibility with new systems and platforms.

Modernization offers improved performance and scalability at a lower cost. It delivers enhanced security in many situations and allows the organization to adapt to change quickly. Refactoring is typically the ideal method of modernization for monolithic software. When an organization refactors to microservices, it breaks a single large codebase into more manageable containerized applications that are easier to update and scale.

Related: Application Modernization Trends: Goals, Challenges, and Resources

Modernization also allows your organization to optimize cloud usage with cloud-native applications and architectures. Your company can deploy and manage applications seamlessly, whether your software is running on-premises or in the cloud. You can use orchestration platforms like Kubernetes for scalability to create new instances and avoid bottlenecks.

How Refactoring to Microservices Addresses Monolithic Challenges

Monolithic architectures offer limited scalability. Refactoring to microservices is often the ideal path to modernizing your organization’s software. The Strangler Fig Pattern is typically the preferred method, breaking the monolith into functions that can be containerized as microservices and deployed one function at a time to streamline the process. Modernized microservices offer enhanced value from the cloud and horizontal scalability that monolithic software cannot deliver.

Horizontal Scalability

Refactoring to microservices allows you to scale your software horizontally. Horizontal scaling is a modern method of scaling, allowing your organization to dynamically and selectively add new servers or nodes rather than adding new hardware to your existing server. Microservices are containerized, allowing you to deploy, manage, and run them on several servers. The increased throughput will ensure that your software will be accessible during periods of heavy use with fewer bottlenecks, compared to monolithic software that runs from a single server.

If a single microservice or several microservices require increased computing power, you can increase the number of instances running on separate servers to ensure there is enough throughput. Using an orchestration platform like Kubernetes, you can automate the deployment, scaling, and management of your containerized microservices or manually scale from a UI or terminal.

Increase Value From the Cloud

When you scale horizontally, you can optimize elasticity and your use of cloud resources. Monolithic architectures only scale vertically, using a fraction of the cloud resources available to your organization. Despite its limitations, your company will still pay for maximum cloud utilization without the benefits of modernization.

Whether your servers run on-premises or in the cloud, users can access microservices with optimal throughput with a cloud-native architecture. You also have the elasticity of the cloud when your server or node is no longer receiving increased traffic. Manually or through automation, you can reduce the size of clusters and reallocate the space to another function.

Improve Efficiency With Modernization

In addition to providing horizontal scalability and increased value from the cloud, refactoring to microservices is an optimal method of modernization. For many organizations, modernization is the goal of getting the most value and scalability from the cloud. 

Microservices are modular with a loose coupling that allows them to be quickly deployed and updated, compared to the tightly coupled, large codebases of monolithic software. As mentioned above, the Strangler Fig Pattern is one way to refactor to microservices and modernize your applications and functions.

Instead of restructuring or replacing the monolithic codebase in a single step, the Strangler Fig Pattern allows you to break down the code into functions that can be replaced with microservices, step-by-step. You can take one function at a time and refactor it as a microservice, allowing you to test, configure, and deploy each microservice confidently. The approach aims to minimize bugs and errors, allowing you to seamlessly modernize without impacting users.

Modernize Your Applications to Optimize the Benefits of the Cloud

Using advanced tools can simplify migration to the cloud with automation and analytics that allow you to refactor monolithic architectures into manageable and cloud-native microservices. They allow you to upgrade from legacy Java and .NET frameworks to modern frameworks like Spring. vFunction can help your organization iterate large backlogs of functions to deploy in several release cycles or sprints for efficient modernization. Our platform can accelerate the process and reduce technical debt. Request a demo to explore the benefits of modernization with vFunction.

Discover how vFunction can simplify your modernization efforts with cutting-edge AI and automation.
Request a Demo

Architectural Observability Critical to Managing Tech Debt

Posted on October 20, 2023 by - Uncategorized

All businesses that depend on modern technology are affected by technical debt. According to a recent McKinsey survey, 10% to 20% of business tech budgets reserved for new projects is redirected to resolve issues related to tech debt. Even worse, unchecked tech debt can lead to operational disruption, slow engineering velocity, and stunt innovation. In the past, the exact origins of tech debt within a system or application have been difficult to pinpoint. Architectural observability gives developers the visibility they need to manage and diminish tech debt.

Understanding Technical Debt

The evolution of software is inevitable. Software developers must implement updates to meet users’ needs for new features, improved performance, or increased safety. On top of these requests, software must also be updated to meet the demands of a changing technological environment. For instance, most legacy apps need to become more modular and refactor or re-architect to increase engineering velocity, scalability, and developer productivity. 

In the most basic sense, technical debt occurs due to  the pressure to release new features quickly, where sacrifices, workarounds and shortcuts cause a product to deviate from its original architecture and nonfunctional requirements. 

These deviations cause technical debt to accumulate at both the code level and the architectural level.Unresolved technical debt results in hidden costs that are revealed later when an application becomes very expensive or impossible to fix. In the best-case scenario, it should be resolved during development instead of being deferred to future releases or after something goes wrong.

Understanding Architectural Observability 

No IT system or software application is perfect, at least, not for long. They change over time,, can’t keep up with current demands, and sometimes, crash completely. To address and remediate problems, development teams need measurable insight into how a system is architected. Such data makes it possible to identify and diagnose deeper architectural issues quickly to make repairs and maintain customer satisfaction.  

Observability is the ability to understand what is happening inside a system based on measurable data produced by that system. This data typically came from event logs, metrics, and traces. By tracking chronological events, quantitative measurements, and transactions completed through applications, analysts used this data to understand an app’s health and performance over time. The data was then applied to the business decision-making process. Architectural observability applies these same approaches to understand, observe, and fix software architecture.

Related: The Role of Observability in Continuous Refactoring

Applied observability allows businesses to plan proactively for improved decision-making. According to Gartner, by 2026, 70% of organizations that successfully apply observability will achieve rapid decision-making that improves their competitive edge for IT processes.

Architectural observability enables development teams to continuously refactor and modernize software without accumulating overwhelming technical debt. When architects can set a baseline to identify changes that affect software design, they can keep track of how architectures drift over time. With a better understanding of application architecture, architects can catch and fix architectural drift and tech debt issues early and often. 

The Role of an Architect in Managing Technical Debt

As we’ve seen, every business that relies on technology has some level of technical debt. However, no single individual or department is fully responsible for technical debt. In most cases, technical debt simply results from the need to meet business demands and release software as quickly as possible. Ad hoc changes resulting in additional tech debt can occur due to unexpected events upon software release. If technical debt cannot be traced to a definite source, it may quickly slide down the list of priorities. 

However, deferring technical debt will get expensive. Since architectural technical debt is a sub-optimal design that results in long-term costs related to the deterioration of standards and quality, it’s a trade-off in which architects accept the costs that will be accrued in the future. Yet, as technology evolves faster than ever, and the impact of these costs is recognized, efforts must be made to curb this process. With the right tools, architects can be in a position to address technical debt incrementally to manage it consistently. 

3 Reasons It’s Time for Development Teams to Play a Vital Role in Tech Debt Management

Development teams alone can’t be held responsible for managing technical debt. It’s essential for stakeholders and other decision-makers to recognize the requirements for tech debt minimization and support efforts for continual management. However, changing trends reveal the reasons architects and software developers will play the most active role.

Application Modernization

As technology changes, old apps must be restructured to eliminate technical debt and integrate into the modern cloud-centric tech environment via application modernization. If such changes are not made, business applications would become outdated and completely non-functional. Unfortunately, technical debt makes this process exceedingly difficult. 

Legacy apps typically feature a monolithic architecture in which the codebase is organized as a single unit. The single-unit architecture creates dependencies, where a single change creates ripples throughout the code, increasing technical debt.  

Modernization begins by iteratively refactoring the structure to a cloud-native distributed microservices architecture. Ongoing modernization is introduced to update apps to the constantly evolving cloud environment. When application modernization is approached with the objective of reducing tech debt, architectural drift and other critical technical debt contributors are more likely to be avoided. 

Heightened Regulations

Businesses are subject to certain industry and security regulations. To maintain compliance, the software and systems they use must meet modern security and reliability standards. In response to the increase in costly and dangerous cyberattacks, cybersecurity regulations are changing. 

The National Cybersecurity Strategy, released in March 2023, sets new standards for the parties responsible for insecure software products and services. Pillar 3 of the strategy is dedicated to creating a more secure digital ecosystem through improved products. Objective 3.3 notes that “too many [software} vendors ignore best practices for secure development” and produce products with insecure default configurations or known vulnerabilities. The framework goes on to say that future legislation will require companies that make software to be held liable for the production of insecure software. 

While these regulations haven’t been put into place, it’s clear they’ll be necessary to address the growing cybersecurity threat landscape. To achieve compliance, architects will need to integrate cybersecurity and the reduction of technical debt into software development. 

Modern Tools

In the past, finding the source of technical debt has been challenging. As software code is continually modified and expanded, the app’s codebase becomes more complex and bloated. When these changes are implemented quickly, and without documentation, dead code, class entanglements, and dependencies are left behind. Without the ability to see the internal structure of an app and how it operates, designers don’t have the data they need to manage the architecture and make necessary changes.

Related: How Continuous Modernization Can Address Architectural Drift

Dealing with technical debt requires a data-driven approach. If software developers don’t have the data to understand their current software architecture and how it’s drifting and changing, they can’t manage it. Tools that use machine learning to measure technical debt allow architects to prioritize tasks based on relevance and importance. 

With the ability to identify architectural drift events, developers can determine which coding issues affect the business and compare the cost of fixing the issue now to the potential costs of restructuring in the future. Modern observability tools help developers address issues associated with architectural drift and avoid increased technical debt.

How to Apply Architectural Observability to the Control of Tech Debt

The modern tech environment demands that development teams play a more active role in maintaining technical debt during the development and updates of applications. To effectively manage technical debt, architects need the right tools to measure the amount of effort that will be required to add new features to an app and the degree of disruption that adding new features will cause to existing ones. This information enables architects to prevent architectural drift by remediating architectural technical debt one fix at a time.

vFunction allows architects to set a baseline by which architectural drift can be recognized. You can then set thresholds and be alerted proactively to changes that are likely to result in technical debt. Once a fix has been applied, the manager can validate the fix and quantify improvements. Request a demo to learn more about how vFunction can help you use architectural observability to manage technical debt and enable successful application modernization.

Unlocking Excellence: Navigating the Path of Continuous Modernization

Posted on October 20, 2023 by - Uncategorized

Navigating the path through the complexities of technical debt, software architecture refactoring, and application modernization is a major challenge facing architects and development teams today. According to National Geographic, navigation is both an art and a science. The earliest forms of navigation used known landmarks to arrive at a destination. It wasn’t until sailors learned how to use the stars that they ventured onto the open seas. However, navigation also required correcting courses to avoid obstacles that could sink a ship.

While safely getting from point A to point B may have been navigation’s original goal, speed was also a concern. Reaching a destination during prime hunting season was essential for a reliable food supply. Navigators were continuously assessing routes to minimize delays. When navigation tools, such as sextants and compasses, became more reliable, expectations grew. Arriving within a particular time window wasn’t enough. Cargo was expected to arrive undamaged despite rough seas. Passengers traveled the fastest, most reliable routes. 

In the world of software development, the analogy of navigation finds its modern counterpart in continuous modernization. Similar to ancient navigators adapting to new tools, today’s software developers employ cutting-edge technologies for constant refactoring and refinement. Continuous modernization involves the ongoing process of updating software to match the evolving tech landscape. 

Just as sailors correct their course to avoid obstacles, developers identify and address challenges in real-time. By embracing continuous modernization, businesses ensure their software not only meets but exceeds user expectations, adapting swiftly to market demands and emerging technologies. This agile approach allows organizations to maintain a competitive edge and deliver seamless user experiences in the ever-changing digital realm.

Navigating a Path to Architectural Excellence

For software organizations, navigating a path to excellence means using human creativity and imagination alongside appropriate modernization tools for exceptional results. Just as early navigators watched their environment for changes, software architects must be able to see what is happening in real time to make adjustments before a disruption occurs. They must continuously assess their location to avoid drifting off course and creating unnecessary delays.

Unlike navigators of old, today’s software architects have access to architectural observability tools for end-to-end visibility. Navigators had to rely on knowledge passed from one navigator to another. Sailors learned the safest and fastest routes from centuries of shared experiences. But modern observability tools allow software engineers to condense years of monitoring into minutes. They do not have to wait months or years to correct structural flaws.

Related: Creating a Technical Debt Roadmap for Modernization

Organizations looking to modernize their applications must combine correction methods with observability to maintain a successful path of continuous modernization. These companies must tap into creativity and imagination to sustain a culture that successfully manages the journey of software evolution.

Why Visibility Matters in Software Architecture Excellence 

Navigational visibility means watching where you are going. It’s about using the next measuring point for determining direction. Suppose the destination is the mouth of the Amazon. Navigators can assume that as long as they keep the shore in sight, they will reach the Atlantic Ocean. What they can’t determine is how soon or how safely they will arrive. Without measuring the distance between a boat and the shore at frequent intervals, navigators do not know if they are on course.

The Science of Visibility

Navigating software modernization is no different. Development teams need to see what their code is doing. For example, teams have typically used the following tools to monitor code performance: 

  • Metrics. Teams can gather data on memory usage and requests per second to assess resource utilization.
  • Logs. Logs record events and errors that occur during execution. Teams can use logs to assess performance or identify anomalies.
  • Traces. Teams can use tracking tools to trace requests and responses as they move through a system to locate where execution errors occur.

These monitoring tools make visibility possible; however, the value of collected data depends on the extent and frequency of the measurements. That’s where the art of visibility enters the process.

The Art of Visibility 

How often a sailor measured a ship’s relative position depended on the navigator. Longer intervals between measurements increased the chances of drifting off course. Shorter periods between calculations could result in unnecessary course corrections that impact transit time. Finding the perfect balance was an art.

Today, 86% of international software development companies use an agile methodology, with the majority following a Scrum framework. That means updated software could be deployed every 30 days since the maximum sprint length is one calendar month. The official Scrum guidelines recommend incremental software releases at least every two months.

Although every sprint may not result in a release, DevOps should monitor each increment. For many organizations, that target may be unreasonable if sprints occur every two weeks. They may not have the resources to support such a pipeline. However, extending the time between measurements may allow the software to veer off course. Software teams must find the right balance.

Charting a Course for Software Excellence

Navigating an agile process is the same as navigating a boat down the Amazon. It’s striking the right balance to maintain a design without delaying releases. Waiting until development is complete to assess a codebase is like using the shoreline to navigate the Amazon. You’ll reach the Atlantic eventually, but the condition of the boat, passengers, and crew is questionable.

Incremental measurements make successfully navigating software modernization possible. Agile methodologies divide a project into intervals that enable organizations to deliver updates efficiently with less drifting and technical debt. The process ensures continuous improvement and is the cornerstone of continuous modernization strategies. 

Why Architectural Observability Is Essential

Architectural observability is the ability to analyze an application statically and dynamically and understand its architecture, observe drift, and find and fix architectural technical debt.

Success depends on the monitoring tools that enable architectural visibility, and the right tools make navigating modernization more reliable by looking at visibility data in context. Architectural observability makes managing architectural technical debt a science—based on data.

The Art of Observability

Observability tools give architects and engineers more time to explore unique and innovative solutions. They provide better control over a system’s architecture as it evolves. Deploying architectural observability solutions allows software teams to experience the art of observability.

When software teams operate reactively, they have little time to look beyond the immediate problem. Their response can often lead to more technical debt. Like a becalmed sailing ship, they cannot progress. Their modernization journey stalls.

Carefully monitoring observability results enables organizations to address architectural drift before it becomes a problem. They can break down the tasks into segments that can be accomplished incrementally with less impact on the modernization process. Development teams can incorporate architectural changes into their normal workflow, minimizing disruptions.

Related: How Continuous Modernization Can Address Architectural Drift

The art of architectural observability involves learning how to use the right tools. Selecting and deploying these tools frees architects and engineers from mundane monitoring tasks. They have time to discover solutions and devise implementation plans that deliver results without disruption.

When architectural drift is allowed to continue, the build-up of technical debt eventually grinds developer productivity to a halt, and the resulting corrections must disrupt development because they must be deployed quickly. Those disruptions can lead to frustrations. When architectural corrections are integrated into the continuous modernization process, technical debt is managed and workflows are not interrupted.

The Science of Architectural Observability

Navigation tools have moved far beyond the sextant. Today, navigators rely on global positioning systems (GPS) to determine their relative position. These satellite-based systems use contextual data to update routes when unexpected disruptions occur, and they recalibrate directions when an object moves off course.

Software architecture observability tools provide architects and engineers with similar capabilities. They can analyze application architecture, identify possible concerns, and monitor technical debt. They can even suggest an appropriate path to success.

The right architectural observability tools continuously monitor system architecture for the following:

  • Sources of technical debt such as cross-domain pollution, database relationship violations, and high debt classes.
  • Deviations from baseline, such as new services or classes, dead code, or exclusivity changes.
  • Anomalies that weaken architectural integrity.

Architectural observability delivers contextual data and actual “to-do” lists in real-time for a more comprehensive analysis and a better understanding of system performance. Architects can proactively address technical debt and architectural drift using more robust information. They can assess the impact and respond proactively rather than devise a reactive solution to an immediate problem. Much like early navigators, teams that make reactive decisions cannot assess the ramifications to the overall journey.

Unlock Software Excellence with Architectural Observability

Companies can continue to operate with the tools equivalent to a navigator’s sextant and compass. They can wait years for their collective experiences to lend accurate observability. Alternatively, they can use the equivalent of a GPS system to guide their modernization efforts, and they can take advantage of advanced architectural observability tools to ensure a continuous modernization process that delivers software excellence.

vFunction’s Architectural Observability Manager is a solution that incorporates the art and science of navigating a continuous modernization path. Businesses can consistently achieve software excellence by relying on AI-driven tools that offer a reliable path forward. To see how we can help you navigate your modernization journey, request a demo.

Taking Control of Technical Debt: Refactor Applications

Posted on September 25, 2023 by - Uncategorized

While we may have reached the peak of digital transformation efforts, the hardest challenges surely lie ahead. According to Gartner estimates, 91% of businesses are now engaged in some type of digital initiative, but the increasing adoption has also unveiled some significant shortcomings of extensive digital development. Large, monolithic software solutions can no longer offer the necessary flexibility and efficiencies of modern applications.

Against that backdrop, continuous refactoring is taking on an essential importance for today’s companies. The ability to continuously update your legacy apps, in fact, might just be the key to taking control of your technical debt and driving sustainable innovation in your digital processes. 

Continuous Refactoring to Microservices

At its core, continuous refactoring describes a process of ongoing improvements using architectural observability. It’s the process of identifying which of your applications are in need of refinement and overhaul, then refactoring its code to improve performance and efficiency without affecting its functionality.

The process becomes especially important when moving from a large, monolithic software solution to a more agile microservices architecture. Turning your rigid, centralized application into more loosely coupled, independent services provides a few major advantages, including:

  • Improving the flexibility and agility of your system, enabling you to work on individual pieces as needed.
  • Enhanced fault isolation in cases of failure, providing the ability to work on any failed modules without compromising the greater whole.
  • Greater simplicity of individual modules that allows for faster onboarding of new engineers working on individual modules.
  • Increased scalability that can be focused on individual modules, without the larger system needing to move and adjust comprehensively.

Finally, and perhaps most importantly, a move to a microservices architecture requires what we’ll describe throughout this guide: a shift to a continuous refactoring approach that can ultimately benefit your entire business.

Why Incremental Transition is Crucial to Your Microservices Architecture Journey

Make no mistake: modern software development has to be agile. To build the digital infrastructure of your business increasingly means not building a foundation designed to stand forever, but creating a flexible infrastructure that can shift and evolve as your business evolves—the above-mentioned microservices architecture.

But building that infrastructure also means rethinking the way you consider transitioning, scaling, and improving any of your software applications.

70% of digital transformations fail, and “taking on more than you can chew” is a major reason why. Stopping all of your team’s ongoing work to focus on a huge new project is nearly impossible, and never recommended. Instead, any implementation of a microservices infrastructure has to focus on a more incremental approach.

The Downfalls of the Big Bang Approach to Transformation

When executives think of software innovation and transformation, they almost always envision a ‘big bang’ effect. Company resources are pooled toward some type of major software milestone, which—once achieved—transforms the entire business operation. With that big bang, a new universe appears, transforming every piece of the business.

Unfortunately, taking this approach is a recipe for failure, both short-term and long-term. It takes resources away from ongoing innovations and improvements, while also building large and inflexible solutions that, especially over time, build significant technical debt and—thanks to architectural drift—may not even accomplish its original objectives.

It’s how the monolithic applications that now drag down the business came to be. And it’s the exact problem that a microservices architecture built on continuous refactoring is designed to solve.

Continuous Refactoring as a Remedy to Innovation Impediments 

At its best, modernization can never be a project. Instead, it’s an ongoing process that continues to account for new variables, business needs, and improvement possibilities. 

For organizations putting a microservices architecture in place, that approach becomes a core requirement. It means building smaller, more agile services at a time, incrementally creating the more innovative processes your business needs to succeed long-term.

Big technology systems, it turns out, tend to slow innovation to a crawl. They make the process less dynamic, making it more difficult to be as agile as needed to move quickly where possible.

Innovation on the back of these big systems also requires such a massive undertaking that it can hamper the regular work needed to keep the lights on. Continuous refactoring, on the other hand, uses architectural observability to bring a more dynamic approach to the issue, ultimately providing a core remedy to the increasing technological impediments many businesses built on monolithic applications face.

Related: Benefits of Adopting a Continuous Modernization Approach

Solving the Technical Debt Problem

At a time when the average company carries between 20% and 40% of their technology’s value in technical debt alone, efficiency naturally suffers. The necessity of taking shortcuts in major development projects, along with an inability to build solutions into a rigid process, can lead to code issues that significantly cut into profitability and time available to move your technology systems forward.

The ability of a continuous refactoring approach to address the architectural technical debt issue is one of its major advantages in these scenarios. At its core, it leverages architectural observability, enabling development teams to monitor, detect, and fix any architectural drift issues within the larger system. This, in turn, enables developers to fix problems within a single system incrementally, ultimately solving technical debt one issue at a time. 

Over time, using architectural observability to determine priorities for ongoing optimization becomes a massive advantage for the developer and the organization as a whole. They are able to extract one microservice application at a time, or even hone in on individual technical debt code sections, working on small improvements that slowly improve the probability of success without losing track of other development priorities. That gradually reduces technical debt without compromising your ability to continue innovating.

Related: How to Prioritize Tech Debt: Strategies for Effective Management

Crucially, continuous refactoring also prevents your architectural technical debt from re-accumulating over time. Because you are able to analyze different issues and microsystems simultaneously, you’re able to prioritize parts of the code that have bigger issues—to make a bigger impact. Fixes are designed to drive toward core organizational priorities, minimizing the chances of architectural drift that could introduce future technical debt as the organization keeps evolving.

Reducing Risk 

Ultimately, and at least partially due to the other benefits mentioned above, a continuous refactoring approach that helps you evolve to a microservices architecture has the potential to significantly reduce risk for your technology infrastructure. 

Aging code naturally bears a wide range of risks:

  • Organizational knowledge of the code diminishes over time, leaving fewer developers to be able to understand and fix potential issues.
  • Individual modules can become “hidden” within larger applications, making them difficult to find and fix within that larger context.
  • Technical debt increases over time, as newer and more efficient solutions can make older and more unreliable sections of the code obsolete.

At best, those risks become a concern for an organization looking toward innovation and the future. At worst, they can endanger the operational security and reliability of the entire organization. It’s why outdated technology can waste billions of dollars, not to mention the potential costs of a data breach that happens due to the outdated code. 

Against that backdrop, continuous refactoring has the potential to be a literal lifesaver for your organization. An ongoing approach to identify, prioritize, and fix outdated code and applications has a direct impact on all of the above risks, ultimately resulting in a safer and more future-facing technology infrastructure for your business.

Transform Your Application Infrastructure with a Continuous Modernization Approach

The world of digital transformation is undergoing a sea change. Simply moving applications into the digital realm is no longer enough, especially when those applications become chunky monoliths that are difficult to evolve, scale, and adjust in a way that benefits your business long-term. 

Instead, modernization and innovation have to become an ongoing process. That means splitting large applications into a more decentralized microservices architecture, making it easier for teams to scale and remain agile in their development process. It also means taking a continuous refactoring approach to modernize, extract, and then improve individual microservices or even sections of code individually, making gradual improvements without compromising the larger structure and functionality.

Of course, that process doesn’t happen on its own. You need a system designed to identify your existing technical debt and assign priorities to them in a way that enables more specific development targets for you to move into a more flexible environment. Continuous refactoring is only effective if you always know what and where to shift your attention to at any given time.

With the right platform in place to accomplish that goal, your transformation and innovation efforts can accelerate drastically. And that’s where vFunction comes in, thanks to an automated solution that dynamically identifies and evolves monolithic applications into more dynamic, future-facing microservice structures. Ready to get started? Request a demo to learn how you can implement and benefit from our continuous modernization platform today.

Continuous Modernization: Tacking Across Headwinds

Posted on September 21, 2023 by - Uncategorized

Introduction

You have picked a new destination for your applications that will bring efficiency, ease of maintenance, and upgraded technology, but you are finding that you have to continuously tack due to headwinds such as:

  • Budget shortages
  • Required upgrades
  • Safety and security patches
  • Priority maintenance and enhancement requests
  • Conflicting business priorities
  • New applications for new revenue streams, or new customer acquisitions.

You can’t get where you want to go in a direct, straight line because of all the conflicting interests and priorities for application maintenance, enhancement, and replacement.

It is not at all clear how you will achieve your goals of modernization, paying down technical debt, and addressing architectural debt, despite the clear business value of doing so.

The first thing to do is identify a target state to codify the strategic business value of the modernization program. The target describes the future state of the IT systems post modernization and ties it to strategic business value such as increased revenue, improved cost efficiency, or supporting the launch of a new product.

If you’re sailing a boat, your target would be a landmark on the other side of the river. If reaching your target means you are sailing into the wind (i.e., you have headwinds), the only way to make progress is to tack across the wind from side to side and make progress incrementally.

An IT practice called “Managed Evolution”1 describes in detail how to continuously make progress toward the business value achieved through modernization.

tackling headwinds figure 1
Figure 1, Central Principle of Managed Evolution

As shown in Figure 1, the central principle of managed evolution is to evaluate each proposed modification to the system in the context of whether or not it helps you to move you closer to the desired system state. The framework allows you to assess the incremental business value of doing so, and therefore help decide whether investments are strategic or not.

It is of course impossible to align every modification to achieving the target, resulting in the zig-zag journey shown in the diagram. It’s like sailing into the wind – you can see your destination, but you can’t head straight toward it. You have to make progress sideways and incrementally.

Modularity to Reduce Complexity

One strategy for implementing the managed evolution approach is to use abstract interfaces to modularize legacy system functionality so that it can be updated without impacting the user-facing part of the application.

For example, wrapping a legacy system function using a REST API transforms the legacy data format into a standard JSON payload for web and mobile applications. Once this is in place you can upgrade the back-end technology without disturbing the API consumers.

Once you have the abstract interfaces in place, the next step is to break out common components into individual services, such as microservices for example.

Recently there’s been a lot of debate about whether monoliths are better than microservices, but this really misses the main point, which is the advantage of modularity. Many studies over the past decade or so have clearly shown that modular systems are easier to maintain and change.

Of course, there’s no single right answer for every application, but in thinking about microservices it’s important to keep in mind how they align to the principles of modular systems.

The first step in moving from a monolith to a modular services architecture is to incrementally break out common functions into independent components, as illustrated in Figure 2.

For example, break out a common function or domain such as a customer lookup or price calculation, deploy it independently, and access it from multiple applications using a REST API.

Once you break out and modularize a critical mass of services, you can start constructing entire applications out of them, effectively replacing the monolith.

The most challenging part can be figuring out the modularity of the interfaces. Practices such as Domain Driven Design (DDD) and Service Oriented Architecture (SOA) can help.

Another very good reason for moving to modular systems is that services can be implemented using different programming languages and software systems. Some might be implemented using Java and deployed using a Java EE application server. Others might be implemented and deployed using .NET.

Modular systems are easier to maintain and evolve and are easier to update and deliver to production. Modular systems also improve developer productivity by dividing up the work.

Staying on Track

Even more important than defining the target state is documenting the current state and finding a way to measure progress from the current state to the target state, daily if possible.

Measuring progress frequently helps the modernization project stay on track and get a handle on how much architectural debt is being paid off. Paying down architectural technical debt is like paying off credit card debt – it has incremental benefits. The more you modularize your systems, for example, the easier they are to develop, maintain, and change.

So, this would be a good measure of progress for example to measure how many independent services have been created? How many abstract interfaces? What is the reuse count of independent services (i.e., how many applications consume them)?

First, get a good picture of what’s out there. Then decide on a methodology or architectural framework to guide the journey from current to target (and by the way, it’s always a target because it moves).

Adjustments to the target state should be made regularly as the modernization work progresses. Documents and designs must be kept up to date during the project to reflect changes that inevitably occur. Ensure that the implementation aligns to the architecture, and update continuously. 

How does vFunction Help?

vFunction analyzes the architecture of your Java and .NET applications to identify domains and score your technical debt. It also identifies candidates for modules or domains that can be broken out and hosted as independent, shareable services.

vFunction can help set the architecture baseline for the current state and uses architectural observability to detect drift, prescribe fixes, and send alerts to architects about architectural events and other actions on high debt modifications. In other words, it helps track progress toward the target state goal and regularly scans and reports on the evolving architecture.

vFunction also helps achieve modularization by refactoring monoliths into microservices and generating abstract APIs for them.

The Intellyx Take

Application modernization is a continuous journey across a jagged line of organizational headwinds. It’s more of a process than a technology, but the right technology can help a lot.

vFunction provides a unique set of tools to help architects understand where they are starting from in the journey, how far they have progressed (and whether course corrections are needed), and to automate the work around modularization, decomposition, and service abstraction.

The capabilities of these tools promise to be extremely valuable to anyone undertaking the continuous modernization zig-zag journey.

Copyright © Intellyx LLC. vFunction is an Intellyx customer. Intellyx retains final editorial control of this article. No AI was used to write this article.

Image by Tim Green, Creative Commons license

[1]See:  https://www.amazon.com/Managed-Evolution-Strategy-Information-Systems/dp/3642016324