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Overcoming the Challenges of DevOps Tool Fragmentation

You are currently viewing Overcoming the Challenges of DevOps Tool Fragmentation

The software development landscape has become extremely complex. To meet the growing list of requirements and expectations and drive operational excellence, teams end up using too many DevOps tools. The reliance on different tools by different teams makes the tool landscape extremely cumbersome. As the size of the software project increases, new toolsets that get added to tackle unique problems lead to complexity, fragmentation, and gaps in quality and security. 

With multiple distinct solutions to manage, it can be difficult to keep track of tasks and activities across your software pipelines. In this blog, we will look at DevOps tool fragmentation in different industries, the causes and challenges, the benefits of DevOps platforms, and best practices for achieving tool integration.  

The Challenges of DevOps Tool Fragmentation in Different Industries 

As DevOps gets adopted across different industries, the challenges of tool fragmentation become more and more rampant. Here’s how DevOps tool sprawl impacts different industries: 

  • Telecom: In the telecom sector, point solutions fail to deliver the intended DevOps benefits while also adding complexity and potential weaknesses to security processes.
  • BFSI: For BFSI organizations, unchecked tool sprawl can impact the total cost of ownership (TCO). Since every extra tool comes with its own infrastructure, upkeep, training, and integration costs, it can lead to uncontrollable development costs for Fintechs. 
  • Manufacturing: In the manufacturing industry, where supply chain disruptions are perennially wreaking havoc, DevOps tool fragmentation makes it difficult for organizations to bring products to the market quickly. Having too many tools—as opposed to a single, unified environment—leads to gaps and disconnects in the development process. 
  • Automotive: Automotive companies that rely on an array of siloed tools end up spending more time navigating between windows than writing code. This impacts the quality and timeliness of code development, which can eventually lead to a weakened market standing. 
  • Retail: For retail companies, the problem of tool fragmentation can result in increased technical debt. Going back and forth between different tools reduces development efficiency, thus demoralizing the team. 
  • Hi-tech: In the hi-tech industry, DevOps tool sprawl tends to disrupt the creative mindset of engineers. Being forced to navigate their way through an array of unstandardized and badly integrated tooling can break their flow, reducing their ability to innovate and solve problems. 

The Causes of DevOps Tool Fragmentation

When teams use different DevOps tools to carry out different tasks and accomplish different goals, a lot of time is wasted in manual data translation, causing bottlenecks and other barriers to development. Here are two main factors that cause fragmentation: 

  • Siloed departments: The objective of DevOps is to bridge the boundaries between different departments and enable better collaboration. Yet, in many organizations, departments continue to be siloed, which causes DevOps tool fragmentation. With every team choosing its tooling, attempts to standardize tools and particular aspects of the lifecycle often go in vain. 
  • Individual tool choices: Another major reason for DevOps tool fragmentation stems from individual tool choices. In most industries, different teams end up investing in different tools for different purposes. Each of these tools is chosen due to various individual user requirements – from simple user interfaces to reporting capabilities, project management, and more.  

The Challenges of DevOps Tool Fragmentation

DevOps tool fragmentation causes several issues for organizations. 

  • Leads to siloed data: Organizations that rely on a multi-tool approach have different users across the DevOps life cycle, utilizing different tools. This feeds into the people and process sides of DevOps, causing data to become siloed. Unchecked tool sprawl resulting from a poorly integrated set of tools often compels teams to implement ad-hoc solutions – which further decreases the resilience and reliability of the toolchain.
  • Increases tech complexity: DevOps tool fragmentation can cause several technical challenges for large projects with hundreds of developers. If every developer ends up using a tool of his/her choice, it will add to the overall complexity of software development.  It also impacts the rate of innovation in the DevOps architecture because of the risks involved in breaking the existing infrastructure.
  • Limits visibility: Organizations that rely on a diverse pool of DevOps tools do not have sufficient visibility into the enterprise. Since data is restricted within each tool, teams find it very difficult to get a clear and detailed view of the software project. 
  • Reduces collaboration: DevOps tool fragmentation is also known to reduce collaboration. Since different teams rely on different sets of tools, they end up working in silos. They also spend a lot of time extracting data from one tool and mapping it with data in another tool.This negates the underlying premise of DevOps which is built on the foundation of collaboration.  
  • Leads to poor decision-making: DevOps tools, when fragmented, also lead to poor decision-making. The lack of a single source of truth causes teams to make decisions based on limited or partial data, which impacts software quality and accuracy in the long run. 
  • Obscures the true potential of DevOps: The absence of an integrated approach to using DevOps tools also limits ROI from DevOps investments. With tool sprawl, teams are more likely to have impaired observability, as data between different tools lies in silos. How Modern DevOps Platforms Help Overcome Fragmentation

Modern DevOps platforms like Atlassian, AWS, GitLab, JetBrains, JFrog, etc. help organizations take a more consolidated approach to tools. 

DevOps platforms offer integrated capabilities across the SDLC, including: 

  • Continuous integration or CI, that ensures the work items of individual developers continuously brought together into a single place. 
  • Continuous delivery, ensuring new features, updates, and changes are constantly integrated and delivered to end users. 
  • Release orchestration, helping coordinate automated tasks performed by multiple systems, ensuring environments are refreshed continuously, and changes are deployed promptly. 
  • Value stream mapping, allowing teams to measure the flow of work across the SDLC, identify waste, streamline the development process, and enable efficient handoffs. 
  • Secure software delivery, enabling teams to build software in a secure, compliant, and optimized environment and make the most of role-based access control measures.  

DevOps platforms support multiple use cases, such as: 

  • Agile software delivery by taking iterative, incremental, and lean approaches to streamline and accelerate the delivery of features. 
  • Mobile app delivery, allowing DevOps teams to build, test, and deliver native mobile and mobile web applications. 
  • Edge computing scenarios by offering support for secure delivery and updates for IoT and edge devices. 
  • Regulatory requirements, enabling teams to ensure compliance with required regulations, carry out auditing, drive traceability, and maintain governance. 
  • Cloud-native application delivery, empowering teams with the capabilities they need to build and deliver cloud-native applications across hybrid and multi-cloud environments. 
  • Platform engineering that delivers self-service, internal developer platforms to scale DevOps, and access to modern software engineering practices. 
  • They break down silos and reduce cognitive load, by utilizing prebuilt integration capabilities. 
  • DevOps platforms also streamline workflows and improve visibility, auditability, and traceability into the software development value stream. 
  • In addition, they deliver faster customer value by simplifying the creation, maintenance, and management of individual components required for the delivery of modern software applications. 

Strategies for Achieving Greater Integration

Despite substantial investments in DevOps tools, organizations are not reaping the full benefits of agility, speed, and quality. 

Here are some strategies for achieving greater integration: 

  • Clarify your DevOps strategy: The first step to minimize DevOps tool sprawl is to clarify your DevOps strategy. Understanding what work needs to be accomplished by whom, how the project must progress, and what issues or bottlenecks need to be addressed is crucial to getting a deep understanding of the tools you would need to accomplish all your DevOps objectives. 
  • Document critical processes: To achieve greater integration across the DevOps tool chain, documentation is key. Documenting critical processes helps in understanding the gaps and challenges in integrating the tools. It helps in crafting a strategy that maintains team efficiency. It also aids in creating key integration KPIs and enabling the right capabilities. 
  • Consolidate and clean up: If your organization is using several different tools today and wants to move to a platform approach, it is best to consolidate and clean up. You must conduct a detailed assessment of your existing tool environment, integrate the important tools, and get rid of those that do not add any value. 
  • Invest in an observability platform: Embracing an observability platform like the ones offered by Atlassian is a great way to analyze and extract insights from multiple tools.  Such a platform can combat data silos and the dangers they bring and minimize tool sprawl. By consolidating observability and monitoring into one platform, you can fix your fragmented tool chain and drive greater ROI from your DevOps tool investment. 
  • Embrace low-code solutions: Instead of investing in a new DevOps tool every time there is a new requirement, you can explore the capabilities of low-code solutions. Low-code platforms offer a quick and easy way to meet application development requirements – with little or no coding. For instance, you can use AWS CodeBuild to package and deploy serverless functions to AWS Lambda and compile source code, run tests, and produce ready-to-deploy software packages.
  • Go serverless: Just like low-code solutions, serverless tools like GitLab can enable you to take advantage of event-driven code execution. This can enable you to build massively scalable and cost-efficient applications composed of small discrete functions without needing to design for or think about the underlying infrastructure where their code runs.

Wrapping Up

As expectations from software applications continue to surge, the reliance on DevOps tools is constantly growing. However, siloed departments with individual tool choices often lead to DevOps tool fragmentation, which can cause several issues and bottlenecks for organizations. 

Using DevOps platforms like Atlassian, AWS, JetBrains, GitLab, and JFrog is a great way to minimize tool friction resulting from complex tool chains, manual handoffs, and a lack of consistent visibility throughout the SDLC. These tools, when combined with best practices, can enable product teams to deliver faster value without compromising quality. 

Are you ready to consolidate technologies across development, security, infrastructure, and operations and streamline software delivery?

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