Gitlab Feature Flag vs Nected.ai: Which Is Best In 2024

Feature flags act like adjustable curtains inside the software development technique, allowing developers to selectively unveil or hide precise functions. This gives flexibility in testing, rolling out, and coping with new functionalities within the CI/CD pipeline. In the context of CI/CD, which is similar to constructing a Lego structure collaboratively or baking a cake, developers regularly combine their code changes to ensure a clean in shape.

Continuous Delivery prepares software for transport with every code exchange, while Continuous Deployment automates the process, immediately setting the software program at the production table. In summary, with the help of characteristic flags, CI/CD will become an green assembly line for software improvement, fostering seamless collaboration, thorough trying out, and quick, reliable delivery of updates to customers.

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The above example shows how feature flags work in a scenario where real time testing is required by enabling a portion of the users to test new features and gradually roll out to everyone so any performance issues can be identified.

Why are feature flags important?

Here are the key reasons why feature flags are significant in context of modern software development-

• Progressive Rollouts: Enable gradual deployment of functions to display performance earlier than full launch.

• A/B Testing: Facilitate trying out more than one feature version with exclusive user corporations for statistics-pushed choices.
  
  

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• Continuous Deployment: Support continuous deployment by using hiding functions in the back of flags until ready for release.

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• Rollback Mechanism: Provide a smooth way to roll again features if issues stand up after deployment.

• Dark Launching: Allow deployment of capabilities to production without immediate consumer visibility.
  

• Decoupling Deployment and Release: Separate the deployment of code from its launch to end-users.

• Configuration Management: Serve as a dynamic configuration device for controlling application conduct.

Incorporating feature flags enhances flexibility, control, and self assurance in dealing with software deployment, contributing to a more adaptive and resilient improvement manner.‍

What is Gitlab?

GitLab is an internet-primarily based DevOps platform that provides a complete set of equipment for supply code management, non-stop integration, continuous transport, and more. Its role in CI/CD is substantial, because it offers an included environment for handling the entire software program improvement.

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Feature Flags in GitLab

GitLab, a versatile platform for collaborative software program improvement, gives developers the flexibility to put into effect feature flags using diverse processes, which include conditional statements, surrounding variables, and custom scripts.

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Developers can leverage GitLab CI/CD capabilities to seamlessly control function flags as a part of the deployment technique, enabling managed rollouts and green checking out of functions in particular environments.

Furthermore, GitLab gives seamless integration with third-party function flag manipulate equipment, allowing builders to utilize specialized services alongside GitLab CI/CD for centralized control of function flags.

The GitLab CI/CD pipeline helps the automation of the deployment process, facilitating the combination of function flag management into the general workflow.

By the use of environment variables in GitLab CI/CD, builders can successfully set and manipulate function flags throughout specific stages of the pipeline. This complete method showcases GitLab's dedication to imparting an adaptable characteristic flag implementation, making it an critical tool for green software program improvement.

Read Also: What Is Feature Flag Management and Why Is It Crucial

Drawbacks of Gitlab Feature Flag

Although the Gitlab feature flag can be useful, it can create some problems from the perspective of a small ecommerce business or a startup that has limited resources and time to deliver efficient applications

One of them is “technical debt” For instance, feature flags may be forgotten and left as stale code, leading to increased complexity and protection overhead.

Additionally, the flawed application of function flags can affect system overall performance and create challenges in phrases of coping with dependencies among specific flags.

Unused flags often creates slowness and confuses developers while reviewing code as the scripts can be lengthy and might take up processing time to execute functionalities. Nected.ai can be the solution for this as it has an easy to use user interface when it comes to enabling and disabling feature flags.

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In this blog we will be highlighting some key comparisons and how Nected’s Experimentation Engine can be a better alternative to Gitlab’s feature flag.‍

Nected.ai’s Feature Flag (Experimentation Engine)

Nected's Experimentation Engine is a effective tool that lets in devlopers to test one-of-a-kind functions of their app quite simply. It's now not just about turning functions on and off; it is a complete tool that allows teams to run all sorts of assessments, including checking unique variations of capabilities or attempting out more than one thing immediately. The pleasant part is that it's notably user-friendly and doesn't require complicated code. With this device, groups can check their ideas, the use of actual statistics, phase customers into one of a kind organizations, and strive out adjustments in how the app works for an extra personalized experience.

Implementation

Nected’s Experimentation engine can be implemented in just 4 easy steps to your existing environment -

STEP 1: Connecting to Data source‍

It's quite simple to go to the integration page of Nected.ai and select the database that suits your requirement and click on connect . You might need to provide connection details but generally that gets auto populated in most cases . Just hit Save and you're good to go .

STEP 2: Create & Publish

Utilizing the no-code editor is easy: define conditions, pick favored output from the dropdown, and click Publish.

For example, it's ideal for scenarios requiring conditional reductions. A few clicks, and clients word the distinction, eliminating the need for codebase adjustments—a substantial relief.

STEP 3: Attach Actions and Reuse 

Depending on the rule results actions can be configured and can be saved as API functions  which in turn can be reused in scenarios as required.

STEP 4: Ready to Call API
Nected is ready to offer you smooth workflow orchestration and integration capabilities. Imagine a customer should get 15% discount on shoes from your website if he is buying products over 10000/-  So the condition and rule configuration should somewhat be like

When

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Cart value “is greater than” 10000/-
Item is “shoe”
Discount is “15%”

 then

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 {SHOW PRICE  —- (SHOE PRICE *15%)}   will be added to the cart value.

Now this can be implemented in other scenarios by changing values .

‍Below are the highlights of Nected.ai’s Experimentation Engine 

• It can be implemented in 15 minutes
• Embedded within a low-code, no-code rule engine
• Empowers non tech teams 
• Less than 1 hour of development effort is required 
• On premise setup can be done for enhanced security
• Custom solutions provided

Gitlab’s Feature Flag vs Nected.ai Feature flag : The Comparison

As we navigate via the function control landscape, the contrast between Nеctеd.Ai and GitLab's function flags well-known shows wonderful strengths. While GitLab is a comprehensive DevOps platform, Nеctеd.Ai emerges as the superior preference inside the area of function flags, offering dynamic rule creation and a streamlined technique to workflow automation.

Choosing Excellence in Workflow Automation:

The choice between GitLab's function flags and Nеctеd.Ai is pivotal for organizations seeking pinnacle-tier workflow automation. Consider the particular desires of your enterprise, and explore both answers diligently. Nеctеd.ai beckons as the desired preference, promising streamlined, user-pleasant workflow automation that goes beyond the skills of GitLab's function flags.

Why go for Nected’s feature flag aka Experimentation Engine?

In the dynamic realm of characteristic control, Nеctеd.Ai shines as a standout solution, bringing forth a powerful aggregate of a sturdy rule engine and dynamic workflow automation. Let's delve into a comparative exploration, highlighting how Nеctеd.Ai outshines GitLab's feature flags in turning in extraordinary performance and innovation to businesses.

Tailored Workflows with Precision:

Nеctеd.Ai's in-house rule engine empowers corporations to tailor workflows precisely to their unique desires. Unlike GitLab, Nеctеd.Ai leverages dynamic rule creation based totally on feature flag effects, presenting a level of customization that goes past conventional techniques. This guarantees not simply productive profits however also tangible price savings for agencies.

Cost-Effective and Value-Driven Plans:

While GitLab gives feature flagging abilities, Nеctеd.Ai takes the lead with pricing and plans designed for greatest value-effectiveness. Nеctеd.Ai stands proud as a cost-pushed choice, offering strong capabilities and low cost answers that make sure every funding counts, making it a strategic choice for corporations with budget considerations.

Decoupled Deployment for Dynamic Changes:

Nеctеd.Ai embraces a decoupled deployment approach, liberating characteristic releases from conventional deployment cycles. This flexibility allows for dynamic adjustments without vast redeployments, providing agility in adapting to evolving business needs—something not as seamlessly completed with GitLab's characteristic flag implementation.

Simplified Management with User-Friendly Interface:

Managing guidelines and workflows ought to be intuitive, and Nеctеd.Ai guarantees simply that with its person-pleasant interface. GitLab's feature flags may additionally offer control abilities, however Nеctеd.Ai simplifies the complexity associated with feature flag proliferation, empowering groups to cognizance of innovation in preference to grappling with convoluted methods.

Enhanced Granularity for Precise Control:

Nеctеd.Ai introduces a finer stage of granularity, giving groups precise control over function releases. In comparison, GitLab's function flags may lack the identical stage of nuanced control, making Nеctеd.Ai the desired preference in situations where in precise, granular management is vital.

Why buy a Rule-Engine when you can build it in-house?

1. Time is money , building a rule engine in house is time consuming and can affect the main codebase adversely .

2. As time passes companies scale and complexity increases, maintaining an in-house rule engine will create unwanted dependencies on developers and might not be a productive effort . So a better option is Nected’s Rule Engine.

3. The user interface required for allowing business teams to easily view, edit, and monitor regulations is also an extra effort that can be outsourced so that employees can focus on making more business.

4. Post-Deployment Challenges:

Testing: Develop solutions for post-deployment checking out to make sure changes do not adversely have an effect on the device.

Model Management: Address the need for an effective model to manipulate and music adjustments in regulations.

Analytics: Implement analytics equipment to evaluate the overall performance of the rules engine and pick out regions for improvement.

Data Integration: Resolve demanding situations associated with connecting the guidelines engine with diverse information sources, each inner and outside.

5. System Complexity:

Managing Data Sources: Handle the complexity of connecting with exceptional data resources, together with internal databases, CRM systems, and third-birthday celebration vendors.

Components Maintenance: Maintain a couple of components, together with UI, rule execution device, version control, analytics, records connectors, and checking out abilities.

Deployment System: Establish a deployment gadget with redundancies to ensure the policies engine meets service stage agreements (SLAs).

6. Concerns about open source components:

Limited Suitability: Highlight the textual content's emphasis at the belief that depending entirely on open source components might not be sufficient to address the intricacies involved in retaining a complete regulations engine machine.

Read Also: Fraud Detection: A Comparative Analysis with Neo4j and Nected

Conclusion: Elevating workflow automation with Nected.ai

In this exploration of feature flags and workflow automation, the distinctions between Nеctеd.ai and GitLab's characteristic flags are obvious. Nеctеd.ai emerges as a powerhouse, imparting a dynamic rule engine and streamlined workflow automation that outshines GitLab's function flags.

We encourage readers to explore and implement Nеctеd.Ai's Experimentation Engine in their projects. With features like quick implementation, low/no code, and data-driven rule creation, Nеctеd.Ai promises to elevate the efficiency of workflow automation. Check out how Brightchamps , an edu tech company reduced their development time by 50% by implementing Nected.ai.

Your feedback matters! If you have explored Nеctеd.ai or have reviews with characteristic flag control, percentage insights you can reach out to us. The remarks make a contribution to the collective expertise of premier feature management. Happy exploring, keep automating!