Guide: How to Create Observability-Driven Development with Feature Flags

Savan Kharod
February 16, 2024

When releasing features, the key to success lies not only in deploying the code but in doing so with a keen awareness of its impact. Enter Observability-Driven Development (ODD), where we trade in uncertainty for a GPS-like precision in understanding our code's journey. Imagine a world where you not only release features but also watch them unfold in real-time, tweak them on the fly (without needing to redeploy), and ensure they hit the right mark for your users.

Say your team's monthly deployment happens tomorrow. You're upgrading a feature and feel confident in your code, but aren't sure how feature usage is changing over time and whether its having the desired impact. 

Observability-driven development is key.

ODD offers a new approach to development that prioritizes vigilance and adaptability. You gain greater control and insights into your projects (and a clearer view of your features’ impact) by combining ODD with feature flags

What is Observability Driven Development (ODD)?

Observability Driven Development (ODD) means actively observing and understanding the performance, behaviour, and impact of code in real time. It involves integrating observability tools and practices in the development process to gain insights into how features behave post-deployment.

What are Feature Flags and How Do They Relate to ODD?

Feature flags, also known as feature toggles or feature switches, are a software development technique that allows developers to turn certain features or functionalities on or off at runtime. Feature flags provide a way to control the availability of specific features within an application without altering the codebase.

Feature flags open the door to:

  • Conditional Control: Feature flags enable developers to conditionally control the execution of specific features by wrapping them in conditional statements. This means a feature's visibility or behaviour can be determined dynamically, often without redeploying the application.
  • Gradual Rollouts: Feature flags facilitate gradual feature rollouts by allowing developers to release a feature to a subset of users or in specific environments. This helps mitigate risks associated with deploying new features to the entire user base all at once.
  • A/B Testing: Feature flags are commonly used in A/B testing. Developers can use flags to expose different variations of a feature to different user groups, collecting data on user interactions and preferences to inform decision-making.

When you use feature flags with observability tools, you can do things like tracking feature flag analytics, running diagnostics, and watching the feature flag lifecycle (to identify things like when a flag can be retired or archived).

How To Create Observability-Driven Development: A Step-by-Step Guide

Head over to Flagsmith to begin the process. You may need to sign up (for free) if you don't have an account.

  1. Create a new project within Flagsmith.
  2. Navigate to the Integration section.
  3. Choose your preferred observability tool.
flagsmith ui screenshot
  1. Enter the API key of your preferred observability tool. For instance, if you enabled the integration with New Relic, all the flag change events will now be sent to New Relic as Deployments.
  2. Return to Flagsmith's dashboard.
  3. Locate the feature you want to monitor and turn it on.
flagsmith ui screenshot
  1. Observe the real-time activation of the feature.
  2. Create triggers or monitoring parameters in your observability tool to capture relevant data.

When this is done, you’ll be able to track your feature flag data in your observability platform, with keen insights into things like:

  • Feature usage over time 
  • Feature flag overhead

Feature flag lifecycle information (to see which feature flags were turned on—and by whom 

Let’s take a look at some use cases.

Use Cases for Observability-Driven Development with Feature Flags

Feature flags complement diagnostics and analytics, providing insights into the health of both the feature flag management system and the usage patterns of individual features.

1. Feature Flag Diagnostics:

  • Monitoring Uptime and Health: ODD encompasses a comprehensive approach to observing the feature flag management system itself. Diagnostics involve continuous monitoring of the uptime and health of the feature flag infrastructure. This ensures that the very mechanism designed to control feature releases remains robust, minimizing the risk of potential bottlenecks.
  • Real-time Health Metrics: Implementing observability practices allows teams to access real-time health metrics of feature flags. Metrics may include flag evaluation times, error rates, and the overall responsiveness of the feature flag management system. Rapid detection and resolution of issues in this area contribute to the reliability and stability of feature releases.
  • Alerts for Feature Flag Management Issues: Automated alerts can be configured to notify teams of any anomalies or issues within the feature flag management system. This proactive alerting system ensures that potential problems are addressed swiftly, preventing disruptions to the feature flag-controlled release process.

2. Feature Flag Analytics and Usage Insights:

  • Understanding Feature Adoption: Observability-driven analytics extend to gaining insights into feature usage patterns. Teams can track and analyze which features are being actively used by end-users, providing valuable data to inform development decisions.
  • User Segmentation: Feature flags enable user segmentation, allowing teams to observe and analyze which segments of users are exposed to specific features. This segmentation provides a granular understanding of how different user groups interact with the software, aiding in targeted feature development and refinement.
  • Insights for Continuous Improvement: Feature flag analytics contribute to a continuous improvement cycle. By understanding how users interact with features, development teams can iterate, optimize, and tailor features to better align with user expectations and business goals.

5 Best Practices for Implementing Observability-Driven Development

Let's delve into key guidelines for implementing ODD and ensuring a streamlined, informed, and resilient development process.

  1. Define Clear Objectives

Think of this as setting the compass for your observability journey. Clearly articulate what you aim to achieve, whether it's accelerated performance, enhanced user experience, or quicker issue resolution.

Gather stakeholders for collaborative sessions. Document objectives and periodically revisit them to ensure alignment with evolving project requirements. This clarity of purpose becomes the north star guiding your development efforts.

  1. Select Appropriate Observability Tools

Choosing the right tools is akin to selecting the perfect toolkit for a craftsperson. It's about finding observability tools that integrate with your tech stack, offering scalability and compatibility.

Treat tool selection like a trial. Conduct proof of concepts, evaluating tools against your application's needs. Opt for tools that not only meet current requirements but are also flexible enough to evolve with your project.

  1. Instrument Key Metrics

It's about identifying and instrumenting the key metrics that resonate with your application's critical functionalities.

Utilize tools that allow for efficient data collection without introducing performance bottlenecks. Implement instrumentation in your code and components, ensuring you capture the metrics essential to your application's heartbeat.

  1. Implement Distributed Tracing

Integrate distributed tracing libraries into your application's architecture. Configure spans to trace the communication paths between services. Visualize and analyze this data to understand the orchestration of your software symphony.

  1. Create Meaningful Alerts

Alerts are your software's emergency sirens, but meaningful alerts are the key to avoiding alert fatigue and ensuring swift responses to actual issues.

Collaborate with your team to establish alerting conditions that truly indicate problems requiring attention. Regularly review and refine alert configurations to maintain their effectiveness. The goal is to be alerted to critical issues without drowning in a sea of notifications.

Concluding thoughts

ODD weaves a narrative of continuous evolution from the precision of feature flag diagnostics to the artistry of user-centric analytics. The call is clear as we step into the next phase: integrate ODD, where adaptability and collaboration become the keystones. The journey ahead promises not just efficiency but a dance with the ever-changing rhythms of software evolution. 

Author Bio

Savan Kharod is a growth marketer at Middleware. He is an engineer turned marketer and a tech enthusiast. He likes to read novels when not solving dev marketing issues at middleware. Say hello to him on LinkedIn.



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