Introduction
Enhancing Grafana's data source integration capabilities to support a wider range of time series databases is a critical challenge that could significantly expand the product's utility and market reach. This improvement aligns with Grafana's core value proposition of providing unified observability across diverse data sources. I'll approach this problem by first clarifying our objectives, then analyzing user segments and pain points, before proposing and evaluating potential solutions.
Step 1
Clarifying Questions (5 mins)
Why it matters: Determines if we're focusing on breadth vs. depth of integrations Expected answer: Aiming to be the universal dashboard for all time series data Impact on approach: Would prioritize ease of integration and flexibility over deep, specialized features
Why it matters: Identifies potential bottlenecks in the current integration process Expected answer: Complex process requiring deep knowledge of both Grafana and the target database Impact on approach: Would focus on simplifying and standardizing the integration process
Why it matters: Helps prioritize which database types to focus on first Expected answer: Growing demand for cloud-native and specialized IoT databases Impact on approach: Would tailor solution to address the most requested database types first
Why it matters: Determines if we should focus on empowering the community or internal development Expected answer: Active community, but struggling with documentation and testing resources Impact on approach: Would prioritize improving developer tools and documentation
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