Summary

This chapter delved into the intricate process of implementing and scaling data observability within organizations, emphasizing the common pitfalls faced during the integration of observability.

We have seen the main challenges, which are the control of costs, the overhead with other jobs, the security concerns, the increase in complexity of the architecture, the trade-off to be handled with legacy systems, and finally, the information overload that teams can experience. We have also seen that all these challenges can be overcome and the risks mitigated.

Then, we listed the questions a data team must answer during observability implementation. The list covered the criteria for selecting the appropriate project and observability tool, considering aspects such as security, compliance, cost, integration, data retention, intelligence, and customization. The discussion on costs explored various strategies, including open source solutions, in-house development, vendor solutions...