Our second panel, 'Devtools and Datastack: What’s the Next Frontier?', at the sixth edition of #Techtonix, featured Aakash Kumar moderating a discussion with Akash Saxena, CPTO of Viacom18, and Utkarsh (UT) from Xmplify.tech. Key takeaways:

⛔ Challenges and Costs in Business Development:
▶ Aakash Kumar: Highlighted the rising costs of making and selling in business and the difficulty in quantifying developer productivity versus new feature development.
▶ Akash Saxena: Noted a reduction in the need for accountability in development cycles and the importance of understanding and controlling changes within the development process.

🛠️ Observability and Data Engineering:
▶ Aakash Kumar: Discussed the significance of observability frameworks in AI and data engineering, focusing on infrastructure and the potential big wins.
▶ Utkarsh: Emphasized the importance of Service Level Agreements (SLAs) and the customer feedback loop in understanding service runtime metrics.

✅ Site Reliability Engineering (SRE):
▶ Aakash Kumar: Mentioned the long-standing role of SRE and the need to approach problem-solving from a customer-backwards perspective.
▶ Akash Saxena: Stressed the importance of following the money to understand business and accountability, implementing the best processes, and maintaining a strong record of platform activities.

🔒 Data Engineering and Reliability:
▶ Aakash Kumar: Raised questions about data reliability, operations, and the current problems in the field, asking for potential changes and easy solutions.
▶ Utkarsh: Pointed out the lack of data strategies in many organizations and the need for proper data definitions and quality tests.
▶ Akash Saxena: Acknowledged that many software teams deal with poor data quality and stressed the importance of establishing measures that matter to the organization.

💡 Practical Insights and Recommendations:
▶ Akash Saxena: Discussed the inevitable challenges of data management and the need for maturity in schema registry and data lifecycle management.
▶ Utkarsh: Highlighted the necessity of understanding company-specific data requirements and building appropriate tools and processes around those needs.

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