Announcing MCP Toolbox Java SDK v1.0: Agentic data access for the enterprise
cloud.google.com·6d ago
Cloud & Infrastructure
The New Stack·Aug 26·5 min read
Observability has a data problem. AI is about to make it worse.
TL;DR
Observability is facing a significant data storage challenge, exacerbated by the increasing volume of telemetry data generated by AI systems. Bronto, a data observability platform, argues that the industry's focus on dashboard improvements is misguided and that the real battle lies in optimizing data storage economics.
✦ Why It Matters
Evaluate your current observability tools and consider investing in solutions that optimize data storage.
Key Takeaways
- Assess your observability data storage costs and limitations.
- Explore BrontoD for enhanced data retention capabilities.
- Prioritize tools that provide full access to telemetry data.
- Consider the impact of AI on your observability strategy.
How It Works
BrontoD is designed to efficiently store and manage high volumes of observability data, addressing issues like high cardinality in metrics and slow log indexing. It allows for sub-second searches across vast datasets without the need for data sampling or reduced retention periods.