Microsoft aimed to shift .NET from being a Windows-focused development platform to a cross-platform, native solution that could run on Linux, macOS, and Windows, enabling developers to build and deploy applications across different environments seamlessly.
Microsoft had a collaborative relationship with the Mono project, working to unify libraries and eventually acquiring Xamarin, which allowed for a unified runtime that could run on both client devices and backend servers with optimized performance.
Honeycomb aims to help developers reshape how they introspect their systems by providing tools that allow for a more intuitive debugging flow, focusing on high-level entry points and probabilistic distributions to guide users toward the right queries and insights.
Honeycomb uses AI to help developers by suggesting queries based on natural language input, making it easier for users to explore their data and debug issues without needing to know the exact query structure upfront. This helps users get unstuck and encourages curiosity.
OpenTelemetry is crucial for Honeycomb as it provides a standardized way to collect and analyze observability data, which aligns with Honeycomb's goal of helping developers understand their systems. Honeycomb's involvement in OpenTelemetry ensures that their product remains compatible with the evolving standard.
Phillip Carter left Microsoft after completing a major milestone with .NET's cross-platform success, seeking new challenges in the developer tools space. Honeycomb's innovative approach to observability and its involvement in OpenTelemetry were key factors in his decision.
Honeycomb's natural language querying feature uses GPT-3.5 to generate queries based on user input, schema, and example data. It helps users formulate queries for slow requests or other issues by suggesting relevant columns and query shapes, making it easier to explore data without deep knowledge of the system.
Honeycomb plans to expand its AI-assisted debugging capabilities by offering more suggestions and guidance for users, helping them explore data, and test hypotheses. The goal is to encourage curiosity and make users better at debugging and building systems, aligning with the company's business interests.
Timescale believes Postgres is well-positioned for AI applications due to its extensibility, performance, and scalability. Extensions like PG Vector Scale and PGAI enhance its capabilities for vector search and LLM reasoning, making it a powerful choice for AI developers without needing to manage multiple databases.
Fly.io differentiates itself by offering a platform with no hard line boundaries, allowing developers to run their apps close to users globally with primitives that enable deep customization. It provides a no-limits approach compared to platforms like Heroku and Vercel, which have more restrictive abstractions.
Phillip Carter, Principal PM at Honeycomb, joins Justin & Autumn to discuss his work at Microsoft & Honeycomb, building AI infrastructure & more.
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