Datadog announced the launch of Bits, a new generative AI-based assistant that learns from customers’ observability data and helps engineers resolve application issues in real time.
Bits AI helps teams become efficient by learning from a customer’s observability data, collaboration platforms, content management systems and many other sources to quickly answer questions, provide recommendations and build automated remediation steps in conversational language that would normally take engineers hours or days to piece together in traditional ways. The types of problems Bits AI helps users with include:
- Answering natural language questions by surfacing and correlating data from logs, metrics, traces, real-user transactions, security signals, cloud costs and more, from across the Datadog platform;
- Debugging and fixing code-level issues by explaining errors, managing incidents end-to-end by paging the right teams, calibrating severity levels, providing status updates about the incident and completing other paperwork such as postmortems—with context carrying over from web to Slack;
- Suggesting code fixes that developers can apply with a few clicks and automatically building unit tests for the fixes.
“When incidents happen, it’s essential for engineering teams to quickly identify root causes and get a quick resolution. However, teams often spend hours piecing together relevant information from disparate systems,” said Michael Gerstenhaber, VP of Product at Datadog. “Bits AI can synthesize data from every layer of the stack and from teams’ institutional knowledge—assisting in debugging and in performing otherwise distracting tasks like escalations, succinct status reports or drafting postmortems. Bits AI enables engineering teams to focus on more complex and valuable work.”
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