SigNoz, an OpenTelemetry-native APM platform, now offers a Datadog-style UI, a dashboard migrator, and Datadog Receiver support to help teams migrate off Datadog's proprietary `dd-trace` library. `dd-…
PostHog has released a guide for small teams and solo founders on setting up minimum viable AI observability after shipping their first AI feature. The guide recommends starting with just three compon…
TipRanks compiled recommendations from Wall Street analysts highlighting three stocks positioned to benefit from AI-driven demand, with CNBC identifying Datadog as a top pick after the company reporte…
LineageLens has launched a self-hosted code provenance tool that records the prompt, model, tool, target file, and inserted code for AI-generated edits, addressing a critical gap in enterprise AI gove…
RoboTrace has launched a new observability platform for AI-powered robots, addressing a critical gap between existing tools like Datadog for backend services and Weights & Biases for training. The pla…
EZLogs launched a plain-English activity logging tool for Rails and Next.js applications that records every request, background job, and database change, then translates each chain of events into read…
Datadog Director of Engineering Diamond Bishop outlined five key lessons for building production-ready AI agents at the MCP Dev Summit North America 2026, based on the company's experience deploying i…
Grafana Labs competes directly with Datadog by charging across five usage meters—metrics, logs, traces, profiles, and k6 load tests—while marketing against Datadog's opaque overage bills. The company …
A benchmark comparing Chronos-Bolt and Toto zero-shot forecasting models on Prometheus and OpenSearch telemetry data found that both models outperformed naive baselines on periodic memory signals but …
Datadog's monitoring and analytics platform is positioned to benefit as companies move artificial intelligence models from development into production, creating a catalyst for the stock. The company's…
A developer built OpsMind AI, an AI-powered incident root cause analysis platform using LangGraph and RAG to automate the investigation of production failures in distributed systems. The platform proc…
The article describes the development of a local AI-powered SOC analyst that runs on an M1 MacBook Pro, designed to assist with daily security operations by triaging and analyzing alerts from existing…
The article explains that approximately 80% of Flask applications still use basic `print()` statements or unstructured logging in production, which hinders effective debugging and monitoring despite t…
The client-facing dashboard is dead for outcome-based AI services, replaced by an email-first "Acknowledgment Loop" that measures trust and engagement through client replies. Pull-based dashboards bur…
A common problem in engineering organizations where modern observability stacks coexist with legacy monitoring tools that cannot integrate with them, creating an "observability seam" that requires man…
Anthropic hosted its Code with Claude 2026 event in San Francisco on May 6, unveiling updates including Managed Agents, proactive workflows, and a "capability curve" for Claude Code. Key announcements…
Productivity and infrastructure companies must now design for AI agents as their primary users, not humans, as agents increasingly handle tasks that people once performed manually. Traditional metrics…
AI inference has become the fastest-growing market in technology, projected to reach $250 billion within seven years, surpassing the database market. Companies like Anthropic, Google Cloud, Datadog, a…
This article explains how to use the `MeterListener` type from the `System.Diagnostics.Metrics` APIs to consume and record metric values in-process within a .NET application. The author demonstrates t…
The article explains that when using `foreach` on an `IEnumerable<T>` variable instead of a concrete type like `List<T>`, the C# compiler generates code that allocates heap memory for the enumerator, …