OpenTelemetry

2026-10-29

REGULATION · 1 SOURCE · MIT Technology Review AI

Research finds major observability gaps in AI agent frameworks and urges real-time monitoring

Researchers report that widely used AI agent frameworks often fail to emit crucial observability records—such as persistent agent IDs and human intervention logs—making it hard to see what agents do and why. The authors call for real‑time monitoring, standards for 'what happened' and 'decision' records, and for the OpenTelemetry working group to finalize agent tracing formats that capture these signals.

7.0

2026-10-09

RESEARCH · 1 SOURCE · arXiv cs.AI

Agent-Controlled Forgetting for Tool-Using Agents (arXiv:2610.10590v1)

This arXiv preprint proposes 'agent-controlled forgetting', where an agent replaces prior tool outputs in its context with short notes while storing exact originals in a recoverable archive; a Python harness enables batch archival and explicit recovery without task-specific training. In an OpenTelemetry debugging case plus an unrelated implementation task the method reduced provider-reported prompt tokens to 231,951 from 912,492, halved cumulative input tokens and cut estimated API cost to roughly USD 1.28–1.44 vs ≈USD 4.38, but made more requests, ran ~17% slower, and showed workload-dependent effectiveness across other test pairs and continuations.

6.0

2026-10-01

OTHER · 1 SOURCE · InfoQ AI, ML & Data Engineering

Panel: Beyond Observability — Evolving Production Operations in the Age of AI

An InfoQ Live panel moderated by Renato Losio discussed how AI and automation are changing production operations and observability, turning operational data into actionable insights for incident response. Panelists from Genesys (formerly AWS), Netflix and Groundcover covered practical uses (e.g., ML/agents reducing MTTR), instrumentation like OpenTelemetry, and architectures such as eBPF and BYOC agentic observability.

3.0

2026-09-30

CODING · 1 SOURCE · NVIDIA Developer

NVIDIA tutorial: use NeMo Relay to trace Hermes Agent runs and inspect ATOF/ATIF/OpenTelemetry traces

NVIDIA published a tutorial showing how to use NeMo Relay as a common observability layer for agent runs, with Hermes Agent producing ATOF event streams, ATIF trajectories, and OpenTelemetry spans that can be inspected in tools like Arize Phoenix; the repo includes runnable examples, verifiers, and setup instructions. A Hermes ToolPerf case study included with the tutorial compared baseline and fixed harness revisions across repeated runs, finding Qwen Coder 30B recovered more tasks but at the cost of increased calls, data, and latency.

5.0

2026-09-22

CODING · 1 SOURCE · AWS Machine Learning

Strands Evals SDK and Amazon Bedrock AgentCore add skill-focused evaluators

Strands Evals SDK and Amazon Bedrock’s AgentCore Evaluations now include skill-focused evaluators that measure whether an agent chose the appropriate skill (Skill Selection Accuracy) and how fully it followed that skill’s instructions (Skill Instruction Following). Strands also provides a deterministic SkillInvoked check; evaluations can run from Strands trajectories or OpenTelemetry traces and be used via the AgentCore CLI.

6.0

2026-09-18

COMPANIES · 1 SOURCE · InfoQ AI, ML & Data Engineering

WSO2 launches Agent Manager (GA) to govern multi-framework AI agents

WSO2 announced the general availability of the open-source WSO2 Agent Manager, a centralized platform for identity, governance, security controls, and operational oversight of AI agents across models, frameworks, and deployment environments. The GA release adds deeper agent identity features, governance for Model Context Protocol (MCP) interactions, a Kubernetes-native sandboxed runtime, OpenTelemetry tracing, lifecycle controls (including suspension), and over 40 built-in policies for things like PII masking and rate limiting.

7.0

2026-04-27

COMPANIES · 1 SOURCE · Mistral AI

Mistral AI launches Workflows orchestration in public preview

Mistral AI has released Workflows in public preview — an orchestration layer inside Studio designed to provide durability, observability, fault tolerance, and human-in-the-loop controls for enterprise AI processes. Workflows are written in Python, can be triggered via Le Chat, record full execution histories (with OpenTelemetry support), and are already in use by customers such as ASML, ABANCA, CMA-CGM, France Travail, La Banque Postale, and Moeve.

7.0