Grafana Labs vs Monte Carlo

Tempo 3.1 release: new features for Kafka, TraceQL metrics updates, trace redaction, and more

Grafana Labs blog features a new post on Tempo 3.1 release with new features for Kafka, TraceQL metrics updates, trace redaction, and more.

Observability Stack: Prometheus, Node Exporter, Grafana

A technical how-to explaining the three-piece observability stack: Prometheus (time-series database that scrapes metrics), Node Exporter (exposes OS-level metrics at a /metrics HTTP endpoint), and Grafana (visualizes Prometheus data as dashboards). The article describes the pull-based model Prometheus uses, the role of Node Exporter as a translator of OS stats, how Grafana queries Prometheus, default ports (Prometheus 9090, Node Exporter 9100, Grafana 3000), basic install commands, a sample prometheus.yml with scrape_interval and job_name, and next steps such as adding scrape targets, writing PromQL queries, and adding Alertmanager for notifications.

• Prometheus is a time-series database and monitoring system that scrapes metrics from HTTP endpoints and exposes its own metrics on port 9090.
• Node Exporter exposes hardware and OS-level metrics at a /metrics endpoint (default port 9100) and is typically installed one-per-machine.
• Grafana queries Prometheus (e.g., via PromQL) to render dashboards and runs by default on port 3000; it stores no metrics itself.

Building an Internal Developer Platform on Azure AKS

This technical article explains how to create an Internal Developer Platform (IDP) using Azure Kubernetes Service (AKS). It outlines core components including AKS as the managed Kubernetes backbone, a service mesh (e.g., Istio or Linkerd) for microservice communication, CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for automated build and deployment, monitoring and logging tools (Azure Monitor, Prometheus, Grafana, Azure Log Analytics), and security/compliance controls (RBAC, Pod Security Policies, Azure Policy, Azure Security Center). The piece describes an example developer workflow from code push to production and summarizes benefits such as increased efficiency, scalability, security, and consistency.

• An Internal Developer Platform (IDP) is a set of tools, processes, and automations that simplifies development, testing, and deployment for developers.
• Azure Kubernetes Service (AKS) is presented as the central managed Kubernetes environment where containerized applications run.
• Service meshes such as Istio or Linkerd are recommended to manage microservice communication, including load balancing, traffic management, and security policies.

Monte Carlo Launches Bayes AI Teammate for Agent Trust

Monte Carlo, a leader in agent trust, has launched Bayes, an AI teammate that autonomously detects, troubleshoots, and fixes issues across AI agents and their underlying data. Bayes integrates platform capabilities into a single system, allowing customers to control how much it handles. It addresses the challenge of enterprises deploying agents faster than they can maintain reliability, with surveys showing low trust and high rollback rates. Bayes learns the customer's data and AI environment, deploys monitoring strategies, and can execute fixes via draft pull requests. It covers the entire stack from agent outputs to data inputs. Monte Carlo reports that Bayes helps detect 200% more incidents with 80% fewer false positives. The launch extends Monte Carlo's partnership with Snowflake, which named it 2026 Data & AI Governance Partner of the Year, to help joint customers build reliable agents on Snowflake.

• Monte Carlo launched Bayes, an AI teammate for autonomous detection, troubleshooting, and fixing of AI agents and their data.
• Bayes helps enterprises detect 200% more incidents than in-house systems, with over 80% fewer false positives.
• Surveys show 70% of leaders lack trust in their agents, and 74% have rolled back a customer-facing AI agent.