AWS has launched the public preview of OpenTelemetry (OTel) metrics support within Amazon CloudWatch, enabling developers to send metrics directly via the OTLP protocol. This update completes CloudWatch's support for logs, traces, and metrics using open standards.
- Support for high-cardinality metrics with up to 150 labels per metric.
- Integration of PromQL, allowing users to use Prometheus query language within the CloudWatch console and Managed Grafana.
- Automatic enrichment of ingested metrics with AWS resource metadata such as account ID, Region, and resource tags.
- Support for high-cardinality metrics with up to 150 labels per metric.
- Integration of PromQL, allowing users to use Prometheus query language within the CloudWatch console and Managed Grafana.
- Automatic enrichment of ingested metrics with AWS resource metadata such as account ID, Region, and resource tags.
At GrafanaCON 2026, Grafana Labs announced significant updates including the launch of Grafana 13 and a major architectural overhaul for Loki. The new Loki design moves away from replication-at-ingestion toward using Kafka as a durability layer to reduce data duplication and improve query performance. Additionally, the company introduced GCX, a new CLI tool in public preview designed to integrate observability data directly into agentic development environments like Claude Code and Cursor, allowing engineers to resolve production issues without leaving their coding tools.
:
- Loki rearchitected with Kafka to reduce storage overhead and improve query speed.
- Introduction of GCX CLI for seamless observability integration within AI coding agents.
- Launch of Grafana 13 featuring dynamic dashboards and expanded data source support.
- New AI Observability product in public preview for monitoring LLM applications.
:
- Loki rearchitected with Kafka to reduce storage overhead and improve query speed.
- Introduction of GCX CLI for seamless observability integration within AI coding agents.
- Launch of Grafana 13 featuring dynamic dashboards and expanded data source support.
- New AI Observability product in public preview for monitoring LLM applications.
Airbnb's observability engineering team has transitioned from a legacy StatsD and proprietary Veneur-based aggregation pipeline to a modern, open-source stack utilizing OpenTelemetry Protocol (OTLP), the OpenTelemetry Collector, and VictoriaMetrics' vmagent. The new system handles over 100 million samples per second in production while reducing costs by roughly an order of magnitude.
Key technical highlights include:
* Migration strategy using dual-emitting metrics to bridge legacy StatsD libraries with OTLP adoption.
* Performance improvements, including a reduction in JVM CPU time spent on metrics processing from 10% to under 1%.
* Use of vmagent for streaming aggregation and horizontal sharding to manage high-cardinality data.
* Implementation of a zero injection technique within the vmagent tier to solve Prometheus counter reset edge cases.
* A two-layer architecture consisting of stateless router pods and stateful aggregator pods.
Key technical highlights include:
* Migration strategy using dual-emitting metrics to bridge legacy StatsD libraries with OTLP adoption.
* Performance improvements, including a reduction in JVM CPU time spent on metrics processing from 10% to under 1%.
* Use of vmagent for streaming aggregation and horizontal sharding to manage high-cardinality data.
* Implementation of a zero injection technique within the vmagent tier to solve Prometheus counter reset edge cases.
* A two-layer architecture consisting of stateless router pods and stateful aggregator pods.
This article explores the emerging category of AI-powered operations agents, comparing AI DevOps engineers and AI SRE agents, how cloud providers are responding, and what engineers should consider when evaluating these tools.
hl is a fast, Rust-based JSON log viewer designed for efficient processing of structured logs. It offers fast indexing and parsing, enabling quick scanning of large log files.
Grafana and GitLab have released a new open-source solution that links GitLab CI/CD events into Grafana's observability stack via a serverless architecture, enabling real-time visibility and correlation between deploy events and performance metrics.
TraceRoot.AI is an AI-native observability platform that helps developers fix production bugs faster by analyzing structured logs and traces. It offers SDK integration, AI agents for root cause analysis, and a platform for comprehensive visualizations.
TraceRoot accelerates the debugging process with AI-powered insights. It integrates seamlessly into your development workflow, providing real-time trace and log analysis, code context understanding, and intelligent assistance. It offers both a cloud and self-hosted version, with SDKs available for Python and JavaScript/TypeScript.
Grafana Labs have launched Grafana 12, bringing significant updates to its visualisation and dashboarding platform. Several new key features are now generally available, including Git Sync, dynamic dashboards, and improvements to Drilldown. A central feature is a new collection of observability-as-code tools, designed to help teams automate observability workflows.
Why developers are spinning up AI behind your back — and how to detect it. The article discusses the rise of 'Shadow AI' - developers integrating LLMs into production without approval, the risks involved, and strategies for organizations to manage it effectively.
>We’ve seen LLMs used to auto-tag infrastructure, classify alerts, generate compliance doc stubs, and spin up internal search tools on top of knowledge bases. We’ve also seen them quietly embedded into CI/CD workflows...
>We’ve seen LLMs used to auto-tag infrastructure, classify alerts, generate compliance doc stubs, and spin up internal search tools on top of knowledge bases. We’ve also seen them quietly embedded into CI/CD workflows...
