# infrastructure monitoring

Infrastructure monitoring is the practice or software of collecting and analyzing health and performance data from backend infrastructure such as servers, containers, databases, and virtual machines.

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## Use OpenTelemetry-native observability with Datadog from ingestion to investigation

DevFeed: [Use OpenTelemetry-native observability with Datadog from ingestion to investigation](<https://devfeed.tech/articles/use-opentelemetry-native-observability-with-datadog-from-ingestion-to-investigation-2300.md>)

Original publisher: [Read original article](<https://www.datadoghq.com/blog/native-otel-with-datadog/>)

Author: Shanel Huang

Published: 2026-07-20T00:00:00Z

Content type: article

Language: en

Sources: [Datadog | The Monitor blog](<https://devfeed.tech/sources/datadog-the-monitor-blog.md>)

Topics: [OpenTelemetry](<https://devfeed.tech/topics/opentelemetry.md>), [observability](<https://devfeed.tech/topics/observability.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Application Performance Management (APM)](<https://devfeed.tech/topics/apm.md>), [infrastructure monitoring](<https://devfeed.tech/topics/infrastructure-monitoring.md>), [Instrumentation](<https://devfeed.tech/topics/instrumentation.md>), [Traces](<https://devfeed.tech/topics/traces.md>), [log management](<https://devfeed.tech/topics/log-management.md>)

Tags: [apm](<https://devfeed.tech/tags/apm.md>), [infrastructure-monitoring](<https://devfeed.tech/tags/infrastructure-monitoring.md>), [instrumentation](<https://devfeed.tech/tags/instrumentation.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [logs](<https://devfeed.tech/tags/logs.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [opentelemetry](<https://devfeed.tech/tags/opentelemetry.md>), [sdks](<https://devfeed.tech/tags/sdks.md>), [serverless](<https://devfeed.tech/tags/serverless.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>), [traces](<https://devfeed.tech/tags/traces.md>), [tracing](<https://devfeed.tech/tags/tracing.md>)

### AI overview

This article explains how Datadog supports OpenTelemetry-native observability from instrumentation through ingestion and investigation. It covers vendor-neutral OTLP ingestion through the OTel Collector's standard HTTP exporter and Datadog's direct OTLP intake for metrics, logs, and traces, including use cases such as managed services and serverless environments.

### Source excerpt

Learn how you can use vendor-neutral telemetry while preserving Datadog's infrastructure and APM experiences.

## Agentic coding with ClickHouse. One person, one data stack, one full-stack application

DevFeed: [Agentic coding with ClickHouse. One person, one data stack, one full-stack application](<https://devfeed.tech/articles/agentic-coding-with-clickhouse-one-person-one-data-stack-one-full-stack-application-4921.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/agentic-coding-app>)

Author: Oussama Chakri

Published: 2026-04-14T13:38:14Z

Content type: article

Language: en

Sources: [ClickHouse Blog](<https://devfeed.tech/sources/clickhouse-blog.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [agentic-coding](<https://devfeed.tech/topics/agentic-coding.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>), [observability](<https://devfeed.tech/topics/observability.md>), [ai observability](<https://devfeed.tech/topics/ai-observability.md>), [infrastructure monitoring](<https://devfeed.tech/topics/infrastructure-monitoring.md>), [Tooling](<https://devfeed.tech/topics/tooling.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-coding](<https://devfeed.tech/tags/agentic-coding.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [coding](<https://devfeed.tech/tags/coding.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [logs](<https://devfeed.tech/tags/logs.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [observability](<https://devfeed.tech/tags/observability.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [tooling](<https://devfeed.tech/tags/tooling.md>), [traces](<https://devfeed.tech/tags/traces.md>), [tracing](<https://devfeed.tech/tags/tracing.md>)

### AI overview

A Solutions Architect describes building ClickShop, a full-stack retail analytics platform, in a few days using agentic coding and ClickHouse. The application combines real-time analytics over billions of rows, transactional workflows, 18 persona-specific AI agents, and observability for LLM tracing, costs, evaluation, metrics, logs, and distributed traces.

### Source excerpt

A Solutions Architect's experience building a retail analytics platform with AI agents, real-time dashboards, and full observability on the ClickHouse data platform

## How Tesla built a quadrillion-scale observability platform on ClickHouse

DevFeed: [How Tesla built a quadrillion-scale observability platform on ClickHouse](<https://devfeed.tech/articles/how-tesla-built-a-quadrillion-scale-observability-platform-on-clickhouse-5299.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/how-tesla-built-quadrillion-scale-observability-platform-on-clickhouse>)

Author: ClickHouse

Published: 2025-07-10T00:00:00Z

Content type: article

Language: en

Sources: [ClickHouse Blog](<https://devfeed.tech/sources/clickhouse-blog.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [observability](<https://devfeed.tech/topics/observability.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>), [infrastructure monitoring](<https://devfeed.tech/topics/infrastructure-monitoring.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [Availability](<https://devfeed.tech/topics/availability.md>), [Prometheus](<https://devfeed.tech/topics/prometheus.md>)

Tags: [2025](<https://devfeed.tech/tags/2025.md>), [availability](<https://devfeed.tech/tags/availability.md>), [case-study](<https://devfeed.tech/tags/case-study.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [prometheus](<https://devfeed.tech/tags/prometheus.md>), [real-time](<https://devfeed.tech/tags/real-time.md>)

### AI overview

This case study describes how Tesla built Comet, a large-scale observability platform on ClickHouse. The system was designed to ingest tens of millions of rows per second, retain data for years, support real-time analysis and anomaly detection, and meet demanding availability and scalability requirements. The article explains why Tesla moved beyond Prometheus and highlights a quadrillion-row load test.

### Source excerpt

"Data in ClickHouse is better than data anywhere else. No other system lets you slice and dice your data, ask interesting questions, and get answers in an acceptable amount of time. There's nothing out there that competes with ClickHouse." Alon Tal, Senio