# Grafana AI visibility in Observability & Monitoring Canonical: https://devtune.ai/verticals/observability-monitoring/grafana [Website](https://grafana.com/) Updated: 2026-09-30T18:42:02.790584+00:00 Prompts: 25 Runs: 6 ## Platforms - google-ai - google-ai-mode - bing-copilot-search - perplexity - chatgpt-search - xai-search Rank: 2 Total brands: 14 Measured responses: 150 Presence percent: 25.333333333333336 Share of voice percent: 18.230563002680967 Average position: 13.132352941176471 Docs presence percent: 19.333333333333332 Blog presence percent: 2 Brand mention percent: 6.666666666666667 ## Profile Overview: Grafana Labs is a New York-based, privately held open-source observability company founded in 2014 by Raj Dutt, Torkel Ödegaard, and Anthony Woods. It is the commercial entity behind Grafana, the world's most widely used open-source dashboard and visualization tool, as well as the LGTM Stack—Loki (logs), Grafana (visualization), Tempo (traces), and Mimir (metrics). The company serves over 25 million users and more than 5,000 enterprise customers globally, including Bloomberg, Citigroup, Salesforce, Dell Technologies, and TomTom. Its core offering spans Grafana Cloud, a fully managed SaaS observability platform, and Grafana Enterprise Stack for self-hosted deployments. Grafana Labs was named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms, placed furthest in Completeness of Vision. Product summary: Grafana Labs provides an open and composable observability platform built around the open-source LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, Mimir for metrics). It is available as a fully managed cloud service (Grafana Cloud) or as a self-hosted enterprise offering. The platform unifies metrics, logs, traces, profiles, and frontend telemetry in a single pane of glass, supports 100+ data sources, and includes AI-powered tools for cost optimization (Adaptive Telemetry), root cause analysis (Asserts), and intelligent investigation (Grafana Assistant). Additional capabilities include performance testing (k6), incident response and management, synthetic monitoring, and database observability. ### Key capabilities - Unified metrics, logs, traces, and profiles via the open-source LGTM stack (Loki, Grafana, Tempo, Mimir) - Highly customizable, real-time dashboards with 100+ data source connectors - Adaptive Telemetry for intelligent cost optimization (filtering, aggregation, sampling) - Kubernetes and infrastructure monitoring with curated out-of-the-box dashboards - Application observability with native OpenTelemetry and Prometheus support - Incident Response & Management (IRM) with on-call scheduling and alerting - Frontend observability (real user monitoring) and synthetic monitoring - Performance and load testing via integrated k6 - AI-powered investigation and root cause analysis (Grafana Asserts, Grafana Assistant) - Flexible deployment: fully managed Grafana Cloud, self-hosted Enterprise Stack, or Federal Cloud ### Target users - DevOps and Site Reliability Engineers (SREs) - Platform and infrastructure engineers - Software developers at cloud-native companies - IT operations teams managing hybrid or multi-cloud environments - Enterprise engineering organizations requiring scalable observability - Startups and individual developers on free/self-hosted Grafana ### Key use cases - Infrastructure and cloud observability for DevOps and SRE teams - Application performance monitoring (APM) across microservices - Log aggregation and analysis at scale - Distributed tracing and root cause analysis - Kubernetes cluster monitoring and cost optimization - Incident detection, on-call management, and response workflows - Observability cost reduction and telemetry optimization - Frontend and digital experience monitoring Integrations ecosystem: Grafana Cloud supports 100+ data sources and 50+ curated infrastructure monitoring integrations, including native support for Prometheus and OpenTelemetry. Cloud provider integrations include AWS, Google Cloud, and Microsoft Azure (via Azure Managed Grafana). The plugin ecosystem spans databases (PostgreSQL, MySQL, InfluxDB, Elasticsearch), infrastructure tools (Kubernetes, Docker), and enterprise connectors (GitLab, Jira, Databricks, Microsoft SQL Server, Zipkin). Grafana also provides direct import integrations with Datadog and New Relic for visualization. The open-source Grafana Alloy collector enables broad agent-based telemetry ingestion. k6 (performance testing) is natively integrated into Grafana Cloud. Pricing summary: Grafana Cloud offers three tiers. Free: permanently free with 10,000 active metrics series, 50 GB/month of logs, traces, and profiles, and 14-day retention. Pro (on-demand): starts at $19/month with pay-as-you-go usage; metrics at $6.50/1,000 series, logs/traces/profiles at $0.50/GB ingested, Grafana visualization at $8/active user/month ($55 with Enterprise plugins), and IRM at $20/active user/month. Enterprise: annual commit starting at $25,000/year with volume discounts (metrics as low as $3/1,000 series, k6 as low as $0.05/virtual user hour), custom retention, premium support, and flexible deployment options including Federal Cloud and Bring Your Own Cloud. Review summary: Grafana Labs receives strong ratings across review platforms, driven by its visualization flexibility, deep integrations, and open-source accessibility. Gartner Peer Insights named it a Customers' Choice in December 2024. Users consistently praise its customizable dashboards, broad data source support, and value relative to proprietary alternatives. Common criticisms focus on a steep learning curve for beginners, complex alerting setup, and cost unpredictability at scale under the pay-as-you-go model. Competitive positioning: Grafana Labs differentiates on an open-source-first, 'big tent' philosophy that explicitly avoids vendor lock-in. It was placed furthest in 'Completeness of Vision' in the 2025 Gartner Magic Quadrant for Observability Platforms and is positioned as a lower-cost, highly composable alternative to proprietary all-in-one platforms like Datadog and Dynatrace. Its hybrid open-source/commercial model—where the core LGTM stack (Loki, Grafana, Tempo, Mimir) is free and monetized through Grafana Cloud or Enterprise licenses—enables a large community-driven adoption funnel that converts organic users to paying enterprise accounts. Grafana actively supports 100+ data sources, including competitors' tools, making it a unifying visualization layer across heterogeneous stacks rather than a closed platform. Limitations: Users and analysts cite a notable learning curve for new users, particularly around advanced query authoring, permission management, and alerting configuration. Costs can escalate quickly under the pay-as-you-go Pro model when data ingestion volumes are high, and the platform lacks native hard-cap billing safeguards to automatically stop ingestion at a spending threshold. Fully unlocking the platform's value requires meaningful observability expertise. Self-hosted deployments require operational overhead for maintenance and scaling. Some enterprise data source plugins are gated behind paid Enterprise tiers. ### Source urls - https://grafana.com/pricing/ - https://grafana.com/about/ - https://grafana.com/careers/ - https://techcrunch.com/2024/08/21/grafana-labs-is-now-valued-at-6b/ - https://siliconangle.com/2026/02/13/grafana-labs-reportedly-raising-funding-9b-valuation/ - https://sacra.com/c/grafana-labs/ - https://pitchbook.com/profiles/company/109176-76 - https://www.g2.com/sellers/grafana-labs - https://grafana.com/blog/2025/07/10/grafana-labs-named-a-leader-again-in-the-2025-gartner-magic-quadrant-for-observability-platforms/ - https://www.businesswire.com/news/home/20250710628287/en/Grafana-Labs-Named-a-Leader-in-2025-Gartner-Magic-Quadrant-for-Observability-Platforms - https://grafana.com/blog/grafana-labs-top-10-moments-of-2024/ - https://www.gartner.com/reviews/market/observability-platforms/vendor/grafana-labs/product/grafana-cloud Reviewed at: 2026-04-28T23:20:14.953+00:00 ### Customer outcomes | Customer | Summary | Metric | | --- | --- | --- | | The Trade Desk | Used Grafana Cloud's Adaptive Metrics feature to identify and eliminate unused time-series data, generating significant cost savings on observability spend. | $1.74M in savings | | Teletracking | Adopted Grafana Cloud's Adaptive Logs to identify commonly ingested but low-value log patterns and reduce unnecessary log ingestion volume. | 50% reduction in log volume | ### Reviews breakdown | Platform | Score | Score max | Review count | Url | | --- | --- | --- | --- | --- | | Gartner Peer Insights | 4.5 | 5 | 268 | https://www.gartner.com/reviews/market/observability-platforms/vendor/grafana-labs/product/grafana-cloud | | G2 | 4.5 | 5 | 157 | https://www.g2.com/sellers/grafana-labs | ### Review themes #### Praised - Highly customizable and visually clean dashboards - Extensive data source and plugin ecosystem (100+ integrations) - Open-source foundation reduces vendor lock-in - Strong Kubernetes and infrastructure monitoring - Unified metrics, logs, and traces in one platform - Generous and functional free tier - Active and large community - Cost-effective vs. proprietary observability tools #### Criticized - Steep learning curve for new users and advanced features - Alerting configuration is complex to set up correctly - Costs can escalate quickly at high data ingestion volumes - Lack of hard billing/ingestion cap safeguards in pay-as-you-go - Requires existing observability knowledge to maximize value - Some enterprise features and plugins gated behind paid tiers ### Company facts Founded year: 2014 Hq: New York, NY, USA #### Founders - Raj Dutt - Torkel Ödegaard - Anthony Woods Employees range: 1600-1800 Total funding: ~$908M Valuation: $6B (Aug 2024); ~$9B reported (Feb 2026) Arr: ~$400M Customer count: 5,000+ Status: Private Readiness: Not available ## Ranking | Display name | Pair count | Total pairs | Presence percent | Avg position | | --- | --- | --- | --- | --- | | Datadog | 50 | 150 | 33.33333333333333 | 10.011764705882353 | | Grafana | 38 | 150 | 25.333333333333336 | 13.132352941176471 | | New Relic | 37 | 150 | 24.666666666666668 | 11.220588235294118 | | Dynatrace | 27 | 150 | 18 | 28.88235294117647 | | Honeycomb | 16 | 150 | 10.666666666666668 | 20.38235294117647 | | Elastic | 11 | 150 | 7.333333333333333 | 20.8 | | Splunk | 9 | 150 | 6 | 26.291666666666668 | | Coralogix | 6 | 150 | 4 | 6.285714285714286 | | Logz.io | 5 | 150 | 3.3333333333333335 | 11.666666666666666 | | Better Stack | 5 | 150 | 3.3333333333333335 | 27 | | Sentry | 2 | 150 | 1.3333333333333335 | 4.5 | | Chronosphere | 1 | 150 | 0.6666666666666667 | 31.5 | | Axiom | 1 | 150 | 0.6666666666666667 | 74.66666666666667 | | Mezmo | 1 | 150 | 0.6666666666666667 | 75 | ## Platform breakdown | Platform | Prompt count | Presence rate | | --- | --- | --- | | google-ai | 1 | 4 | | google-ai-mode | 1 | 4 | | bing-copilot-search | 0 | 0 | | perplexity | 12 | 48 | | chatgpt-search | 19 | 76 | | xai-search | 5 | 20 | ## Strengths | Prompt text | Platform count | Avg position | | --- | --- | --- | | Which SaaS monitoring platforms have the lowest ingestion lag during high-volume log bursts so alerting stays fast? | 1 | 1 | | What's the quickest distributed tracing platform to set up across a microservices architecture on a container orchestration platform? | 2 | 1 | | Which distributed tracing platforms add the least overhead to latency-sensitive APIs — safe to run in production at full sampling? | 1 | 2 | | What observability platforms support unified metrics, traces, and logs instrumentation for Node.js and Python polyglot applications? | 1 | 2 | ## Gaps | Prompt text | Competitor presence count | | --- | --- | | Which observability platforms make it easiest to correlate a user-reported error with the right trace and log lines in a distributed system? | 5 | | Which observability platforms integrate with deployment pipelines to correlate performance regressions with specific code changes? | 3 | | Which APM tools have the best day-one onboarding to get immediate value without drowning in noise? | 3 | | Which APM tools integrate best with cloud provider managed databases and serverless functions for end-to-end visibility? | 3 | | Which monitoring platforms offer the best on-call experience — from alert firing through to root cause identification? | 3 | ## Topic scores | Topic name | Prompt count | Cited prompt count | | --- | --- | --- | | Capability | 5 | 4 | | Developer Experience | 5 | 4 | | Integrations & Ecosystem | 5 | 4 | | Performance & Reliability | 5 | 5 | | Setup & First Run | 5 | 4 | ## Prompt results - Prompt text: Which observability platforms integrate with deployment pipelines to correlate performance regressions with specific code changes? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | Datadog | 2 | ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 3 | | Dynatrace | 4 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 2 | | Dynatrace | 3 | ##### Xai-search - Prompt text: I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Honeycomb | 3 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Elastic | 1 | | Grafana | 2 | | New Relic | 3 | | Honeycomb | 4 | ##### Xai-search - Prompt text: Which SaaS monitoring platforms have the lowest ingestion lag during high-volume log bursts so alerting stays fast? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 1 Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | Dynatrace | 2 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 3 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 1 | ##### Xai-search | Display name | Position | | --- | --- | | Logz.io | 9 | | Elastic | 10 | | Splunk | 16 | | New Relic | 35 | | Better Stack | 51 | | Dynatrace | 59 | | Datadog | 61 | | Axiom | 71 | | Mezmo | 75 | - Prompt text: Which enterprise observability platforms handle multi-tenant environments with isolated views per team or service best? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 2 Chatgpt-search: 1 Xai-search: 56 #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Dynatrace | 1 | | Grafana | 2 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 1 | | New Relic | 2 | ##### Xai-search | Display name | Position | | --- | --- | | Logz.io | 5 | | Datadog | 17 | | Dynatrace | 26 | | New Relic | 36 | | Splunk | 46 | | Grafana | 56 | | Elastic | 66 | - Prompt text: Which observability platforms have the best alert management features to help teams reduce alert fatigue through smart routing and thresholds? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: 6 Xai-search: 23 #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | New Relic | 1 | | Datadog | 3 | | Grafana | 4 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Grafana | 6 | | Splunk | 11 | ##### Xai-search | Display name | Position | | --- | --- | | Splunk | 7 | | New Relic | 9 | | Grafana | 23 | | Datadog | 35 | | Dynatrace | 72 | - Prompt text: Which distributed tracing platforms add the least overhead to latency-sensitive APIs — safe to run in production at full sampling? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 2 | ##### Xai-search - Prompt text: What's the quickest distributed tracing platform to set up across a microservices architecture on a container orchestration platform? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 1 Chatgpt-search: 1 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Honeycomb | 1 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | Coralogix | 3 | ##### Perplexity | Display name | Position | | --- | --- | | Grafana | 1 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 1 | ##### Xai-search | Display name | Position | | --- | --- | | Logz.io | 6 | | Splunk | 9 | | Dynatrace | 10 | | New Relic | 18 | | Honeycomb | 20 | - Prompt text: What observability platforms can a small engineering team realistically get to meaningful dashboards and alerting on quickly? #### Brand position by platform Google-ai: 3 Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: 1 Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | Grafana | 3 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | | Honeycomb | 3 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | New Relic | 1 | | Grafana | 4 | | Datadog | 7 | | Better Stack | 8 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 1 | | Better Stack | 2 | | Honeycomb | 3 | ##### Xai-search - Prompt text: What observability platforms support unified metrics, traces, and logs instrumentation for Node.js and Python polyglot applications? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | Datadog | 4 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 5 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 2 | | Datadog | 3 | | New Relic | 4 | | Splunk | 5 | ##### Xai-search - Prompt text: Which cloud observability platforms have the most reliable synthetic monitoring checks with the lowest false positive rates? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 5 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 3 | | Dynatrace | 5 | ##### Chatgpt-search | Display name | Position | | --- | --- | | New Relic | 1 | | Datadog | 2 | | Dynatrace | 3 | | Grafana | 5 | ##### Xai-search - Prompt text: Which observability platforms make it easiest to correlate a user-reported error with the right trace and log lines in a distributed system? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | Honeycomb | 1 | | Dynatrace | 2 | ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | New Relic | 1 | ##### Perplexity | Display name | Position | | --- | --- | | New Relic | 1 | | Datadog | 4 | | Honeycomb | 6 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Sentry | 3 | | Honeycomb | 4 | ##### Xai-search | Display name | Position | | --- | --- | | New Relic | 1 | | Dynatrace | 9 | | Honeycomb | 18 | | Splunk | 33 | | Datadog | 55 | - Prompt text: Which observability platforms make it easiest for developers new to OpenTelemetry to adopt a trace-first workflow? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: 2 Xai-search: 65 #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Honeycomb | 1 | | Grafana | 4 | | New Relic | 6 | | Datadog | 8 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 2 | | Datadog | 3 | | New Relic | 4 | ##### Xai-search | Display name | Position | | --- | --- | | New Relic | 7 | | Coralogix | 13 | | Honeycomb | 23 | | Grafana | 65 | - Prompt text: Which APM tools have the best day-one onboarding to get immediate value without drowning in noise? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | New Relic | 1 | ##### Perplexity | Display name | Position | | --- | --- | | New Relic | 1 | | Datadog | 3 | | Sentry | 6 | ##### Chatgpt-search | Display name | Position | | --- | --- | | New Relic | 1 | | Datadog | 2 | ##### Xai-search - Prompt text: Which APM tools integrate best with cloud provider managed databases and serverless functions for end-to-end visibility? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 5 Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | New Relic | 6 | ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | New Relic | 1 | | Coralogix | 4 | ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 4 | | New Relic | 7 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 2 | | New Relic | 3 | | Grafana | 5 | ##### Xai-search - Prompt text: Which monitoring platforms offer the best on-call experience — from alert firing through to root cause identification? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Honeycomb | 1 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | Grafana | 4 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Dynatrace | 1 | | Datadog | 2 | | New Relic | 3 | ##### Xai-search | Display name | Position | | --- | --- | | Better Stack | 16 | | New Relic | 17 | | Datadog | 51 | | Dynatrace | 70 | - Prompt text: Which observability backends support receiving OpenTelemetry data simultaneously to avoid vendor lock-in? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 1 Chatgpt-search: 2 Xai-search: 14 #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 3 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Grafana | 1 | | Coralogix | 2 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 2 | | Datadog | 3 | ##### Xai-search | Display name | Position | | --- | --- | | Datadog | 7 | | Logz.io | 12 | | Grafana | 14 | | Honeycomb | 16 | | Splunk | 17 | | Elastic | 19 | - Prompt text: What are the best cloud-hosted observability platforms for migrating from a legacy self-hosted logging stack without losing historical data? #### Brand position by platform Google-ai: Not available Google-ai-mode: 2 Bing-copilot-search: Not available Perplexity: 8 Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | Grafana | 2 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | Coralogix | 9 | ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | Elastic | 3 | | New Relic | 4 | | Grafana | 8 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Elastic | 1 | | Grafana | 2 | | Datadog | 3 | ##### Xai-search - Prompt text: What log shipping tools work best for getting structured logs from containerized applications to an observability platform without code changes? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: Not available Xai-search: 39 #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 6 | ##### Chatgpt-search ##### Xai-search | Display name | Position | | --- | --- | | Logz.io | 10 | | Datadog | 16 | | Chronosphere | 27 | | Elastic | 32 | | Grafana | 39 | - Prompt text: Which monitoring platforms have the best anomaly detection — automatically surfacing regressions without manual threshold tuning? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: Not available Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 3 | | New Relic | 6 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Dynatrace | 1 | | Datadog | 2 | | New Relic | 3 | ##### Xai-search - Prompt text: Which observability platforms have the best ad-hoc query experience for high-cardinality log data during an active incident? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 3 Chatgpt-search: 3 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Honeycomb | 1 | | Grafana | 3 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Elastic | 2 | | Grafana | 3 | ##### Xai-search - Prompt text: What observability platforms offer the best tail-based sampling for high-throughput systems to control costs without losing important traces? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: 1 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Honeycomb | 2 | | Grafana | 4 | | Elastic | 7 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 1 | ##### Xai-search - Prompt text: Which observability platforms handle data retention and query performance best as log volume grows into terabytes per day? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 2 Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode | Display name | Position | | --- | --- | | New Relic | 1 | | Dynatrace | 3 | ##### Bing-copilot-search | Display name | Position | | --- | --- | | Coralogix | 3 | ##### Perplexity | Display name | Position | | --- | --- | | Elastic | 1 | | Grafana | 2 | | Datadog | 4 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Grafana | 2 | | Elastic | 3 | ##### Xai-search - Prompt text: Which observability platforms support business-level metrics like conversion funnels alongside infrastructure and application telemetry? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai | Display name | Position | | --- | --- | | Dynatrace | 2 | | Splunk | 4 | ##### Google-ai-mode | Display name | Position | | --- | --- | | Dynatrace | 1 | | Datadog | 3 | ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Dynatrace | 1 | | New Relic | 3 | | Datadog | 5 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Dynatrace | 1 | | Grafana | 2 | ##### Xai-search - Prompt text: Which observability platforms integrate best with incident management and on-call scheduling tools for a seamless response workflow? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: 4 Chatgpt-search: 2 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 3 | | Grafana | 4 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Grafana | 2 | | Better Stack | 4 | ##### Xai-search - Prompt text: Which observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance? #### Brand position by platform Google-ai: Not available Google-ai-mode: Not available Bing-copilot-search: Not available Perplexity: Not available Chatgpt-search: 4 Xai-search: Not available #### Platform rows ##### Google-ai ##### Google-ai-mode ##### Bing-copilot-search | Display name | Position | | --- | --- | | Datadog | 1 | ##### Perplexity | Display name | Position | | --- | --- | | Datadog | 1 | | New Relic | 2 | | Dynatrace | 3 | ##### Chatgpt-search | Display name | Position | | --- | --- | | Datadog | 1 | | Dynatrace | 2 | | New Relic | 3 | | Grafana | 4 | ##### Xai-search ## Top sources | Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count | | --- | --- | --- | --- | --- | --- | --- | --- | | https://grafana.com/docs/tempo/latest/set-up-for-tracing/ | Set up for tracing \| Grafana Tempo documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | documentation | 9 | 9 | | https://grafana.com/compare/grafana-vs-pagerduty/ | Grafana Cloud vs. PagerDuty: On-Call Alerting & IRM \| Grafana Labs | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | comparison | 6 | 6 | | https://grafana.com/docs/grafana/latest/setup-grafana/configure-access/multi-team-access/ | Manage multi-team access in a single Grafana instance | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | product_page | 5 | 5 | | https://grafana.com/docs/opentelemetry/ingest/ | Send and ingest OTLP data \| OpenTelemetry documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | documentation | 5 | 5 | | https://grafana.com/docs/loki/latest/configure/storage/ | Storage \| Grafana Loki documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | documentation | 5 | 5 | | https://grafana.com/docs/grafana-cloud/observe-and-act/monitor-applications/frontend-observability/integrate/apm-integration/ | Integrate Frontend Observability with Application Observability \| Grafana Cloud documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | blog_post | 5 | 5 | | https://grafana.com/docs/opentelemetry/ | grafana.com › docs › opentelemetryOpenTelemetry at Grafana Labs \| OpenTelemetry documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | documentation | 4 | 4 | | https://grafana.com/docs/loki/latest/get-started/labels/cardinality/ | Cardinality \| Grafana Loki documentation | grafana.com | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/17930c7f6264be9838468e7fd0a08efdbb07cf6d.png | commercial | documentation | 4 | 4 | ## Response excerpts | Prompt text | Platform | Excerpt | | --- | --- | --- | | What's the quickest distributed tracing platform to set up across a microservices architecture on a container orchestration platform? | chatgpt-search | If your container orchestration platform is Kubernetes, the quickest practical setup is usually OpenTelemetry + Grafana Tempo, especially if you already use Grafana. | | Which monitoring platforms have the best anomaly detection — automatically surfacing regressions without manual threshold tuning? | chatgpt-search | ...exploratory anomaly workflows \| Strong for changes you can query \| Medium \| High-cardinality/distributed systems \| \| Grafana Cloud \| Good, but more configuration-dependent \| Good \| Medium–high \| Teams wanting Prometheus/OpenTelemetry flexibility... | | I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach? | chatgpt-search | \[1\] \| \| Grafana Cloud \| Balanced / logs-first capable \| You want Loki for logs plus Tempo for traces and Grafana as the common investigation UI \| Strong signal correlation and an open-source/OpenTelemetry-oriented architecture. | ## Competitor excerpts | Platform | Competitor name | Excerpt | | --- | --- | --- | | google-ai | Honeycomb | Honeycomb (Best for High-Cardinality Root-Cause Analysis) Honeycomb was built from the ground up for exploratory debugging in complex, distributed systems using high-cardinality data. | | google-ai | Dynatrace | Dynatrace (Best for Automated AI-Driven Correlation) Dynatrace uses a deterministic, AI-powered topology engine (Smartscape) and a central data lake (Grail) to correlate signals automatically. | | bing-copilot-search | New Relic | Leading options include New Relic, Datadog, OpenObserve, and Grafana’s COS stack. | | perplexity | New Relic | New Relic looks like the easiest fit for this specific workflow: its Errors Inbox can show related sampled traces alongside an error occurrence, and its log details can show the correlated trace. | | chatgpt-search | Datadog | If the goal is specifically “a user reports an error → find the exact distributed trace → inspect the relevant log lines”, the platforms I’d shortlist are Datadog, Sentry, and Honeycomb. | | chatgpt-search | Sentry | If the goal is specifically “a user reports an error → find the exact distributed trace → inspect the relevant log lines”, the platforms I’d shortlist are Datadog, Sentry, and Honeycomb. | | bing-copilot-search | Datadog | The most prominent examples include OpenTelemetry-based setups, Datadog CI Visibility, and specialized load-testing tools like LoadTester, k6, and WebLOAD. 🔑 Key Platforms and Approaches ------------------------------- \| Platform / Tool \| How It In... | | perplexity | Datadog | Datadog — Its Continuous Delivery Visibility tracks deployments, and Code Changes Detection identifies commits included in each deployment so teams can investigate deployment-related incidents and pinpoint potential causes. | | perplexity | New Relic | New Relic — Change Tracking connects deployments and other changes to performance charts, errors, and incidents. | | chatgpt-search | Datadog | ...ployment / CI integration \| Correlation with code changes \| Particularly useful for \| \| --- \| --- \| --- \| --- \| \| Datadog \| CI/CD Visibility + CD Visibility \| Deployment metadata includes repository/commit SHA; its Code Changes Detection... | | chatgpt-search | New Relic | \[1\] \| Teams wanting CI → deployment → production telemetry in one platform \| \| New Relic \| Change Tracking + CI/CD integrations \| Deployment events can contain commit SHAs and CI/CD metadata; deployment markers can be overlaid on performance/e... | | chatgpt-search | Dynatrace | \[2\] \| Explicit deployment-regression analysis \| \| Dynatrace \| Pipeline Observability + SDLC events \| Ingests CI/CD lifecycle events and connects pipeline/deployment telemetry with runtime observability; supports GitHub Actions, GitLab, Jenkins... | ## Trend Visibility delta: -8.4 Avg position delta: 0.18333333333333313 Citation count delta: -14