# Chronosphere AI visibility in Observability & Monitoring

Canonical: https://devtune.ai/verticals/observability-monitoring/chronosphere

[Website](https://chronosphere.io/)

Updated: 2026-10-15T01:11:58.916899+00:00
Prompts: 25
Runs: 6


## Platforms

- chatgpt-search
- perplexity
- bing-copilot-search
- google-ai-mode
- google-ai
- xai-search

Rank: 12
Total brands: 14
Measured responses: 150
Presence percent: 1.3333333333333335
Share of voice percent: 0.5535055350553505
Average position: 22.333333333333332
Docs presence percent: 0
Blog presence percent: 0
Brand mention percent: 3.3333333333333335


## Profile

Overview: Chronosphere is a cloud-native observability platform founded in 2019 by Martin Mao and Rob Skillington, former Uber engineers who built M3, Uber's open-source metrics system. The platform provides end-to-end observability for Kubernetes and microservices environments through metrics, distributed tracing, log management, and a Fluent Bit-based telemetry pipeline. Its flagship Control Plane enables policy-based telemetry governance, allowing teams to reduce data volumes and costs while maintaining critical visibility. Chronosphere has been named a Leader in the Gartner Magic Quadrant for Observability Platforms for two consecutive years (2024 and 2025). In November 2025, Palo Alto Networks acquired Chronosphere for $3.35 billion to unify observability and security capabilities for AI-era workloads. Customers include DoorDash, Snap, Robinhood, Zillow, and Affirm.
Product summary: Chronosphere offers two core products: (1) the Observability Platform — an end-to-end SaaS solution covering metrics, distributed tracing, logs, and events with a proprietary Control Plane for cost and cardinality governance, AI-guided troubleshooting (DDx), SLO management, and Chronosphere Lens for incident response; and (2) the Telemetry Pipeline — a Fluent Bit-based data collection, transformation, and routing solution for logs, metrics, events, and traces from any source to any destination, built from the Calyptia acquisition. Both products emphasize open-standards compatibility (Prometheus, OpenTelemetry) and freedom from proprietary agent lock-in. As of late 2025, both products operate under Palo Alto Networks following a $3.35B acquisition.


### Key capabilities

- Control Plane for policy-based telemetry data shaping, aggregation, and cost governance
- High-cardinality metrics management at scale (M3DB backend, Prometheus/OTel compatible)
- Distributed tracing with dynamic head and tail sampling
- Log management and optimization (Chronosphere Logs with Control Rules)
- Fluent Bit-based Telemetry Pipeline: any-source to any-destination data routing
- AI-guided troubleshooting (Differential Diagnosis / DDx) with queryless root cause analysis
- SLO management with automated SLO creation and burn-rate alerting
- Chronosphere Lens: integrated incident response and correlated signal navigation
- 99.99% uptime SLA with proven reliability at tens of millions of data points per second
- Open-standards-first architecture (Prometheus, OpenTelemetry, Fluent Bit) with no proprietary agent lock-in



### Target users

- Site reliability engineers (SREs) and DevOps teams at cloud-native and Kubernetes-heavy organizations
- Platform engineering teams managing observability infrastructure at scale
- Engineering managers and VPs of Engineering at high-growth or enterprise software companies
- FinOps and infrastructure cost optimization teams
- Security operations teams routing telemetry to SIEMs
- AI/ML platform teams monitoring LLM and AI workloads



### Key use cases

- Cloud-native and Kubernetes workload observability for microservices architectures
- Observability cost control and data volume reduction at enterprise scale
- Scaling Prometheus deployments beyond single-instance limits
- Incident detection and accelerated remediation for SRE and DevOps teams
- Telemetry pipeline management: log collection, transformation, and multi-destination routing
- AI and LLM workload monitoring and infrastructure observability
- Security log pre-processing and SIEM routing
- SLO tracking and automated service health governance

Integrations ecosystem: Chronosphere is built on open standards: it natively ingests metrics via Prometheus and OpenTelemetry, and supports distributed tracing via OpenTelemetry. Its backend is based on M3DB, the open-source time-series database originally developed at Uber. The Telemetry Pipeline product is built on Fluent Bit (acquired via Calyptia in January 2024), supporting collection, transformation, and routing from any source to any destination. Infrastructure integrations include AWS (CloudWatch metrics, AWS Marketplace listing), Google Cloud (Personalized Service Health integration, multi-year go-to-market agreement), and Kubernetes-native deployments. Developer tooling includes a Terraform provider and Pulumi provider (both open-sourced on GitHub), a CLI (chronoctl), and an MCP server for AI-assisted workflows. Alerting integrations include Slack, email, and PagerDuty-compatible workflows. The platform supports SIEM routing for security log pipelines.
Pricing summary: Chronosphere does not publish a public pricing schedule. For its Observability Platform, billing is usage-based and charged on the volume of observability data retained (not all data ingested), giving customers control over their bill via the Control Plane. Customers can set capacity limits (e.g., transformed writes per second) with no overage charges beyond the contracted threshold. For the Telemetry Pipeline product, pricing is based on raw data throughput volume. Custom contracts are negotiated directly with the vendor. No free plan or permanent free tier is available. Pilots are typically free for standard evaluations (2-3 weeks), with longer pilots potentially billed. All final pricing is determined through enterprise sales engagement.
Review summary: Chronosphere earns strong marks on Gartner Peer Insights with a 4.7/5 overall score in the 2024 Voice of the Customer report (70 reviews) and 4.6/5 with 93 reviews on the current Gartner product page. The company scored 4.8/5 specifically for support experience, and 90% of reviewers in the VoC report indicated they would recommend the product. Recurring praise centers on the quality and responsiveness of the customer success team, the cost control tooling of the Control Plane, seamless Prometheus/OpenTelemetry compatibility, and high platform reliability. Criticisms include the learning curve around PromQL, less mature logging features relative to metrics, and a UI that can take time to navigate for new users.
Competitive positioning: Chronosphere positions itself as the observability platform 'built for control,' differentiating from legacy APM and full-stack monitoring vendors (Datadog, Dynatrace, Splunk) by focusing on cost transparency and data reduction in cloud-native, Kubernetes-heavy environments. Its Control Plane — which lets teams set policy-based rules on what telemetry is retained and billed — is a primary differentiator. Unlike broad-scope competitors, Chronosphere targets enterprises struggling with observability cost explosions from microservices sprawl. It also avoids proprietary agent lock-in by building on open standards (Prometheus, OpenTelemetry, Fluent Bit). Following its $3.35B acquisition by Palo Alto Networks in 2025, it is now positioning at the intersection of observability and security for AI-era workloads, competing with Splunk (now part of Cisco) and Elastic in the converged security/observability segment.
Limitations: Chronosphere targets enterprise cloud-native organizations and does not offer a free tier or self-serve trial; pricing is custom-negotiated and opaque, creating a barrier for smaller teams or individual evaluators. Pilots are typically short (2-3 weeks) and may be paid for extended evaluations. The platform has a steeper learning curve for users unfamiliar with PromQL and the Prometheus data model. Logging capabilities (Chronosphere Logs) are newer and reviewers note they are less mature than the metrics product. The review corpus on public platforms (G2, Gartner Peer Insights) is smaller than that of larger competitors like Datadog and Grafana Labs, limiting benchmark comparisons. Following the November 2025 acquisition by Palo Alto Networks, Forrester analysts have flagged risks around roadmap reprioritization toward security-first features, potential bundle-driven pricing changes, and cultural friction between IT/DevOps buyers and a security vendor's go-to-market approach.


### Source urls

- https://chronosphere.io/
- https://www.paloaltonetworks.com/company/press/2025/palo-alto-networks-to-acquire-chronosphere--next-gen-observability-leader--for-the-ai-era
- https://www.paloaltonetworks.com/company/press/2026/palo-alto-networks-completes-chronosphere-acquisition--unifying-observability-and-security-for-the-ai-era
- https://techcrunch.com/2023/01/10/observability-platform-chronosphere-raises-another-115m-at-a-1-6b-valuation/
- https://www.gartner.com/reviews/market/observability-platforms/vendor/chronosphere/product/chronosphere-platform
- https://chronosphere.io/learn/gartner-voice-of-the-customer-report-2024/
- https://chronosphere.io/news/chronosphere-marks-a-year-of-new-capabilities/
- https://chronosphere.io/partner/chronosphere-and-aws/
- https://chronosphere.io/news/winners-of-inaugural-observability-innovation-awards/
- https://www.forrester.com/blogs/paying-to-observe-it-all-palo-alto-networks-acquisition-of-chronosphere/
- https://www.prnewswire.com/news-releases/chronosphere-named-a-leader-for-second-consecutive-year-in-the-2025-gartner-magic-quadrant-for-observability-platforms-302503383.html
- https://github.com/chronosphereio

Reviewed at: 2026-04-28T23:22:06.327+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| DoorDash | DoorDash migrated its metrics and observability infrastructure to Chronosphere, eliminating constant packet loss and unreliable monitoring. 90% of DoorDash engineers adopted the platform, and the team automated 14,000 SLOs. | 54% reduction in observability data volumes; $40M+ cost savings over 3 years |
| Astronomer | Astronomer switched to Chronosphere during a period of ~300% growth in 2023, drastically reducing observability costs by optimizing data volumes while improving developer productivity and query performance. | 85% cost reduction; 80% data volume optimization |
| Rubrik | Rubrik migrated to an open-source-compatible observability architecture with Chronosphere to improve cost efficiency, scalability, and consolidate tooling, completing a large-scale migration rapidly. | 1,200+ assets migrated in 8 weeks |



### Reviews breakdown

| Platform | Score | Score max | Review count | Url |
| --- | --- | --- | --- | --- |
| Gartner Peer Insights | 4.6 | 5 | 93 | https://www.gartner.com/reviews/market/observability-platforms/vendor/chronosphere/product/chronosphere-platform |



### Review themes



#### Praised

- Responsive and knowledgeable customer success and support team
- Effective cost control tooling via the Control Plane
- Seamless Prometheus and OpenTelemetry compatibility
- High platform reliability and uptime at scale
- Intuitive UI for metrics dashboards and alerting
- Painless onboarding and migration from existing Prometheus setups
- Strong partnership and feedback responsiveness from the Chronosphere team
- Powerful cardinality and data volume management tools



#### Criticized

- Steep PromQL learning curve for engineers new to Prometheus
- Log management capabilities newer and less mature than metrics
- UI takes time to get used to for new users
- Prometheus histogram handling described as clunky
- SLO product onboarding and education could be clearer
- Data processing cost impact not always apparent during POC phase
- Post-acquisition roadmap uncertainty under Palo Alto Networks




### Company facts

Founded year: 2019
Hq: New York, NY, USA


#### Founders

- Martin Mao
- Rob Skillington

Employees range: 251-500
Total funding: $343M
Valuation: $3.35B (acquisition price, Nov 2025)
Arr: >$160M
Customer count: Not available
Status: Acquired by Palo Alto Networks (NASDAQ: PANW), Nov 2025


Readiness: Not available


## Ranking

| Display name | Pair count | Total pairs | Presence percent | Avg position |
| --- | --- | --- | --- | --- |
| Datadog | 46 | 150 | 30.666666666666664 | 10.60576923076923 |
| New Relic | 45 | 150 | 30 | 10.10576923076923 |
| Grafana | 37 | 150 | 24.666666666666668 | 12.446601941747574 |
| Dynatrace | 23 | 150 | 15.333333333333332 | 24.176470588235293 |
| Elastic | 17 | 150 | 11.333333333333332 | 16.97222222222222 |
| Honeycomb | 17 | 150 | 11.333333333333332 | 18.05 |
| Splunk | 15 | 150 | 10 | 19.57894736842105 |
| Coralogix | 7 | 150 | 4.666666666666667 | 6.588235294117647 |
| Better Stack | 6 | 150 | 4 | 16 |
| Logz.io | 5 | 150 | 3.3333333333333335 | 11.666666666666666 |
| Sentry | 2 | 150 | 1.3333333333333335 | 3 |
| Chronosphere | 2 | 150 | 1.3333333333333335 | 22.333333333333332 |
| Axiom | 1 | 150 | 0.6666666666666667 | 74.66666666666667 |
| Mezmo | 1 | 150 | 0.6666666666666667 | 75 |



## Platform breakdown

| Platform | Prompt count | Presence rate |
| --- | --- | --- |
| chatgpt-search | 0 | 0 |
| perplexity | 0 | 0 |
| bing-copilot-search | 0 | 0 |
| google-ai-mode | 1 | 4 |
| google-ai | 0 | 0 |
| xai-search | 1 | 4 |



## Strengths





## 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 enterprise observability platforms handle multi-tenant environments with isolated views per team or service best? | 4 |
| What observability platforms offer the best tail-based sampling for high-throughput systems to control costs without losing important traces? | 4 |
| What are the best cloud-hosted observability platforms for migrating from a legacy self-hosted logging stack without losing historical data? | 4 |
| Which observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance? | 4 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 0 |
| Developer Experience | 5 | 0 |
| Integrations & Ecosystem | 5 | 1 |
| Performance & Reliability | 5 | 1 |
| Setup & First Run | 5 | 0 |



## Prompt results

- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| Grafana | 4 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai

| Display name | Position |
| --- | --- |
| Grafana | 2 |



##### Xai-search

| Display name | Position |
| --- | --- |
| Logz.io | 6 |
| Splunk | 9 |
| Dynatrace | 10 |
| New Relic | 18 |
| Honeycomb | 20 |


- Prompt text: Which observability platforms integrate with deployment pipelines to correlate performance regressions with specific code changes?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 4 |
| Dynatrace | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Datadog | 3 |
| Dynatrace | 5 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Dynatrace | 3 |



##### Google-ai





##### Xai-search




- Prompt text: Which monitoring platforms have the best anomaly detection — automatically surfacing regressions without manual threshold tuning?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| Dynatrace | 2 |
| New Relic | 5 |
| Elastic | 8 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Dynatrace | 1 |
| Datadog | 5 |
| New Relic | 6 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Elastic | 1 |
| Splunk | 3 |
| Grafana | 6 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search




- Prompt text: What observability platforms can a small engineering team realistically get to meaningful dashboards and alerting on quickly?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 1 |
| Better Stack | 2 |
| New Relic | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Grafana | 1 |
| Datadog | 3 |
| Better Stack | 5 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search





##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 4 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Elastic | 5 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Elastic | 9 |



##### Xai-search




- Prompt text: Which enterprise observability platforms handle multi-tenant environments with isolated views per team or service best?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 1 |
| Datadog | 4 |
| Dynatrace | 5 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Dynatrace | 1 |
| Grafana | 3 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Grafana | 1 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Grafana | 1 |



##### 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 make it easiest to correlate a user-reported error with the right trace and log lines in a distributed system?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Grafana | 2 |
| New Relic | 10 |



##### Perplexity

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Datadog | 3 |
| Honeycomb | 5 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| New Relic | 2 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Sentry | 2 |
| Honeycomb | 3 |
| Datadog | 5 |



##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Dynatrace | 9 |
| Honeycomb | 18 |
| Splunk | 33 |
| Datadog | 55 |


- Prompt text: Which APM tools have the best day-one onboarding to get immediate value without drowning in noise?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Datadog | 3 |



##### Perplexity

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Sentry | 3 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| New Relic | 1 |



##### Google-ai-mode





##### Google-ai





##### Xai-search




- Prompt text: Which observability backends support receiving OpenTelemetry data simultaneously to avoid vendor lock-in?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 1 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Grafana | 1 |
| New Relic | 3 |
| Datadog | 4 |
| Honeycomb | 8 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| Datadog | 7 |
| Logz.io | 12 |
| Grafana | 14 |
| Honeycomb | 16 |
| Splunk | 17 |
| Elastic | 19 |


- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| Grafana | 3 |
| New Relic | 5 |
| Coralogix | 9 |
| Datadog | 11 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| Grafana | 3 |
| Datadog | 8 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Datadog | 3 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Datadog | 2 |
| Grafana | 3 |



##### Xai-search




- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Elastic | 4 |
| New Relic | 6 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Elastic | 1 |
| Datadog | 3 |
| New Relic | 6 |
| Grafana | 8 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Datadog | 1 |



##### Google-ai

| Display name | Position |
| --- | --- |
| Datadog | 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: 4
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Coralogix | 1 |
| Datadog | 11 |
| Elastic | 17 |
| Grafana | 19 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Grafana | 1 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Chronosphere | 4 |
| Coralogix | 6 |



##### Google-ai





##### Xai-search




- Prompt text: Which observability platforms support business-level metrics like conversion funnels alongside infrastructure and application telemetry?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 4 |
| Dynatrace | 8 |
| Splunk | 12 |
| Elastic | 16 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Dynatrace | 3 |
| New Relic | 6 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Coralogix | 9 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Dynatrace | 1 |
| New Relic | 2 |



##### Google-ai





##### Xai-search




- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 2 |
| Datadog | 6 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 4 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| New Relic | 4 |



##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 3 |
| Grafana | 6 |
| Splunk | 10 |
| New Relic | 11 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 5 |
| Grafana | 6 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search




- Prompt text: Which observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Dynatrace | 3 |
| New Relic | 5 |
| Splunk | 7 |
| Elastic | 9 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 2 |
| Dynatrace | 3 |
| Elastic | 5 |
| Splunk | 6 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Dynatrace | 1 |
| Grafana | 2 |
| Datadog | 3 |
| New Relic | 6 |
| Elastic | 9 |



##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 3 |
| Dynatrace | 8 |



##### Perplexity

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Dynatrace | 5 |



##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| New Relic | 3 |
| Coralogix | 4 |



##### Google-ai-mode

| Display name | Position |
| --- | --- |
| New Relic | 1 |
| Datadog | 3 |



##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Better Stack | 2 |
| New Relic | 3 |
| Datadog | 4 |
| Grafana | 8 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Grafana | 5 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| Better Stack | 16 |
| New Relic | 17 |
| Datadog | 51 |
| Dynatrace | 70 |


- Prompt text: Which cloud observability platforms have the most reliable synthetic monitoring checks with the lowest false positive rates?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Dynatrace | 1 |
| Datadog | 3 |
| New Relic | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| New Relic | 2 |
| Splunk | 3 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| New Relic | 1 |



##### Google-ai





##### 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Splunk | 1 |
| Grafana | 3 |
| New Relic | 5 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Splunk | 1 |
| New Relic | 3 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### 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 observability platforms make it easiest for developers new to OpenTelemetry to adopt a trace-first workflow?


#### Brand position by platform

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Honeycomb | 6 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| New Relic | 4 |
| Datadog | 6 |
| Grafana | 7 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| New Relic | 7 |
| Coralogix | 13 |
| Honeycomb | 23 |
| Grafana | 65 |


- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Datadog | 1 |
| Grafana | 2 |
| Dynatrace | 3 |
| New Relic | 5 |
| Splunk | 7 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Grafana | 1 |
| New Relic | 2 |



##### Bing-copilot-search





##### Google-ai-mode





##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| Splunk | 7 |
| New Relic | 9 |
| Grafana | 23 |
| Datadog | 35 |
| Dynatrace | 72 |


- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: 27



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Grafana | 7 |
| Elastic | 8 |



##### Perplexity





##### Bing-copilot-search

| Display name | Position |
| --- | --- |
| Coralogix | 6 |



##### Google-ai-mode





##### Google-ai





##### Xai-search

| Display name | Position |
| --- | --- |
| Logz.io | 10 |
| Datadog | 16 |
| Chronosphere | 27 |
| Elastic | 32 |
| Grafana | 39 |


- 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

Chatgpt-search: Not available
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: Not available



#### Platform rows



##### Chatgpt-search

| Display name | Position |
| --- | --- |
| Better Stack | 1 |
| Datadog | 2 |
| Elastic | 3 |
| Grafana | 12 |



##### Perplexity

| Display name | Position |
| --- | --- |
| Honeycomb | 1 |
| Grafana | 6 |



##### Bing-copilot-search





##### Google-ai-mode

| Display name | Position |
| --- | --- |
| Honeycomb | 3 |



##### Google-ai





##### Xai-search







## Top sources

| Url | Title | Domain | Logo url | Source vertical | Content type | Citation count | Last30d count |
| --- | --- | --- | --- | --- | --- | --- | --- |
| https://chronosphere.io/platform/logs/ | Chronosphere Log Management | chronosphere.io | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/5f11b3cb0575de6e1944938d652477f833bab94b.png | commercial | product_page | 1 | 1 |
| https://chronosphere.io/learn/fluent-bit-vs-beats/ | Fluent Bit and Beats: Two approaches to a task | chronosphere.io | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/5f11b3cb0575de6e1944938d652477f833bab94b.png | commercial | home | 1 | 0 |
| https://chronosphere.io/learn/fluent-bit-loki/ | How to send Logs to Loki using Fluent Bit | chronosphere.io | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/5f11b3cb0575de6e1944938d652477f833bab94b.png | commercial | home | 1 | 0 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| Which observability platforms have the best ad-hoc query experience for high-cardinality log data during an active incident? | google-ai-mode | Honeycomb vs Grafana Cloud vs ChronosphereTop 7 Grafana Alternatives In 2026 \| Honeycomb Observability 2. Grafana Cl... |
| Which observability platforms handle data retention and query performance best as log volume grows into terabytes per day? | google-ai-mode | ...de) The top-performing observability platforms designed or optimized for terabyte-to-petabyte scale include: * * Chronosphere Built specifically for massive enterprise scale (handling high-volume telemetry for companies like Zillow and Affirm... |
| What observability platforms offer the best tail-based sampling for high-throughput systems to control costs without losing important traces? | google-ai | Chronosphere * How it works: Chronosphere was built specifically to combat data growth and cardinality explosion in cloud-native, high-throughput Kubernetes environments. |



## Competitor excerpts

| Platform | Competitor name | Excerpt |
| --- | --- | --- |
| chatgpt-search | Datadog | If your goal is to take a user report like “Checkout failed at 14:03, and I got a 500 error” and quickly find the exact distributed trace, the relevant log lines, and the failing service, I’d shortlist Datadog, Sentry, Honeycomb, New Relic, and Grafana Cloud. |
| chatgpt-search | Grafana | If your goal is to take a user report like “Checkout failed at 14:03, and I got a 500 error” and quickly find the exact distributed trace, the relevant log lines, and the failing service, I’d shortlist Datadog, Sentry, Honeycomb, New Relic, and Grafana Cloud. |
| perplexity | New Relic | The strongest fits are New Relic and Datadog; Honeycomb is a good option when your team is comfortable investigating structured telemetry. |
| perplexity | Datadog | The strongest fits are New Relic and Datadog; Honeycomb is a good option when your team is comfortable investigating structured telemetry. |
| bing-copilot-search | New Relic | The strongest options today are OpenObserve, New Relic, Datadog, Honeycomb, and OpenTelemetry-based stacks. ## 🔑 Key Considerations When choosing an observability platform for correlating user-reported errors: * Unified telemetry: Does the p... |
| google-ai-mode | Sentry | ...SREs](https://openobserve.ai/blog/logs-traces-metrics-correlation/)Errors, traces, logs, metrics: when to reach for what - Sentry Blog The observability platforms that make thi... |
| google-ai-mode | Honeycomb | ...lation the easiest—largely by natively bridging user context with backend telemetry—stand out in distinct ways: * * _Honeycomb_ — Best for High-Cardinality Root Cause Analysis * Why it shines: Honeycomb treats high-cardinality data (lik... |
| chatgpt-search | Grafana | ## Best enterprise observability platforms to evaluate ## 1. Grafana Enterprise and Grafana Cloud Best for flexible team isolation Strong choice for organizations that want shared observability infrastructure with team-specific data access, dashboar... |
| perplexity | Dynatrace | For team- or service-level views with access controls, Dynatrace and Grafana Enterprise/Cloud are the strongest fits among the platforms covered by the available evidence—but they isolate access in different ways. |
| perplexity | Grafana | For team- or service-level views with access controls, Dynatrace and Grafana Enterprise/Cloud are the strongest fits among the platforms covered by the available evidence—but they isolate access in different ways. |
| google-ai-mode | Grafana | Manage tenant isolation[Building a Multi-Tenant Observability Platform with SigNoz + OneUptime - DEV Community](https://dev.to/starkprince/building-a-multi-tenant-observability-pla... |
| google-ai | Grafana | Grafana Enterprise & Grafana Cloud (Mimir/Loki/Tempo) Grafana is widely regarded as an industry standard for multi-team and multi-tenant visualization. |



## Trend

Visibility delta: -1.2
Avg position delta: 0.6666666666666665
Citation count delta: -2