# Elastic AI visibility in Observability & Monitoring

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

[Website](https://www.elastic.co/)

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: 5
Total brands: 14
Measured responses: 150
Presence percent: 11.333333333333332
Share of voice percent: 6.642066420664207
Average position: 16.97222222222222
Docs presence percent: 7.333333333333333
Blog presence percent: 0.6666666666666667
Brand mention percent: 28.666666666666668


## Profile

Overview: Elastic N.V. (NYSE: ESTC) is the Search AI Company, offering a unified platform for enterprise search, observability, and cybersecurity built on the open-source Elastic Stack (Elasticsearch, Kibana, Logstash, Beats). Founded in 2012 in Amsterdam by Shay Banon and co-founders, the company went public on the NYSE in October 2018 and reported $1.48 billion in total revenue for fiscal year 2025. Elastic Observability provides unified visibility across logs, metrics, APM traces, real user monitoring, and synthetic data, all powered by Elasticsearch's real-time, petabyte-scale search engine. The platform is OpenTelemetry-native, includes ML-based anomaly detection and an AI Assistant for root cause analysis, and supports cloud, hybrid, and on-premises deployments. Elastic is a Gartner Magic Quadrant Leader for Observability Platforms in 2024 and 2025, trusted by more than 50% of the Fortune 500.
Product summary: Elastic Observability is a full-stack observability solution built on the Elasticsearch platform that unifies logs, metrics, APM traces, real user monitoring (RUM), and synthetic testing into a single interface powered by Kibana. It ingests and correlates petabytes of telemetry data in real time using OpenTelemetry-native collection via the Elastic Distribution of OpenTelemetry (EDOT) SDK, applies ML-based anomaly detection and AIOps, and provides an AI Assistant grounded in organizational knowledge bases to accelerate incident response and root cause analysis. Deployable as a fully managed serverless service, hosted cloud (AWS, Azure, GCP), or self-managed on-premises cluster via Kubernetes (ECK), it is designed to handle modern multi-cloud and hybrid environments at enterprise scale.


### Key capabilities

- Unified log analytics with real-time search across petabyte-scale log data via Elasticsearch
- Application performance monitoring (APM) with distributed tracing and service maps
- Infrastructure monitoring for cloud, hybrid, and on-premises environments
- Digital experience monitoring via Real User Monitoring (RUM) and synthetic testing
- AIOps with ML-based anomaly detection and AI Assistant for root cause analysis
- LLM observability for monitoring GenAI application performance, cost, and safety
- OpenTelemetry-native MELT data ingestion and correlation (EDOT SDK)
- Kibana for customizable visualization, dashboards, and exploration
- Elastic Search AI Platform with vector database and RAG support for GenAI applications
- Flexible deployment: Elastic Cloud Serverless, Cloud Hosted (AWS/Azure/GCP/Alibaba), or self-managed (on-prem/Kubernetes)



### Target users

- Site reliability engineers (SREs) and DevOps teams at mid-to-large enterprises
- Platform engineering and infrastructure teams managing multi-cloud or hybrid environments
- Security operations (SecOps) teams requiring unified observability and SIEM
- Software developers building and monitoring distributed microservices
- IT operations teams seeking to consolidate fragmented monitoring toolsets
- Data engineers managing large-scale log ingestion pipelines



### Key use cases

- Centralized log management and analysis at enterprise scale
- Full-stack APM and distributed tracing for microservices and cloud-native applications
- Cloud and infrastructure monitoring across AWS, Azure, GCP, and Kubernetes
- AI-driven incident detection, triage, and root cause analysis (AIOps)
- Observability platform consolidation (replacing fragmented multi-vendor monitoring toolsets)
- LLM and GenAI application observability and cost monitoring
- Real user monitoring and synthetic testing for digital experience management
- Combined security and observability on a single platform (with Elastic Security/SIEM)

Integrations ecosystem: Elastic maintains a catalog of hundreds of pre-built integrations spanning AWS (CloudWatch, S3, EC2, GuardDuty, Kinesis Firehose, Lambda, and more), Azure (Activity Logs, Monitor, Sentinel, OpenAI, AI Foundry, and more), Google Cloud (GKE, Pub/Sub, Vertex AI, Security Command Center, and more), Kubernetes, Docker, Prometheus (with native PromQL in Kibana), OpenTelemetry (via the Elastic Distribution of OpenTelemetry / EDOT SDK), Apache Kafka, Logstash, Fluentd, and major security vendors including CrowdStrike, Palo Alto Networks, Okta, Cisco, and SentinelOne. Alerting and ITSM integrations include PagerDuty, ServiceNow, Jira, OpsGenie, Slack, and Microsoft Teams. Available on AWS, Azure, and Google Cloud marketplaces. Elastic Agent provides a unified data collection layer across platforms.
Pricing summary: Elastic Cloud Hosted starts at $99/month (resource-based, pay-as-you-go or prepaid annual) available across AWS, Azure, GCP, and Alibaba in 60+ regions. Elastic Cloud Serverless is usage-based (pay-as-you-go or prepaid annual) and auto-scales with no cluster management overhead. Self-managed deployments use license-based pricing on Platinum and Enterprise subscription tiers, based on node count and RAM. A 14-day free trial (no credit card required) covers all solutions on Elastic Cloud. Four support tiers are available for cloud deployments, with a 99.95% monthly uptime SLA for Platinum and Enterprise tiers.
Review summary: Elastic Observability holds a 4.2/5 on G2 (90 reviews) and a 4.4/5 on Gartner Peer Insights (270 reviews in the Observability Platforms market). PeerSpot rates it 8.0/10, noting it is most popular among large enterprises (58% of researchers). Users consistently praise its powerful and flexible Elasticsearch-powered search, highly customizable Kibana dashboards, extensive pre-built integrations, and unified MELT visibility. Common criticisms include a steep learning curve, complex cluster administration, resource-intensive infrastructure demands, and pricing that can escalate at enterprise scale. Gartner reviewers also ranked Elastic among the five highest-scoring vendors across all six use cases in the 2025 Gartner Critical Capabilities for Observability Platforms report.
Competitive positioning: Elastic positions as an open-source-rooted Search AI platform that unifies observability, security, and enterprise search on a single stack, differentiating through Elasticsearch's unmatched search query performance, OpenTelemetry-native data ingestion, and breadth of MELT coverage. It competes with pure-play APM and log-management vendors by offering lower total cost of ownership claims, flexible deployment (serverless, hosted, self-managed), and an AI Assistant grounded in organizational knowledge bases. Named a Gartner Magic Quadrant Leader for Observability Platforms in both 2024 and 2025, and a Forrester Wave Leader for Security Analytics Q2 2025, Elastic targets enterprises seeking platform consolidation across observability and security.
Limitations: Users commonly report a steep learning curve and complex initial configuration, particularly around cluster management, index lifecycle policies, and schema optimization at scale. Elasticsearch is resource-intensive (high CPU and memory), which can raise infrastructure costs in self-managed deployments. Pricing at scale is frequently cited as less competitive versus some newer cloud-native observability vendors. Log retention occasionally requires manual intervention due to agent instability. The platform's breadth can make it harder to articulate focused value to C-suite decision-makers compared to more narrowly positioned competitors. Serverless deployment options are still maturing in feature parity relative to hosted and self-managed capabilities.


### Source urls

- https://www.elastic.co/
- https://www.elastic.co/pricing
- https://www.elastic.co/customers/pepsico
- https://www.elastic.co/customers/uol
- https://www.elastic.co/integrations/data-integrations
- https://finance.yahoo.com/news/elastic-reports-fourth-quarter-fiscal-200500982.html
- https://www.sec.gov/Archives/edgar/data/1707753/000170775325000021/estc-20250430.htm
- https://www.g2.com/products/elastic-observability/reviews
- https://www.gartner.com/reviews/market/observability-platforms/vendor/elastic/product/elastic-observability
- https://www.peerspot.com/products/elastic-observability-reviews
- https://en.wikipedia.org/wiki/Elastic_NV
- https://www.elastic.co/resources/observability/analyst-report/gartner-magic-quadrant-observability-platforms

Reviewed at: 2026-04-28T23:21:54.887+00:00


### Customer outcomes

| Customer | Summary | Metric |
| --- | --- | --- |
| PepsiCo | PepsiCo standardized on Elastic Observability for its Full Stack Observability platform, consolidating MELT data from 38+ critical applications and rationalizing its monitoring tool count from 55 to fewer than 20, achieving 99.9% application uptime and a 23% automation rate in in | 30% MTTR reduction; 25% annual hardware cost reduction |
| UOL | Brazil's largest digital media company migrated from Splunk to Elastic Security and unified observability and security on a single Elastic platform, enabling AI-assisted root cause analysis with Amazon Bedrock integration and reducing false positives by 50%. | 80% faster incident resolution time |



### Reviews breakdown

| Platform | Score | Score max | Review count | Url |
| --- | --- | --- | --- | --- |
| G2 | 4.2 | 5 | 90 | https://www.g2.com/products/elastic-observability/reviews |
| Gartner Peer Insights | 4.4 | 5 | 270 | https://www.gartner.com/reviews/market/observability-platforms/vendor/elastic/product/elastic-observability |



### Review themes



#### Praised

- Powerful and flexible full-text search via Elasticsearch
- Highly customizable Kibana dashboards
- Extensive pre-built integrations ecosystem
- Real-time log analysis and visualization
- Unified MELT data visibility in a single platform
- OpenTelemetry-native data collection
- Active open-source community and developer ecosystem
- Scalable architecture for petabyte-scale telemetry



#### Criticized

- Steep learning curve and complex initial setup
- Resource-intensive (high CPU and memory usage)
- Pricing can escalate significantly at enterprise scale
- Cluster and index lifecycle management complexity
- Log retention occasionally requires manual intervention
- Difficult to communicate value proposition to C-suite vs. competitors
- Serverless feature parity still maturing




### Company facts

Founded year: 2012
Hq: Amsterdam, Netherlands / San Francisco, CA, USA


#### Founders

- Shay Banon
- Simon Willnauer
- Steven Schuurman
- Uri Boness

Employees range: 3500-5000
Total funding: ~$104M pre-IPO; $252M IPO (Oct 2018)
Valuation: Not available
Arr: Not available
Customer count: ~21,500 subscription customers
Status: Public (NYSE: ESTC)


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 | 8 | 32 |
| perplexity | 2 | 8 |
| bing-copilot-search | 0 | 0 |
| google-ai-mode | 2 | 8 |
| google-ai | 1 | 4 |
| xai-search | 4 | 16 |



## Strengths

| Prompt text | Platform count | Avg position |
| --- | --- | --- |
| I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach? | 1 | 1 |



## 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 |
| Which observability platforms support real user monitoring alongside backend APM for correlating frontend and backend performance? | 4 |
| Which APM tools integrate best with cloud provider managed databases and serverless functions for end-to-end visibility? | 4 |



## Topic scores

| Topic name | Prompt count | Cited prompt count |
| --- | --- | --- |
| Capability | 5 | 5 |
| Developer Experience | 5 | 1 |
| Integrations & Ecosystem | 5 | 2 |
| Performance & Reliability | 5 | 2 |
| Setup & First Run | 5 | 2 |



## 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: 8
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: 1
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: 5
Google-ai: 9
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: 66



#### 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: 19



#### 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: 4
Perplexity: 1
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: 17
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 |
| --- | --- |
| 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: 16
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: 9
Perplexity: 5
Bing-copilot-search: Not available
Google-ai-mode: 9
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: 10



#### 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: 8
Perplexity: Not available
Bing-copilot-search: Not available
Google-ai-mode: Not available
Google-ai: Not available
Xai-search: 32



#### 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: 3
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://www.elastic.co/docs/deploy-manage/tools/snapshot-and-restore | Snapshot and restore \| Elastic Docs | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 5 | 5 |
| https://www.elastic.co/docs/manage-data/migrate | Migrate your Elasticsearch data \| Elastic Docs | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 4 | 4 |
| https://www.elastic.co/docs/solutions/observability | Elastic Observability overview | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 3 | 3 |
| https://www.elastic.co/docs/manage-data/lifecycle/data-tiers | Elasticsearch data tiers: hot, warm, cold, and frozen storage explained \| Elastic Docs | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 3 | 3 |
| https://www.elastic.co/blog/3-pillars-of-observability | The 3 pillars of observability: Unified logs, metrics, and traces \| Elastic Blog | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | blog_post | 2 | 2 |
| https://discuss.elastic.co/t/how-rum-and-apm-works/373846 | How RUM and APM works - APM - Discuss the Elastic Stack | discuss.elastic.co | Not available | commercial | discussion | 2 | 2 |
| https://www.elastic.co/docs/solutions/observability/apm/logs | Logs | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 2 | 2 |
| https://www.elastic.co/docs/explore-analyze/query-filter/languages/eql | EQL | elastic.co | https://izgwnlozsmjmqjsnddmg.supabase.co/storage/v1/object/public/domain-logos/9dbab6f8-54b2-49a0-8181-89a0ed130318/4f638bff-15d9-4202-be76-d55ee1111439/7a5044129a1f2fb48fca4de6f23551f8836f1853.png | commercial | documentation | 2 | 2 |



## Response excerpts

| Prompt text | Platform | Excerpt |
| --- | --- | --- |
| I'm evaluating observability platforms — which ones are best suited for a logs-first approach versus a traces-first approach? | google-ai-mode | Elastic Observability : Built on the Elasticsearch search engine, Elastic treats logs as a core semantic capability. |
| What observability platforms support unified metrics, traces, and logs instrumentation for Node.js and Python polyglot applications? | google-ai-mode | Datadog vs New Relic vs Dynatrace vs AppDynamics (2026) * * * * * 3. Elastic Observability * Overview: Built on the powerful search foundation of Elasticsearch, tailored heavily toward log-driven application context. |
| Which SaaS monitoring platforms have the lowest ingestion lag during high-volume log bursts so alerting stays fast? | google-ai-mode | * Top SaaS Monitoring Platforms for Ingestion Latency Under Load * * Datadog Logs * Ingestion Behavior: Highly elastic stream-processing pipeline. |



## 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: 1.4000000000000004
Avg position delta: 8.594155844155845
Citation count delta: 17