New Relic Serverless Monitoring

Name: New Relic Serverless Monitoring
Brand: New Relic
Rating: 4.4 (2537 reviews)

Leader

Data for Engineers

Est 2007|Valuation $6.1B|Raised $385.3M

LinkedIn 188K|Website|Web traffic 1.3M|FTEs 3,034|HQ San Francisco, California, US

MarketsObservability Platform Application Performance Monitoring (APM)

New Relic Serverless Monitoring screenshot

01Competitive Landscape

Narrative analysis

Where New Relic tends to be aligned with buyer needs: - Organizations that prefer a single vendor for APM, serverless, logs, and tracing, and that value queryability and telemetry correlation across entities. - The vendor has emphasized OpenTelemetry compatibility and features marketed as AI-assisted workflow capabilities in recent announcements. Where competitors may be relatively stronger: - Datadog: broad integration coverage and rapid product expansion; selection depends on the customer’s existing tooling and usage profile. - Dynatrace: automation and deep analytics; typically positioned for enterprise customers and may have perceived higher costs. - Elastic Observability: attractive to teams that want more control over storage, search, and query workflows, particularly when self-managed or using Elastic Cloud.

	New Relic Serverless Monitoring	Datadog (Serverless)	Dynatrace (Serverless)
Starting Price	Free tier includes a limited free ingest allowance; paid plans combine ingest-based billing with user- or compute-based billing.	Public pricing pages exist; serverless pricing depends on SKUs and usage.	Public rate cards exist; pricing often uses credits/usage and may be targeted at enterprise customers.
Recommended For	Teams that want an integrated view across APM, logs, traces, and serverless telemetry.	Teams that value broad SaaS integrations and extensive cloud monitoring coverage.	Enterprises that prioritize automation-driven correlation and platform analytics.
Key Strength	Integrated telemetry and query-based workflows; alignment of serverless into the APM entity model.	Broad integration coverage and an extensive ecosystem.	Automation and end-to-end correlation with deep analytics capabilities.
Key Weakness	Cost predictability concerns and platform complexity for small teams.	Cost surprises are a common complaint; large-scale onboarding can be complex.	Perception of premium pricing and a steep learning curve for some teams.

01Competitive Landscape

Narrative analysis

Where New Relic tends to be aligned with buyer needs:

Organizations that prefer a single vendor for APM, serverless, logs, and tracing, and that value queryability and telemetry correlation across entities.
The vendor has emphasized OpenTelemetry compatibility and features marketed as AI-assisted workflow capabilities in recent announcements.

Where competitors may be relatively stronger:

Datadog: broad integration coverage and rapid product expansion; selection depends on the customer’s existing tooling and usage profile.
Dynatrace: automation and deep analytics; typically positioned for enterprise customers and may have perceived higher costs.
Elastic Observability: attractive to teams that want more control over storage, search, and query workflows, particularly when self-managed or using Elastic Cloud.

	New Relic Serverless Monitoring	Datadog (Serverless)	Dynatrace (Serverless)
Starting Price	Free tier includes a limited free ingest allowance; paid plans combine ingest-based billing with user- or compute-based billing.	Public pricing pages exist; serverless pricing depends on SKUs and usage.	Public rate cards exist; pricing often uses credits/usage and may be targeted at enterprise customers.
Recommended For	Teams that want an integrated view across APM, logs, traces, and serverless telemetry.	Teams that value broad SaaS integrations and extensive cloud monitoring coverage.	Enterprises that prioritize automation-driven correlation and platform analytics.
Key Strength	Integrated telemetry and query-based workflows; alignment of serverless into the APM entity model.	Broad integration coverage and an extensive ecosystem.	Automation and end-to-end correlation with deep analytics capabilities.
Key Weakness	Cost predictability concerns and platform complexity for small teams.	Cost surprises are a common complaint; large-scale onboarding can be complex.	Perception of premium pricing and a steep learning curve for some teams.