groundcover

Name: groundcover
Brand: groundcover
Rating: 4.7 (58 reviews)

AI NativeLeader

Monitor everything you run on the cloud without compromising on cost, granularity, or scale.

Est 2021|Valuation $520M|Raised $159.5M|12 Ref Customers

LinkedIn 10K|Website|Web traffic 53K|FTEs 140|HQ Tel Aviv, Israel

MarketsInfrastructure Monitoring Observability Platform Application Performance Monitoring (APM)

01Competitive Landscape

| Aspect | groundcover | Datadog | Dynatrace | |--------|-------------|---------|-----------| | Starting Price | Public page lists Free/Team/Enterprise but exact per-node list pricing not clearly extractable from captured view; pricing is node-based (monthly average monitored K8s nodes) plus BYOC hosting costs | Public list pricing is modular by product; common entry points include infrastructure monitoring per host/month and separate charges for logs/APM/etc. (see Datadog pricing list) | Consumption/commitment model with rate card by capability; billed via consumption against a commitment (Dynatrace docs/rate card) | | Best For | K8s-heavy orgs wanting BYOC data residency and predictable pricing not tied to ingest volume; teams sensitive to telemetry-data privacy | Broadest “one platform” SaaS with large integration ecosystem and mature UX; orgs prioritizing speed of adoption and wide product breadth | Enterprise-grade full-stack observability with strong auto-discovery/mapping and AI-assisted analysis; orgs willing to manage consumption model | | Key Strength | BYOC architecture + eBPF-based zero/low instrumentation narrative; cost predictability tied to nodes | Mature workflows, huge ecosystem, strong cross-team “single pane” adoption | Automated discovery, dependency mapping, feature breadth; enterprise-grade capabilities | | Key Weakness | Smaller review footprint; perceived as less mature vs incumbents; BYOC shifts infra costs to customer cloud | Pricing complexity and unpredictability widely complained about in community discussions; costs can scale quickly with logs/traces/modules | Premium pricing and potentially complex consumption math; may be overkill for small teams | - Narrative analysis - groundcover vs Datadog - groundcover’s core differentiation is BYOC + “volume-agnostic” pricing (node-based) and the promise of high-fidelity telemetry via eBPF without heavy code instrumentation. - Datadog’s advantage is maturity: breadth of integrations, UX polish, and a proven ecosystem. However, community discussions frequently complain about Datadog pricing complexity and cost growth. - A practical buyer question: whether groundcover can match Datadog’s “workflow ease” and broad product modules (RUM, synthetics, security monitoring) at similar depth. - groundcover vs Dynatrace - Dynatrace is commonly perceived as enterprise-grade and feature-rich, with strong automated discovery and mapping. - groundcover may appeal more to Kubernetes-native teams wanting in-account deployment and predictable cost, while Dynatrace’s consumption/commitment approach may be less intuitive for some teams. - groundcover vs New Relic - New Relic publishes ingest-based pricing ($/GB beyond free allotments) and user-based components, which can still become cost-sensitive in high-volume environments. - groundcover’s pitch is to avoid per-GB billing by running storage in the customer’s account. - Market share and adoption trends - No authoritative market-share numbers were found in the accessed sources. - Thoughtworks Technology Radar entry indicates groundcover is notable enough to be tracked as an emerging platform trend, but that is not equivalent to market share. - When customers choose competitors instead (and why) - Customers may choose Datadog/Dynatrace when they need: - The most mature UX and workflow features immediately - Very broad integration catalogs - Established enterprise procurement comfort and long reference lists

01Competitive Landscape

Aspect	groundcover	Datadog	Dynatrace
Starting Price	Public page lists Free/Team/Enterprise but exact per-node list pricing not clearly extractable from captured view; pricing is node-based (monthly average monitored K8s nodes) plus BYOC hosting costs	Public list pricing is modular by product; common entry points include infrastructure monitoring per host/month and separate charges for logs/APM/etc. (see Datadog pricing list)	Consumption/commitment model with rate card by capability; billed via consumption against a commitment (Dynatrace docs/rate card)
Best For	K8s-heavy orgs wanting BYOC data residency and predictable pricing not tied to ingest volume; teams sensitive to telemetry-data privacy	Broadest “one platform” SaaS with large integration ecosystem and mature UX; orgs prioritizing speed of adoption and wide product breadth	Enterprise-grade full-stack observability with strong auto-discovery/mapping and AI-assisted analysis; orgs willing to manage consumption model
Key Strength	BYOC architecture + eBPF-based zero/low instrumentation narrative; cost predictability tied to nodes	Mature workflows, huge ecosystem, strong cross-team “single pane” adoption	Automated discovery, dependency mapping, feature breadth; enterprise-grade capabilities
Key Weakness	Smaller review footprint; perceived as less mature vs incumbents; BYOC shifts infra costs to customer cloud	Pricing complexity and unpredictability widely complained about in community discussions; costs can scale quickly with logs/traces/modules	Premium pricing and potentially complex consumption math; may be overkill for small teams

Narrative analysis
- groundcover vs Datadog
  - groundcover’s core differentiation is BYOC + “volume-agnostic” pricing (node-based) and the promise of high-fidelity telemetry via eBPF without heavy code instrumentation.
  - Datadog’s advantage is maturity: breadth of integrations, UX polish, and a proven ecosystem. However, community discussions frequently complain about Datadog pricing complexity and cost growth.
  - A practical buyer question: whether groundcover can match Datadog’s “workflow ease” and broad product modules (RUM, synthetics, security monitoring) at similar depth.
- groundcover vs Dynatrace
  - Dynatrace is commonly perceived as enterprise-grade and feature-rich, with strong automated discovery and mapping.
  - groundcover may appeal more to Kubernetes-native teams wanting in-account deployment and predictable cost, while Dynatrace’s consumption/commitment approach may be less intuitive for some teams.
- groundcover vs New Relic
  - New Relic publishes ingest-based pricing ($/GB beyond free allotments) and user-based components, which can still become cost-sensitive in high-volume environments.
  - groundcover’s pitch is to avoid per-GB billing by running storage in the customer’s account.
Market share and adoption trends
- No authoritative market-share numbers were found in the accessed sources.
- Thoughtworks Technology Radar entry indicates groundcover is notable enough to be tracked as an emerging platform trend, but that is not equivalent to market share.
When customers choose competitors instead (and why)
- Customers may choose Datadog/Dynatrace when they need:
  - The most mature UX and workflow features immediately
  - Very broad integration catalogs
  - Established enterprise procurement comfort and long reference lists

Aspect

groundcover

Datadog

Dynatrace

Starting Price

Public page lists Free/Team/Enterprise but exact per-node list pricing not clearly extractable from captured view; pricing is node-based (monthly average monitored K8s nodes) plus BYOC hosting costs

Public list pricing is modular by product; common entry points include infrastructure monitoring per host/month and separate charges for logs/APM/etc. (see Datadog pricing list)

Consumption/commitment model with rate card by capability; billed via consumption against a commitment (Dynatrace docs/rate card)

Best For

K8s-heavy orgs wanting BYOC data residency and predictable pricing not tied to ingest volume; teams sensitive to telemetry-data privacy

Broadest “one platform” SaaS with large integration ecosystem and mature UX; orgs prioritizing speed of adoption and wide product breadth

Enterprise-grade full-stack observability with strong auto-discovery/mapping and AI-assisted analysis; orgs willing to manage consumption model

Key Strength

BYOC architecture + eBPF-based zero/low instrumentation narrative; cost predictability tied to nodes

Mature workflows, huge ecosystem, strong cross-team “single pane” adoption

Automated discovery, dependency mapping, feature breadth; enterprise-grade capabilities

Key Weakness

Smaller review footprint; perceived as less mature vs incumbents; BYOC shifts infra costs to customer cloud

Pricing complexity and unpredictability widely complained about in community discussions; costs can scale quickly with logs/traces/modules

Premium pricing and potentially complex consumption math; may be overkill for small teams