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There is no single winner. Choose New Relic’s traditional CLI for profile-based administration, entity and workload operations, deployment markers, NRQL, and NerdGraph automation. Choose Datadog’s Pup CLI for a broad, structured interface to Datadog resources; choose datadog-ci for CI instrumentation, Continuous Testing, or coverage uploads; and choose Datadog’s agentic onboarding CLI when the job is configuring a repository. New Relic’s Ground Truth CLI is a newly announced option for investigation and recovery evidence, but its production availability and complete command coverage are not yet established.
This comparison treats each tool according to the work it actually performs, rather than pretending that “Datadog CLI” names one product.
New Relic CLI vs. Datadog CLI: the short answer
The right command-line tool follows the workflow you need to automate:
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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →- New Relic platform administration and queries: use the traditional New Relic CLI. Its documented commands cover entity tags, workloads, APM deployment markers, NRQL, NerdGraph, profiles, and related operations.
- Broad Datadog resource operations: use Pup CLI, which Datadog documents as an AI-agent-ready interface with JSON and YAML output and coverage that includes monitors, logs, metrics, RUM, and security.
- Build and release pipelines: use
datadog-ci. It traces commands, adds tags and numerical measures, runs Continuous Testing tests, and uploads code-coverage reports. - Repository setup: use Datadog’s agentic onboarding CLI. It can configure supported products and edit application or infrastructure configuration, including in headless automation, and requires Node.js 22 or later.
- Terminal-based incident investigation and recovery evidence: watch New Relic Ground Truth CLI. New Relic announced it on October 6, 2026, but the announcement is not a complete availability or command-reference document.
Your existing telemetry vendor, account structure, authentication controls, and deployment process should decide the choice. CLI documentation does not establish comparable pricing, plan eligibility, performance, or reliability.
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What “Datadog CLI” actually means
Datadog’s documentation describes several command-line tools with different boundaries. Treating them as one general-purpose CLI leads to poor comparisons and brittle automation.
Pup CLI: the broad observability interface
Datadog describes Pup as a comprehensive, AI-agent-ready command-line interface that gives AI agents access to Datadog’s observability platform
in its Pup CLI documentation. The documentation highlights discoverable commands, structured JSON or YAML output, and scoped authentication. Listed areas include monitors, logs, metrics, real user monitoring (RUM), and security. The complete command inventory is maintained in the project documentation, so verify a resource’s command before building a production script.
datadog-ci: pipeline instrumentation, testing, and coverage
datadog-ci is not presented as an account-administration shell. Datadog’s CI Visibility guide documents command tracing plus custom tags and numerical measures on pipeline traces. Its Continuous Testing documentation covers running tests in CI/CD, including workflows that block a branch or trigger a rollback when tests fail. Datadog’s coverage documentation also describes uploading code-coverage reports and provides several installation routes.
Agentic onboarding CLI: repository configuration
The agentic onboarding setup documentation describes a repository-oriented tool. It links a Datadog account to a local project, configures supported products, and can edit infrastructure-as-code and application files for supported setups. Headless operation is intended for AI agents, CI jobs, and scripts. The setup page specifies Node.js 22 or later and describes site and product selection plus API/application-key or OAuth authorization paths. Because the tool can upload source code and execute commands as part of authorization, review proposed changes and credentials in your own environment before allowing unattended runs.
New Relic’s traditional CLI
New Relic’s getting-started guide calls the CLI a terminal interface for managing entity tags, defining workloads, recording deployment markers, and automating common DevOps tasks. New Relic’s CLI Reference lists command areas for APM, entities, NerdGraph, NerdStorage, NRQL, profiles, and workloads. Global options include account ID, profile, debug or trace output, and JSON, text, or YAML formatting.
New Relic Documentation states: The New Relic CLI enables the integration of New Relic into your existing workflows.
That is a useful description of its role, not a promise that every New Relic UI feature has a command-line equivalent. The reference documents a command set; it does not claim complete platform parity.
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Installation and supported package routes
The getting-started guide documents installation through Homebrew on macOS, Snap on Linux, and Scoop on Windows. It also mentions additional binaries and packages in the project repository. Exact operating-system and package requirements can change, so use the current installation instructions rather than pinning a version based on an older article.
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Profile-based credentials and regions
Profiles are central to the traditional CLI. A profile stores credentials and settings, and you can select a profile or account when running commands. During the documented initial setup, you provide a New Relic user key and choose a region: us, eu, or jp.
- Install the CLI using the package method for your operating system.
- Run the documented profile setup flow and provide a New Relic user key.
- Select the region that hosts the account:
us,eu, orjp. - Save the profile, then select it explicitly when a script must target a particular account.
- Use the global account, profile, format, and debug or trace options to make automation’s target and output unambiguous.
For teams operating multiple accounts, separate profiles reduce the chance that a deployment marker or workload change is sent to the wrong account. Protect the user key as a secret and avoid placing it in a repository or command history.
What you can automate
- Entities: apply and manage entity tags.
- Workloads: define and manage workload groupings.
- APM: record deployment markers so releases can be correlated with application behavior.
- NRQL: run New Relic Query Language operations from scripts or an operator terminal.
- NerdGraph: send GraphQL-format requests for supported queries and configuration operations.
- Profiles: create, inspect, and switch the credential and settings contexts used by commands.
New Relic recommends NerdGraph for querying data and selected configuration because it provides one interface across New Relic APIs and microservices. NerdGraph is distinct from New Relic’s data-ingest APIs; it is not a replacement for sending telemetry. See Meet NerdGraph: our GraphQL API for that boundary.
New Relic Ground Truth CLI: a different kind of command line
In a press release dated October 6, 2026, New Relic announced Ground Truth CLI and described connections to Autopilot, NerdGraph, and memory APIs. The stated focus is helping developers, agents, and AI coding tools investigate production issues, assess recovery criteria, and preserve operational evidence in terminal workflows.
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This announcement establishes positioning, not a complete product reference. It does not by itself establish general availability, release cadence, supported operating systems, production maturity, or the full command list. Treat Ground Truth as an emerging investigation and evidence workflow until detailed product documentation confirms the capabilities your team requires. It should not be substituted silently for the established profile-and-command model of the traditional New Relic CLI.
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Datadog Pup CLI in an observability workflow
Resource breadth and output
Pup is the closest Datadog counterpart to a broad observability interface. Its documentation names monitors, logs, metrics, RUM, and security, rather than limiting the tool to CI or repository setup. JSON and YAML output make it suitable for scripts that need to parse results, pass structured data to another process, or let an agent inspect a response without screen-scraping human-formatted text.
The documentation emphasizes discoverable commands. That matters when a team’s automation spans several Datadog products, but it does not guarantee identical operations across every product. Check the current command reference for the resource and action you intend to automate.
Authentication scope
Pup’s documentation describes scoped authentication using OAuth2 with PKCE or credentials supplied through the environment. Scope the identity to the least privilege needed by the command, keep secrets in the CI or runtime secret store, and use a separate identity for read-only investigation versus mutating configuration. The available authentication path and required permissions depend on the Datadog site and operation.
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| Decision axis | New Relic traditional CLI | Datadog Pup CLI | Datadog datadog-ci |
Datadog agentic onboarding CLI | New Relic Ground Truth CLI |
|---|---|---|---|---|---|
| Primary job | New Relic platform operations, queries, deployment markers, and profiles | Broad Datadog observability operations | CI command tracing, testing, and coverage workflows | Repository and product onboarding configuration | Announced investigation, recovery verification, and operational evidence |
| Documented resource or feature areas | APM, entities, NerdGraph, NerdStorage, NRQL, profiles, workloads | Monitors, logs, metrics, RUM, and security | Pipeline traces, Continuous Testing, and code-coverage uploads | Supported application and infrastructure configurations | Connections to Autopilot, NerdGraph, and memory APIs were announced |
| Structured output | JSON, text, and YAML global formatting options | JSON and YAML output | Pipeline traces and uploaded test or coverage data | Configuration and command execution are oriented to repository changes | Detailed output formats are not established by the announcement |
| Credential model described in documentation | Profiles containing a user key and settings; account and profile selection | OAuth2/PKCE or environment-provided credentials with scoped access | CI-focused Datadog authentication configured for the relevant integration | API/application-key or OAuth paths; site and product selection for headless use | Detailed credential requirements are not established by the announcement |
| CI/CD role | Scriptable operations and release markers | Can be used by scripts or agents when its commands fit | Core use case: trace commands, run tests, attach measures, upload coverage | Headless use in CI jobs and scripts | Announced terminal and AI-agent workflow; CI details are not established |
| Repository modification | Not the documented focus | Not the documented focus | Not the documented focus | Can edit supported infrastructure-as-code and application files | Not established by the announcement |
| Evidence status | Current CLI guides and reference | Current product documentation | Current CI documentation | Current onboarding documentation | October 6, 2026 announcement; detailed documentation still needed |
Using datadog-ci where it fits
Use datadog-ci when the unit of work is a build, test job, or release pipeline rather than a general account resource.
Trace a command and add pipeline context
CI Visibility supports tracing command execution and attaching custom tags and numerical measures to pipeline traces. Tags can carry the repository, service, branch, or deployment context your team needs to filter; measures can record numeric values relevant to the pipeline. Design those fields before rollout so dashboards and alerts receive stable names instead of one-off labels.
Run Continuous Testing in CI/CD
The Continuous Testing integration runs tests in CI/CD. A failed test can be used to block a branch or trigger a rollback, depending on how your pipeline is designed. Treat the CLI as one stage in a larger control flow: define the failure policy in the pipeline, make the test environment reproducible, and ensure the identity can publish results without granting unrelated administrative access.
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Upload code coverage
The coverage workflow uploads reports generated by your test tools. Installation routes vary by environment; follow Datadog’s current coverage documentation and preserve the report format expected by the uploader. Coverage upload is an artifact-publishing task, not evidence that the CLI can administer every Datadog resource.
Using the agentic onboarding CLI safely
Prerequisites and headless inputs
Install Node.js 22 or later before following the setup guide. In headless operation, provide the Datadog site and the products to configure. The documentation describes API/application-key and OAuth authorization paths for this mode.
Review the changes it proposes
Because onboarding can edit infrastructure-as-code and application files for supported setups, run it first in a branch or disposable workspace. Review the diff, generated configuration, dependency changes, and any commands it intends to execute. Confirm exactly what source code is uploaded and where credentials are read before enabling a CI or AI-agent run.
When it is the wrong tool
Do not select onboarding merely because you need to query a monitor or fetch logs. Its documented purpose is linking an account to a repository and configuring products. Use Pup for broad resource operations and datadog-ci for pipeline instrumentation, tests, or coverage.
Which observability CLI should I use?
Choose New Relic’s traditional CLI when…
- Your telemetry and account are already in New Relic.
- You need entity tags, workloads, APM deployment markers, NRQL, or NerdGraph requests.
- You need explicit profile switching across New Relic accounts or regions.
- Your scripts need JSON, text, or YAML output and account or profile flags.
Choose Pup when…
- Your Datadog automation spans several observability products.
- You need documented access to monitors, logs, metrics, RUM, or security from one discoverable interface.
- Your automation or agent consumes JSON or YAML rather than terminal-oriented text.
- You can provision scoped OAuth2/PKCE or environment-based credentials.
Choose datadog-ci when…
- The command runs inside a CI/CD job.
- You need command traces with custom tags or numerical measures.
- Continuous Testing results must influence branch protection or rollback behavior.
- You need to upload code-coverage reports.
Choose agentic onboarding when…
- The immediate task is configuring a supported application or infrastructure repository.
- You want headless setup for an AI agent, CI job, or script.
- Your team can review repository diffs and control source-code upload and command execution.
- Node.js 22 or later is available in the setup environment.
Evaluate Ground Truth when…
- Your desired workflow is terminal-based incident investigation, recovery verification, or preserving operational evidence.
- You are prepared to validate availability and command coverage against detailed documentation as it becomes available.
- You understand that the October 6, 2026 announcement is not a benchmark or production-readiness assessment.
Datadog CLI alternatives: compare the job, not the label
If someone asks for a “Datadog CLI alternative,” first identify the task. New Relic’s traditional CLI is an alternative for teams moving platform operations, NRQL, NerdGraph requests, workloads, or deployment markers to New Relic; it is not a drop-in replacement for datadog-ci’s CI Visibility, Continuous Testing, or coverage functions. Conversely, Pup is a more like-for-like comparison for broad Datadog resource access, while onboarding is a repository configuration tool.
Vendor migration also changes the surrounding telemetry stack, account permissions, query language, dashboards, alerts, and deployment integrations. A command-line interface cannot abstract those differences away. Inventory the existing account and pipeline dependencies before selecting a replacement.
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A practical selection and rollout checklist
- Name the unit of work. Write down whether it is a platform resource, a query, an incident investigation, a build command, a test, a coverage report, or a repository change.
- Match the tool’s documented boundary. Select the traditional New Relic CLI, Pup,
datadog-ci, onboarding, or Ground Truth according to that unit of work. - Confirm the exact command. Check the current vendor reference for the resource, action, site, and version you plan to automate.
- Design authentication first. Use New Relic profiles and region selection where applicable; use scoped Datadog OAuth or environment credentials; separate read and write identities.
- Standardize machine output. Choose JSON or YAML where supported, define stable fields, and make scripts fail clearly when a response is empty or malformed.
- Test against a non-production account or branch. This is especially important for workload changes, onboarding edits, and any command that can mutate configuration.
- Log the target context. Record the selected account, profile, site, product, repository, and pipeline run without exposing secrets.
- Define failure and recovery behavior. For CI tests, specify whether failure blocks a branch or triggers rollback. For administrative scripts, decide whether to stop on the first error or continue with an auditable error report.
- Recheck documentation at upgrade time. OS packages, runtimes, permissions, commands, and product availability can change.
Security and operational pitfalls
Wrong account or region
A valid credential can still target the wrong New Relic account if a script relies on an implicit profile. Select the profile and account explicitly for automated jobs, and set the documented us, eu, or jp region during profile setup.
Overpowered credentials
Broad keys make a first test easy but increase blast radius. Use read-only access for investigation where possible, narrowly scoped identities for CI, and separate credentials for repository onboarding. Rotate secrets through the platform that runs the job rather than committing them to source control.
Parsing human output
Screen-scraping text is fragile. Prefer New Relic’s JSON or YAML formatting options and Pup’s structured JSON or YAML output when a script needs machine-readable data. Pin the fields your automation consumes and add validation for missing fields.
Assuming feature parity
The New Relic reference lists supported command areas; it does not promise a command for every UI action. Pup’s product list is broad, but each resource still has its own command coverage. Verify the exact operation instead of treating either CLI as a complete mirror of the web console.
Letting onboarding change production blindly
Repository edits, source-code upload, and automatic command execution deserve a review gate. Use a branch, inspect the diff, constrain permissions, and make headless runs reproducible before connecting them to a production repository.
Bottom line for developers, SREs, and platform engineers
For New Relic account and telemetry operations, the traditional New Relic CLI is the clearest fit: profiles, regions, entities, workloads, deployment markers, NRQL, NerdGraph, and structured output are all documented. For Datadog, choose by function: Pup for broad observability access, datadog-ci for CI instrumentation, testing, and coverage, and agentic onboarding for repository setup. Ground Truth CLI may become the New Relic option for terminal-centered investigation and recovery evidence, but the October 6, 2026 announcement is not enough to judge its availability or maturity. The best choice is therefore the tool whose documented boundary matches the operation you need to automate, within the telemetry stack and account controls your team already runs.
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