Generic CI Providers

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Overview

If you don’t use CircleCI Orbs or GitHub Actions, you can run the Datadog CLI directly in your CI pipeline platform.

Prerequisites:

  • unzip
  • Node.js 14 or later

Configure the following environment variables:

NameDescriptionRequiredDefault
DD_API_KEYYour Datadog API key. This key is created by your Datadog organization and should be stored as a secret.Yes
DD_APP_KEYYour Datadog application key. This key, created by your Datadog organization, should include the code_analysis_read scope and be stored as a secret.Yes
DD_SITEThe Datadog site to send information to. Your Datadog site is .Nodatadoghq.com

Provide the following inputs:

NameDescriptionRequiredDefault
serviceThe name of the service to tag the results with.Yes
envThe environment to tag the results with. ci is a helpful value for this input.Nonone
cpu_countSet the number of CPUs used by the analyzer. Defaults to the number of CPUs available.No
subdirectoryThe subdirectory path the analysis should be limited to. The path is relative to the root directory of the repository.No

To obtain execution time statistics for analyzed files, add a --performance-statistics flag to your static analysis command.

Select an analyzer for your architecture and OS from the following options:

ArchitectureOSNameLink
aarch64Darwindatadog-static-analyzer-aarch64-apple-darwin.zipDownload
aarch64Linuxdatadog-static-analyzer-aarch64-unknown-linux-gnu.zipDownload
x86_64Darwindatadog-static-analyzer-x86_64-apple-darwin.zipDownload
x86_64Linuxdatadog-static-analyzer-x86_64-unknown-linux-gnu.zipDownload
x86_64Windowsdatadog-static-analyzer-x86_64-pc-windows-msvc.zipDownload

Add the following to your CI pipeline:

# Set the Datadog site to send information to
export DD_SITE="datadoghq.com"

# Install dependencies
npm install -g @datadog/datadog-ci

# Download the latest Datadog static analyzer:
# https://github.com/DataDog/datadog-static-analyzer/releases
DATADOG_STATIC_ANALYZER_URL=https://github.com/DataDog/datadog-static-analyzer/releases/latest/download/datadog-static-analyzer-x86_64-unknown-linux-gnu.zip
curl -L $DATADOG_STATIC_ANALYZER_URL > /tmp/ddog-static-analyzer.zip
unzip /tmp/ddog-static-analyzer.zip -d /tmp
mv /tmp/datadog-static-analyzer /usr/local/datadog-static-analyzer

# Run Static Analysis
/usr/local/datadog-static-analyzer -i . -o /tmp/report.sarif -f sarif

# Upload results
datadog-ci sarif upload /tmp/report.sarif
This example uses the x86_64 Linux version of Datadog's static analyzer. If you're using a different OS or architecture, you should select it from the table above and update the DATADOG_STATIC_ANALYZER_URL value below. You can view all releases on the GitHub Releases page.

Diff-aware scanning

Diff-aware scanning is a feature that enables Datadog Static Analysis to only scan the files modified by a commit in a feature branch. It accelerates scan time significantly by not having the analysis run on every file in the repository for every scan. The first scan performed, as well as default branch scans, always produce an analysis of the full repository (not diff-aware).

If you are using GitHub Actions, diff-aware scanning is enabled by default.

For other CI providers, follow these steps to enable diff-aware scanning:

  1. Make sure your DD_APP_KEY, DD_SITE and DD_API_KEY variables are set in your CI pipeline.
  2. Add a call to datadog-ci git-metadata upload before invoking the static analyzer. This command ensures that Git metadata is available to the Datadog backend. Git metadata is required to calculate the number of files to analyze.
  3. Ensure that the datadog-static-analyzer is invoked with the flag --diff-aware.

Example of commands sequence (these commands must be invoked in your Git repository):

datadog-ci git-metadata upload

datadog-static-analyzer -i /path/to/directory -g -o sarif.json -f sarif –-diff-aware <...other-options...>

Note: When a diff-aware scan cannot be completed, the entire directory is scanned.

Further Reading

추가 유용한 문서, 링크 및 기사:

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