### Quick Start: Chaos Lab Setup and Experiment Execution

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/chaos_engineering/README.md

Use these Make commands for a quick setup of the chaos lab environment, listing experiments, running a specific experiment, and tearing down the lab. Ensure Docker, Kind, kubectl, Helm, and a Python virtual environment are installed.

```bash
export DD_API_KEY='your-api-key'   # omit if using CHAOS_LAB_FLAGS=--skip-datadog
# export KUBECTL_CONTEXT=kind-tracer-k8s-test   # optional

make chaos-lab-up

make chaos-experiment-list
make chaos-experiment-up EXPERIMENT=pod-failure
make chaos-experiment-down EXPERIMENT=pod-failure

make chaos-lab-down
```

--------------------------------

### OpenSRE Quick Start Commands

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Executes the initial setup and investigation commands for OpenSRE. This sequence is used to onboard, investigate an incident, and update the system.

```bash
opensre onboard
opensre investigate -i tests/e2e/kubernetes/fixtures/datadog_k8s_alert.json
opensre update
```

--------------------------------

### Manual Chaos Mesh and Baseline Workload Setup

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/chaos_engineering/README.md

Apply Chaos Mesh and baseline workloads to the Kind cluster. This involves installing Chaos Mesh, verifying its pods, applying the base chaos-demo and pod-kill-demo, and verifying the default namespace pods.

```bash
make chaos-mesh-up
kubectl get pods -n chaos-mesh --context=kind-tracer-k8s-test
make chaos-engineering-apply
kubectl get pods -n default --context=kind-tracer-k8s-test
```

--------------------------------

### Install Make using Chocolatey

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Install the 'make' utility on Windows using Chocolatey. This command should be run after Chocolatey has been installed.

```powershell
choco install make
```

--------------------------------

### Verify Setup with Make Commands

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Run linting, type checking, and tests with coverage to verify the development environment setup. All checks must pass.

```bash
make lint && make typecheck && make test-cov
```

--------------------------------

### Install Make using winget

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Install the 'make' utility on Windows using the winget package manager. This is an alternative to using Chocolatey.

```powershell
winget install GnuWin32.Make
```

--------------------------------

### Install OpenSRE

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/introduction-monitoring.mdx

Run this command to install OpenSRE. Once installed, it begins tracing all jobs and processes in real time.

```bash
curl -sSL https://install.tracer.cloud | sh -s
```

--------------------------------

### Install Mintlify CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/README.md

Installs the Mintlify CLI globally. This is a prerequisite for local development.

```bash
npm i -g mint
```

--------------------------------

### Run Mintlify Development Server

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/README.md

Starts the local development server for previewing documentation. Access the docs at http://localhost:3000.

```bash
mint dev
```

--------------------------------

### OpenSRE Onboard Wizard

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Initiates an interactive setup wizard to configure LLM credentials and validate integrations. Use `local_llm` for zero-config local LLM setup via Ollama.

```bash
# Full interactive wizard
opensre onboard
```

```bash
# Zero-config local LLM via Ollama (no API key needed)
opensre onboard local_llm
```

--------------------------------

### Setup AWS Infrastructure for RNA-seq Pipeline

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/aws-batch.mdx

Run the setup script to provision the necessary AWS infrastructure, including VPC, S3 buckets, AWS Batch compute environment, and IAM roles. This script automates the creation of all required AWS resources.

```bash
cd nextflow-test-pipelines/pipelines/aws-batch/rnaseq
./run.sh setup
```

--------------------------------

### Clone Repository and Install OpenSRE

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Clones the OpenSRE repository from GitHub and installs the project locally using make. This is the initial step for setting up a development environment.

```bash
git clone https://github.com/Tracer-Cloud/opensre
cd opensre
make install
```

--------------------------------

### Start OpenSRE Agent

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/codespaces.mdx

Initialize the OpenSRE agent to start tracking pipelines. You will be prompted to configure a pipeline name. Obtain your personal token from the onboarding page.

```bash
tracer init --token <your-token>
```

--------------------------------

### Install Hub helpers for OpenSRE

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/benchmarks/openrca_scenarios/README.md

Install the OpenSRE package with the 'opensre-hub' extra, which includes dependencies for interacting with the Hugging Face Hub.

```bash
pip install 'opensre[opensre-hub]'
```

--------------------------------

### Install OpenSRE with Homebrew

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Installs the OpenSRE framework using the Homebrew package manager. Ensure Homebrew is installed and configured before running this command.

```bash
brew install Tracer-Cloud/opensre/opensre
```

--------------------------------

### Manual Datadog Installation via Helm

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/chaos_engineering/README.md

Install and configure the Datadog agent on the Kind cluster using Helm. This includes setting the API key, namespace, and potentially the Datadog site. Ensure the Datadog Helm repository is added and updated.

```bash
export DD_API_KEY='your-api-key'
# export DD_SITE=datadoghq.eu   # if not US1

kubectl create namespace tracer-test --context=kind-tracer-k8s-test --dry-run=client -o yaml \
  | kubectl apply -f - --context=kind-tracer-k8s-test

helm repo add datadog https://helm.datadoghq.com
helm repo update datadog

helm upgrade --install datadog datadog/datadog \
  --kube-context kind-tracer-k8s-test \
  -n tracer-test \
  -f tests/e2e/kubernetes/k8s_manifests/datadog-values.yaml \
  --set "datadog.apiKey=${DD_API_KEY}" \
  ${DD_SITE:+--set datadog.site=${DD_SITE}} \
  --wait --timeout 10m
```

--------------------------------

### Initialize OpenSRE Agent

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/tutorials/fastquorum-debugging.mdx

Starts the OpenSRE agent to begin tracking pipeline metrics. Replace '(your token)' with your actual user token.

```bash
tracer init --token eyJh---- (your token)
```

--------------------------------

### Verify All Local Integrations with CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/integrations-overview.mdx

Run this command after setup to confirm that all configured local integrations are functioning correctly. It checks the status of all connected services.

```bash
opensre integrations verify
```

--------------------------------

### Initialize Pipeline Tracking

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/macos.mdx

Run this command to configure and start tracking a new pipeline. You will be prompted to enter a unique pipeline name for identification and searchability.

```bash
sudo tracer init
```

--------------------------------

### Install OpenSRE CLI

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Choose the installation method appropriate for your operating system. For macOS, Homebrew is recommended. Linux and WSL users can use curl, while Windows users can use PowerShell. Building from source requires Python 3.11+.

```bash
# macOS (Homebrew)
brew install Tracer-Cloud/opensre/opensre
```

```bash
# Linux / WSL (curl)
curl -fsSL https://raw.githubusercontent.com/Tracer-Cloud/opensre/main/install.sh | bash
```

```powershell
# Windows PowerShell
irm https://raw.githubusercontent.com/Tracer-Cloud/opensre/main/install.ps1 | iex
```

```bash
# From source (Python 3.11+)
git clone https://github.com/Tracer-Cloud/opensre && cd opensre
make install
```

--------------------------------

### Setup ClickHouse via Interactive CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/clickhouse.mdx

Use the OpenSRE CLI to set up the ClickHouse integration by selecting it and providing host and credentials when prompted.

```bash
opensre integrations setup
```

--------------------------------

### Setup RabbitMQ Integration via CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/rabbitmq.mdx

Use the OpenSRE CLI to set up the RabbitMQ integration interactively. You will be prompted for necessary connection details.

```bash
opensre integrations setup rabbitmq
```

--------------------------------

### Initialize OpenSRE Agent

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/linux-cloud.mdx

Start tracking a pipeline by initializing the OpenSRE agent with your unique token. You will be prompted to configure the pipeline name.

```bash
sudo tracer init --token <your-token>
```

--------------------------------

### Setup MariaDB Integration via CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/mariadb.mdx

Use the OpenSRE CLI to interactively set up the MariaDB integration. You will be prompted for connection details and SSL preferences.

```bash
opensre integrations setup mariadb
```

--------------------------------

### Setup Bitbucket Integration via Environment Variables

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/bitbucket.mdx

Configure Bitbucket integration by setting the BITBUCKET_WORKSPACE, BITBUCKET_USERNAME, and BITBUCKET_APP_PASSWORD environment variables in your .env file.

```bash
BITBUCKET_WORKSPACE=your-workspace-slug
BITBUCKET_USERNAME=your-username
BITBUCKET_APP_PASSWORD=your-app-password
```

--------------------------------

### AWS Batch EC2 LaunchTemplate UserData Example

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/aws-batch.mdx

This is an example of the UserData field within an EC2 Launch Template for AWS Batch. It shows where to append OpenSRE installation commands.

```yaml
Resources:
  NextflowLaunchTemplate:
    Properties:
      LaunchTemplateData:
        UserData: !Base64 |
          #cloud-config
          runcmd:
            - ...

```

--------------------------------

### Get OpenSRE Version Information

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Displays the installed version of OpenSRE, the Python version, and operating system details. The `--json` flag provides this information in a machine-readable format.

```bash
opensre version
```

```bash
# opensre 2026.4.5
# Python  3.13.0
# OS      linux (x86_64)
```

```bash
opensre version --json
```

```json
# {"opensre": "2026.4.5", "python": "3.13.0", "os": "linux", "arch": "x86_64"}
```

--------------------------------

### Context Source Annotations for Investigation

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/AGENTS.md

This Python dictionary example shows how to use annotations to declare available evidence sources and provide specific details for each source. This guides the agent's investigation strategy by indicating which data is accessible.

```python
annotations={
    # Evidence source declarations
    "context_sources": "s3,lambda,cloudwatch",
    
    # S3 context
    "s3_bucket": "landing-bucket",
    "s3_key": "raw/data/2024/file.json",
    
    # Lambda context
    "function_name": "processor-function",
    "lambda_log_group": "/aws/lambda/processor",
    
    # CloudWatch context
    "cloudwatch_log_group": "/ecs/pipeline",
    "correlation_id": "run-123",
}
```

--------------------------------

### Launch Demo Pipeline

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/codespaces.mdx

Execute this command to launch a prepared nf-core fastquorum pipeline for demonstration purposes. This pipeline has specific resource requirements.

```bash
tracer demo
```

--------------------------------

### Run Demo Pipeline

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/linux-cloud.mdx

Launch a sample nf-core fastquorum pipeline to test OpenSRE tracking. This pipeline has specific resource requirements.

```bash
sudo tracer demo
```

--------------------------------

### Install OpenSRE

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/codespaces.mdx

Run this command to install OpenSRE in your Codespaces environment. Ensure you have curl installed.

```bash
curl -sSL https://install.tracer.cloud | sh
```

--------------------------------

### Run Documentation Development with Make

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/README.md

Alternative command to run the documentation development server from the project root.

```bash
make docs-dev
```

--------------------------------

### Manual Cluster Setup with Kind

Source: https://github.com/tracer-cloud/opensre/blob/main/tests/chaos_engineering/README.md

Manually create and configure a Kind Kubernetes cluster. This involves creating the cluster with a specified name and waiting for it to become ready, then setting the kubectl context.

```bash
kind create cluster --name tracer-k8s-test --wait 60s
kubectl config use-context kind-tracer-k8s-test
```

--------------------------------

### Onboard OpenSRE and Investigate Alerts

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Runs the OpenSRE onboarding process to configure local LLM providers and integrations. It also demonstrates how to investigate alerts using a provided JSON fixture.

```bash
opensre onboard
opensre investigate -i tests/e2e/kubernetes/fixtures/datadog_k8s_alert.json
```

--------------------------------

### Install OpenSRE with cURL

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Installs the OpenSRE framework using a cURL command. This is a common method for fetching and executing installation scripts.

```bash
curl -fsSL https://raw.githubusercontent.com/Tracer-Cloud/opensre/main/install.sh | bash
```

--------------------------------

### Install Development Dependencies

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Install the project's development dependencies using pip. This command installs the package in editable mode with development extras.

```bash
pip install -e ".[dev]"
```

--------------------------------

### Install OpenSRE with PowerShell

Source: https://github.com/tracer-cloud/opensre/blob/main/README.md

Installs the OpenSRE framework using PowerShell. This is suitable for Windows environments where PowerShell is available.

```powershell
irm https://raw.githubusercontent.com/Tracer-Cloud/opensre/main/install.ps1 | iex
```

--------------------------------

### Start MCP Server

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Command to start the MCP server. This server exposes the `run_rca` tool for root cause analysis.

```bash
opensre-mcp
# or via uvx:
uvx opensre-mcp
```

--------------------------------

### Install OpenSRE Agent in UserData

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/environments/aws-batch.mdx

Append this command to the 'runcmd' section of your EC2 Launch Template UserData to install the OpenSRE agent.

```bash
- curl -sSL https://install.tracer.cloud | sh

```

--------------------------------

### Setup Honeycomb Integration via Environment Variables

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/honeycomb.mdx

Configure Honeycomb integration by setting environment variables. HONEYCOMB_DATASET is optional and defaults to '__all__'. HONEYCOMB_API_URL can be overridden for specific regions or proxies.

```bash
HONEYCOMB_API_KEY=your-api-key
HONEYCOMB_DATASET=your-dataset      # optional, defaults to __all__
HONEYCOMB_API_URL=https://api.honeycomb.io  # optional
```

--------------------------------

### Setup Alertmanager Integration via CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/alertmanager.mdx

Use the interactive CLI wizard to set up the Alertmanager integration. Follow the prompts to provide the Alertmanager URL and authentication method.

```bash
opensre integrations setup alertmanager
```

--------------------------------

### Install Chocolatey Package Manager

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Install Chocolatey, a package manager for Windows, by running a PowerShell script. Review the script before execution.

```powershell
Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
```

--------------------------------

### Start OpenSRE MCP Server

Source: https://github.com/tracer-cloud/opensre/blob/main/SETUP.md

Start the OpenSRE MCP server. This command makes the 'run_rca' tool available for MCP clients.

```bash
opensre-mcp
```

--------------------------------

### Install OpenSRE Agent

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/tutorials/fastquorum-debugging.mdx

Installs the OpenSRE agent using a curl command. Ensure you are using the correct CLI branch and user token.

```bash
curl -sSL https://install.tracer.cloud | CLI_BRANCH=dev sh -s user_35Fukh3QxSAxJLgfyE9SwPoPy9K
```

--------------------------------

### Setup Better Stack Integration via CLI

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/betterstack.mdx

Use this command to interactively set up the Better Stack integration. You will be prompted for necessary credentials and configuration details.

```bash
opensre integrations setup betterstack
```

--------------------------------

### Update OpenSRE

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Manages OpenSRE self-updates. Use `--check` to see if a newer version is available without installing, and `--yes` to download and install the latest release.

```bash
# Check if a newer version is available (no install)
opensre update --check
```

```bash
# Download and install the newest release
opensre update --yes
```

--------------------------------

### Nextflow Pipeline Example

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/quickstart-monitoring.mdx

This is an example of a Nextflow pipeline configuration file that includes various modules and subworkflows for bioinformatics analysis. It demonstrates how different components are included and potentially integrated with monitoring tools.

```groovy
/*
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
    IMPORT MODULES / SUBWORKFLOWS / FUNCTIONS
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
*/

include { paramsSummaryMap } from 'plugin/nf-schema'
include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline'
include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline'
include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_fastquorum_pipeline'

include { ALIGN_BAM as ALIGN_RAW_BAM } from '../modules/local/align_bam/main'
include { ALIGN_BAM as ALIGN_CONSENSUS_BAM } from '../modules/local/align_bam/main'
include { FASTQC } from '../modules/nf-core/fastqc/main'
include { FGBIO_FASTQTOBAM as FASTQTOBAM } from '../modules/local/fgbio/fastqtobam/main'
include { FGBIO_GROUPREADSBYUMI as GROUPREADSBYUMI } from '../modules/local/fgbio/groupreadsbyumi/main'
include { FGBIO_CALLMOLECULARCONSENSUSREADS as CALLMOLECULARCONSENSUSREADS } from '../modules/local/fgbio/callmolecularconsensusreads/main'
include { FGBIO_CALLDDUPLEXCONSENSUSREADS as CALLDDUPLEXCONSENSUSREADS } from '../modules/local/fgbio/callduplexconsensusreads/main'
include { FGBIO_FILTERCONSENSUSREADS as FILTERCONSENSUSREADS } from '../modules/local/fgbio/filterconsensusreads/main'
include { FGBIO_COLLECTDUPLEXSEQMETRICS as COLLECTDUPLEXSEQMETRICS } from '../modules/local/fgbio/collectduplexseqmetrics/main'
include { FGBIO_CALLANDFILTERMOLECULARCONSENSUSREADS as CALLANDFILTERMOLECULARCONSENSUSREADS } from '../modules/local/fgbio/callandfiltermolecularconsensusreads/main'
include { FGBIO_CALLANDFILTERDUPLEXCONSENSUSREADS as CALLANDFILTERDUPLEXCONSENSUSREADS } from '../modules/local/fgbio/callandfilterduplexconsensusreads/main'
include { SAMTOOLS_MERGE as MERGE_BAM } from '../modules/nf-core/samtools/merge/main'

include { MULTIQC } from '../modules/nf-core/multiqc/main'

/*
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

```

--------------------------------

### LLMSettings.from_env

Source: https://context7.com/tracer-cloud/opensre/llms.txt

Builds LLM configuration from environment variables, reading provider and API keys.

```APIDOC
## LLMSettings.from_env

### Description
Reads LLM configuration from environment variables, specifically `LLM_PROVIDER` and the corresponding API key. It validates the combination and returns a Pydantic model. Providers that do not require an API key are whitelisted.

### Method
Python Function Call

### Parameters
None (reads from environment variables)

### Request Example
```python
import os
from app.config import LLMSettings

# Example for Anthropic
os.environ["LLM_PROVIDER"] = "anthropic"
os.environ["ANTHROPIC_API_KEY"] = "sk-ant-..."
settings = LLMSettings.from_env()
print(settings.provider) # Output: "anthropic"

# Example for Ollama (local, no API key)
os.environ["LLM_PROVIDER"] = "ollama"
os.environ["OLLAMA_MODEL"] = "llama3.2"
os.environ["OLLAMA_HOST"] = "http://localhost:11434"
settings = LLMSettings.from_env()

# Example for Amazon Bedrock (IAM auth, no API key)
os.environ["LLM_PROVIDER"] = "bedrock"
os.environ["AWS_REGION"] = "us-east-1"
settings = LLMSettings.from_env()
print(settings.bedrock_reasoning_model) # Output: "us.anthropic.claude-sonnet-4-6"
```

### Response
#### Success Response (200)
Returns a Pydantic model representing the LLM configuration.
* **provider** (str) - The configured LLM provider (e.g., "anthropic", "ollama").
* **anthropic_reasoning_model** (str) - The reasoning model for Anthropic.
* **bedrock_reasoning_model** (str) - The reasoning model for Bedrock.

#### Response Example
```json
{
  "provider": "anthropic",
  "anthropic_reasoning_model": "claude-sonnet-4-6",
  "anthropic_toolcall_model": "claude-haiku-4-5-20251001",
  "bedrock_reasoning_model": "us.anthropic.claude-sonnet-4-6"
}
```
```

--------------------------------

### Bug Report Example - Expected vs. Actual Behavior

Source: https://github.com/tracer-cloud/opensre/blob/main/CONTRIBUTING.md

This example demonstrates how to structure the 'Expected Behavior' and 'Actual Behavior' sections of a bug report, including specific commands and error messages.

```markdown
### Expected Behavior
`opensre investigate --org myorg` should return investigation results

### Actual Behavior
Command exits silently with no output
Error: exit code 0
```

--------------------------------

### Launch nf-core/fastquorum Pipeline

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/tutorials/fastquorum-debugging.mdx

Executes the nf-core/fastquorum pipeline with specified inputs and configurations. Includes options for trace and report generation.

```bash
nextflow run .
  --input samplesheet.csv \
  --fasta data/chr17.fa \
  --outdir results \
  --duplex_seq true \
  -profile test,docker \
  -with-trace \
  -with-report results/report.html
```

--------------------------------

### Bug Report Example - Steps to Reproduce and Environment

Source: https://github.com/tracer-cloud/opensre/blob/main/CONTRIBUTING.md

Provides clear, minimal steps to consistently trigger a bug and details the necessary environment information for effective debugging.

```markdown
### Steps to Reproduce
1. Run `opensre investigate --org myorg`
2. Observe output

### Environment
- OS: macOS 14.2
- Python: 3.11.5
- opensre version: v0.2.1
```

--------------------------------

### Update OpenSRE

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/quickstart.mdx

Run this command to update your OpenSRE installation to the latest version.

```bash
opensre update
```

--------------------------------

### Verify OpsGenie Integration

Source: https://github.com/tracer-cloud/opensre/blob/main/docs/opsgenie.mdx

Run this command to verify the OpsGenie integration is set up correctly and can connect to the service.

```bash
opensre integrations verify opsgenie
```