Oodle

To directly send OpenTelemetry metrics generated by OpenLIT SDK from your AI Application to Oodle, Follow the below steps.

Install OpenTelemetry Collector (Optional)

This step is optional if you have the OpenTelemetry Collector already running.

For detailed installation instructions for the OpenTelemetry Collector , please refer to the OpenTelemetry Collector Documentation. This guide provides comprehensive steps to get you up and running with the Collector on various platforms.

Configure the OpenTelemetry Collector

Configure HTTP Receiver: In the receivers section of your OpenTelemetry Collector config, ensure the http receiver is set with endpoint: 0.0.0.0:4318 and otlp receiver is set with endpoint: 0.0.0.0:4317.

receivers:
    otlp:
        protocols:
            grpc:
                endpoint: 0.0.0.0:4317
            http:
                endpoint: 0.0.0.0:4318

Define Exporters: Add otlphttp exporter to export metrics to Oodle. debug exporter is used as a dummy exporter for traces (As Oodle doesnt work with Traces yet)

exporters:
    otlphttp/oodle:
        metrics_endpoint: "https://<OODLE_ENDPOINT>/v1/otlp/metrics/<INSTANCE_ID>"
        headers:
            X-API-KEY: "<API_KEY>"
debug:
    verbosity: detailed
    sampling_initial: 5
    sampling_thereafter: 200

Assign Exporters to Pipelines: Link otlphttp/oodle to service.pipelines.metrics and debug to service.pipelines.traces for data export.

service:
    pipelines:
        metrics:
            receivers: [otlp]
            processors: [batch]
            exporters: [otlphttp/oodle]
        traces:
            receivers: [otlp]
            processors: [batch]
            exporters: [debug]

Complete Configuration Example

receivers:
    otlp:
        protocols:
        grpc:
            endpoint: 0.0.0.0:4317
        http:
            endpoint: 0.0.0.0:4318

processors:
    batch:

exporters:
    otlphttp/oodle:
        metrics_endpoint: "https://<OODLE_ENDPOINT>/v1/otlp/metrics/<INSTANCE_ID>"
        headers:
            X-API-KEY: "<API_KEY>"
    debug:
        verbosity: detailed
        sampling_initial: 5
        sampling_thereafter: 200

service:
    pipelines:
        metrics:
            receivers: [otlp]
            processors: [batch]
            exporters: [otlphttp/oodle]
        traces:
            receivers: [otlp]
            processors: [batch]
            exporters: [debug]

Add the following two lines to your application code:

import openlit

openlit.init(
  otlp_endpoint="YOUR_OTELCOL_URL:4318", 
)

Replace:

YOUR_OTELCOL_URL:4318 with the URL HTTP endpoint of your OpenTelemetry Collector.
- Example - http://127.0.0.1:4318

Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.

Start monitoring using a pre-built Oodle dashboard

Log into your Oodle Instance.
Click Dashboards in the primary menu.
Click New and select Import in the drop-down menu.
Copy the dashboard JSON provided in the accordion named Dashboard below.
Paste the dashboard JSON text directly into the text area.
Click Import.
Save the dashboard.

{
    "annotations": {
        "list": [
        {
            "builtIn": 1,
            "datasource": {
            "type": "grafana",
            "uid": "-- Grafana --"
            },
            "enable": true,
            "hide": true,
            "iconColor": "rgba(0, 211, 255, 1)",
            "name": "Annotations & Alerts",
            "type": "dashboard"
        }
        ]
    },
    "editable": true,
    "fiscalYearStartMonth": 0,
    "graphTooltip": 1,
    "id": 748,
    "links": [
        {
        "asDropdown": false,
        "icon": "bolt",
        "includeVars": false,
        "keepTime": false,
        "tags": [],
        "targetBlank": true,
        "title": "OpenLIT Github",
        "tooltip": "Github",
        "type": "link",
        "url": "https://github.com/openlit/openlit"
        },
        {
        "asDropdown": false,
        "icon": "doc",
        "includeVars": false,
        "keepTime": false,
        "tags": [
            "GPU",
            "AI"
        ],
        "targetBlank": true,
        "title": "OpenLIT Docs",
        "tooltip": "Documentation",
        "type": "link",
        "url": "https://docs.openlit.io/"
        }
    ],
    "panels": [
        {
        "fieldConfig": {
            "defaults": {},
            "overrides": []
        },
        "gridPos": {
            "h": 5,
            "w": 12,
            "x": 0,
            "y": 0
        },
        "id": 21,
        "options": {
            "code": {
            "language": "plaintext",
            "showLineNumbers": false,
            "showMiniMap": false
            },
            "content": "---\n# GenAI Observability\n\nThis dashboard displays the usage stats of LLMs, Vector Databases, tracking OpenTelemetry Metrics sent using [OpenLIT](https://github.com/openlit/openlit).\n\n---",
            "mode": "markdown"
        },
        "pluginVersion": "11.3.0",
        "title": "",
        "transparent": true,
        "type": "text"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the LLM Request Rate ",
        "fieldConfig": {
            "defaults": {
            "color": {
                "fixedColor": "blue",
                "mode": "palette-classic-by-name"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "red",
                    "value": null
                },
                {
                    "color": "#EAB839",
                    "value": 10
                },
                {
                    "color": "#6ED0E0",
                    "value": 100
                }
                ]
            },
            "unit": "reqps"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 2,
            "w": 12,
            "x": 12,
            "y": 0
        },
        "id": 22,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "value_and_name",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum(rate(openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\"}[$__rate_interval]))",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "LLM Request Rate",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the VectorDB Request Rate",
        "fieldConfig": {
            "defaults": {
            "color": {
                "fixedColor": "blue",
                "mode": "palette-classic-by-name"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "red",
                    "value": null
                },
                {
                    "color": "#EAB839",
                    "value": 10
                },
                {
                    "color": "#6ED0E0",
                    "value": 100
                }
                ]
            },
            "unit": "reqps"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 2,
            "w": 12,
            "x": 12,
            "y": 2
        },
        "id": 23,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "value_and_name",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum(rate(openlit_otel_metrics_db_total_requests{telemetry_sdk_name=\"openlit\"}[$__rate_interval]))",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "VectorDB Request Rate",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the total cost incurred from using GenAI models. It reflects the financial impact of operational activities, offering insights into budgetary allocation and efficiency. Tracking this helps in effective cost management and financial planning for GenAI usage.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "fixedColor": "blue",
                "mode": "shades"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "red",
                    "value": 80
                }
                ]
            },
            "unit": "currencyUSD"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 3,
            "w": 12,
            "x": 12,
            "y": 4
        },
        "id": 2,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "auto",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum(last_over_time(openlit_otel_metrics_gen_ai_usage_cost_sum{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"}[$__interval]))",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "Total Usage Cost",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the total number of successful requests made to the GenAI system. A successful request is one that is completed without errors, indicating seamless operation and effective utilization of the GenAI service. Tracking this helps in understanding the reliability and performance of the GenAI system.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "mode": "palette-classic-by-name"
            },
            "mappings": [],
            "min": 0,
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "red",
                    "value": 80
                }
                ]
            },
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 5,
            "w": 6,
            "x": 0,
            "y": 5
        },
        "id": 1,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "auto",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "code",
            "expr": "sum by() (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "Total Successful GenAI Requests",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the total count of successful VectorDB requests. It indicates requests that have been processed completely without any errors, showcasing VectorDB's effectiveness and reliability. Watching this helps gauge how well VectorDB is performing and its success in handling operations.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "mode": "thresholds"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "red",
                    "value": 80
                }
                ]
            },
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 5,
            "w": 6,
            "x": 6,
            "y": 5
        },
        "id": 7,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "auto",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum(openlit_otel_metrics_db_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "Total Successful VectorDB Requests",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the total number of tokens consumed by GenAI requests, providing a direct measure of usage. Monitoring this helps in assessing the demand on GenAI services and guiding resource allocation or optimization strategies.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "fixedColor": "purple",
                "mode": "shades"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "red",
                    "value": 80
                }
                ]
            },
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 3,
            "w": 6,
            "x": 12,
            "y": 7
        },
        "id": 3,
        "options": {
            "colorMode": "background",
            "graphMode": "area",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "auto",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum(openlit_otel_metrics_gen_ai_usage_total_tokens{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "Total Usage Tokens",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the average cost per use of the GenAI models and related services. It provides insights into the cost-effectiveness of interactions with GenAI, helping to identify trends in expense per operation. Monitoring this assists in optimizing budget allocation and improving cost efficiency in GenAI utilization.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "fixedColor": "blue",
                "mode": "shades"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "#EAB839",
                    "value": 0.5
                },
                {
                    "color": "red",
                    "value": 1
                }
                ]
            },
            "unit": "currencyUSD"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 3,
            "w": 6,
            "x": 18,
            "y": 7
        },
        "id": 5,
        "options": {
            "colorMode": "background",
            "graphMode": "none",
            "justifyMode": "auto",
            "orientation": "auto",
            "percentChangeColorMode": "standard",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showPercentChange": true,
            "textMode": "auto",
            "wideLayout": true
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "avg by() (openlit_otel_metrics_gen_ai_usage_cost_sum{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "Avg Usage Cost",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "",
        "transparent": true,
        "type": "stat"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the ranking of GenAI models based on their usage frequency. It identifies which models are most popular or in-demand, providing insights into user preferences and operational trends. Analyzing this helps in resource allocation, optimizing model availability, and understanding which GenAI features are driving usage.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "mode": "continuous-BlYlRd"
            },
            "mappings": [],
            "thresholds": {
                "mode": "absolute",
                "steps": [
                {
                    "color": "green",
                    "value": null
                },
                {
                    "color": "red",
                    "value": 80
                }
                ]
            },
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 10,
            "w": 14,
            "x": 0,
            "y": 10
        },
        "id": 17,
        "options": {
            "displayMode": "lcd",
            "legend": {
            "calcs": [],
            "displayMode": "list",
            "placement": "bottom",
            "showLegend": false
            },
            "maxVizHeight": 300,
            "minVizHeight": 16,
            "minVizWidth": 8,
            "namePlacement": "auto",
            "orientation": "horizontal",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "showUnfilled": true,
            "sizing": "auto",
            "valueMode": "text"
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "topk(5, sum by(gen_ai_request_model) (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"}))",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "__auto",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "Top GenAI Models by Usage",
        "transparent": true,
        "type": "bargauge"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the distribution of GenAI requests based on the environment, such as production, development, testing, etc. It shows where the requests are being utilized, providing a clear picture of operational focus and deployment strategies. Tracking this helps in aligning resources appropriately and optimizing the performance across different environments.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "mode": "palette-classic"
            },
            "custom": {
                "hideFrom": {
                "legend": false,
                "tooltip": false,
                "viz": false
                }
            },
            "mappings": [],
            "min": 0,
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 5,
            "w": 5,
            "x": 14,
            "y": 10
        },
        "id": 15,
        "options": {
            "legend": {
            "displayMode": "list",
            "placement": "bottom",
            "showLegend": false
            },
            "pieType": "pie",
            "reduceOptions": {
            "calcs": [
                "lastNotNull"
            ],
            "fields": "",
            "values": false
            },
            "tooltip": {
            "mode": "single",
            "sort": "none"
            }
        },
        "pluginVersion": "11.3.0",
        "targets": [
            {
            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
            },
            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum by(gen_ai_environment) (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "__auto",
            "range": true,
            "refId": "A",
            "useBackend": false
            }
        ],
        "title": "GenAI Requests by Environment",
        "type": "piechart"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the distribution of GenAI requests based on the application, such as production, development, testing, etc. It shows where the requests are being utilized, providing a clear picture of operational focus and deployment strategies. Tracking this helps in aligning resources appropriately and optimizing the performance across different environments.",
        "fieldConfig": {
            "defaults": {
            "color": {
                "mode": "palette-classic"
            },
            "custom": {
                "hideFrom": {
                "legend": false,
                "tooltip": false,
                "viz": false
                }
            },
            "mappings": [],
            "min": 0,
            "unit": "none"
            },
            "overrides": []
        },
        "gridPos": {
            "h": 5,
            "w": 5,
            "x": 19,
            "y": 10
        },
        "id": 27,
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            "showLegend": false
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            "pieType": "pie",
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            "values": false
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            "datasource": {
                "type": "prometheus",
                "uid": "${metricsDatasource}"
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            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum by(gen_ai_application) (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
            "fullMetaSearch": false,
            "includeNullMetadata": true,
            "instant": false,
            "legendFormat": "__auto",
            "range": true,
            "refId": "A",
            "useBackend": false
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        ],
        "title": "GenAI Requests by Application",
        "type": "piechart"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the distribution of GenAI requests across different platforms such as OpenAI, Cohere, Anthropic, etc. It shows where requests are being sent, giving insights into platform popularity and usage patterns. Monitoring this helps in understanding platform preferences, and it can guide strategic decisions for integration or diversification of GenAI services.",
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                "uid": "${metricsDatasource}"
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            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum by(gen_ai_system) (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
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        ],
        "title": "GenAI Requests by Platform",
        "type": "piechart"
        },
        {
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            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the breakdown of GenAI requests by type, such as Chat, Embedding, Image, Audio, and Fine Tuning. It reveals the diversity in usage, highlighting which types of requests are most common. Understanding this distribution assists in optimizing resources for the most demanded services and planning for future needs based on usage trends.",
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                "uid": "${metricsDatasource}"
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            "disableTextWrap": false,
            "editorMode": "builder",
            "expr": "sum by(gen_ai_type) (openlit_otel_metrics_gen_ai_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
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        ],
        "title": "GenAI Requests by Type",
        "type": "piechart"
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        {
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            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays a comparative graph showing the average number of tokens consumed for completions and prompts against the average usage cost. It provides a visual representation of the relationship between the volume of data processed (in tokens) and the financial implications of using GenAI services. Analyzing this comparison helps in assessing cost-effectiveness and guiding strategic decisions for efficient resource utilization.",
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            "editorMode": "builder",
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            "editorMode": "builder",
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        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the breakdown of database requests based on the type of operation, such as add, updates, deletes, and queries. It provides insights into the operational dynamics of database interactions, highlighting the most common actions performed. Understanding this distribution helps in optimizing database performance and planning for capacity based on operational needs.",
        "fieldConfig": {
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            "disableTextWrap": false,
            "editorMode": "builder",
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            "fullMetaSearch": false,
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        ],
        "title": "DB Requests by Operation",
        "transparent": true,
        "type": "bargauge"
        },
        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
        },
        "description": "This panel displays the distribution of requests across different VectorDB systems, such as Chroma, Pinecone, etc. It highlights which VectorDB services are most frequently used, providing insights into system preference and usage patterns. Monitoring this helps in evaluating the performance and scalability of each VectorDB system, guiding strategic decisions for technology adoption and integration.",
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            "editorMode": "builder",
            "expr": "sum by(db_system) (openlit_otel_metrics_db_total_requests{telemetry_sdk_name=\"openlit\", gen_ai_application_name=~\"$application\", gen_ai_environment=~\"$environment\"})",
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        ],
        "title": "DB Requests by System",
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        {
        "datasource": {
            "type": "prometheus",
            "uid": "${metricsDatasource}"
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        "description": "This panel displays the breakdown of DB requests by application name, offering insights into which applications are leveraging VectorDB services the most. This identification helps in understanding application-specific demand, guiding resource allocation, and supporting targeted optimization efforts for enhanced efficiency in application performance.\"",
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        "description": "This panel displays the breakdown of DB requests by application name, offering insights into which applications are leveraging VectorDB services the most. This identification helps in understanding application-specific demand, guiding resource allocation, and supporting targeted optimization efforts for enhanced efficiency in application performance.\"",
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