diff --git a/docs/tools/telemetry.md b/docs/tools/telemetry.md
index b8709e4..c455963 100644
--- a/docs/tools/telemetry.md
+++ b/docs/tools/telemetry.md
@@ -187,19 +187,21 @@ To use telemetry with Graphistry, you need to:
 1. **Jaeger Dashboard:** Access the [Jaeger Dashboard URL](#jaeger-dashboard).
 2. **Key Tracing Information:**
    - List of traces generated by the system for the graph rendering flow (for instance: show the trace list including a trace with errors).
-![List of traces generated by the system for the graph rendering flow](../_static/img/jaeger-trace-list-including-trace-with-error.png)
+
+<img alt="List of traces generated by the system for the graph rendering flow" src="../_static/img/jaeger-trace-list-including-trace-with-error.png"/>
+
    - The root span for the graph rendering flow is `streamgl-viz: handleFalcorSocketConnections`.
    - The service that generates the root span for the graph rendering flow is `streamgl-viz`.
    - ETL dataset fetch spans from the Python ETL Service service.
    - Detailed spans for actions by the visualization service and GPU workers (for instance: inspecting trace with error).
-![Detailed spans for actions by the visualization service and GPU workers](../_static/img/jaeger-inspecting-trace-with-error.png)
+<img alt="Detailed spans for actions by the visualization service and GPU workers" src="../_static/img/jaeger-inspecting-trace-with-error.png"/>
 
 ### Accessing Metrics
 1. **Prometheus Dashboard:** Access the [Prometheus Dashboard URL](#prometheus-dashboard).
 2. **Critical Metrics to Monitor:**
    - `worker_read_crashes_total`: Monitor GPU worker crashes.
    - File upload and dataset creation metrics in the Python ETL service (all metrics with the name `forge_etl_python_upload_*`, for instance: `forge_etl_python_upload_datasets_request_total`).
-![File upload and dataset creation metrics in the Python ETL service](../_static/img/prometheus-forge-etl-python-metric-example.png)
+<img alt="File upload and dataset creation metrics in the Python ETL service" src="../_static/img/prometheus-forge-etl-python-metric-example.png"/>
 
 ### GPU Monitoring with Grafana and NVIDIA Data Center GPU Manager
 
@@ -207,7 +209,7 @@ To provide comprehensive monitoring of GPU performance, we utilize Grafana in co
 - **NVIDIA Data Center GPU Manager (DCGM):** [DCGM](https://developer.nvidia.com/dcgm) is a suite of tools for managing and monitoring NVIDIA GPUs in data centers.  It provides detailed metrics on GPU performance, health, and utilization.
 - **Grafana:** Grafana is an open-source platform for monitoring and observability.  It allows users to query, visualize, alert on, and explore metrics from a variety of data sources, including Prometheus.  By default the Grafana instance has the metrics and GPU dashboard from the `DCGM exporter` service (see `DCGM Exporter Dashboards` in the Grafana main page).
 
-![grafana-import-dcgm-dashboard-6](../_static/img/grafana-import-dcgm-dashboard-6.png)
+<img alt="grafana-import-dcgm-dashboard-6" src="../_static/img/grafana-import-dcgm-dashboard-6.png"/>
 
 ## Advanced configuration