Add Images to documentation (#140)

* Add Images to documentation

* Add Images to documentation

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Co-authored-by: brunnert <brunnert@hm.edu>

Author: brunnert

README.md

@@ -4,11 +4,19 @@
 This repository contains an **extension** for the [OpenTelemetry Java Auto-Instrumentation agent](https://github.com/open-telemetry/opentelemetry-java-instrumentation) **to collect resource demand data and to publish carbon emissions**. The following readme assumes that you are already familiar with the basic concepts of [OpenTelemetry](https://opentelemetry.io/) [Traces](https://opentelemetry.io/docs/concepts/signals/traces/) and [Metrics](https://opentelemetry.io/docs/concepts/signals/metrics/), otherwise please read the corresponding documentation first before you continue. 
 
 This Java agent extension attaches 
-resource demand data as [Attributes](https://opentelemetry.io/docs/concepts/signals/traces/#attributes) to all [Spans](https://opentelemetry.io/docs/concepts/signals/traces/#spans) captured by the Java Auto-Instrumentation Agent (e.g., API calls), such as storage, network and memory demand in bytes, and CPU demand in milliseconds. You can find an overview of the Span [Attributes](https://opentelemetry.io/docs/concepts/signals/traces/#attributes) added by this extension in the [corresponding section](#opentelemetry-tracing-span-attributes-added-by-this-extension). You can view and analyze these attributes with any compatible OpenTelemetry tracing backend such as [Jaeger](https://www.jaegertracing.io/). If you are interested to automate the analysis of this data of this data please check out our [RETIT Performance Analysis Suite](https://www.retit.io/) which will give you an automated aggregation of these values.
+resource demand data as [Attributes](https://opentelemetry.io/docs/concepts/signals/traces/#attributes) to all [Spans](https://opentelemetry.io/docs/concepts/signals/traces/#spans) captured by the Java Auto-Instrumentation Agent (e.g., API calls), such as storage, network and memory demand in bytes, and CPU demand in milliseconds as shown in Figure 1. You can find an overview of the Span [Attributes](https://opentelemetry.io/docs/concepts/signals/traces/#attributes) added by this extension in the [corresponding section](#opentelemetry-tracing-span-attributes-added-by-this-extension). You can view and analyze these attributes with any compatible OpenTelemetry tracing backend such as [Jaeger](https://www.jaegertracing.io/). If you are interested to automate the analysis of this data of this data please check out our [RETIT Performance Analysis Suite](https://www.retit.io/) which will give you an automated aggregation of these values.
 
 In addition to attaching Span attributes for OpenTelemetry Traces this extension publishes the resource demand data as OpenTelemetry [Metrics](https://opentelemetry.io/docs/concepts/signals/metrics/) for all entry level transactions (e.g., API calls) of an instrumented application. You can find a list of metrics published by this extension in the corresponding [section](#OpenTelemetry-Metrics-published-by-this-extension).  If you are just starting with analyzing the resource demand of your application this is the best starting point for you, before you dig into the span attributes to analyze where exactly the resources are consumed.
 
-Furthermore, the extension follows the [Methodology](https://www.cloudcarbonfootprint.org/docs/methodology/) published by the [Cloud Carbon Footprint (CCF)](https://www.cloudcarbonfootprint.org/) project to calculate the carbon emissions of an instrumented application. It contains data from the [CCF coefficients project](https://github.com/cloud-carbon-footprint/ccf-coefficients) for the biggest clouds (AWS, Azure, and GCP) and their instances. Using the resource demand data and the data of the CCF coefficents allows you to calculate the carbon emissions of single API calls of your application. This is usually done in an OpenTelemetry compatible backend, you can find an examples on how this works in the [Examples](#Examples) section of this document. If you want to use the extension for your own application check out the [Quickstart](#Quickstart) and [Configuration Options](#configuration-options) section of this document.  
+![extension_data_capture.png](img/extension_data_capture.png)
+
+*Figure 1: The OpenTelemetry Java-Agent Extension captures resource demand data for all transactions of instrumented applications*
+
+Furthermore, the extension follows the [Methodology](https://www.cloudcarbonfootprint.org/docs/methodology/) published by the [Cloud Carbon Footprint (CCF)](https://www.cloudcarbonfootprint.org/) project to calculate the carbon emissions of an instrumented application as shown in Figure 2. It contains data from the [CCF coefficients project](https://github.com/cloud-carbon-footprint/ccf-coefficients) for the biggest clouds (AWS, Azure, and GCP) and their instances. Using the resource demand data and the data of the CCF coefficents allows you to calculate the carbon emissions of single API calls of your application. This is usually done in an OpenTelemetry compatible backend, you can find an examples on how this works in the [Examples](#Examples) section of this document. If you want to use the extension for your own application check out the [Quickstart](#Quickstart) and [Configuration Options](#configuration-options) section of this document.  
+
+![energy_emission_calculations.png](img/energy_emission_calculations.png)
+
+*Figure 2: The OpenTelemetry Java-Agent Extension follows the methodology published by the Cloud Carbon Footprint (CCF) project to calculate software energy consumption and carbon emissions based on the collected data*
 
 # Quickstart