> For the complete documentation index, see [llms.txt](https://docs.akamas.io/quick-guides/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.akamas.io/quick-guides/quick-guides-akamas-in-a-box/aiab-01-optimize-a-java-based-application-renaissance-benchmark/aiab-01-configure-the-telemetry.md).
# \[AIAB-01] Configure the Telemetry
In this section you will configure how Akamas collects metrics related to the `renaissance` system. Metrics are required both to define your optimization goal (e.g.: minimize the `renaissance.response_time` metric) and analyze the optimization results.
A **Telemetry Provider** specifies how to collect these metrics from a source, such as a monitoring platform (e.g. Prometheus or Dynatrace), a test tool (eg. Neoload or Loadrunner) or a simple CSV file. Akamas ships several out-of-the-box Telemetry Providers.
For each specific source, an instance of the corresponding Telemetry Provider needs to be defined at the system level.
#### **Create a CSV telemetry instance**
The output of the Renaissance benchmark suite is a CSV report file once the benchmark completes, which includes the benchmark execution time, CPU, and memory usage. Therefore, you will now create a CSV telemetry instance.
The file `tel_csv.yaml` provides the following definition:
```yaml
provider: CSV File
config:
protocol: scp
address: benchmark
username: akamas
authType: password
auth: akamas
remoteFilePattern: renaissance-parsed.csv
componentColumn: component
timestampColumn: TS
timestampFormat: yyyy-MM-dd HH:mm:ss zzz
metrics:
- metric: response_time
datasourceMetric: duration_ns
- metric: cpu_used
datasourceMetric: cpu_used
- metric: mem_used
datasourceMetric: mem_used
```
Create the telemetry instance as follows:
```bash
akamas create telemetry-instance tel_csv.yaml renaissance
```
You can verify your new telemetry instance under the corresponding tab within the UI:
You can always list all telemetry instances in a system and verify that they have been correctly created:
```bash
akamas list telemetry-instances renaissance
```
So far you have defined what the application to be optimized looks like in terms of Akamas system and components, and the telemetry required to gather the relevant metrics. Your next step is to create a workflow, that is defining how to run optimization experiments.
---
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