> For the complete documentation index, see [llms.txt](https://docs.akamas.io/akamas-docs/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/akamas-docs/using.md).

# Using

This section describes the main steps to optimize an application

To optimize a new application on Akamas Studio you have to follow four steps shown in the following picture and described in the next sections by means of a simple example.

<figure><img src="https://4014737669-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAIcn4Sm6yks9E7r1avPd%2Fuploads%2Fgit-blob-60c0f143b5c06dea0f19c9b4f00ad64cf70350ea%2Fakflow.png?alt=media" alt=""><figcaption><p>Steps to setup a new optimization</p></figcaption></figure>

As depicted in the picture above, to optimize a new application you should:

* Create a system that models the key parts of your application (e.g. containers, runtimes, APIs) that will be interested in the optimization initiative.
* Set up the integration with a monitoring tool via telemetry providers so that Akamas Studio can gather metrics about the performance of your application.
* Create a workflow that allows Akamas Studio to configure your application (e.g. write a configuration file, relaunch a process).
* Define the optimization study according to your goal and SLOs so that Akamas Studio knows what you want to achieve.

These steps relate to how Akamas Studio integrates with your environment.

## Example Application

In the following sections, we will use a simple yet representative web application to illustrate how to onboard a new application on Akamas Studio. The application is called Online Boutique. It is a microservices application composed of 11 microservices that allow users to browse items, add them to the cart, and purchase them in an online store.

Suppose that we are about to deploy a major upgrade to one of the microservices, the Ad Service, that handles the advertisement logic, and we want to reduce the costs of running this service while meeting our SLO on the response time given an increasing number of users.

As shown in the diagram below, our service is built in Java, deployed as a pod in a Kubernetes cluster, and exposes an API using a service. The whole platform is monitored with Dynatrace.

<figure><img src="https://4014737669-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FAIcn4Sm6yks9E7r1avPd%2Fuploads%2Fgit-blob-51bd89e78ed511f1b4437fd78ad6e35a6e952227%2Fusing-kube-example.png?alt=media" alt="" width="273"><figcaption><p>Online Boutique Ad microservice deployment</p></figcaption></figure>

{% hint style="info" %}
If your technology stack or optimization need does not fit this example, take a look at the [Optimization Guide](/akamas-docs/optimization-guides.md) section where you can find many optimization scenarios for different use cases.
{% endhint %}

You can now proceed to the first step, creating the system to model this application.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.akamas.io/akamas-docs/using.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
