SubhasmitaSw commented on code in PR #865:
URL: https://github.com/apache/camel-website/pull/865#discussion_r906700149


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content/blog/2022/03/Optimizing-Camel-K-Integration-Build-Time/index.md:
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@@ -0,0 +1,105 @@
+---
+title: "Optimizing Camel-K Integration Build Time"
+date: 2022-06-24
+draft: true
+authors: [SubhasmitaSw][astefanutti]
+categories: ["Camel-K"]
+preview: "Using performance benchmarks to demonstrate the optimised camel-k 
integration build time."
+---
+
+The Integration is the resource which represents the actual Camel application 
and building a container image that packages the integration within an elevated 
cloud platform (be it locally in a Minikube or K8s hosted cluster to Openshift 
clusters) takes ample amount of time.
+
+### Enhancing the Camel-K Integration build time
+
+Our goal was to reduce overhead and improve user experience. We were able to 
narrow down the major contributors that had a significant influence on the 
integration build time.
+
+We identified that the CPU resources available to the operator can have a 
significant impact on integration build time. Following that, we modified the 
Camel-K operator to be aware of the CPU quota set on the operator container, 
and then we made the Maven process and container image layers push scaling 
vertically based on the CPU quota. Users may use Maven to download dependencies 
in parallel by configuring a group of concurrent threads. We modified the 
technique for configuring the build by default to account for the maximum 
number of CPU cores available simultaneously. In addition we modified the 
container Image push method to use the parallelization. 
+
+The effect of faster build times may be seen in the benchmark comparisons 
below. 
+
+### System Configuration 
+
+
+| Device         | Chip              | Total Number of Cores | Memory |
+| -------        | -----             | --------              |--------|
+|MacBook Air (M1)| Apple Sillicon M1 |   8 core CPU (4 performance and 4 
efficiency), 7 Core GPU                |                  8GB
+
+
+
+### Environment Configuration 
+
+The tests are graded using the following configurations: 
+
+1. **Minikube Version:**  v1.25.2
+2. **Minimum no. of cores:** 2
+3. **Maximum no. of cores:** 4
+4. **Maximum memory used:** 3933 MB
+5. **Registry Addon:** Enabled 
+
+*PS: These metrics are exclusive to my system; they may differ for others.*
+
+### Evaluating Performing 
+
+1. Start a new minikube cluster with minimum permissible cores and maximum 
memory (as per docker desktop)
+    ```
+    minikube start --addons registry --cpus 2 --memory=3GB
+    ```
+2. Setup the Camel-K environment by installing the client (Kamel)
+
+    ```
+    kamel install
+    ```
+3. Run a sample Integration in the dev mode
+    ```
+    kamel run --env MY_ENV_VAR="hello world" Env.java --dev
+    ```
+4. Get the build duration 
+    The build duration is ~6mins using default usage of cores available. 
+
+    ![default CPU usage build time](build-time-default.png)
+
+5. Delete the minikube cluster to reinstate the environment and avoid any 
usage of previously build Integration images. 
+    ```
+    minikube delete
+    ```
+6. Start a new minikube cluster with maximum permissible cores and maximum 
memory (as per docker desktop)
+    ```
+    minikube start --addons registry --cpus 4 --memory=3GB
+    ```
+7. Repeat steps 2 and 3. 
+8. Get the build duration
+    The build duration is ~2mins utilizing the maximum CPU cores available for 
my system. 
+
+    ![build time based on max CPU quota](optimized-build-time.png)
+
+#### Benchmark Comparison
+
+
+| Integration | Integration Kit Name | Build Time |CPUs |
+| -------- | -------- | -------- |----- |
+| Env.java     |  kit-caopeg968cvc73fie4t0   |   6m26.044974722s   | 2 | 
+|Env.java | kit-caort9bmr3lc73emiifo | 2m24.9183443385s | 4
+
+It is clear that the build time has decreased significantly; with more 
powerful systems (e.g., 16, 32 cores), the build time will be reduced to a few 
tens of seconds.
+
+
+### Leveraging the benefit 
+
+To utilise this newly available functionality and apply CPU constraints on 
operator deployment, select from the following example measures or consult the 
[Resource 
Management](https://camel.apache.org/camel-k/1.9.x/installation/advanced/resources.html#scheduling-infra-pod-resources)
 guide to modify it about their own needs.
+
+```
+kamel install --operator-resources requests.cpu=256m --operator-resources 
limits.cpu=500m --operator-resources limits.memory=512Mi ...
+```
+The operator Pod's Maven builds are most likely the largest contributor to 
compute resource consumption (assuming you use the default build strategy). As 
a result, the resource needs must be determined properly. The conditions listed 
below are reasonable defaults that should work in most cases, probably giving 
you the freedom to customize it as per your system to leverage the full 
potential of it.
+
+```

Review Comment:
   specify the yaml language usage for the last example you mean? I'm not very 
clear here 



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