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Byte-Sized Tech Tips Round-Up: Week 5

Steve Martinelli
Canadian | IBMer | FOSS | Python | Kubernetes
・Updated on ・2 min read

Tip 1: Level up your Terminal with PowerLevel10k

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As developers we spend a big chunk of our day in the terminal. So making it visually appealing is not a bad idea. There are a ton of ways to customize the look and feel of the terminal UI and you can get into this rabbit hole of custom bash scripts.

If you want a quick and easy way to make your terminal look all fancy like, then look no further than PowerLevel10k. In less than 10 minutes you can get your terminal to look from this (left) to this (right)

Tip 2: Kubernetes namespace management made EASY

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I use namespaces in Kubernetes for testing out deployments and services. I am able to try things out in the test namespace without affecting anything in the integration namespace. The goal is to always have a working solution in the integration namespace. There are a few ways to switch between the namespaces.

The Kubernetes documentation describes a good way to do this by creating two contexts, one for test and another for integration. The user would then use the use-context command as follows

kubectl config use-context <context-name>
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Another quick way to set the current namespace is by using the kubectx and kubens.

Let's take a look. Here I am currently in the default namespace:

$ kubectl get po
NAME                                READY   STATUS    RESTARTS   AGE
mariadb34-6957-47-master-0          1/1     Running   11         49d
mariadb34-6957-47-slave-0           1/1     Running   7          49d
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Now use kubens to switch to the test namespace:

$ kubens test
Context "Prometeo-Kubernetes/bs8vr7fl0civct1kgnpg" modified.
Active namespace is "test".
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Now let’s list the pods again:

$ kubectl get po
NAME                            READY   STATUS    RESTARTS   AGE
hello-server-5bfd595c65-ct8n9   1/1     Running   0          2d21h
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It's just that simple!

Tip 3: Generate a Jupyter Notebook with AutoAI

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This week I discovered a beta feature to save your AutoAI data model on IBM's data science platform. IBM's AutoAI experiment feature, which generates multiple models with a few clicks based on your data set, will now generate a Jupyter Notebook automatically! You can then use the AutoAI experiment results in a notebook to visualize and read your data to test, deploy and score a model!

Generating models with AutoAI
Screen Shot 2020-11-04 at 2.29.19 PM

Generating a notebook with AutoAI
Screen Shot 2020-11-04 at 2.30.07 PM

Read more about AutoAI

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