#37: K8s tools to boost productivity

#37: K8s tools to boost productivity

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7 K8s tools to boost productivity

96% of software engineering organizations are using k8s, which means you probably are too. Aly Ibrahim shared 7 tools that can help you use k8s to its fullest potential.


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1️⃣ kubectx and kubens

Switching between clusters can be tough when working with multiple, the native kubectl command ain't easy.

Try kubectx, it's a huge fix & it works with auto-completion. It also ships with a companion tool, kubens, to do the same thing but for namespaces.

2️⃣ krew

Wondering how to find these awesome tools? Meet Krew. It’s a plugin manager. Think dnf for Linux, brew on MacOS, or chocolatey on Windows.

3️⃣ kube-capacity

kube-capacity is awesome for getting an on-the-fly snapshot of whether you need to upgrade your infra.

You can also sort the output using custom metrics, namespaces, or pods. You just need to make sure you have k8s Metrics Server running on your clusters.

4️⃣ kube spy

This plugin is great for understanding what's going on behind the scenes. Aly recommends it for learners, but it also provides useful visibility.

It offers two functional modes: a tracing mode and a status mode.

5️⃣ Stern

Sometimes, you'll want to see your pods' logs as you’re working but the kubectl command doesn't cut it.

Using a command like stern <resource>/<name> shows you live, color-coded updates for multiple matching pods & containers.

6️⃣ K9s

K9s is a terminal-based UI that lets you watch your apps from the command line.

It gives you multiple views that let you observe things happening in real-time like resource usage, events & the status of deployments, pods, & clusters.

7️⃣ OpenLens

OpenLens is an open-source dashboard that accomplishes many of the same things you can achieve with K9s, but with a muuuch slicker interface.

Read the full article here.


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🥐 Will the platform engineering hype hit the dreaded trough of disillusionment? I dove into this topic (and more!) on this episode of The Cloudcast.

🥐 Can ChatGPT help DevOps teams overcome the Kubernetes skills gap?

🥐 This is an interesting look at software delivery performance indicators at different granularities. 

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Have you joined the Platform Engineering Slack channel? If not, you're missing out. Here are some highlights:


Gbemisola Shitta

Technical Program Manager | SaaS Product Optimization Expert | ERP CRM | Adj. Professor |Ex-Loblaw Digital, BMO, FirstBank

1y

Cc: Caleb Adeyemi and Luca Landi

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Evgenios Soroka

Senior DevOps Engineer at Distribusion

1y

I suggest kubeswitch - replaces both kubectx and kubens. And most importantly it has terminal isolation, so you can have different contexts in different terminal windows. Very useful when working with multiple clusters. Switched to it and never looked back

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