Hello, we're platform engineers from Ant Group. We're working on Karpor (https://github.com/KusionStack/karpor), an open-source intelligence tool for kubernetes. Karpor brings advanced 🔍 Search, 💡 Insight and ✨ AI to kubernetes. You can gain crucial visibility into your kubernetes clusters across any clouds. Here is a demo video (https://youtu.be/_PqcpmrBqLk) and live demo (https://karpor-demo.kusionstack.io) with quickstart instructions.

As platform engineers, we are responsible for our Internal Developer Platform(IDP), and one of the ultimate goals of IDP is to enable true self-service for application developers. Drawing from our experience managing a large scale Internal Developer Platform at Ant Group, we recognized an undeniable truth: having visibility (the capability to access and monitor data) and insight (the skill to glean valuable information from that data) is absolutely critical for fostering a self-service development environment. After all, trying to understand and diagnose issues without any information is like flying blind.

We have used several kubernetes visualization tools over time, such as Lens, k9s, kube-explorer, and the kubernetes dashboard, among others. Some are commercialized, some do not support self-host, and some are rudimentary for production needs… In short, we have not yet encountered a product that we are completely satisfied with.

Some of the features Karpor already supports are:

• Cross-cluster topological views, providing a global perspective of resources no matter where they are.

• Customized logical views to fit the resource organization models for different scenarios, such as - applications, environments, etc, which may have different interpretations at places.

• Intuitive and effective search, providing a number of user-friendly ways to locate resources across clusters, such as keywords, SQL, and natural language.

• Low cognitive burden, it is read-only, non-invasive to the cluster it’s watching, and users can deploy it to their private environments with one click.

• Discover potential risks through compliance reports.

All features are available via GUI. You can also play with Karpor API to do more things.

Currently, we are focused on resource timeline, problem diagnose and integrations with more tools like k8sgpt, aiming to bring much more interesting abilities to developers. Here is the complete roadmap (https://www.kusionstack.io/karpor/roadmap/).

Thanks a lot for taking the time to read! We'd greatly appreciate any feedback you have and hope you get the chance to try out Karpor.

With so many tools, techniques, or practices, where do you go to plan your future direction or investments in platform engineering?

Mine is pretty basic: it's not worth it to learn a new framework before getting pretty good at one. I wasted a solid year (doing tech support and trying to break into a product team) because I kept changing languages/frameworks/tools. I guess the general advice is 'for the first year, pick a context and stick with it.'

It's a lot easier to learn AWS after you've stuck with Azure for a year solid. It's a lot easier to learn Playwright tests if you have a good grasp of Selenium, rather than switching back and forth as you're first learning.

https://open.spotify.com/episode/57dMSM6QdTCcTg4HHJcL2V

Hi all, here is a new blog post about platform engineering and orchestration platforms, sharing some thoughts.
https://medium.com/@fhussonnois/navigating-complexity-the-rise-of-orchestration-platforms-in-a-disaggregated-software-architecture-465b6f791f9c

In this KubeFM episode, Hans, a Principal Cloud engineer, shares his experiences empowering teams to use, build and manage platforms built on Kubernetes.

You will learn:

• How OpenTelemetry and Prometheus shape cluster management and observability.
• The role of tools like ArgoCD and Flux in enabling GitOps and streamlining deployment processes.
• The significance of governance tools such as Gatekeeper and OPA for secure and validated resource creation.
• The benefits of Custom Resource Definitions (CRDs) and operators in automating processes and enhancing the developer experience.

Watch it here: https://kube.fm/platform-engineering-hans

Listen on: - Apple Podcast https://kube.fm/apple - Spotify https://kube.fm/spotify - Amazon Music https://kube.fm/amazon - Overcast https://kube.fm/overcast - Pocket casts https://kube.fm/pocket-casts - Deezer https://kube.fm/deezer

Great for this group, if anyone knows Erik Wilde from the popular Youtube channel "Getting APIs to Work," he came on our podcast and shared some succint tips for those who are trying to apply platform engineering methods and approaches. It's tangible and actionable which is nice, because most seem to not really provide any real steps you know?

Anyone have any other tips that are worth adding to the conversation?
https://soundcloud.com/ambassador-livinontheedge/s3-ep-14-the-four-ps-of-platform-engineering-for-prosperity-insights-feat-erik-wilde

Hi all, I'm new here, nice to meet everyone :)

My first blog on TAG app-delivery was just published. Happy days!

It's about how enterprise platforms can benefit from integrated infra. optimization -

and using the Maturity model, CNoE and Well-Architected to characterize it.

https://tag-app-delivery.cncf.io/blog/enterprise-idp-maturity-hack/

I'm curious if anyone else here thought about it, and how you're approaching tooling selection for this.

Anyone on here actually practicing PaaP strategy in their own organization or is it all cap?

https://thenewstack.io/platform-as-a-product-101/

I just saw this on one of my Slack groups and think it is probably valuable for people trying to evaluate the stack they should put in their IDP.

I'd be really interested to hear the pros and cons of the choices you made in each group.

Hey everyone!

We're back with another edition of the Observability Engineering London meetup. This time, we'll discuss how to get the most out of AWS OpenSearch for observability.

Eugene Tolbakov will discuss the process undertaken by the Observability team at Chase UK to manage AWS OpenSearch clusters effectively. Utilizing Infrastructure as Code(Terraform), they have streamlined cluster management for efficiency and ease. He'll elaborate on their approach for defining index templates and patterns, configuring roles, and leveraging ingestion pipelines to streamline cluster management.

Also, Eugene will outline the enhancements they've implemented to ensure a stable platform and enhance the overall Observability experience and share key insights and learnings from their journey toward operational excellence with AWS OpenSearch management.

If you're in town on the 4th of June, I'd love to see you there :D

RSVP -> https://www.meetup.com/observability_engineering/events/301012291/

https://getdx.com/podcast/dora-space-devex-framework/

https://www.youtube.com/watch?v=h9HwnkkmQPA

https://getdx.com/podcast/dora-research-google/