Cloud Native weekly highlights:

  • Dapr joins CNCF incubator
  • Knative 1.0 release
  • Canonical is starting to offer Ubuntu graphics optimized for Intel CPUS
  • Longhorn brings cloud native distributed storage to CNCF Incubator
  • Open Source Project Recommendation
  • The article recommended

Cloud native dynamics

Dapr (Distributed Application Runtime) joins CNCF incubator

Today, THE CNCF Technical Oversight Committee (TOC) has voted to accept Dapr as the CNCF incubation program.

Dapr is a set of apis that make it easy for developers to write distributed applications. Dapr runs as a Sidecar process alongside applications, whether in Kubernetes or any other environment, and provides developers with a secure set of primitives in the form of publish/subscribe, state management, secret management, event triggers, and service-to-service calls. With Dapr, developers focus on building business logic rather than infrastructure.

Main ingredients:

  • Dapr Sidecar — Runs alongside applications and contains developer-oriented apis.
  • CLI and SDK – the developer tool experience that makes up the project.
  • Components- Contrib repository – Developers can extend Dapr to integrate and support a variety of cloud services and open source technologies.

Important milestones:

  • 15.1 k making Stars
  • 1940 pull requests
  • 3703 issues
  • 1.3 k contributors
  • 14 stable versions v1.4
  • 26M Docker pulls

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Knative 1.0 release

Knative 1.0 was released today, thanks to the contributions and collaboration of over 600 developers. Launched by Google in July 2018, the Knative project was developed in close collaboration with VMWare, IBM, Red Hat, and SAP. Over the past three years, Knative has become the most widely installed serverless layer on Kubernetes.

Knative consists of a number of version-controlled components: Core components (Serving, Eventing) the entire GA (generally available); Extension components (service/event functions, NET -* plug-ins, channels/proxies, sources) will be in Alpha, Beta, or GA states.

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Canonical is starting to offer Ubuntu graphics optimized for Intel CPUS

Canonical has released the first Ubuntu images optimized for the next generation Intel iot platform to meet the unique needs of intelligent edges across multiple vertical industries.

As the number and scale of iot deployments continue to grow, maintaining a large number of devices in the field has become a major focus for operations teams. Stability and reliability are key pain points addressed by Canonical, which integrates the latest Intel kernel patches in various Ubuntu releases, as well as the well-known security and reliability features provided through the containerized Ubuntu Core. In addition, hardware-based security measures integrated into Intel chips help mitigate firmware, code and data attacks, while dedicated encryption accelerators speed up data encryption.

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Longhorn brings cloud native distributed storage to CNCF Incubator

Today, THE CNCF Technical Oversight Committee (TOC) has voted to accept Longhorn as the CNCF incubator project.

Longhorn is Kubernetes’ distributed block storage system designed to run on different types of physical storage devices, infrastructures and architectures. It is built on Kubernetes for workloads running on Kubernetes. Longhorn’s control plane is based on the controller design pattern and utilizes dynamic POD management to provide its data plane communication stack.

Longhorn joined CNCF as a sandbox project in October 2019. Since then, Longhorn has seen phenomenal growth, going from 200 contributors to 30 companies to more than 800 contributors to more than 120 companies. The number of submitters increased from 14 from three companies to more than 70 from more than 13 companies. The number of nodes running Longhorn worldwide increased tenfold, from 2,700 to more than 34,000.

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Open Source Project Recommendation

MangoDB

MongoDB abandoned full open source and changed its license to SSPL, making it unavailable for other open source and commercial projects. MangoDB is an open source alternative to MongoDB that converts MongoDB’s line-protocol queries into SQL and uses PostgreSQL as its database engine.

kubectl-slice

Kubectl-slice is a CLI tool that rules a Kubernetes configuration list containing multiple object resources into multiple YAML files.

For example, there is a configuration list like this:

# example.yaml
apiVersion: v1
kind: Pod
metadata:
  name: nginx-ingress
---
apiVersion: v1
kind: Namespace
metadata:
  name: production
Copy the code

Kubectl-slice regrets generate two separate configuration lists:

$ kubectl-slice --input-file=example.yaml
Wrote pod-nginx-ingress.yaml -- 57 bytes.
Wrote namespace-production.yaml -- 60 bytes.
2 files generated.
Copy the code

Peirates

Peirates is a Kubernetes penetration tool that enables attackers to infiltrate the Kubernetes cluster by upgrading permissions to steal the Service Account in the cluster in order to gain further code execution permissions and gain control of the cluster.

PortX

PortX is a cross-platform SSH client that macOS users can use as an alternative to Xshell.

The article recommended

KubeSphere 3.2.0 release: Brings GPU scheduling and more flexible gateways for AI scenarios

What are the hottest server-side technologies today? The answer is probably cloud native! KubeSphere, as a cloud native distributed operating system based on Kubernetes kernel, is also a part of the cloud native boom in full swing. KubeSphere continues its commitment to 100% open source and is rapidly going global thanks to the power of the open source community.

KubeSphere 3.2.0 brings more anticipated features, including new support for “GPU resource scheduling management” and GPU usage monitoring, further enhancing the experience in cloud native AI scenarios. In addition, features such as “multi-cluster management, multi-tenant management, observability, DevOps, App Store, and micro-service governance” have been enhanced to further improve the interaction design and overall improve user experience.

Efficiently deploy the Prometheus federated cluster

Personally, I would rather deploy a Set of Thanos in front of a Prometheus cluster than manually deploy a Prometheus federated cluster. The authors of this article may not have the freedom to deploy other services in a cluster, so they are trying to optimize their federated solution. If that’s you, take a good look at this article.

Azimo’s path to world-class surveillance

Monitoring is divided into three levels:

  • Infancy: monitoring is always one step behind customers
  • Advanced stage: The monitoring is consistent with the information obtained by the customer
  • Mahayana: monitoring is always one step ahead of customers

Most of us are stuck in the first and second realms. To get to the highest realms, check out Azimo’s shared experience.

This article is published by OpenWrite!