kuma kong

Now that we have the service mesh and our application deployed, it’s time to configure a way to allow outside traffic to our application. value: "8080"

app: random-sports-team So, Kong Gateway has a lot more metrics available that we can gain insight into if we can reuse the same Prometheus server. # deploy the Kong requirements such as namespace, CRDs, deployment, etc. kind: Ingress First we are going to deploy Kuma so that we have our service mesh deployed before deploying our application and the Kong ingress gateway. Kong Inc., the leading cloud connectivity company, today announced a significant upgrade to open source Kuma, the universal service mesh originally … name: http Own your Kubernetes cluster by extending Kong functionality as an ingress controller. To do so, it really is quite simple. paths: namespace: random-sports-team Well, let me show you. Based on the popular open source Envoy proxy, Kuma is a universal control plane that addresses limitations of first-generation service mesh technologies by enabling seamless management of any service on the network. We need to create a Kubernetes Ingress object which I’ll do below as well as annotate our randoms-sports-team service to allow Kuma to handle the load balancing instead of Kong. Just run the following kumactl install [..] command and it will deploy the stack.

To have a look at the mTLS settings in the UI, we can port-forward the service again and head over to Meshes → Overview and verify it is using the built-in CA we specified. template:

name: random-sports-team That’s all for this blog. For this, we will use Kong which is an Ingress Controller created by the same team that built Kuma. selector: Follow the steps.

But you may ask, “wait, didn’t we just set up Prometheus by enabling the metrics option on the entire Kuma mesh? In the remainder of this tutorial, I will explain how you can extend the Prometheus monitoring stack we just deployed to work in conjunction with Kong. import page in Grafana (http://localhost:3000/dashboard/import) to import a new dashboard: On this page, you will enter the Kong Grafana dashboard ID, Here, you need to select the Prometheus data source. The concept of service mesh continues to become increasingly popular over the last year or so as we shift to a more containerized approach for our application workloads. We will create a Custom Resource in Kubernetes to enable the Prometheus plugin in Kong.

Say it with me, Jerry Harry. Go back to the Kong Grafana dashboard and watch those sweet metrics trickle in: You now have Kuma and Kong metrics using one Prometheus monitoring stack. When enabling the metrics option on the mesh, Prometheus only has access to metrics exposed by the. )

kuma.io/sidecar-injection: enabled, apiVersion: apps/v1

ports: Say it with me. Kong Inc., creators of the leading API and service lifecycle management platform for modern architectures, has released a new open source project called Kuma. But why reinvent the wheel when my previous blog post already covered exactly how to do this. But why reinvent the wheel when my previous blog post already covered exactly how to do this.

metadata:

to set up Kong and Kuma in a Kubernetes cluster.

Jacob has spent a lot of his early career in Python development as well as networking. To do so, it really is quite simple. This will be the same PROXY_IP step we used in the prerequisite blog post. So, Kong Gateway has a lot more metrics available that we can gain insight into if we can reuse the same Prometheus server. that sit alongside the services in the mesh, not from the actual services. There are plenty of ways we can go from here but some of the features I want to cover in a future blog focus around getting this production ready by adding traffic shaping, custom TLS certificates to Kong through cert-manager, and exploring what other additional features Kuma can provide for us. This configures Kong to collect metrics for all requests proxies via Kong and expose them to Prometheus. It does so by abstracting the underlying complexity of a mesh away so that it looks like everything runs on one central cluster from the outside which makes it easier to integrate with other infrastructure. How does this change observability for the microservices in our Kubernetes cluster? Clear up this mesh: Control plane Kong Kuma gets hybrid universal mode... What’s the point: Puppet Comply, Qt 6.0 beta, cf-for-k8s, Prometheus, and Kata Containers, Former rivals at OpenTelemetry lock in tracing specification, to focus on metrics next, Let the right one in: Kubermatic Kubernetes Platform hits 2.15 with external cluster support, new installer, What’s the point: LLVM 11, HashiCorp Boundary, Atlassian, and OpenCV, What’s the point: Rook, Kong, Docker Hub, Elixir, Sumo Logic, and Sonatype, Cloud native shopping: Cisco plans Portshift acquisition, Kasten to join Veeam, Open sauce: Rancher 2.5 puts new UI forward, gets to continuously delivering, What’s the point: GitHub, CircleCI, Puppet, Jaeger, Ruby, and HashiCorp, Grafana 7.2 adds flexibility to date displays and transformations. Kuma is now deployed and we have port-forwarded the control-plane service so we can access it through a browser and see what we have just deployed. service: '*' The first thing to do is to set up Kuma and Kong. Gain visibility and empower teams to provide security, governance and compliance. kind: Service Hell! We’ll leave this section short and sweet as I want to keep the focus on Kuma and Kong. periodSeconds: 3, # you will see the application pod CrashLoopBackoff until this is created, apiVersion: v1 app: random-sports-team # deploy the Kong requirements such as namespace, CRDs, deployment, etc. The drop down should only have one option named “Prometheus,” so be sure to just select that. We need the Prometheus plugin to expose metrics related to Kong and proxied upstream services in Prometheus exposition format. If nothing shows up when you echo $PROXY_IP, you will need to revisit the prerequisite and make sure Kong is set up correctly within your mesh. - match: This configures Kong to collect metrics for all requests proxies via Kong and expose them to Prometheus. port: 8080 # label the Kong namespace so that Kuma will inject the ingress controller with a data-plane proxy, # delete the current ingress pod so that it can be injected with the data-plane proxy, # verify the ingress pod and services have come up successfully, # create an ingress object in the random-sports-team namespace, apiVersion: extensions/v1beta1 containers:

Kuma is a universal open source control-plane for Service Mesh and Microservices that can run and be operated natively across both Kubernetes and VM environments, in order to be easily adopted by every team in the organization. In the UI, you will also notice there are not any data planes and this is because we have not on-boarded any applications onto a Kuma mesh. Rapidly design, publish and consume APIs and services.

ME. The drop down should only have one option named “Prometheus,” so be sure to just select that. If nothing shows up when you. Once the prerequisite cluster is set up, getting Prometheus monitoring stack setup is a breeze.

backend: It is not included by default, so you can edit the mesh object using kubectl like so: We can visualize our metrics with Kuma’s prebuilt Grafana dashboards. targetPort: 8080

THE. servicePort: 8080, apiVersion: kuma.io/v1alpha1

Build, secure and observe your modern Service Mesh.

kind: Mesh We will create a. in Kubernetes to enable the Prometheus plugin in Kong. kind: Deployment API platform provider Kong has pushed out version 0.6 of open source control plane Kuma – the last release before the project is handed over to the Cloud Native Computing foundation. Take control of your microservices traffic with the world’s most popular API gateway.

Thanks, Harry, for the idea! When we first created Kuma – which means “bear” in Japanese – we dreamed of creating a service mesh that could run across every cluster, every cloud and every application. Once the prerequisite cluster is set up, getting Prometheus monitoring stack setup is a breeze. Kuma now also knows the concept of global and remote control planes. Outside of writing Ansible roles and Terraform modules for customers, Jacob has also used his development skills to write multiple Ansible modules in Python. The kong-proxy service is now securely talking to the random-sports-team service over the Kuma service mesh securely using mTLS. How does this change observability for the microservices in our Kubernetes cluster? METRICS. According to Kong CTO Marco Palladino, the project’s open sourcing last autumn was already done with a new vendor-neutral home in mind. Prerequisites.

livenessProbe: - match: Kong powers reliable digital connections across APIs, hybrid and multi-cloud environments. The first thing to do is to set up Kuma and Kong. serviceName: random-sports-team

sources: This is very easy to configure in Kuma and is very configurable. But we can do better…by stealing more ideas from Harry’s blog. But before we go explore that new dashboard we created, we need to set up the Prometheus plugin on the Kong API gateway. And if Kong sits within this mesh, why do we need an additional Prometheus plugin?” I know it may seem redundant, but let me explain. metadata: METRICS. The UI is very user friendly and gives plenty of help to get users started with the tool. If you are interested in learning more about Kuma or service mesh in general, as well as Kong, let me know and I’d love to discuss it with you. initialDelaySeconds: 3 backends: Execute the following to enable the Prometheus plugin for all requests: Export the PROXY_IP once again since we’ll be using it to generate some consistent traffic. In this blog, we deployed the Kuma control-plane which gave us the grounds to deploy the default service mesh and deploy our application within it. By default, Kuma deploys a default mesh called default and this is the one we will use for this blog. And thank you for following along. The first thing to do is to set up Kuma and Kong.

enabledBackend: ca-1 Notable Improvements in 0.7.1 Official Helm Charts now…, We are happy to announce the general availability of Kuma 0.7! - name: ca-1 This repository houses the demo application used to illustrate Kuma's extensive features. CTRL + SPACE for auto-complete. It then provides users with an ingress data plane mode to automate cross-platform and cross-cluster service mesh communication, automated service connectivity, and a native universal DNS service discovery API.

Jacob also spends lots of time building new projects with his multiple Raspberry Pis.

namespace: random-sports-team

Kuma Demo Application. labels: In this example we are using a built-in CA to sign our certificates but Kuma does allow you to provide your own if required. Moving to Arctiq has allowed Jacob to transition to a more hybrid role and get hands on experience with microservices and automation tooling as well as still getting time to work on development projects. With this, I’ve acquired a keen interest in trying out a bunch of them to see what they each bring to the table. labels: env:

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