Is there a way I can get a list of all helm releases, and then all resources that have been created by this release, using the Kubernetes REST API?
I mean something similar to helm and kubectl commands
helm list
kubectl get all --all-namespaces -l=release-name
but using REST - https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/
Helm is built on top of the Kubernetes API layer, in that it creates objects like Deployments and Services and stores its state in Secrets; but a Helm release is not itself a Kubernetes object and you can't directly use the Kubernetes API to access it.
If your application is in Go, then Helm 3 includes a Go SDK, which essentially exposes most of the helm binary as Go-native library calls. This isn't a network-visible API, though, and if your application is in any other language you won't be able to integrate with it.
If instead it's more important to be able to manipulate your application using Kubernetes's REST API than to be using Helm proper, one alternative is to write a program (a Kubernetes controller) that interacts with the Kubernetes API, and have it be driven by a custom resource, a Kubernetes object that would include your application-specific configuration. This pair is commonly called an operator. Much more so than a Helm chart, though, this involves actually writing code and not just dropping in bits of Kubernetes YAML. (And, much more so than a Helm chart, you can unit-test more complex logic using your host language's native test tools.)
But in short, no, unless you can use the Helm Go SDK then there's not a good way to programmatically interact with a Helm chart beyond shelling out to the helm command.
Related
I am creating deployment,service manifest files using helm charts, also secrets by helm but separately not with deployments and service.
secretes are being loaded as env variables on pod level.
we are looking to refresh or restart PODs when we update secrets with new content.
Kubernetes does not itself support this feature at the moment and there is feature in the works (https://github.com/kubernetes/kubernetes/issues/22368).
You can use custom solution available to achieve the same and one of the popular ones include Reloader.
i'm working on a continuous deployment routine for a kubernetes application: everytime i push a git tag, a github action is activated which calls kubectl apply -f kubernetes to apply a bunch of yaml kubernetes definitions
let's say i add yaml for a new service, and deploy it -- kubectl will add it
but then later on, i simply delete the yaml for that service, and redeploy -- kubectl will NOT delete it
is there any way that kubectl can recognize that the service yaml is missing, and respond by deleting the service automatically during continuous deployment? in my local test, the service remains floating around
does the developer have to know to connect kubectl to the production cluster and delete the service manually, in addition to deleting the yaml definition?
is there a mechanism for kubernetes to "know what's missing"?
You need to use a CI/CD tool for Kubernetes to achieve what you need. As mentioned by Sithroo Helm is a very good option.
Helm lets you fetch, deploy and manage the lifecycle of applications,
both 3rd party products and your own.
No more maintaining random groups of YAML files (or very long ones)
describing pods, replica sets, services, RBAC settings, etc. With
helm, there is a structure and a convention for a software package
that defines a layer of YAML templates and another layer that
changes the templates called values. Values are injected into
templates, thus allowing a separation of configuration, and defines
where changes are allowed. This whole package is called a Helm
Chart.
Essentially you create structured application packages that contain
everything they need to run on a Kubernetes cluster; including
dependencies the application requires. Source
Before you start, I recommend you these articles explaining it's quirks and features.
The missing CI/CD Kubernetes component: Helm package manager
Continuous Integration & Delivery (CI/CD) for Kubernetes Using CircleCI & Helm
There's no such way. You can deploy resources from yaml file from anywhere if you can reach the node and configure kube config. So kubernetes will not know how to respond on a file deletion. If you still want to do this, you can write a program (a go code) which checks the availability of files in one place and deletes the corresponding resource whenever the file gets deleted.
There's one way via kubernetes is by using kubernetes operator, and whenever there is any change in your files you can update the crd used to deploy resources via operator.
Before deleting the yaml file, you can run kubectl delete -f file.yaml, this way all the resources created by this file will be deleted.
However, what you are looking for, is achieving the desired state using k8s. You can do this by using tools like Helmfile.
Helmfile, allow you to specify the resources you want to have all in one file, and it will achieve the desired state every time you run helmfile apply
I have a requirement where my client applications are having almost same properties and even the URL is same, as they are running behind a load balancer, the only change they have is a particular set of environment properties that differ.
Is it possible to register them uniquely based on that property.
I would say there are a few approaches.
One would be loading Environment Variables from a Kubernetes Secret.
Second using helm(https://helm.sh/)
Helm helps you manage Kubernetes applications — Helm Charts help you define, install, and upgrade even the most complex Kubernetes application.
Charts are easy to create, version, share, and publish — so start using Helm and stop the copy-and-paste.
Explanation:
If you would use a secret option, you would probably create two separate secrets with env variables that you need and load those based on the app name, or if you have them setup in different namespaces then copy the secret over to each as those resources will not work between different namespaces.
If you would use helm, you will have to write your chart and put the env variables into values.yaml or mix it together and load secret from inside Kubernetes.
This will work on Kubernetes, I do not know (based on your tags) if it's the same on OpenShift.
Please provide some samples of what you have already done and I'll provide more details.
The github repo of Prometheus Operator https://github.com/coreos/prometheus-operator/ project says that
The Prometheus Operator makes the Prometheus configuration Kubernetes native and manages and operates Prometheus and Alertmanager clusters. It is a piece of the puzzle regarding full end-to-end monitoring.
kube-prometheus combines the Prometheus Operator with a collection of manifests to help getting started with monitoring Kubernetes itself and applications running on top of it.
Can someone elaborate this?
I've always had this exact same question/repeatedly bumped into both, but tbh reading the above answer didn't clarify it for me/I needed a short explanation. I found this github issue that just made it crystal clear to me.
https://github.com/coreos/prometheus-operator/issues/2619
Quoting nicgirault of GitHub:
At last I realized that prometheus-operator chart was packaging
kube-prometheus stack but it took me around 10 hours playing around to
realize this.
**Here's my summarized explanation:
"kube-prometheus" and "Prometheus Operator Helm Chart" both do the same thing:
Basically the Ingress/Ingress Controller Concept, applied to Metrics/Prometheus Operator.
Both are a means of easily configuring, installing, and managing a huge distributed application (Kubernetes Prometheus Stack) on Kubernetes:**
What is the Entire Kube Prometheus Stack you ask? Prometheus, Grafana, AlertManager, CRDs (Custom Resource Definitions), Prometheus Operator(software bot app), IaC Alert Rules, IaC Grafana Dashboards, IaC ServiceMonitor CRDs (which auto-generate Prometheus Metric Collection Configuration and auto hot import it into Prometheus Server)
(Also when I say easily configuring I mean 1,000-10,000++ lines of easy for humans to understand config that generates and auto manage 10,000-100,000 lines of machine config + stuff with sensible defaults + monitoring configuration self-service, distributed configuration sharding with an operator/controller to combine config + generate verbose boilerplate machine-readable config from nice human-readable config.
If they achieve the same end goal, you might ask what's the difference between them?
https://github.com/coreos/kube-prometheus
https://github.com/helm/charts/tree/master/stable/prometheus-operator
Basically, CoreOS's kube-prometheus deploys the Prometheus Stack using Ksonnet.
Prometheus Operator Helm Chart wraps kube-prometheus / achieves the same end result but with Helm.
So which one to use?
Doesn't matter + they achieve the same end result + shouldn't be crazy difficult to start with 1 and switch to the other.
Helm tends to be faster to learn/develop basic mastery of.
Ksonnet is harder to learn/develop basic mastery of, but:
it's more idempotent (better for CICD automation) (but it's only a difference of 99% idempotent vs 99.99% idempotent.)
has built-in templating which means that if you have multiple clusters you need to manage / that you want to always keep consistent with each other. Then you can leverage ksonnet's templating to manage multiple instances of the Kube Prometheus Stack (for multiple envs) using a DRY code base with lots of code reuse. (If you only have a few envs and Prometheus doesn't need to change often it's not completely unreasonable to keep 4 helm values files in sync by hand. I've also seen Jinja2 templating used to template out helm values files, but if you're going to bother with that you may as well just consider ksonnet.)
Kubernetes operator are kubernetes specific application(pods) that configure, manage and optimize other Kubernetes deployments automatically. They are implemented as a custom controller.
According to official coreOS website:
Operators were introduced by CoreOS as a class of software that operates other software, putting operational knowledge collected by humans into software.
The prometheus operator provides the easy way to deploy configure and monitor your prometheus instances on kubernetes cluster. To do so, prometheus operator introduces three types of custom resource definition(CRD) in kubernetes.
Prometheus
Alertmanager
ServiceMonitor
Now, with the help of above CRD's, you can directly create a prometheus instance by providing kind: Prometheus and the prometheus instance is ready to serve, likewise you can do for AlertManager. Without this you would have to setup the deployment for prometheus with its image, configuration and many more things.
The Prometheus Operator serves to make running Prometheus on top of Kubernetes as easy as possible, while preserving Kubernetes-native configuration options.
Now, kube-prometheus implemented the prometheus operator and provides you minimum yaml files to create your basic setup of prometheus, alertmanager and grafana by running a single command.
git clone https://github.com/coreos/prometheus-operator.git
kubectl apply -f prometheus-operator/contrib/kube-prometheus/manifests/
By running above command in kube-prometheus directory, you will get a monitoring namespace which will have an instance of alertmanager, prometheus and grafana for UI. This is enough setup for most of the basic implementation and if you need any more specifics according to your application, you can add more yamls of exporter you need.
Kube-prometheus is more of a contribution to prometheus-operator project, which implements the prometheus operator functionality very well and provide you a complete monitoring setup for your kubernetes cluster. You can start with kube-prometheus and extend the functionality of your monitoring setup according to your application from there.
You can learn more about prometheus-operator here
As of today, 28-09-2020, this is the way to install Prometheus in a Kubernetes cluster
https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack#kube-prometheus-stack
According to official documentation, kube-prometheus-stack is a rename of prometheus-operator.
As I understood, kube-prometheus-stack also has preinstalled grafana dashboards and prometheus rules.
Note: This chart was formerly named prometheus-operator chart, now
renamed to more clearly reflect that it installs the kube-prometheus
project stack, within which Prometheus Operator is only one component.
Taken from https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack
Architecturally the container runs docker
The default container logs are managed by Docker, and the default log driver uses JSON-file
log-driver": "json-file
https://docs.docker.com/config/containers/logging/configure/
If the default jSON-file is used to manage container logs, log rotation is not performed by default. Therefore, the default JSON-file log driver the log files stored by the log driver can result in a large amount of disk space for containers that generate a large amount of output, which can cause disk space to run out.
In this case, save the log to ES, store it separately, and periodically delete the index using curator kubernetes
And run a scheduled task in K8S to delete the index periodically
Another solution for disk space is to periodically delete old logs from jSON-files
Typically we set the size and number of logs
This will set up a maximum of 10 log files, each with a maximum size of 20 Mb. Therefore, the container has a maximum of 200 Mb of logs
"log-driver": "json-file", "log-opts": { "max-size": "20m", "max-file": "10" },
Note: In general, the default Docker log is placed
/var/lib/docker/containers/
But in the same case kubernetes also saves logs and creates a directory structure to help you find pods-based logs, so you can find container logs for each Pod running on a node
/var/log/pods/<namespace>_<pod_name>_<pod_id>/<container_name>/
When removing pod, / var/lib/container under the docker/containers/log and k8s created under/var/log/pods/pod log will be deleted
For example, if the POD is restarted during production, the pod log will be deleted whether it is on the original node or jumped to another node
Therefore, this log needs to be saved in ES for centralized management. Many R&D projects will check the log for troubleshooting in most cases
I am using the Kubernetes Provider to describe services/pods in Terraform.
It can get confusing using the Hashicorp Configuration Language to define kubernetes_pod or kubernetes_service resources because the Kubernetes documentation describes everything in YAML which it means you need to translate it into HCL.
Is it possible to define pods as YAML and use them with kubernetes_pod and kubernetes_service resources as templates?
While Terraform normally uses HCL, this is a superset of JSON (much like YAML itself) so can also read JSON.
One possible option would be to take the YAML examples you already have and convert them into JSON and then use Terraform on those.
Unfortunately, that's unlikely to work because keywords are likely to be different for how Terraform is expecting things so you'd need to write something to do some basic translation of the input YAML to a Terraform resource JSON. At this point, it'd probably be worth just adding HCL output to the conversion so your outputted Terraform config is more readable if you ever intend to keep the Terraform config around instead of just one shot converting and applying the config.
The benefit of doing things this way would be that you have a reusable Kubernetes config that could be ran using kubectl or other tools but gives you the power of Terraform's lifecycle management, being able to plan changes and integration with non Kubernetes parts of your infrastructure (such as setting up instances to run the Kubernetes cluster on).
I've not used it much but I believe Kops will allow you to keep pod/service config in typical Kubernetes YAML files but can then use Terraform to manage the configuration and even allows you to output the Terraform configuration so you can run it outside of Kops itself.
The hashicorp/kubernetes provider does not support raw YAML/JSON, and they have no intention of implementing it.
The possible solutions are:
K2tf, a tool for converting Kubernetes RAW YAML manifests into Terraform HCL for the Kubernetes provider.
Use an alternative community Kubernetes provider, such as gavinbunny/kubectl, which does support raw YAML and can track each resource and the attributes in Terraform state, unlike the kubernetes-alpha provider.
Another solution is to use the hashicorp/kubernetes-alpha provider, you can pass in either a Terraform object or convert raw YAML manifest into a TF object for using in the provider resource. The downside is that the attributes are not tracked as individual objects and thus a change will cause the entire resource to be tainted.
Using the kubectl provider.
This core of this provider is the kubectl_manifest resource, allowing free-form yaml to be processed and applied against Kubernetes. This yaml object is then tracked and handles creation, updates and deleted seamlessly - including drift detection. This provider is ideal if you want to track the manifest in Terraform:
resource "kubectl_manifest" "test" {
yaml_body = file("path/to/manifest.yaml")
}
Using the kubernetes-alpha provider
The kubernetes_manifest represents one Kubernetes resource as described in the manifest attribute. The manifest value is the HCL transcription of a regular Kubernetes YAML manifest. To transcribe an existing manifest from YAML to HCL, use the Terrafrom built-in function yamldecode(), or use the tfk8s tool to convert YAML into manifest attributes for the kubernetes-alpha provider manifest resource.
Example using yamldecode:
resource "kubernetes_manifest" "service" {
provider = kubernetes-alpha
manifest = yamldecode(file("path/to/manifest.yaml"))
}
Why doesn't the kubernetes provider support RAW YAML?
Supporting YAML/JSON in hashicorp/kubernetes was considered before (the very first proposal of K8S provider was exactly that) and during the initial implementation of this provider and we decided not to do it.
The reason is that you can't accurately track resources created from RAW YAML as Terraform objects.
From Terraform's developer perspective it is very tricky to get around
the way K8S API works where you send an array [a, b, c] to the Create
API and then you Get back [a, b, c, d]. This happens for example with
pods that get some secret volumes attached automatically, but happens
with most other resources I had the chance to play with. The
whitelisting/blacklisting is tricky part.
You may also be interested in the following project, which allows you to convert YAML files to Terraform's HCL.
https://github.com/sl1pm4t/k2tf
Description:
A tool for converting Kubernetes API Objects (in YAML format) into HashiCorp's Terraform configuration language.
The converted .tf files are suitable for use with the Terraform Kubernetes Provider