Kubernetes liveness probe - kubernetes

How can I write kubernetes readiness probe for my spring boot application, which takes around 20 second to startup ? I tried to follow example from Configure Liveness, Readiness and Startup Probes, but I'm not sure how does Kubernetes figure out status code 200 as success
apiVersion: v1
kind: Pod
metadata:
labels:
app: backend
name: liveness-http
spec:
containers:
- name: liveness
image: k8s.gcr.io/liveness
args:
- /server
livenessProbe:
httpGet:
path: /healthz
port: 8080
httpHeaders:
- name: Custom-Header
value: Awesome
initialDelaySeconds: 3
periodSeconds: 3

Kubernetes kubelet will make a http request at /healthz path in your application and expects http status code 200 returned from that endpoint for the probe to be successful. So you need to have a rest endpoint in a rest controller which will return 200 from /healthz. An easy way to achieve it would be to include spring boot actuator dependency and change the liveness probe path to /actuator/health/liveness. Spring boot actuator by default comes with a rest controller endpoint which returns 200 from /actuator/health/liveness.
https://docs.spring.io/spring-boot/docs/current/reference/html/production-ready-features.html#production-ready-kubernetes-probes

initialDelaySeconds field tells the kubelet that it should wait 20 seconds before performing the first probe. So this is generally configured to the value/time that the container / pod takes to start.
Configure initialDelaySeconds: 20 with the value as 20 seconds.

K8 engine considers response code 200-399 as a successful probe. In your case you can add initial delay seconds for your probe to start with a delay of 20 seconds.

Related

Debugging slow Kubernetes deployment

We are using K8S in a managed Azure environment, Minikube in Ubuntu and a Rancher cluster built on on-prem machines and in general, our deployments take up to about 30 seconds to pull containers, run up and be ready. However, my latest attempt to create a deployment (on-prem) takes upwards of a minute and sometimes longer. It is a small web service which is very similar to our other deployments. The only (obvious) difference is the use of a startup probe and a liveness probe, although some of our other services do have probes, they are different though.
After removing Octopus deploy from the equation by extracting the yaml it was running and using kubectl, as soon as the (single) pod starts, I start reading the logs and as expected, the startup and liveness probes are called very quickly. Startup succeeds and the cluster starts calling the live probe, which also succeeds. However, if I use kubectl describe on the pod, it shows Initialized and PodScheduled as True but ContainersReady (there is one container) and Ready are both false for around a minute. I can't see what would cause this other than probe failures but these are logged as successful.
They eventually start and work OK but I don't know why they take so long.
kind: Deployment
apiVersion: apps/v1
metadata:
name: 'redirect-files-deployments-28775'
labels:
Octopus.Kubernetes.SelectionStrategyVersion: "SelectionStrategyVersion2"
OtherOctopusLabels
spec:
replicas: 1
selector:
matchLabels:
Octopus.Kubernetes.DeploymentName: 'redirect-files-deployments-28775'
template:
metadata:
labels:
Octopus.Kubernetes.SelectionStrategyVersion: "SelectionStrategyVersion2"
OtherOctopusLabels
spec:
containers:
- name: redirect-files
image: ourregistry.azurecr.io/microservices.redirectfiles:1.0.34
ports:
- name: http
containerPort: 80
protocol: TCP
env:
- removed connection strings etc
livenessProbe:
httpGet:
path: /api/version
port: 80
scheme: HTTP
successThreshold: 1
startupProbe:
httpGet:
path: /healthcheck
port: 80
scheme: HTTP
httpHeaders:
- name: X-SS-Authorisation
value: asdkjlkwe098sad0akkrweklkrew
initialDelaySeconds: 5
timeoutSeconds: 5
imagePullSecrets:
- name: octopus-feedcred-feeds-azure-container-registry
So the cause was the startup and/or liveness probes. When I removed them, the deployment time went from over a minute to 18 seconds, despite the logs proving that the probes were called successfully very quickly after containers were started.
At least I now have something more concrete to look for.

K8S Pod with startupProbe and initialDelaySeconds specified waits too long to become Ready

I have been trying to debug a very odd delay in my K8S deployments. I have tracked it down to the simple reproduction below. What it appears is that if I set an initialDelaySeconds on a startup probe or leave it 0 and have a single failure, then the probe doesn't get run again for a while and ends up with atleast a 1-1.5 minute delay getting into Ready:true state.
I am running locally with Ubutunu 18.04 and microk8s v1.19.3 with the following versions:
kubelet: v1.19.3-34+a56971609ff35a
kube-proxy: v1.19.3-34+a56971609ff35a
containerd://1.3.7
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: microbot
name: microbot
spec:
replicas: 1
selector:
matchLabels:
app: microbot
strategy: {}
template:
metadata:
labels:
app: microbot
spec:
containers:
- image: cdkbot/microbot-amd64
name: microbot
command: ["/bin/sh"]
args: ["-c", "sleep 3; /start_nginx.sh"]
#args: ["-c", "/start_nginx.sh"]
ports:
- containerPort: 80
startupProbe:
httpGet:
path: /
port: 80
initialDelaySeconds: 0 # 5 also has same issue
periodSeconds: 1
failureThreshold: 10
successThreshold: 1
##livenessProbe:
## httpGet:
## path: /
## port: 80
## initialDelaySeconds: 0
## periodSeconds: 10
## failureThreshold: 1
resources: {}
restartPolicy: Always
serviceAccountName: ""
status: {}
---
apiVersion: v1
kind: Service
metadata:
name: microbot
labels:
app: microbot
spec:
ports:
- port: 80
protocol: TCP
targetPort: 80
selector:
app: microbot
The issue is that if I have any delay in the startupProbe or if there is an initial failure, the pod gets into Initialized:true state but had Ready:False and ContainersReady:False. It will not change from this state for 1-1.5 minutes. I haven't found a pattern to the settings.
I left in the comment out settings as well so you can see what I am trying to get to here. What I have is a container starting up that has a service that will take a few seconds to get started. I want to tell the startupProbe to wait a little bit and then check every second to see if we are ready to go. The configuration seems to work, but there is a baked in delay that I can't track down. Even after the startup probe is passing, it does not transition the pod to Ready for more than a minute.
Is there some setting elsewhere in k8s that is delaying the amount of time before a Pod can move into Ready if it isn't Ready initially?
Any ideas are greatly appreciated.
Actually I made a mistake in comments, you can use initialDelaySeconds in startupProbe, but you should rather use failureThreshold and periodSeconds instead.
As mentioned here
Kubernetes Probes
Kubernetes supports readiness and liveness probes for versions ≤ 1.15. Startup probes were added in 1.16 as an alpha feature and graduated to beta in 1.18 (WARNING: 1.16 deprecated several Kubernetes APIs. Use this migration guide to check for compatibility).
All the probe have the following parameters:
initialDelaySeconds : number of seconds to wait before initiating
liveness or readiness probes
periodSeconds: how often to check the probe
timeoutSeconds: number of seconds before marking the probe as timing
out (failing the health check)
successThreshold : minimum number of consecutive successful checks
for the probe to pass
failureThreshold : number of retries before marking the probe as
failed. For liveness probes, this will lead to the pod restarting.
For readiness probes, this will mark the pod as unready.
So why should you use failureThreshold and periodSeconds?
consider an application where it occasionally needs to download large amounts of data or do an expensive operation at the start of the process. Since initialDelaySeconds is a static number, we are forced to always take the worst-case scenario (or extend the failureThreshold that may affect long-running behavior) and wait for a long time even when that application does not need to carry out long-running initialization steps. With startup probes, we can instead configure failureThreshold and periodSeconds to model this uncertainty better. For example, setting failureThreshold to 15 and periodSeconds to 5 means the application will get 15 (fifteen) x 5 (five) = 75s to startup before it fails.
Additionally if you need more informations take a look at this article on medium.
Quoted from kubernetes documentation about Protect slow starting containers with startup probes
Sometimes, you have to deal with legacy applications that might require an additional startup time on their first initialization. In such cases, it can be tricky to set up liveness probe parameters without compromising the fast response to deadlocks that motivated such a probe. The trick is to set up a startup probe with the same command, HTTP or TCP check, with a failureThreshold * periodSeconds long enough to cover the worse case startup time.
So, the previous example would become:
ports:
- name: liveness-port
containerPort: 8080
hostPort: 8080
livenessProbe:
httpGet:
path: /healthz
port: liveness-port
failureThreshold: 1
periodSeconds: 10
startupProbe:
httpGet:
path: /healthz
port: liveness-port
failureThreshold: 30
periodSeconds: 10
Thanks to the startup probe, the application will have a maximum of 5 minutes (30 * 10 = 300s) to finish its startup. Once the startup probe has succeeded once, the liveness probe takes over to provide a fast response to container deadlocks. If the startup probe never succeeds, the container is killed after 300s and subject to the pod's restartPolicy.

Fake liveness/readiness probe in kubernetes

Is it possible to fake a container to always be ready/live in kubernetes so that kubernetes thinks that the container is live and doesn't try to kill/recreate the container? I am looking for a quick and hacky solution, preferably.
Liveness and Readiness probes are not required by k8s controllers, you can simply remove them and your containers will be always live/ready.
If you want the hacky approach anyways, use the exec probe (instead of httpGet) with something dummy that always returns 0 as exit code. For example:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
labels:
app: nginx
spec:
replicas: 1
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80
livenessProbe:
exec:
command:
- touch
- /tmp/healthy
readinessProbe:
exec:
command:
- touch
- /tmp/healthy
I'd like to add background contextual information about why
/ how this can be useful to real world applications.
Also by pointing out some additional info about why this question is useful I can come up with an even better answer.
First off why might you want to implement a fake startup / readiness / liveness probe?
Let's say you have a custom containerized application, you're in a rush so you go live without any liveness or readiness probes.
Scenario 1:
You have a deployment with 1 replica, but you notice that whenever you go to update your app (push a new version via a rolling update), your monitoring platform reports occasionally 400, 500, and timeout errors during the rolling update. Post update you're at 1 replica and the errors go away.
Scenario 2:
You have enough traffic to warrant autoscaling and multiple replicas. You consistently get 1-3% errors, and 97% success.
Why are you getting errors in both scenarios?
Let's say it takes 1 minute to finish booting up / be ready to receive traffic. If you don't have readiness probes then newly spawned instances of your container will receive traffic before they've finished booting up / become ready to receive traffic. So the newly spawned instances are probably causing temporary 400, 500, and timeout errors.
How to fix:
You can fix the occasional errors in Scenario 1 and 2 by adding a readiness probe with an initialDelaySeconds (or startup probe), basically something that waits long enough for your container app to finish booting up.
Now the correct and proper best practice thing to do is to write a /health endpoint that properly reflects the health of your app. But writing an accurate healthcheck endpoint can take time. In many cases you can get the same end result (make the errors go away), without the effort of creating a /health endpoint by faking it, and just adding a wait period that waits for your app to finish booting up before sending traffic to it. (again /health is best practice, but for the ain't nobody got time for that crowd, faking it can be a good enough stop gap solution)
Below is a better version of a fake readiness probe:
Also here's why it's better
exec based liveness probes don't work in 100% of cases, they assume shell exists on the container, and that commands exist on the container. There's scenarios where hardened containers don't have things like a shell or touch command.
httpGet, tcpSocket, and grcp liveness probes are done from the perspective of the node running kubelet (the kubernetes agent) so they don't depend on the software installed in the container and should work in on hardened containers that are missing things like touch command or even scratch container. (In other words this soln should work in 100% of cases vs 99% of the time)
An alternative to startup probe is to use initialDelaySeconds with a readiness Probe, but that creates unnecessary traffic compared to a startup probe that runs once. (Again this isn't the best solution in terms of accuracy/fastest possible startup time, but often a good enough solution that's very practical.)
Run my example in a cluster and you'll see it's not ready for 60 seconds, then becomes ready after 60 seconds.
Since this is a fake probe it's pointless to use readiness/liveness probe, just go with startup probe as that will cut down on unnecessary traffic.
In the absence of a readiness probe the startup probe will have the effect of a readiness probe (block it from being ready until the probe passes, but only during initial start up)
apiVersion: apps/v1
kind: Deployment
metadata:
name: useful-hack
labels:
app: always-true-tcp-probe
spec:
replicas: 1
strategy:
type: Recreate #dev env fast feedback loop optimized value, don't use in prod
selector:
matchLabels:
app: always-true-tcp-probe
template:
metadata:
labels:
app: always-true-tcp-probe
spec:
containers:
- name: nginx
image: nginx:1.7.9
startupProbe:
tcpSocket:
host: 127.0.0.1 #Since kubelet does the probes, this is node's localhost, not pod's localhost
port: 10250 #worker node kubelet listening port
successThreshold: 1
failureThreshold: 2
initialDelaySeconds: 60 #wait 60 sec before starting the probe
Additional Notes:
The above example keeps traffic within the LAN this has several benefits.
It'll work in internet disconnected environments.
It won't incur egress network charges
The below example will only work for internet connected environments and isn't too bad for a startup probe, but would be a bad idea for a readiness / liveness probe as it could clog the NAT GW bandwidth, I'm only including it to point out something of interest.
startupProbe:
httpGet:
host: google.com #default's to pod IP
path: /
port: 80
scheme: HTTP
successThreshold: 1
failureThreshold: 2
initialDelaySeconds: 60
---
startupProbe:
tcpSocket:
host: 1.1.1.1 #CloudFlare
port: 53 #DNS
successThreshold: 1
failureThreshold: 2
initialDelaySeconds: 60
The interesting bit:
Remember I said "httpGet, tcpSocket, and grcp liveness probes are done from the perspective of the node running kubelet (the kubernetes agent)." Kubelet runs on the worker node's host OS, which is configured for upstream DNS, in other words it doesn't have access to inner cluster DNS entries that kubedns is aware of. So you can't specify Kubernetes service names in these probes.
Additionally Kubernetes Service IPs won't work for the probes either since they're VIPs (Virtual IPs) that only* exist in iptables (*most cases).

20 percent of requests timeout when a node crashing in k8s. How to solve this?

I was testing my kubernetes services recently. And I found it's very unreliable. Here are the situation:
1. The test service 'A' which receives HTTP requests at port 80 has five pods deployed on three nodes.
2. An nginx ingress was set to route traffic outside onto the service 'A'.
3. The ingress was set like this:
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: test-A
annotations:
nginx.ingress.kubernetes.io/proxy-connect-timeout: "1s"
nginx.ingress.kubernetes.io/proxy-next-upstream: "error timeout invalid_header http_502 http_503 http_504"
nginx.ingress.kubernetes.io/proxy-next-upstream-tries: "2"
spec:
rules:
- host: <test-url>
http:
paths:
- path: /
backend:
serviceName: A
servicePort: 80
http_load was started on an client host and kept sending request to the ingress nginx at a speed of 1000 per-seconds. All the request were routed to the service 'A' in k8s and eveything goes well.
When I restarted one of the nodes manually, things went wrong:
In the next 3 minutes, about 20% requests were timeout, which is unacceptable in product environment.
I don't know why k8s reacts so slow and is there a way to solve this problem?
You can speed up that fail-over process by configuring liveness and readiness probes in the pods' spec:
Container probes
...
livenessProbe: Indicates whether the Container is running. If the liveness probe fails, the kubelet kills the Container, and the Container is subjected to its restart policy. If a Container does not provide a liveness probe, the default state is Success.
readinessProbe: Indicates whether the Container is ready to service requests. If the readiness probe fails, the endpoints controller removes the Pod’s IP address from the endpoints of all Services that match the Pod. The default state of readiness before the initial delay is Failure. If a Container does not provide a readiness probe, the default state is Success.
Liveness probe example:
apiVersion: v1
kind: Pod
metadata:
labels:
test: liveness
name: liveness-exec
spec:
containers:
- name: liveness
image: k8s.gcr.io/busybox
args:
- /bin/sh
- -c
- touch /tmp/healthy; sleep 30; rm -rf /tmp/healthy; sleep 600
livenessProbe:
exec:
command:
- cat
- /tmp/healthy
initialDelaySeconds: 5
periodSeconds: 5
Thanks for #VAS's answer!
Liveness probe is a way to solve this problem.
But I finally figured out that what I want was passive health check, which the k8s dosen't surpport.
And I solved this problem by introducing istio into my cluster.

What is the http url to get readiness and liveness probes of service instances from kubernetes

I searched for 'readi', 'ready', 'live' etc in the kub swagger. I only see
io.k8s.api.core.v1.PodReadinessGate
thank you
That's one thing you would define. For example the following yaml file:
apiVersion: v1
kind: Pod
metadata:
name: nginx
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx
ports:
- containerPort: 80
livenessProbe: #this block performs liveness probes
httpGet:
path: /healthz
port: 80
readinessProbe: #this block performs readiness probes
httpGet:
path: /
port: 80
So, a pod with nginx. I can simply add the blocks highlighted in the yaml file and there it is. kubelet will check on them. Of course you have to have something serving there (/healthz, in this example), otherwise you will get 404.
You can add some configuration to the probes, like the other answer suggests. There are some more options than those.
According to Configure Liveness and Readiness Probes services can be configured to use
liveness command
TCP liveness probe
liveness HTTP request
So if your service use HTTP requests for liveness and readiness you can see in pod definition section livenessProbe (same for readinessProbe)
livenessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 3
periodSeconds: 3
See full example here
There is no way to check the state of Liveness and Readiness probes directly.
You can check the resulting state of the pod which reflects changes in the state of Liveness and Readiness probes, but with some delay caused by threshold values.
Using kubectl describe pod you can also see some events at the bottom, but you can only see them after they occur. You can’t have it as a reply to the request.
You can also look into REST requests that are running under the hood of kubectl commands. All you need to do is adding a verbose flag to kubectl command:
-v, --v=0: Set the level of log output to debug-level (0~4) or trace-level (5~10)