OCI Basics – Putting Data into Object Storage OCI

The Object Storage service provides reliable, secure, and scalable object storage. Object storage is a storage architecture that stores and manages data as objects. Some typical use cases include data backup, file sharing, and storing unstructured data like logs and sensor-generated data.

Creating a Bucket

  1. Open the navigation menu and click Storage. Under Object Storage, click Buckets.A list of the buckets in the compartment you’re viewing is displayed.
  2. Select a compartment from the Compartment list on the left side of the page.A list of existing buckets is displayed.
  3. Click Create Bucket.
    • Bucket Name
    • Default Storage Tier: Select the default tier in which you want to store your data
      • Standard is the primary, default storage tier Use the Standard tier for storing frequently accessed data that requires fast and immediate access.
      • Archive is the default storage tier used for archive storage, Use the Archive tier for storing rarely accessed data that requires long retention periods. Access to data in the Archive tier is not immediate. Archived data must be restored before the data is accessible.
      • Object Events: Select Emit Object Events if you want to enable the bucket to emit events for object state changes. For more information about events.
      • Encryption: Buckets are encrypted with keys managed by Oracle by default, but you can optionally encrypt the data in this bucket using your own Vault encryption key. To use Vault for your encryption needs, select Encrypt Using Customer-Managed Keys

Uploading Files to a Bucket

To upload files to your bucket using the Console:

  1. From the Object Storage Buckets screen, click the bucket name to view its details.
  2. Click Upload.
  3. In the Object Name Prefix field, optionally specify a file name prefix for the files that you plan to upload.
  4. If the Storage Tier field displays Standard, you can optionally change the storage tier to upload objects to.

Cheers

Osama

Launching Windows Instance on OCI

In this post  I will show you how to launch and connect to a Windows instance.

  • Create a cloud network and subnet that enables internet access
  • Launch an instance
  • Connect to the instance
  • Add and attach a block volume

I already posted a post how to Launch Linux Instance on OCI here, in the post you will have to follow the first two steps which is creating

  • Choose a compartment for your resources.
  • Create a cloud network.

Once you are done, you can start with steps #3 which will allow you to launch a instance – windows one.

  1. Open the navigation menu and click Compute. Under Compute, click Instances.
  2. Click Create instance.
  3. In the Placement section, accept the default Availability domain.
  4. In the Image and shape section, do the following:
    • In the Image source list, select Platform images.
    • Select Windows. Then, in the OS version list, select Server 2019 Standard.
    • Review and accept the terms of use, and then click Select image.
  5. In the Shape section, click Change Shape. Then, do the following:
    • For Instance type, accept the default, Virtual machine.
    • For Shape series, select AMD, and then choose either the VM.Standard.E4.Flex shape or the VM.Standard.E3.Flex shape (it doesn’t matter which). Accept the default values for OCPUs and memory.
    • The shape defines the number of CPUs and amount of memory allocated to the instance.
  6. In the Networking section, configure the network details for the instance. Do not accept the defaults.
    • For Primary network, leave Select existing virtual cloud network selected.
    • Select the cloud network that you created. If necessary, click Change Compartment to switch to the compartment containing the cloud network that you created.
  7. In the Boot volume section, leave all the options cleared.

Your instance now is ready.

Connect to the windows instance done by using Remote desktop, enter the public ip, username which is (opc), and the password.

Cheers

Osama

Using PersistentVolumes in Kubernetes

PersistentVolumes provide a way to treat storage as a dynamic resource in Kubernetes. This lab will allow you to demonstrate your knowledge of PersistentVolumes. You will mount some persistent storage to a container using a PersistentVolume and a PersistentVolumeClaim.

Create a custom Storage Class by using “`vi localdisk.yml`.

apiVersion: storage.k8s.io/v1 
kind: StorageClass 
metadata: 
  name: localdisk 
provisioner: kubernetes.io/no-provisioner
allowVolumeExpansion: true

Finish creating the Storage Class by using kubectl create -f localdisk.yml.
Create the PersistentVolume by using vi host-pv.yml.

kind: PersistentVolume 
apiVersion: v1 
metadata: 
   name: host-pv 
spec: 
   storageClassName: localdisk
   persistentVolumeReclaimPolicy: Recycle 
   capacity: 
      storage: 1Gi 
   accessModes: 
      - ReadWriteOnce 
   hostPath: 
      path: /var/output

Finish creating the PersistentVolume by using kubectl create -f host-pv.yml.

Check the status of the PersistenVolume by using kubectl get pv

Create a PersistentVolumeClaim

Start creating a PersistentVolumeClaim for the PersistentVolume to bind to by using vi host-pvc.yml.

apiVersion: v1 
kind: PersistentVolumeClaim 
metadata: 
   name: host-pvc 
spec: 
   storageClassName: localdisk 
   accessModes: 
      - ReadWriteOnce 
   resources: 
      requests: 
         storage: 100Mi

Finish creating the PersistentVolumeClaim by using kubectl create -f host-pvc.yml.

Check the status of the PersistentVolume and PersistentVolumeClaim to verify that they have been bound:

kubectl get pv
kubectl get pvc

Create a Pod That Uses a PersistentVolume for Storage

Create a Pod that uses the PersistentVolumeClaim by using vi pv-pod.yml.

apiVersion: v1 
kind: Pod 
metadata: 
   name: pv-pod 
spec: 
   containers: 
      - name: busybox 
        image: busybox 
        command: ['sh', '-c', 'while true; do echo Success! > /output/success.txt; sleep 5; done'] 

Mount the PersistentVolume to the /output location by adding the following, which should be level with the containers spec in terms of indentation:

volumes: 
 - name: pv-storage 
   persistentVolumeClaim: 
      claimName: host-pvc

In the containers spec, below the command, set the list of volume mounts by using:

volumeMounts: 
- name: pv-storage 
  mountPath: /output 

Finish creating the Pod by using kubectl create -f pv-pod.yml.

Check that the Pod is up and running by using kubectl get pods.

If you wish, you can log in to the worker node and verify the output data by using cat /var/output/success.txt.

Managing Container Storage with Kubernetes Volumes

Kubernetes volumes offer a simple way to mount external storage to containers. This lab will test your knowledge of volumes as you provide storage to some containers according to a provided specification. This will allow you to practice what you know about using Kubernetes volumes.

Create a Pod That Outputs Data to the Host Using a Volume

  • Create a Pod that will interact with the host file system by using vi maintenance-pod.yml.
apiVersion: v1
kind: Pod
metadata:
    name: maintenance-pod
spec:
    containers:
    - name: busybox
      image: busybox
      command: ['sh', '-c', 'while true; do echo Success! >> /output/output.txt; sleep 5; done']
  • Under the basic YAML, begin creating volumes, which should be level with the containers spec:
volumes:
- name: output-vol
  hostPath:
      path: /var/data
  • In the containers spec of the basic YAML, add a line for volume mounts:
volumeMounts:
- name: output-vol
  mountPath: /output

The complete YAML will be

apiVersion: v1
kind: Pod
metadata:
    name: maintenance-pod
spec:
  containers:
    - name: busybox
      image: busybox
      command: ['sh', '-c', 'while true; do echo Success! >> /output/output.txt; sleep 5; done']
      volumeMounts:
      - name: output-vol
        mountPath: /output
  volumes:
   - name: output-vol
     hostPath:
      path: /var/data

Create a Multi-Container Pod That Shares Data Between Containers Using a Volume

  1. Create another YAML file for a shared-data multi-container Pod by using vi shared-data-pod.yml
  2. Start with the basic Pod definition and add multiple containers, where the first container will write the output.txt file and the second container will read the output.txt file:
apiVersion: v1
kind: Pod
metadata:
    name: shared-data-pod
spec:
    containers:
    - name: busybox1
      image: busybox
      command: ['sh', '-c', 'while true; do echo Success! >> /output/output.txt; sleep 5; done']
    - name: busybox2
      image: busybox
      command: ['sh', '-c', 'while true; do cat /input/output.txt; sleep 5; done']

Set up the volumes, again at the same level as containers with an emptyDir volume that only exists to share data between two containers in a simple way:

volumes:
- name: shared-vol
  emptyDir: {}

Mount that volume between the two containers by adding the following lines under command for the busybox1 container:

volumeMounts:
- name: shared-vol
  mountPath: /output

For the busybox2 container, add the following lines to mount the same volume under command to complete creating the shared file:

volumeMounts:
- name: shared-vol
  mountPath: /input

The complete file

Finish creating the multi-container Pod using kubectl create -f shared-data-pod.yml.

apiVersion: v1
kind: Pod
metadata:
    name: shared-data-pod
spec:
    containers:
    - name: busybox1
      image: busybox
      command: ['sh', '-c', 'while true; do echo Success! >> /output/output.txt; sleep 5; done']
      volumeMounts:
        - name: shared-vol
          mountPath: /output
    - name: busybox2
      image: busybox
      command: ['sh', '-c', 'while true; do cat /input/output.txt; sleep 5; done']
      volumeMounts:
        - name: shared-vol
          mountPath: /input
    volumes:
    - name: shared-vol
    emptyDir: {}

And you can now apply the YAML file.

Cheers

Osama

Upgrade k8s using kubeadm

First, upgrade the control plane node

Drain the control plane node.

kubectl drain master-node-name --ignore-daemonsets

Upgrade kubeadm.

sudo apt-get update && \
sudo apt-get install -y --allow-change-held-packages kubeadm=version

kubeadm version

Plan the upgrade.

sudo kubeadm upgrade plan v-version (for example v1.24.2)

Upgrade the control plane components.

sudo kubeadm upgrade apply v1.22.2

Upgrade kubelet and kubectl on the control plane node.

sudo apt-get update && \
sudo apt-get install -y --allow-change-held-packages kubelet=version kubectl=version 

Restart kubelet.

sudo systemctl daemon-reload
sudo systemctl restart kubelet

Uncordon the control plane node.

kubectl uncordon master-node-name

Verify that the control plane is working

Note:- you should not perform upgrades on all worker nodes at the same time. Make sure enough nodes are available at any given time to provide uninterrupted service.

Worker nodes

Run the following on the control plane node to drain worker node 1:

kubectl drain worker1-node-name --ignore-daemonsets --force

Log in to the first worker node, then Upgrade kubeadm.

sudo apt-get update && \ sudo apt-get install -y --allow-change-held-packages kubeadm=version

Upgrade the kubelet configuration on the worker node.

sudo kubeadm upgrade node

Upgrade kubelet and kubectl on the worker node.

sudo apt-get update && \ sudo apt-get install -y --allow-change-held-packages kubelet=version kubectl=verion

Restart kubelet.

sudo systemctl daemon-reload 
sudo systemctl restart kubelet

From the control plane node, uncordon worker node 1.

kubectl uncordon worker1-node-name

Repeat the upgrade process for worker nodes.

Cheers

Osama

Install k8s as one control plane and one worker node

The first thing you will need to do which is configure the two servers, either you can choose one of the following options:-

  • VMWARE
  • Cloud

Master Node Setup

Step #1

Create configuration file for containerd:

cat <<EOF | sudo tee /etc/modules-load.d/containerd.conf
overlay
br_netfilter
EOF

After the above step, you need to load the modules.

sudo modprobe overlay
sudo modprobe br_netfilter

Step #2

Set system configurations for Kubernetes networking

cat <<EOF | sudo tee /etc/sysctl.d/99-kubernetes-cri.conf
net.bridge.bridge-nf-call-iptables = 1
net.ipv4.ip_forward = 1
net.bridge.bridge-nf-call-ip6tables = 1
EOF

Apply new settings

sudo sysctl --system

Step #3

Install Containerd

sudo apt-get update && sudo apt-get install -y containerd

Step #4

Create default configuration file for containerd

sudo mkdir -p /etc/containerd

Generate default containerd configuration and save to the newly created default file

sudo containerd config default | sudo tee /etc/containerd/config.toml

Load the new configuration

sudo systemctl restart containerd
sudo systemctl status containerd

Step #5

Disable Swap

sudo swapoff -a

Step #6

Install dependency packages:

sudo apt-get update && sudo apt-get install -y apt-transport-https curl

Download and add GPG key

curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -

Add Kubernetes to repository list

cat <<EOF | sudo tee /etc/apt/sources.list.d/kubernetes.list
deb https://apt.kubernetes.io/ kubernetes-xenial main
EOF

sudo apt-get update

Step #6

Install Kubernetes packages (Note: If you get a dpkg lock message, just wait a minute or two before trying the command again):

sudo apt-get install -y kubelet=1.24.0-00 kubeadm=1.24.0-00 kubectl=1.24.0-00

Just in case Turn off automatic updates

sudo apt-mark hold kubelet kubeadm kubectl

The above steps should be done on the worker node even if you have 3 or 4.

Initialize the Cluster

Initialize the Kubernetes cluster on the control plane node using kubeadm (Note: This is only performed on the Control Plane Node):

sudo kubeadm init --pod-network-cidr 192.168.0.0/16 --kubernetes-version 1.24.0

Set kubectl access:

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config

You can test your cluster by run

kubectl get nodes

Install the Calico Network Add-On

On the control plane node, install Calico Networking

kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml

Check status of the control plane node:

kubectl get nodes

Join the Worker Nodes to the Cluster

In the control plane node, create the token and copy the kubeadm join command (NOTE:The join command can also be found in the output from kubeadm init command):

kubeadm token create --print-join-command

Copy the output

Worker node Setup.

from the above command of Kubeadm join run it using sudo command.

In the control plane node, view cluster status (Note: You may have to wait a few moments to allow all nodes to become ready)

kubectl get nodes

Cheers

Enjoy the DevOps

AUSOUG

The Australian Oracle User Group, AUSOUG, have a focus on bringing together our Oracle community and servicing their core technical, development and applications needs. A balanced program is aimed at all levels of skill and experience within a forum of User led independent knowledge sharing.

Register here

I will be speaking about Kubernetes in Depth But in simple way

Regards

Osama

Another year – Top 100 Oracle Blogs and Website

The best Oracle blogs from thousands of blogs on the web ranked by traffic, social media followers, domain authority & freshness.

Happy to share that my blog has been choosen for another year as the Top 100 Blogs around the world, the list contains talened, experience and professional people 🎉🎉🎉

Thank you all for the support.

Cheers

Osama

Deployment strategies

All-at-once

All-at-once deployments instantly shift traffic from the original (old) Lambda function to the updated (new) Lambda function, all at one time. All-at-once deployments can be beneficial when the speed of your deployments matters. In this strategy, the new version of your code is released quickly, and all your users get to access it immediately.

Canary

A linear deployment is similar to canary deployment. In this strategy, you direct a small amount of traffic to

In a canary deployment, you deploy your new version of your application code and shift a small percentage of production traffic to point to that new version. After you have validated that this version is safe and not causing errors, you direct all traffic to the new version of your code.

Linear

A linear deployment is similar to canary deployment. In this strategy, you direct a small amount of traffic to your new version of code at first. After a specified period of time, you automatically increment the amount of traffic that you send to the new version until you’re sending 100% of production traffic.

Comparing deployment strategies

To help you decide which deployment strategy to use for your application, you’ll need to consider each option’s consumer impact, rollback, event model factors, and deployment speed. The comparison table below illustrates these points.

DeploymentConsumer ImpactRollbackEvent Model FactorsDeployment Speed
All-at-onceAll at onceRedeploy older versionAny event model at low concurrency rateImmediate 
Canary/
Linear
1-10% typical initial traffic shift, then phased Revert 100% of traffic to previous deploymentBetter for high-concurrency workloadsMinutes to hours

Deployment preferences with AWS SAM

Traffic shifting with aliases is directly integrated into AWS SAM. If you’d like to use all-at-once, canary, or linear deployments with your Lambda functions, you can embed that directly into your AWS SAM templates. You can do this in the deployment preferences section of the template. AWS CodeDeploy uses the deployment preferences section to manage the function rollout as part of the AWS CloudFormation stack update. SAM has several pre-built deployment preferences you can use to deploy your code. See the table below for examples. 

Deployment Preferences TypeDescription
Canary10Percent30MinutesShifts 10 percent of traffic in the first increment. The remaining 90 percent is deployed 30 minutes later.
Canary10Percent5MinutesShifts 10 percent of traffic in the first increment. The remaining 90 percent is deployed 5 minutes later.
Canary10Percent10MinutesShifts 10 percent of traffic in the first increment. The remaining 90 percent is deployed 10 minutes later.
Canary10Percent15MinutesShifts 10 percent of traffic in the first increment. The remaining 90 percent is deployed 15 minutes later.
Linear10PercentEvery10MinutesShifts 10 percent of traffic every 10 minutes until all traffic is shifted.
Linear10PercentEvery1MinuteShifts 10 percent of traffic every minute until all traffic is shifted.
Linear10PercentEvery2MinutesShifts 10 percent of traffic every 2 minutes until all traffic is shifted.
Linear10PercentEvery3MinutesShifts 10 percent of traffic every 3 minutes until all traffic is shifted.
AllAtOnceShifts all traffic to the updated Lambda functions at once.

Creating a deployment pipeline

When you check a piece of code into source control, you don’t want to wait for a human to manually approve it or have each piece of code run through different quality checks. Using a CI/CD pipeline can help automate the steps required to release your software deployment and standardize on a core set of quality checks.

Reference

Redeploy and roll back a deployment with CodeDeploy

What is AWS Lambda?

Cheers

Osama