DISCLAIMER : Please note that blog owner takes no responsibility of any kind for any type of data loss or damage by trying any of the command/method mentioned in this blog. You may use the commands/method/scripts on your own responsibility.If you find something useful, a comment would be appreciated to let other viewers also know that the solution/method work(ed) for you.

How to start your career in DevOps and Cloud ?



Are you new to DevOps & Cloud?

Do you want to pursue a career as a DevOps/Cloud Engineer ?

Then start learning the below tools with good practice.

OS: Linux (Rhel/Ubuntu)
Cloud: Start with AWS, learn & practice it well then move to other clouds like Azure & Google Cloud. Openstack is Optional
Programming/scripting: Bash/python/Groovy/Powershell
Infrastructure Orchestration: Terraform
Configuration Management: Ansible/Chef/Puppet - Ansible is good to begin with
Containers: Docker
Container Orchestration :Kubernetes
CI/CD: Jenkins
Repository: Github/Bitbucket/Git
DataStore: Sql (postgress) & nosql (Mongodb/Redis)

Last but not least learn apache/tomcat, Nginx.

Learning above tools/technologies will transition you to DevOps/Cloud profile.
However, we must keep updating our skills and catchup with latest technologies..

If you have any Suggestions/Questions/Comments, feel free to share in the below comment section.

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Introduction to kubernetes - k8s

For a new learner, Kubernetes (commonly referred to as K8s) can be a steep learning curve. This article covers a brief conceptual overview to kickstart your journey.



Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.

The name Kubernetes originates from Greek, meaning helmsman or pilot. Google open-sourced the Kubernetes project in 2014. Kubernetes combines over 15 years of Google's experience running production workloads at scale with best-of-breed ideas and practices from the community.

Kubernetes Cluster

A Kubernetes cluster has two components:

1. master nodes which run the Kubernetes related daemons (Kube API, Kube proxy, Kube DNS, Kube dashboard,)
2. Cluster nodes belonging to one or more node pools which serve as the underlying physical resources for all the containers.

Node pools

A homogenous set of physical resources that provide the underlying resources for the cluster. A cluster can have one or more instance groups with labels to provide information to the Kubernetes scheduler on what can be run on the provided hardware.

Containers

A container is a resource running a single image (generally a docker image) containing all executable packages, runtime, operating system, system libraries. This is analogous to docker containers used by other orchestration tools.

Pod

Pods are the smallest deployable units of computing that can be created and managed in Kubernetes. A pod is a set of one or more containers deployed and run together, sharing the same local network space. The recommendation is to run one container on a pod so that you can atomically control a process at a Kubernetes level but multi-container pods are not uncommon.

ReplicaSet

A ReplicaSet ensures that a specified number of pod replicas are running at any time. In other words, a ReplicaSet makes sure that a pod or a homogeneous set of pods is always up and available.

Deployment

A Deployment controller provides a declarative wrapper on top of replica sets defining the templates used to build the homogenous pods and the replication number. Even if you need to just run one container instance of a particular service, it is recommended to create a deployment for it with a configuration of 1 replica.

Horizontal Pod Scaler

With Horizontal Pod Autoscaling, Kubernetes automatically scales the number of pods in a replication controller, deployment, or replica set based on observed CPU utilization (or, with custom metrics support, on some other application-provided metrics).

Daemonset

A DaemonSet ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the cluster, Pods are added to them. As nodes are removed from the cluster, those Pods are garbage collected. Deleting a DaemonSet will clean up the Pods it created.

Some typical uses of a DaemonSet are:
  1. running a cluster storage daemon, such as glusterd, ceph, on each node.
  2. running a logs collection daemon on every node, such as fluentd or logstash.

StatefulSets

  1. Used to manage stateful applications.
  2. Provides guarantees about the ordering and uniqueness of these Pods
  3. StatefulSet maintains a sticky identity for each of their Pods
  4. Used typically for cases where predictability of deletion and creation order is important.

Service

A Service is an abstraction that defines a logical set of Pods and a policy by which to access them — sometimes called a micro-service. So if a deployment from the previous step exposed a web service through a port, then a service is how you would expose the deployment.

A service can be exposed outside using a load balancer or a cluster IP that is reachable from within the K8s cluster. The load balancer is a cloud-native LB like ELB in AWS. The cluster IP is a virtually routable IP.

Additionally, Kubernetes also gives each service a routable A record of the form $service-name.$namespace.svc.cluster.local

Configmap

Every K8s cluster can have one or more config maps. A configmap is a key-value store that is that can be made available to each container as part of the environment variables.

Network Topology


Every Kubernetes cluster satisfies the following requirements
  1. all pods can communicate with all other pods without NAT
  2. all nodes can communicate with all pods (and vice-versa) without NAT
  3. the IP that a pod sees itself as is the same IP that others see it as

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