What is Kubernetes (k8s) ?
- Kubernetes is just like the control panel (flight instrucment) of an aircraft.
- For aviators, they have lots of component to control and manage, so there is a control panel for them.
- For developers, when we have lots of computer to manage, so there is Kubernetes for us!
In short, Kubernetes is a tool for developers to manage a cluster of computers.
Think of you have lots of service to manage…
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You have Kafka, Cassandra, MySQL, Redis, Elasticsearch and many services. For each service, you need:
- Deploy newer version to certain machines, rollback if deployment failed
- Restart the service once it failed
- Scale up when heavy loading
- …
Why should we use Kubernetes ?
- self-healing: auto restart services once if failed
- automated rollouts and rollbacks
- built-in load balancing
- easier service discovery
- secret and configuration management
- it abstracts away the hardware infrastructure and exposes your whole cluster as a single enormous computational resource
- better resource allocation: you can specify the CPU & memory for each service, k8s will automatically allocate them for you.
- storage orchestration: you don’t need to think where to store your data*
Who invents Kubernetes ?
- 15 years of experience of building production workloads at Google: Borg, Omega
Before we dive into details
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Let’s have a very simple practice today.
Core concepts of Kubernetes
Fundaments
- Container: a technique to package our application, and run it in an isolated environment. You can think of that we packed our our application, and run it in a virtualized computer.
Architecture
- Node: a real computer or a virtualized machine (e.g. ec2, gce) who has computing resource (CPU, memory)
- Cluster: a bunch of real computers or VMs managed by Kubernetes
- Pod: basic working unit of kubernetes
- Container: a container instance by containerized technology, e.g. docker
A cluster can contain many nodes, a node can contain many pods, and a pod can contain many containers
Important resource types
- Pod
- Service (NodePort, LoadBalancer) & Ingress
- ReplicaSet
- Deployment
- Persistent Volume
Pod
- Purpose: the basic working unit for scaling/deployment
- each container in a pod share same host and port space
- each pod inside cluster has its own unique IP address
- we can specify multiple containers you would like to use in a single pod
When we use multiple containers in a pod ?
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Sidecar pattern: log collecting
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Ambassador/Adapter pattern: proxy / adaptor
When we should NOT use multiple containers in a pod ?
when we want to scale up different applications inside a pod in different scale, we should separate it as different pods
Service
- Purpose: make cluster’s internal and external networking more convenient and feasible
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Use cases:
- Pod-to-Pod communication
- Pod to connect external service
- External client to connect internal pod
Pod-to-Pod communication
- Pod can fail / be deleted / be created at any time, we are not possible to setup our application by IP address mannually
- By using service, we can refer to one or more pods by a selector
- When a service can to muliple pods, the service can load balancing the requests
Pod to connect external service
External client to connect internal pod
ReplicaSet
- Purpose: to maintain a stable number of replica Pods running
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Use case:
- High Availability (HA): to ensure service always being available
- Load Balance
- For example: Login service, API service, …
Deployment
- Purpose: to deploy our application more gracefully
- Use case: almost every application
- Before introducting Deployment, let’s see what kind of strategies we can use for deploying new version of application:
And actually, Deployment works by ReplicaSet:
Persistent Volume
Pods can be deleted/removed at any time, and all the files inside pod will disappear by default. However, for some of service, persistent storage is crucial. (e.g. DB service)
Important resource types recap
- Pod: basic working unit
- Service (NodePort, LoadBalancer) & Ingress: for networking
- ReplicaSet: to keep stable number of replica pods
- Deployment: to deploy application more gracefully
- Persistent Volume: to save data persistently
Tips for inspecting issues in Kubernetes cluster while on duty
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Common tasks for onduty person:
- ensure applications running correctly
- scale up/down service if needed
How to monitor whether application is running properly ?
- Pod: status, age
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Monitoring service like Grafana & Prometheus
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worker: understand the source of jobs, usually a queue.
- how many tasks are there in a queue ?
- what is the producing / consuming velocity ?
- what is the oldest task in the queue ?
- server: request per second / latency (response time)
- cronjob: log
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