DigitalOcean Kubernetes (DOKS) is a managed Kubernetes service. Deploy Kubernetes clusters with a fully managed control plane, high availability, autoscaling, and native integration with DigitalOcean Load Balancers and volumes. You can add node pools using shared and dedicated CPUs, and NVIDIA H100 GPUs in a single GPU or 8 GPU configuration. DOKS clusters are compatible with standard Kubernetes toolchains and the DigitalOcean API and CLI.
Kubernetes clusters require a balance of resources in both pods and nodes to maintain high availability and scalability. This article outlines some best practices to help you avoid common disruption problems.
We recommend deploying all of your applications in a highly available manner. This means deploying multiple stable replicas of your applications and not using bare pods. Using replicas ensures that a stable set of pods are running your application at any given time.
Use the replicas
field in your application spec to define at least three replicas:
apiVersion: apps/v1
kind: Deployment
metadata:
name: frontend
labels:
app: guestbook
tier: frontend
spec:
# modify replicas according to your case
replicas: 3
selector:
matchLabels:
tier: frontend
template:
metadata:
labels:
tier: frontend
spec:
containers:
- name: php-redis
image: gcr.io/google_samples/gb-frontend:v3
The size of nodes determines the maximum amount of memory you can allocate to pods. Because of this, we recommend using nodes with less than 2GB of allocatable memory only for development purposes and not production. For production clusters, we recommend sizing nodes large enough (2.5 GB or more) to absorb the workload of a down node.
During cluster creation, choose a plan from the NODE PLAN drop-down menu that fits your project’s purpose. Plans are divided into two categories: Development plans and Production plans.
To further ensure high availability, node pools with production workloads should have at least three nodes. This gives the cluster more flexibility to distribute and schedule work on other nodes if a node becomes unavailable.
You can specify three or more nodes during a cluster’s creation or you can configure the autoscale function to ensure minimum cluster size of three nodes.
To keep your cluster running efficiently, we recommend defining the requests
and limits
objects in your application spec for all deployments.
requests
- Specifies how much of a resource (such as CPU and memory resources) a pod is allowed to request on a node before being scheduled. If the node doesn’t have the available resources, the pod will not be scheduled. This prevents pods from being scheduled on nodes that are already under heavy workload.
limits
- Specifies the amount of resources (such as CPU and memory resources) a pod is allowed to utilize on a node. This prevents pods from potentially slowing down the work of other pods.
To set requests
and limits
, define their values in your application spec. See the Kubernetes’ documentation for more resource types.
apiVersion: v1
kind: Deployment
metadata:
name: frontend
spec:
containers:
- name: app
image: images.my-company.example/app:v4
resources:
requests:
cpu: 250m
memory: 64Mi
limits:
memory: 128Mi
cpu: 500m
- name: log-aggregator
image: images.my-company.example/log-aggregator:v6
resources:
requests:
memory: 64Mi
cpu: 250m
limits:
memory: 128Mi
cpu: 500m
To avoid disruptions to your production, such as during cluster upgrades, you can set up a pod disruption budget (PDB) that limits the number of replicated pods that can be down simultaneously. For example, you can have a replica count of 10 and a PDB that allows downtime of three simultaneous replicas by setting the minAvailable
to 7.
To set up a pod disruption budget, you need to create a PodDisruptionBudget
policy spec.
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
name: zk-pdb
spec:
minAvailable: 7
selector:
matchLabels:
app: example-app
You can set the minimum available pods for an application using the minAvailable
field and apply it to your applications using the matchLabels
object.
Enabling automatic upgrades ensures that your cluster is running the latest features, security patches, and stability improvements.
We also recommend enabling surge upgrades when upgrading a cluster.
To enable automatic upgrades, follow our Kubernetes upgrade guide.
Surge upgrades reduce the overall cluster upgrade time and impact on applications. We recommend enabling surge upgrades when upgrading an existing cluster. Surge upgrades are enabled by default when you create a new cluster.
To enable surge upgrades, follow our surge upgrade guide.
Clusterlint is a standalone tool that connects to the cluster’s API server and flags issues with workloads deployed in a cluster. These issues might cause downtime during maintenance or upgrades and could complicate the maintenance or upgrade itself. Using clusterlint
regularly can inform you of ongoing issues that otherwise might not be immediately apparent.
You can access clusterlint
using three different methods:
clusterlint
messages from the control panel, click Kubernetes in the main navigation menu, then select your cluster from the list of clusters. From the cluster’s Overview page, under Operational Readiness Check, click Run Check. After the card updates, it displays any clusterlint
results.clusterlint
from the command line and begin using it to access your clusters.For a list of common clusterlint
errors and their respective fixes, see Clusterlint Error Fixes.