The Workloads section in Ankra gives you complete visibility and control over all running applications in your Kubernetes clusters.
Overview
Workloads are the applications running in your cluster. Ankra provides a unified interface to view, manage, and troubleshoot all workload types:- Deployments - Stateless applications with declarative updates
- Pods - The smallest deployable units
- StatefulSets - Stateful applications with stable identities
- DaemonSets - Pods that run on every node
- ReplicaSets - Maintain replica pod counts
- Jobs - Run-to-completion tasks
- CronJobs - Scheduled jobs
- Horizontal Pod Autoscalers (HPAs) - Automatic scaling
Accessing Workloads
Navigate to your cluster and click Kubernetes in the sidebar. The Workloads section includes:| Resource | Path |
|---|---|
| Deployments | Kubernetes → Deployments |
| Pods | Kubernetes → Pods |
| StatefulSets | Kubernetes → StatefulSets |
| DaemonSets | Kubernetes → DaemonSets |
| ReplicaSets | Kubernetes → ReplicaSets |
| Jobs | Kubernetes → Jobs |
| CronJobs | Kubernetes → CronJobs |
| HPAs | Kubernetes → Horizontal Pod Autoscalers |
⌘+K) to jump directly to any resource type.
Deployments
Deployments manage ReplicaSets and provide declarative updates for Pods.Viewing Deployments
The Deployments list shows:| Column | Description |
|---|---|
| Name | Deployment name |
| Namespace | Kubernetes namespace |
| Ready | Ready replicas / Desired replicas |
| Up-to-date | Pods running the latest spec |
| Available | Pods available for traffic |
| Age | Time since creation |
Deployment Details
Click a deployment to view:- Status - Current rollout state and conditions
- Replicas - Desired, current, ready, and available counts
- Strategy - Rolling update or recreate
- Pod Template - Container specs, resources, environment
- Events - Recent Kubernetes events
- Managed Pods - List of pods owned by this deployment
Actions
- Scale - Adjust replica count
- Restart - Trigger a rolling restart
- View YAML - See the full resource definition
- Troubleshoot - AI-assisted diagnosis
- Delete - Remove the deployment
Pods
Pods are groups of containers that share storage and network.Viewing Pods
The Pods list shows:| Column | Description |
|---|---|
| Name | Pod name |
| Namespace | Kubernetes namespace |
| Ready | Ready containers / Total containers |
| Status | Running, Pending, Failed, etc. |
| Restarts | Container restart count |
| Age | Time since creation |
| Node | Node the pod is scheduled on |
Pod Details
Click a pod to view:- Containers - List of containers with status, image, and resources
- Conditions - PodScheduled, ContainersReady, Ready
- Events - Recent events (scheduling, pulling, started, etc.)
- Labels & Annotations - Metadata
- Volumes - Mounted volumes and claims
Pod Logs
View real-time and historical logs:- Click on a pod
- Select the Logs tab
- Choose the container (for multi-container pods)
- Toggle Follow for real-time streaming
- Search within logs using the filter
Actions
- View Logs - Stream container logs
- View YAML - Full pod specification
- Troubleshoot - AI analysis of pod issues
- Delete - Remove the pod (will be recreated by controllers)
StatefulSets
StatefulSets manage pods with persistent identities and stable storage.Key Features
- Stable Pod Names - Pods have predictable names (app-0, app-1, etc.)
- Persistent Storage - Volume claims are retained across restarts
- Ordered Operations - Pods are created/deleted in order
Viewing StatefulSets
The list shows replica status, update status, and age. Details include:- Pod management policy
- Update strategy
- Volume claim templates
- Managed pods
DaemonSets
DaemonSets ensure a pod runs on every (or selected) node.Use Cases
- Log collectors (Fluentd, Filebeat)
- Node monitoring (Prometheus node exporter)
- Network plugins (CNI, kube-proxy)
- Storage plugins (CSI drivers)
Viewing DaemonSets
The list shows:| Column | Description |
|---|---|
| Desired | Pods that should be scheduled |
| Current | Currently running pods |
| Ready | Pods ready to serve |
| Up-to-date | Pods with latest spec |
| Available | Pods available |
Jobs & CronJobs
Jobs
Jobs create pods that run to completion:- Completions - How many successful completions are needed
- Parallelism - How many pods can run concurrently
- Status - Active, succeeded, failed counts
CronJobs
CronJobs schedule Jobs on a time-based schedule:- Schedule - Cron expression (e.g.,
0 */6 * * *) - Last Schedule - When it last ran
- Active - Currently running jobs
- Suspend - Whether scheduling is paused
Horizontal Pod Autoscalers
HPAs automatically scale workloads based on metrics.Viewing HPAs
| Column | Description |
|---|---|
| Name | HPA name |
| Reference | Target deployment/statefulset |
| Min/Max | Replica bounds |
| Replicas | Current replica count |
| Metrics | CPU/Memory utilization |
HPA Details
- Target metrics and current values
- Scaling history
- Conditions and events
Bulk Delete Resources
You can select and delete multiple Kubernetes resources at once across all resource types.How to Bulk Delete
Navigate to a Resource List
Go to any Kubernetes resource list (Deployments, Pods, StatefulSets, Services, ConfigMaps, etc.).
Select Resources
Click the checkbox next to each resource you want to delete. Use the top checkbox to select all visible resources.
Click Delete
A toolbar appears showing the number of selected items. Click Delete Selected to begin.
Supported Resource Types
Bulk delete is available across all Kubernetes resource types in Ankra, including:- Workloads: Deployments, Pods, StatefulSets, DaemonSets, ReplicaSets, Jobs, CronJobs
- Networking: Services, Ingresses, Network Policies, Endpoints
- Configuration: ConfigMaps, Secrets
- Storage: Persistent Volume Claims, Persistent Volumes, Storage Classes
- RBAC: Roles, RoleBindings, ClusterRoles, ClusterRoleBindings, ServiceAccounts
Common Tasks
Troubleshooting a Failing Pod
- Navigate to Pods and find the failing pod
- Check the Status column for error indicators
- Click the pod and review:
- Events for scheduling or pull errors
- Logs for application errors
- Conditions for readiness issues
- Click Troubleshoot for AI-assisted diagnosis
Scaling a Deployment
- Navigate to Deployments
- Click on the deployment to scale
- Click Scale and enter the new replica count
- Confirm the change
Restarting Pods
- Navigate to Deployments
- Click on the deployment
- Click Restart to trigger a rolling restart
- Monitor the rollout in Events
Nodes
The Nodes view under Kubernetes → Nodes shows all nodes in your cluster with their status, roles, resource usage, and scheduling state.Node List
The node list displays:| Column | Description |
|---|---|
| Name | Node hostname |
| Status | Ready / NotReady and scheduling state |
| Roles | Control plane, worker, etcd |
| Version | Kubelet version |
| Age | Time since node joined the cluster |
| CPU / Memory | Allocatable resources |
Node Actions
Cordon & Uncordon
Cordoning a node marks it as unschedulable — no new pods will be placed on it, but existing pods continue running. This is the first step when preparing to move workloads off a node.- Single node: Click a node to open its detail view, then click Cordon or Uncordon in the header.
- Bulk action: Select multiple nodes using the checkboxes, then click Cordon or Uncordon in the floating action bar. The action bar dynamically shows the relevant buttons based on the scheduling state of selected nodes.
Drain
Draining a node cordons it and then evicts all running pods (ignoring DaemonSets and deleting emptyDir data). This is equivalent to:- Single node: Click a node, then click Drain in the header.
- Bulk action: Select one or more nodes, then click Drain in the floating action bar.
Moving Workloads to New Node Groups
To migrate workloads from old nodes to a new node group:Create a new node group
Add a new node group in Cluster Settings → Nodes with your desired instance type, labels, and taints.
Cordon old nodes
In Kubernetes → Nodes, select the old nodes and click Cordon to prevent new scheduling.
Drain old nodes
With the same nodes selected, click Drain to evict all running pods. Pods managed by Deployments or StatefulSets will be automatically rescheduled onto the new node group.
Tips
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