Update stateful sets to modify pod resources - Precisely Data Integrity Suite

Data Integrity Suite
Product
Spatial_Analytics
dis_mcp
Data_Integration
Data_Enrichment
Data_Governance
Precisely_Data_Integrity_Suite
geo_addressing_1
platform_spatial_analytics
Data_Observability
Data_Quality
dis_core_foundation
Services
Spatial Analytics
Precisely MCP
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
ft:title
Data Integrity Suite
ft:locale
en-US
PublicationType
pt_product_guide
copyrightfirst
2000
copyrightlast
2026

Adjust the resource allocation for pods only when the required resources exceed the default allocation. No changes are needed if the calculated resources are less than or equal to the default allocation.

Note:
  • POD memory must always be greater than JVM memory.
  • Pods reset to default values after upgrades. Reapply changes as needed.

Pod-Specific Instructions

Pod allocation refers to the process of assigning CPU, memory, and storage resources to individual pods that run components of Data Integration workflows. Proper allocation gives each pod the resources required for its workload, which helps avoid bottlenecks and align performance with the integration use case. It provides detailed instructions for configuring pod-specific settings, including namespaces, JVM options, and resource limits for various components such as connect-cdc, connect-hub, cloud-applier, and sqdata-management.

To apply these configurations, you can use the command:

sudo KUBECONFIG=/home/k3s/.kube/k3s.yaml /usr/local/bin/k3s kubectl

This command allows you to interact with your Kubernetes cluster, specifying a custom KUBECONFIG path and using the k3s distribution's kubectl tool to modify or apply pod configurations as needed.

connect-cdc

kubectl edit statefulset connect-cdc-runtime-engine -n precisely-ns

Update JVM Options:

- name: JVM_MIN_MEMORY
   value: "2000"
- name: JVM_MAX_MEMORY
   value: "2000"

Update Resources:

resources:
  limits:
    cpu: 1200m
    memory: 3072Mi
  requests:
    cpu: 1200m
    memory: 3072Mi

connect-hub

kubectl edit statefulset connect-hub -n precisely-connect-hub-ns

Update JVM Options:

- name: _JAVA_OPTIONS
  value: -Xms512m -Xmx512m

Update Resources:

resources:
  limits:
    cpu: 1000m
    memory: 1024Mi
  requests:
    cpu: 1000m
    memory: 1024Mi

cloud-applier

kubectl edit statefulset connect-cloud-applier -n precisely-cloud-applier-ns

Update JVM Options:

- name: _JAVA_OPTIONS
  value: -Xms1560m -Xmx1560m
Update Resources: 
resources:
  limits:
    cpu: 1000m
    memory: 2432Mi
  requests:
    cpu: 1000m
    memory: 2432Mi

sqdata-management
kubectl edit statefulset mainframe-replication-manager -n precisely-sqdata-management-ns
Note: No JVM memory setting is required.
Update Resources: 
resources:
  limits:
    cpu: 500m
    memory: 2048Mi
  requests:
    cpu: 200m
    memory: 500Mi

Best Practices

  • Always scale pods based on real usage.
  • Use default values when calculated requirements are lower than defaults.
  • Ensure _JAVA_OPTIONS are correctly configured.
  • Ensure POD memory > JVM memory.
  • Always check pre-requisites before running configuration commands.