pires/kubernetes-elasticsearch-clusterArchived
Kubernetes Elasticsearch Cluster
Kubernetes-elasticsearch-cluster is an orchestration tool designed to deploy and manage distributed Elasticsearch search and analytics clusters within container environments. It provisions multi-node architectures with separated master, data, and ingest roles, utilizing stateful workload orchestration to maintain stable network identities across restarts.
The system implements automated persistent storage provisioning through dynamic volume requests, alongside anti-affinity rules that distribute redundant data pods across distinct physical hosts for fault isolation. Operational availability is maintained through disruption budget limits and sequential pod startups that verify instance health. Additional capabilities include environment-based plugin injection, automated index maintenance scheduling for data retention, management dashboard exposure, and external service load balancing.
Features
- Elasticsearch Clusters - Manages master, data, and ingest roles for distributed search workloads inside container clusters.
- Application Packaging Templates - Stands up complete multi-node search environments using pre-packaged configuration templates with adjustable replica counts.
- Containerized Database Administration - Manages automated index maintenance, plugin installations, and visualization dashboards for distributed database workloads running in containers.
- Distributed Search Engines - Deploys scalable search clusters with separated master, data, and ingest roles for optimized performance.
- Search Cluster Deployments - Runs scalable database clusters inside Kubernetes environments with automated stateful workloads.
- Persistent Storage Provisioning - Requests dynamic storage volumes of specified capacities for database nodes using automated cluster storage classes.
- Operator Package Deployments - Stands up a complete search environment using pre-packaged charts with adjustable replica counts and resource allocations.
- Cluster Node Management - Runs dedicated control plane nodes as ordered stateful workloads to manage cluster state reliably.
- Application Cluster Deployments - Deploys a multi-node cluster with separated master, data, and ingest roles to optimize performance and handle high workloads.
- Clustered Worker Nodes - Runs database worker nodes as ordered stateful workloads that maintain stable network identities across restarts.
- Any-Workload Deployments - Deploys database pods as stateful workloads that maintain stable network identities and persistent storage across restarts.
- StatefulSet Lifecycle Management - Manages ordered database workloads using persistent network identities and sequential pod startup sequences.
- Pod Anti-Affinity Constraints - Distributes redundant cluster pods across distinct underlying physical hosts to guarantee resilience during outages.
- Dynamic Storage Provisioning - Requests automated storage volumes from underlying cluster storage classes to persist database records reliably.
- StatefulSet Orchestrators - Coordinates stateful workloads, persistent volumes, and anti-affinity rules for distributed databases.
- Availability Budget Protection - Enforces safety limits on concurrent node unavailabilities to maintain high cluster stability during maintenance.
- Distributed Role Separation - Deploys distributed nodes with dedicated master, data, and ingest roles to optimize performance and workload isolation.
- Cluster Monitoring Dashboards - Deploys and configures visualization interfaces with customizable settings to monitor and interact with cluster data.
- Startup Sequencing - Spawns cluster pods one at a time in a controlled sequence, verifying health before launching the next instance.
- Recurring Maintenance Scheduling - Schedules recurring background routines to prune outdated indices and enforce defined data retention policies automatically.
