Red Hat OpenShift on AWS: Implementation and Integration (Case Study)


Our Biotech client was experiencing degraded performance with their initial implementation OpenShift cluster on EC2. They needed real-time visibility into their OpenShift clusters and applications. Client engaged Shadow-Soft to review architecture, implement an integrated logging and alerting solution, and provide recommendations on how to improve performance with best practice configuration.

Solution and Architecture

  • Perform review with client to discover requirements and gather baseline metrics to determine optimum configurations for: Cluster Sizing, Performance and Scalability characteristics, Logging and Metrics, Security, Backup and Recovery
  • Provide recommendations around best practices and OpenShift add-ons
  • Implement recommendations to optimize logging and alerting solution on AWS Elasticsearch Service, FluentD, Kibana Stack (EFK), VictorOps, Slack
  • The fluentd collects the logs and forward them to Elasticsearch, enabling the client to see one consolidated view of all the logs from one location.
  • Configure VictorOps integration with Slack to notify errors in Openshift Clusters. Used alertmanager on all the clusters to send the NodeNotReady alert to VictorOps
  • Assist troubleshooting the OpenShift 4 cluster configuration
  • Enablement and training on advanced troubleshooting of OpenShift cluster
  • Best practice capacity management, autoscaling, and cluster optimization
  • CI/CD for application deployment using application packaging and existing CI/CD tooling (Jenkins) and processes
  • Terraform scripts to create backups for RDS databases (Cross-Region Read Replicas)


  • Improved logging solution to quickly detect issues with OpenShift cluster
  • Improved visibility with alerts and notifications directly to system admins
  • Resolved insufficient storage issue in OpenShift environment
  • Finely-tuned OpenShift clusters now enable customer to run and scale applications with confidence
  • Awareness and ability to respond quickly to issues, allowing the customer to reduce time to resolution and increase uptime.

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