Challenge:

Like a lot of growing companies, CyGlass needed to overcome challenges holding back its deployment speed and agility. Technical and cost limitations associated with CyGlass’s current platform architecture impacted their ability to meet growing customer demand for its solution.

Solution:

Shadow-Soft engineers helped CyGlass in three phases: Assessment, Implementation, and Enablement.

Results:

CyGlass is realizing a 3X reduction in platform infrastructure costs and a 12X reduction in build time.

 

We’re delighted to see that all of Shadow-Soft’s recommendations helped energize and galvanize the team, pointing us in the right direction. CyGlass now has a solid platform to bring on more large customers.”

The Client:

Shadow-Soft supports a federal civilian agency that leverages significant raw data to assist with investigations of fraud and waste.

The Challenge:

The customer lacked visibility to how they consumed AWS services, forecasting demand, and required assistance with best practices related to its highly regulated policy driven environment.

The Results:

• Shadow-Soft helped implement a cost observability tool to provide visibility to stakeholders
• Provided an Amazon Web Services well architected review to validate strengths and weaknesses
• Implemented AWS organizations for ease of account management
• Provided access to proof of concept project money for new machine learning services

Challenge: 
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. The client engaged Shadow-Soft to review architecture, implement integrated logging and alerting solutions, and provide recommendations on how to improve performance with best practice configuration.

Solution and Architecture:

• Perform review with the 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 solutions on AWS Elasticsearch Service, FluentD, Kibana Stack (EFK), VictorOps, Slack
• The fluent collects the logs and forwards 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 alert manager on all the clusters to send the NodeNotReady alert to VictorOps
• Assist in 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)

Results:

• 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 customers 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.