We decided to place a lot of trust in Velotio to help build out our HIPAA compliant Cloud infrastructure. Velotio went above and beyond to deliver a world class solution.
Established in 2007, the customer is one of the leading SaaS-based platforms that enables US healthcare institutes to deliver an improved elderly care experience, while adding to their business growth.
The software is currently being used by over 12000 institutes every day and aims to establish a more collaborative and data-backed approach to address the challenges faced by elderly all across the country.
- Implemented a self-healing, HIPAA-compliant architecture to ensure the safety of patients’ data.
- Implemented a completely automated continuous delivery pipeline that reduced operational costs considerably.
- Ensured a secure connection with the customer's production data center to enable single sign-on with other services.
The patient data on the platform is collected from medical institutes around North America. As the company deals directly with the sensitive personal health information (PHI) of patients, their cloud infrastructure must comply with the Health Insurance Portability and Accountability Act (HIPAA) and all the latest security guidelines defined under it.
The customer was looking for a technology partner that could help them set up a continuous delivery pipeline that fully complies with HIPAA security guidelines. Velotio’s proven expertise in DevOps services as well as building HIPAA-compliant architectures made it easier to choose them over other vendors.
Velotio’s team of experienced Solution Architects designed and implemented a fault-tolerant architecture that fully complied with all HIPAA requirements and ensured safe processing of patient data on the analytics platform.
The DevOps experts helped build an automated delivery pipeline with clear segregation of duty policies. The discovery mechanism was built to configure the overall stack, automate DNS management, relevant secrets management, et al. The pipeline also enabled integration with the customer’s release process, making it faster for the development team to iterate and push frequent releases, while the operations team took responsibility for the final validation and updation to the production environment.
The team isolated all the services inside the network, but ensured a secure connection with the customer's production data center. This facilitated the data loading and ingestion and enabled single sign-on with other web application services used by the customer.
The platform can now easily handle high volumes of data and scale to meet the demands of a Hadoop-based ingestive service, such as higher processing speed and low latency data replication.
The team combined multiple solutions to achieve this:
- I/O and compute intensive instances running on dedicated hardware were put closer in placement groups
- Enhanced networking and provisioned IOPS were used to handle the high query load on the PostgreSQL data warehouse
- Instance types were optimized to manage bandwidth needs required by Tableau and the application’s servers to perform analytics operations and data modeling
Improving the infrastructure had a snowball effect in other aspects of technology as well. The customer could now take advantage of several tools and managed services (like IAM, VPC, S3, CloudFormation, AutoScaling, ELB and Route53) that improved their deployment automation and reduced operational costs.
The team combined Chef with AWS tools to implement complete automation and utilized the DevOps expertise to build a powerful continuous delivery pipeline, which is now used by both Development and Operations teams.
After building the continuous delivery pipeline, Velotio’s team worked with the customer’s in-house team to automate bootstrapping and resource provisioning by combining Chef-based provisioning with AWS CloudFormation. This helped us build a fully-automated infrastructure that is managed as a code and can be used to build additional sandbox, staging or pre-production environments, or to rebuild the main production environment in the event of a disaster or in the event that moving to another AWS region is needed.
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