I Need A Scalable & Highly Available Environment
One of the chief reasons companies adopt cloud infrastructure is the promise of enhanced scalability and availability for their workloads. Many companies fail to achieve this promise due to application architectures that were not designed to operate in a cloud environment. Blue Sentry will examine your code architecture with specific attention to statelessness and service orientation. We will advise you regarding serverless deployment options as well as traditional virtual machine and container deployments.
Where code refactoring or decoupling is necessary to achieve your desired end state, Blue Sentry will provide a technical execution plan for the refactoring of your workloads.. Your transformation team will also consider the scalability of your data operations and execute on the adoption of the appropriate AWS services to ensure scalability, performance, and high availability of your data.
When it comes to high availability and disaster recovery your Blue Sentry Transformation Team assumes that everything eventually fails. We employ the latest in AWS Best Practice to ensure your availability objectives are consistently met. You will have the confidence of having implemented the appropriate scaling and high availability regime, considering your code deployment automation pipelines and other operational processes established during your planning and preparation.
The key deliverables in this theme include:
- Reference architecture and associated documentation detailing high availability and scalability design
- Fully configured and tested autoscaling and elastic load balancing groups, where appropriate
- Stack deployment code templates for scaling and high availability services
- Initial golden image AMIs where appropriate
- Failover and/or workload scalability testing
Learn more about how Blue Sentry created scalable and highly available cloud environments for its clients.
PeopleFluent’s business involves continuous product development, so a DR capability was needed to include an automated code deployment pipeline — allowing for changes that were moved to production, to also be replicated in DR.
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