Vertical Relevance’s Monolith to Microservices Foundation provides a proven framework on how to break the monolith and deliver improved agility to increase the pace of innovation and drive value to your customers and your business. By following the approaches laid out in this Foundation, customers will manage risk and lay out a consistent iterative approach to decompose the monolith into cloud native microservices, following a well-defined process.
The Experiment Generator simplifies the resiliency testing process and accelerates its adoption, organization wide. Implementing the Experiment Generator brings an organization one step closer to its resiliency goals, both in relation to people and processes, in breaking down team barriers and automating as much as we can.
With the ever-growing adoption of the cloud and hybrid cloud, businesses are struggling to “connect the dots” when it comes to customer experience – regardless of whether the customer is in-house or external. By implementing instrumentation and distributed tracing as discussed throughout this solution, enterprises will be able to leverage their single pane of glass to improve performance at the margins and quickly identify and remediate application issues as they arise.
Vertical Relevance's Experiment Broker provides the infrastructure to implement automated resiliency experiments via code to achieve standardized resiliency testing at scale. The Experiment broker is a resiliency module that orchestrate experiments with the use of state machines, the input is driven by a code pipeline that kicks off the state machine but also can be executed manually. Coupled with a deep review and design of targeted resiliency tests, it can help ensure your AWS cloud application will meet business requirements in all circumstances.
Organizations are rapidly adopting modern development practices – agile development, continuous integration and continuous deployment (CI/CD), DevOps, multiple programming languages – and cloud-native technologies such as microservices, Docker containers, Kubernetes, and serverless functions. As a result, they're bringing more services to market faster than ever. In this solution, learn how to implement a monitoring system to lower costs, mitigate risk, and provide an optimal end user experience.
Monitoring is the act of observing a system’s performance over time. Monitoring tools collect and analyze system data and translate it into actionable insights. Fundamentally, monitoring technologies, such as application performance monitoring (APM), can tell you if a system is up or down or if there is a problem with application performance. Monitoring data aggregation and correlation can also help you to make larger inferences about the system. Load time, for example, can tell developers something about the user experience of a website or an app. Vertical Relevance highly recommends that the following foundational best practices be implemented when creating a monitoring solution.