Vertical Relevance's ART provides a RAG generative AI conversational chatbot that allows teams to self-discover standards and guidelines and have their architectures and migration plans evaluated in an engaging manner at their own pace and at any time. This extensible platform can be expanded and focused on any information store, integrated with your own authentication mechanisms and RBAC authorization controls. When teams have completed their preparations, they can submit to the ARB for review. This significantly reduces the time and cost involved in developing your architecture and migration approaches for migration to AWS.
The Automated Regression Testing Framework significantly streamlines the regression testing process, making it more accessible and swiftly adopted across entire organizations. By integrating the framework, there is a bolstered assurance that all distributed application solutions undergo comprehensive testing coverage in the continuously integrated software development process. Furthermore, it offers the flexibility to automate testing in a way that best suites the needs of the application module, moving away from the constraints of a one-size-fits-all approach. This adaptability not only enhances efficiency but also ensures that diverse solutions receive the meticulous testing they require, paving the way for more reliable and high-quality software deployments.
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.
As organizations mature in their cloud journey, they are bound to have many workloads and resources across different AWS regions and accounts. This raises a tough challenge for the security teams to gain visibility into where the organization has the highest risks of security incidents. To avoid financial and reputational repercussions, security engineers and executives need a high-level, real-time view of their security posture within the cloud. This solution addresses the crucial question that keeps organizations’ security executives up at night – “is our IT infrastructure secure and are we meeting compliance requirements?”
A Data Mesh is an emerging technology and practice used to manage large amounts of data distributed across multiple accounts and platforms. It is a decentralized approach to data management, in which data remains within the business domain (producers), while also making data available to qualified users in different locations (consumers), without moving data from producer accounts. It is a step forward in the adoption of modern data architecture and aims to improve business outcomes. A Data Mesh is a modern architecture made to ingest, transform, access, and manage analytical data at scale.
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.
In non-production AWS environments today, security and IAM are often deprioritized to increase velocity of development. Vertical Relevance’s Role Broker was created as an alternative to the costly, error-prone strategies that many organizations use to manage their IAM roles in non-production environments.
In this use case learn how a leading financial services company obtained a carefully planned, scalable, and maintainable testing framework that dramatically reduced testing time for their mission-critical application and enabled them to constantly test the applications releasability.