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.
Vertical Relevance, a financial services-focused consulting firm and Amazon Web Services (AWS) Advanced Tier Services Partner, today announced it has achieved the AWS Service Delivery designation for Amazon Systems Manager.
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.
Vertical Relevance, a financial services-focused consulting firm and Amazon Web Services (AWS) Advanced Tier Services Partner, today announced it has achieved the AWS Service Delivery designation for Amazon API Gateway. The achievement signifies Vertical Relevance’s extensive and AWS-recognized understanding of best practices and validated success in delivering Amazon API Gateway implementations to its customers.
In this use case learn how a leading financial services company obtained a data platform that is capable of scaling to accommodate the various steps of the data lifecycle along with tracking of all the steps involved including cost allocation, parameter capturing, and the providing of metadata required for integration of the client’s third party services.
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.
In this use case learn how a leading payment technology company leveraged a Resiliency Automation Framework to execute test cases to improve the architecture of applications being taken to the cloud. As a result, the customer can now operate at scale with the full knowledge of how their system works in the event of a failure.
How a multinational payments company achieves PCI Compliance on AWS. By engaging with AWS and Vertical Relevance, the Customer was provided with a mechanism to create new AWS environments quickly and ultimately decreased their onboarding time for partners which materially improves their business. Additionally, the solution enabled the Customer to pass internal and external audits.
The Data Pipeline Foundations provide guidance on the fundamental components of a data pipeline such as ingestion and data transformations. For data ingestion, we heavily leaned on the concept of data consolidation to structure our ingestion paths. For transforming your data, be sure to utilize our step-by-step approach to optimize architecting your data for end-user consumption. By following the strategies provided, your organization can create a pipeline to meet your data goals.