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.
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.
The Vertical Relevance Automated Performance Testing Framework lowers the barrier to entry in performance tests by providing a starting point upon which a mature solution can be built to meet the needs of your organization. By following this guidance, you can gain confidence that your production systems are going to meet the current and future demands of your organization and customers
Regular and robust resiliency testing provides assurances your cloud application can weather whatever outages may occur. The Vertical Relevance Resiliency Automation Framework can help guarantee your workload can prevail through disruptions and failures and prevent the damaging consequences of an outage. Reach out to us to learn more about how we can help you meet your resiliency requirements.
While there are many different components involved with securing the cloud, a carefully architected IAM strategy is paramount. A solid IAM strategy allows engineers to develop quickly, provides key stakeholders with a comprehensive picture of the actions that can be performed by different IAM principals, and results in a more secure cloud environment overall. Security without reasonable user experience can lead to workarounds and dysfunction, and by implementing this solution, both key stakeholders and engineers can all be satisfied with the result.
Best Practices for Designing and Automating Scalable Networks on AWS. Vertical Relevance highly recommends that the following foundational best practices be implemented to create a sustainable AWS Network that will support an enterprise-level organization.
This AWS Network Foundation solution provides an opinionated, foundational set of network architectures, design considerations, automated solutions, and best practices that help our clients “quick start” their AWS journey with a strong foothold while ensuring the scalability and growth they are likely to require as their AWS footprint grows. Vertical Relevance highly recommends that the following foundational best practices be implemented to create a sustainable AWS Network that will support an enterprise-level organization.
By implementing a Lakehouse, an organization can avoid creating a traditional data warehouse. Organizations are enabled to perform cross-account data queries directly against a Lake Formation Data Lake through Redshift Spectrum External Tables and/or Athena. Table and Column-Level access granularity achieved through Lake Formation Permissions. Data Lake Governance enabled through Lake Formation Resource Shares. Multi-regional, parameterized, infrastructure-as-code deployments. Full data flow and processing pipeline with Glue Jobs, orchestrated by a single Step Function.
The Account Foundation solution provides organizations with a simple, automated approach to managing their AWS cloud environments as the quantity and complexity of AWS accounts increase. Currently, many organizations begin their cloud journey by manually provisioning accounts, configuring guardrails, and leaving baseline account setup to the account owners. However, as an organization’s cloud presence scales upwards, this manual process slows down the account provisioning process and introduces many security vulnerabilities.