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.
This designation recognizes Vertical Relevance’s expertise in enabling customers in the financial services industry to effectively utilize the AWS cloud and deliver application functionality to customers quickly and efficiently.
This is the latest example of how Vertical Relevance is a leader in the Policy as Code space. This post outlined how to operationalize PaC with a serverless Evaluation Engine as part of the broader Control Broker solution. Get in touch with us to learn more about the benefits of operationalizing the automated enforcement of security policies
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.
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.
How a leading multinational asset management firm is leveraging AWS Control tower to automate account provisioning and configuration of guardrails to ensure agility and security at scale.
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.
It is difficult to navigate the constantly evolving world of compliance and regulations. Manual risk management often leads to gaps in security, and requires high effort and collaboration to achieve compliance. Reaching compliance is a huge undertaking, often involving guesswork and extensive research just to have information to get started. By leveraging AWS Audit Manager and the VR Cloud Controls Framework, we can create a custom audit framework that meets our individual business requirements, automate the audit process, and attain routine compliance.
How a leading global investment banking, securities, and investment management firm is leveraging policy-as-code techniques to enable application teams to adapt to the cloud faster without sacrificing security or compliance.