Tag: AWS Partner Solutions Architects (SA)

Being able to support varying tenant configurations is a common requirement for SaaS providers. Learn how LaunchDarkly creates varied tenant experiences with entitlement flags and how to model entitlements as feature flags, targeted to tiers to give tenants access to specific features. We’ll also dive into ways you can use the LaunchDarkly feature for flagging deployments/releases, doing progressive rollouts, or running experimentation—all important release practices for SaaS providers.

Sisense Fusion Embed and Amazon Redshift Serverless provide customers with an integrated and seamless AI-powered data analytics experiences combined with predictive intelligence, natural language querying, and more. Together, these solutions enable data-driven decisions and deliver business insights at the point of decision making. Explore the benefits and synergy of these two powerful data solutions and how they can help organizations turn data into actionable insights.

Organizations running Oracle Database on vSphere environments are looking for migration paths for the database and the best path for them. In this post, explore database migration paths to AWS from on-premises vSphere environments and the benefit of integrating VMware Cloud on AWS with AWS Cloud Databases. We’ll also discuss how each migration path helps customers streamline operations, reduce costs, and improve overall business agility.

Kubernetes provides several autoscaling features that enable organizations to dynamically adjust their application resources in response to varying demands, but optimizing Kubernetes costs can be challenging. Learn how optimization tools like Karpenter and StormForge Optimize Live help organizations automate resource allocation, optimize performance, and reduce costs, thus making the process of cost optimization more accessible and efficient for anyone.

Gremlin is an AWS Partner that gives users a solution for safely and securely improving the reliability of their technology stack. Teams can use Gremlin to find hidden reliability risks, standardize reliability testing and measurement, and simulate real-world outages with an ever-growing library of tests. Learn how to test and measure the reliability of AWS systems using Gremlin Reliability Management and Amazon CloudWatch.

Optimizing environments for cost, however, is often an activity that happens only in response to unexpected growth of charges in the bill. nOps nSwitch makes this process easy, allowing both engineering and finance teams to explore, identify, and automate optimization opportunities. Learn how nOps’ integration with Amazon EventBridge helps customers to pause, reconfigure, and right-size a broad variety of popular AWS services so they can tune for the most optimal cost while maintaining reliability and security.

To sustain innovation and drive business value, organizations are realizing the importance of decentralization of data products using a data mesh architectural design approach. Experts from AWS and IBM explain how to set the right balance of business ownership using data mesh to modernize data platform and accelerate innovation. We’ll also describe referenceable techniques to build data mesh solutions using AWS native services including Amazon DataZone, AWS Lake Formation, and AWS Glue.

Infosys has crafted an automated self-service landing zone solution for AWS which employs AWS Control Tower to generate the customer’s organization unit structure and set up individual accounts. It uses the infrastructure as code tools from Terraform for infrastructure provisioning and Ansible for service configuration. The landing zone provides a pre-configured and secure environment, functioning as a springboard for organizations to manage their AWS resources effectively.

Amazon EKS provides a managed scaled control plane which eliminates the undifferentiated heavy lifting for the enterprise platform team. Learn how using the Lightrun developer observability platform and Amazon EKS together, organizations can maximize their mean time to resolution of defects, enhance developer productivity, and reduce overall logging costs. Lightrun and Amazon EKS enable full-cycle developer observability.

Maintaining multiple machine learning models across different teams can be challenging. Having a centralized platform to monitor and manage them can significantly reduce operational overhead and improve efficiency. Learn how the models trained and deployed in Amazon SageMaker can be monitored by DataRobot in a highly scalable fashion. In this way, customers can monitor both DataRobot-originated models and SageMaker-originated models under a single pane of glass.