Tag: AWS Partner Solutions Architects (SA)

Leveraging the AWs serverless quick start solution which details core integration requirements of AWS Marketplace, this post builds on that foundation and offers techniques for providing end-to-end AWS Marketplace-to-SaaS application integration, using the quick start as a starting point. Specifically, we’ll look at ways you can use AWS Marketplace to onboard new tenants into your SaaS application. We’ll also cover a few of strategies for leveraging the billing capabilities of AWS Marketplace to charge for usage.

Traditional cloud monitoring, observability, and security approaches often require manual processes for data analytics. The Dynatrace Grail data lakehouse platform provides instant, cost-efficient, AI-powered analytics and automation of unified observability, security, and business data at any scale. Learn how this enables organizations to store, process, and analyze the enormous volume and variety of data from modern cloud ecosystems while retaining its context and without structuring or rehydrating it.

IoT leverages edge computing and unlocks many use cases, but developers will tell you collecting and processing data at the edge is not without its challenges. Issues of scalability, connectivity, security, reliability, integration, and management are commonplace. This complexity led the Edge Signal development team to create the Edge Signal infrastructure platform. Learn how it helps keep developers focused on their core business and reduces the distractions of infrastructure complexities.

Data mesh is a decentralized approach to data management which strives to develop the data platform from a technology-led and project-centric model into a paradigm about federated business-led and product-centric data, by design. Learn how AWS and Accenture are helping customers rapidly set up data mesh architecture on AWS leveraging the newly-announced Velocity platform. Explore how Velocity’s Data Mesh Fabric component can minimize time and effort to set up data mesh architecture on AWS.

In this post, delve into the process of detecting tenant activities within microservices spanning multiple AWS accounts. We provide insights into instrumenting AWS Lambda functions to include tenant information in tracing using ADOT and demonstrated how to establish a service map across several AWS accounts using Amazon CloudWatch. By leveraging AWS observability technology, SaaS providers can enhance operational efficiency and redirect their attention towards their desired development goals.

For years, the Aurea team managed and maintained 120+ AWS-hosted SaaS products across hundreds of AWS accounts. With escalating costs, they needed a way to identify cost savings across their accounts and applications in a safe and scalable way. Learn how Aurea responded to this challenge by developing CloudFix, a scalable solution for finding and fixing cost-saving opportunities in your AWS environment. CloudFix is an AWS cost optimization tool that helps you adopt and use AWS services efficiently.

Embracing cloud FinOps presents organizations with a solution to drive the right governance model and align business and engineering teams to accelerate business value. Deloitte is a FinOps Certified Service Provider and its services help customers examine and plan for cloud consumption and monitor costs to minimize cloud-spend waste. By implementing the Deloitte FinOps framework, organizations gain a holistic understanding of their cloud usage and costs to help them make data-driven decisions.

By automating performance testing and including chaos testing, organizations can identify failure scenarios in systems before they develop and cause downtime. Learn how Distributed Load Testing on AWS (DLT) automates performance testing at scale, and how AWS Fault Injection Simulator (AWS FIS) performs controlled chaos engineering experiments on AWS resources. By combining the power of AWS FIS and DLT, organizations can perform comprehensive resilience testing and continuously validate their systems.

With the rise of large language models, natural language processing, and generative AI models, embeddings are becoming a critical piece of data in more machine learning use cases. In this post, explore different ways embeddings are used in machine learning and where problems can show up that impact your ML models, and how you can use WhyLabs to identify those problems and create monitors to avoid them showing up again in the future.

AWS experts break down how you can build a multi-tenant data ingestion and processing engine using AWS services. We examine each component of this data pipeline and examine some of the key considerations that can influence how you approach designing a SaaS multi-tenant data ingestion process. We also explore how multi-tenant streaming data can be ingested, transformed, and stored using AWS services while ensuring there are constructs built in to the pipeline to ensure secure processing of the data.