Tag: AWS Partner Solutions Architects (SA)

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed, highly available, and secure Apache Kafka service that makes it easy to build and run applications that use Kafka to process steaming data. Learn how to use the new open source Kafka Connect Connector (StreamReactor) from Lenses.io to query, transform, optimize, and archive data from Amazon MSK to Amazon S3. We’ll also demonstrate how to use Amazon Athena to query the partitioned parquet data directly from S3.

The massive scale and efficiencies offered by cloud data lakes are best served by a continuous replication mechanism from on-premises and cloud-based enterprise resource planning (ERP) applications. Learn how SAP ERP, Amazon Redshift, and HVR Change Data Capture (CDC) add up to more than the sum of the individual parts, and dive deep into HVR’s architecture and the unique value proposition for SAP customers building their data lakes with AWS.

The main thing that all interested parties need when a vessel is in port—and this has never changed—is information. Learn how Inchcape, a global organization and leader in ships agency and maritime services that covers around 2,500 ports, teamed up with DataArt to reimagine its core operational platform, Optic, as a bespoke .NET Core-based microservices solution. Optic builds trust through transparency of the vessel program, real-time updates, and standardized workflow and data across all port calls and locations.

As more organizations make the move to a SaaS delivery model, many are choosing Amazon EKS as the target for their solutions. The programming model, cost efficiency, security, deployment, and operational attributes of Amazon EKS represent a compelling model for SaaS providers. Walk through the key architectural elements of a sample architecture, and learn how to isolate tenants within an EKS cluster, automate tenant onboarding, manage tenant identities, and support routing of tenant workloads.

Environmental, social, and governance (ESG) factors are increasingly important for financial institutions as they look to assess portfolio risk, meet investment mandates, align with customer values, and report on the sustainability of their portfolios. Working closely with CSRHub, a data provider on AWS Data Exchange, learn how AWS has produced a demonstration to illustrate how customers can analyze company-level ESG scoring data with Amazon QuickSight.

As organizations continue to adopt AWS, their risk footprint increases from both an infrastructure and network perspective as it relates to compliance posturing, configuration risk, and network threats. Explore the integration between AWS and Secure Cloud Analytics, a SaaS-delivered Network Detection (NDR) offering from Cisco that monitors multi-cloud and hybrid environments for threats and policy violations and provides comprehensive visibility for any environment.

Saturn Cloud is a data science and machine learning platform for Python. Its multi-node, multi-GPU computing enables 100x faster workflows, reducing the time to business value. Saturn Cloud is compatible with the entire Python ecosystem and a variety of tools, which makes workflows customizable and the computing experience highly flexible for a range of setups and preferences. In a recent release, Saturn Cloud added Amazon EC2 Spot compatibility.

Splunk recently announced the availability of Armv8 64-bit architecture support for the Splunk Universal Forwarder. This allows AWS Graviton2 customers with Linux workloads to collect and forward machine data to their Splunk environment. Follow a step-by-step guide to set up a Universal Forwarder on a Graviton2 instance running Linux, and learn how to configure the instance and the Universal Forwarder to forward data to Splunk Cloud.

Increasing the agility of mainframe workloads is critical for organizations processing core-business processes and data on mainframes. Together, AWS and Micro Focus can help you accelerate the transition to agile services with a tool-based evolutionary approach, avoiding the expensive, risky, and slow rip-and-replace approach. Learn about the overall approach to agility and detail the transitions and Micro Focus tools for transforming mainframe workloads into agile services on AWS.

Given the breadth of use cases, data lakes need to be a complete analytical environment with a variety of analytical tools, engines, and languages supporting a variety of workloads. These include traditional analytics, business intelligence, streaming event and Internet of Things (IoT) processing, advanced machine learning, and artificial intelligence processing. Learn how Cazena builds and deploys a production ready data lake in minutes for customers.