Tag: AWS Partner Solutions Architects (SA)

As the old saying goes, “You never get a second chance to make a first impression.” Customer trust is hard-earned and easily lost. Properly architecting a scalable and secure SaaS-based product is just as important as feature development and sales. No one wants to fail on Day 1— you worked too hard to get there. Get a comprehensive introduction to the common ways in which customers consume cloud-based SaaS models, and explore the different ways in which ISVs sell their software products to customers.

Howdy Partner is a weekly Twitch series highlighting APN Technology Partners that have built innovative solutions validated by AWS Solutions Architects. This is the premiere season of Howdy Partner, and episodes are hosted by AWS Partner Solutions Architects whose goal is to help you add new tools and skills while having a great time watching the stream. Each episode explores a different APN Technology Partner solution and how you can implement it with your workloads.

Data scientists creating enterprise machine learning models to process large volumes of data spend a significant portion of their time managing the infrastructure required to process the data, rather than exploring the data and building ML models. You can reduce this overhead by running Qubole data processing tools and Amazon SageMaker. An open data lake platform, Qubole automates the administration and management of your resources on AWS.

Customers want to use Teradata Vantage to analyze the data they have stored in Amazon S3, but the AWS service that prepares and loads data stored in S3 for analytics, AWS Glue, does not natively support Teradata Vantage. To use AWS Glue to prep and load data for analysis by Teradata Vantage, you need to rely on AWS Glue custom database connectors. Follow step-by-step instructions and learn how to set up Vantage and AWS Glue to perform Teradata-level analytics on the data you have stored in Amazon S3.

Deploying AI solutions with ML models into production introduces new challenges. Machine Learning Operations (MLOps) has been evolving rapidly as the industry learns to marry new ML technologies and practices with incumbent software delivery systems and processes. WordStream is a SaaS company using ML capabilities to help small and mid-sized businesses get the most out of their online advertising. Learn how Slalom developed ML architecture to help WordStream productionize their machine learning efforts.

For many organizations, the amount of data they own and manage is growing at a very high rate, but so is the number of applications they’re responsible for. This growth, coupled with the heterogeneity of technology infrastructure, makes managing IT systems and applications more complex. Veritas solutions, including Veritas Cloud Mobility, help enterprises address information management challenges including backup and recovery, business continuity, software-defined storage, and information governance.

Amazon CloudWatch Synthetics monitors RESTful APIs, URLs, and website content endpoints via synthetic traffic. Dynatrace also offers powerful, integrated synthetic capabilities, but if you use both CloudWatch and Dynatrace you have to switch between their consoles to check status. Now, you can integrate CloudWatch Synthetics into Dynatrace and check for unexpected behavior across both platforms from a single dashboard in your Dynatrace account.

The amount and variety of existing and newly-generated data in today’s connected world is unparalleled. As this growth continues, so does the opportunity for organizations to extract real value from their data. Teradata Vantage is a modern analytics platform that combines open source and commercial analytic technologies. It can drive autonomous decision-making by helping you to operationalize insights, solve complex business problems, and enable descriptive, predictive, and prescriptive analytics.

Learn how Mactores helped Seagate Technology to use Apache Hive on Apache Spark for queries larger than 10TB, combined with the use of transient Amazon EMR clusters leveraging Amazon EC2 Spot Instances. It was imperative for Seagate to have systems in place to ensure the cost of collecting, storing, and processing data did not exceed their ROI. Moving to Hive on Spark enabled Seagate to continue processing petabytes of data at scale with significantly lower TCO.

Amazon EC2 Spot Instances let you reduce costs by taking advantage of unused capacity. You can further reduce costs by using the policy-based automation in Qubole Data Platform to balance performance, cost, and SLA requirements anytime you use Spot Instances. Learn how the Qubole Data Platform optimizes your Spot usage, and how it applies policy-based automation to balance your performance, cost, and SLAs whenever you use Amazon EC2 Spot Instances.