Category: Amazon Kinesis

This blog post explores a scalable architecture for centralized log monitoring in multi-region, multi-account AWS environments. The proposed solution leverages AWS CloudWatch account-level subscription filters to efficiently deliver logs from various sources to Grafana Cloud, a unified platform for log analysis, visualization, and alerting. By consolidating logs from disparate sources, organizations can gain improved visibility, streamline troubleshooting, enhance security and compliance, and optimize performance across their cloud infrastructure. The article provides a detailed overview of the architecture, highlighting the benefits of this approach and guiding readers on implementing this scalable log delivery solution.

By combining Amazon DynamoDB with SingleStore, organizations can efficiently capture, process, and analyze DynamoDB data at scale. SingleStore has high-throughput data ingestion and near-real time analytical query capability for both relational and JSON data. This integration empowers businesses to derive actionable insights from their data in near real time, enabling faster decision-making and improved operational efficiency.

Learn more about the Next-Gen Digital Analytics, a solution built on Amazon Web Services, using Snowplow and Snowflake. This joint solution empowers organizations to unlock the untapped value of customer behavioral data. It improves data quality, governance, and real-time activation within their AWS environment. By implementing this solution, customers can supercharge the use of Artificial Intelligence (AI) and generative AI adoption to help address key business objectives, such as user acquisition, retention, and customer lifetime value.

HCLTech’s Intelligent Ingestion solution provides automated low-code to no-code approach, simplifying ETL build efforts for both batch and real-time data ingestion workloads. It is built using rich set of AWS services like AWS Step Functions, AWS Glue, AWS Glue DataBrew, AWS Lambda, AWS Lake Formation, Amazon Kinesis, Amazon S3, Amazon Simple Notification Service (SNS), etc., among other services to achieve seamless data integration, transformation and quality assurance. This solution entirely automates ETL ingestion upon a single click (event trigger) and provides reusable ETL workflows for rapid ETL development. It also brings quick actionable insights and decision making into business.

To collect massive amounts of time-critical data, setting up data streaming pipelines is essential. The combination of Qlik Talend data integration and Amazon Kinesis provides a complete solution for easily building, running, and maintaining streaming data pipelines with low operational overhead. Learn how Qlik Talend with Amazon Kinesis supporting Spark streaming enables an accessible, no-code methodology for building Spark streaming pipelines leveraging the power of AWS.

Infor OS provides deep integration capabilities and includes Intelligent Open Network (ION), which is an interoperability and business process management platform designed to integrate applications, processes, people, and data to run your business. Infor ION enables you to easily integrate your Infor and non-Infor enterprise systems, whether they’re on-premises, in the cloud, or both. In this post, we discuss general scenarios and integration patterns while using ION.

As technology advances and business requirements change, organizations may find themselves needing to migrate away from legacy data processing systems like HBase, Solr, and HBase Indexer. Explore the advantages of migrating from HBase, Solr, and HBase indexer to a modern data ecosystem based on AWS, and dive deep on the discuss architecture, design, and pathways for implementation. This post offers insights and guidance from Rackspace for those looking to embark on this intricate migration journey.

A serverless architecture strategy reduces complexity and provides more flexibility in adopting the features and non-functional requirements needed to support market agility. In this post, walk through an example of an IoT use case and build a serverless scalable platform using Amazon Kinesis Data Firehose, Amazon Managed Service for Apache Flink, and MongoDB Realm. You’ll learn how easy it is to develop mobile and desktop applications on top of the data platform for different personas.

It can be complicated to maintain a robust, scalable, and reliable monitoring system that inputs terabytes of data under heavy traffic. Learn how Thundra has delivered 99.9 percent availability to customers since incorporating AWS services into its product. Thundra’s platform can handle scalability and availability challenges, recover both from partial failures and major outages, and support point-in-time recovery in case of disaster.

By hosting a Palo Alto Networks VM-Series firewall in an Amazon VPC, you can use AWS native cloud services—such as Amazon CloudWatch, Amazon Kinesis Data Streams, and AWS Lambda—to monitor your firewall for changes in configuration. This post explains why that’s desirable and walks you through the steps required to do it. You now have a way to monitor your Palo Alto Networks firewall that is very similar to how you monitor your AWS environment with AWS Config.