Category: Software

Containers are a leading method for packaging applications, with Kubernetes emerging as the top orchestration solution. You can enable secure and efficient self-service cluster provisioning on Amazon EKS using open-source tools like AWS Controllers for Kubernetes (ACK), Kyverno, and ArgoCD. This post demonstrates how enterprises can leverage these tools along with Nirmata’s Policy Manager to streamline EKS cluster management, apply security policies, and ensure compliance in a Kubernetes environment.

Explore how LenelS2, a Carrier company, transformed its existing OnGuard thick-client application into a software-as-a-service (SaaS) solution on AWS utilizing the multi-session feature of Amazon AppStream 2.0. With this approach, LenelS2 successfully streamed the OnGuard desktop application to users via the internet without the need to redesign the core application.

Organizations can achieve robust cloud network security by combining Arista Network Detection and Response (NDR) with AWS traffic mirroring. This provides deep packet inspection and threat monitoring without disrupting traffic flow. Arista’s AI-driven NDR platform maps the attack surface and detects threats across networks. The solution automates enabling traffic mirroring as AWS instances spin up/down, ensuring seamless security coverage in dynamic environments.

Cornerstone Consulting Group developed a plugin to simplify migrating on-premises or Amazon EC2 self-managed Apache Kafka clusters to Amazon MSK. The plugin automates MirrorMaker 2 replication, scales connectors, and integrates monitoring and notifications. It supports requirements like zero data loss, minimal code changes, auto-scaling, and performance/security parity. The plugin eases complex setup steps, working seamlessly for a smooth cutover to Amazon MSK after replication completes.

The new SaaS on AWS hub is a dynamic platform that serves as your one-stop destination for navigating the intricate landscape of building, launching, and managing SaaS applications on AWS. As you embark on your SaaS cloud journey, you’ll encounter a myriad of challenges, from crafting scalable architectures to fine-tuning performance and enhancing customer retention. SaaS on AWS is designed to accompany you through every step of this transformative process.

Amazon Security Lake centralizes security data from multiple AWS sources into a customer-owned data lake. A New Relic integration provides a single pane for performance and security telemetry, ingests Amazon Security Lake data, and allows threat detection via curated dashboards and anomaly alerts. This solution improves cloud security posture by consolidating data, providing insights, and enabling automated response to potential threats.

Amazon Athena allows analyzing petabytes of data directly with SQL queries or via analytics tools like ThoughtSpot. This post covers creating an IAM access key, two Amazon S3 buckets (one for data storage, one for query results), creating an Amazon Athena table from sample data using an AWS Glue crawler, and establishing a connection between Athena and ThoughtSpot. With the connection, ThoughtSpot can search and visualize the Athena data using AI capabilities.

Fine-tuning large language models (LLMs) is crucial for leveraging their full potential across industries. Quantiphi unveils how fine-tuning supercharges LLMs to deliver domain-specific AI solutions that redefine possibilities. From personalized healthcare to precise financial predictions and streamlined legal reviews, fine-tuned models offer transformative value and unleash the power of customized, efficient, and responsible generative AI deployments.

SaaS relies on the cloud for efficient delivery, but faces data challenges like tenant isolation, high storage costs, and compliance requirements. Amazon FSx for NetApp ONTAP solves these by providing multi-tenancy, storage efficiencies, persistent Kubernetes storage, and more. It enables SaaS providers to enhance agility while managing data availability, protection, security and costs. Arcesium reduced dev/test refreshes by 80% and overall costs by 46% using FSx for ONTAP.

Pinecone has developed a novel serverless vector database architecture optimized for AI workloads like retrieval-augmented generation. Built on AWS, it decouples storage and compute and enables efficient intermittent querying of large datasets. This provides elasticity, fresher data, and major cost savings over traditional architectures. Pinecone serverless removes bottlenecks to building more knowledgeable AI applications economically at scale on AWS.