Amazon DynamoDB is a serverless, NoSQL database service that enables you to develop modern applications at any scale. DynamoDB on-demand mode offers a truly serverless experience that can serve millions of requests per second without capacity planning, and automatic scale down to zero when no requests are being issued against the table. With on-demand mode’s simple, pay-per-request pricing model, you don’t have to worry about idle capacity because you only pay for the capacity you actually use. Customers increasingly use on-demand mode to build new applications where the database workload is ..read more

The intricate hierarchical data structures in data warehouses and lakes sourced from diverse origins can make data modeling a protracted and error-prone process. To quickly adapt and create data models that meet evolving business requirements without having to rework them excessively, you need data models that are flexible, modular and adaptable enough to accommodate many requirements. This requires advanced technologies, proficient personnel, and robust methodologies. The advancements in generative AI offer numerous opportunities to address these challenges. Multimodal large language models ..read more

In the realm of modern application design, developers have a range of choices available to them for crafting architectures that are not only simple, but also scalable, performant and resilient. Container platforms like Kubernetes (k8s) offer users the ability to seamlessly adjust node and pod specifications, so that services can scale. This scalability does not come at the expense of elasticity, and also ensures consistent performance for service consumers. So it’s no surprise that Kubernetes has become the de facto standard for building distributed and resilient systems in medium-to-large o ..read more

Ensuring application and service teams have the resources they need is crucial for platform administrators. Fleet team management features in Google Kubernetes Engine (GKE) make this easier, allowing each team to function as a separate “tenant” within a fleet. In conjunction with Config Sync, a GitOps service in GKE, platform administrators can streamline resource management for their teams across the fleet. Specifically, with Config Sync team scopes, platform admins can define fleet-wide and team-specific cluster configurations such as resource quotas and network policies, allowing each app ..read more

Introduction One challenge with any distributed system, including Workflows, is ensuring that requests sent from one service to another are processed exactly once, when needed; for example, when placing a customer order in a shipping queue, withdrawing funds from a bank account, or processing a payment. In this blog post, we’ll provide an example of a website invoking Workflows, and Workflows in turn invoking a Cloud Function. We’ll show how to make sure both Workflows and the Cloud Function logic only runs once. We’ll also talk about how to invoke Workflows exactly once when using HTTP callb ..read more

AWS Database Migration Service (AWS DMS) makes it possible to replicate to Amazon Kinesis Data Streams from relational databases, data warehouses, NoSQL databases, and other types of data stores. You can use Kinesis data streams to collect and process large streams of data records in real time. Replicating data changes to a Kinesis data stream is usually expected to be long-running and highly performant. AWS DMS offers multi-threaded full load and change data capture (CDC) task settings to help increase the speed of data transfer and the performance of CDC. Customers often ask the following q ..read more

In Part 1 of this series, we discussed the high-level architecture of multi-threaded full load and change data capture (CDC) settings to tune related parameters for better performance to replicate data to an Amazon Kinesis Data Streams target using AWS Database Migration Service (AWS DMS). In Part 2, we provided some examples of how we can yield different results by adjusting the multi-threaded settings. In this post, we discuss other key considerations when using Kinesis Data Streams as a target. Prerequisites To follow along with this post, you should have familiarity with the following AWS ..read more

In Part 1 of this series, we discussed the architecture of multi-threaded full load and change data capture (CDC) settings, and considerations and best practices for configuring various parameters when replicating data using AWS Database Migration Service (AWS DMS) from a relational database system to Amazon Kinesis Data Streams. In this post, we demonstrate the effect of changing various parameters on the throughput for the full load and CDC phases. The main parameters we considered are the AWS DMS settings for the parallel load and parallel apply and the number of shards in Kinesis Data Str ..read more

In the ever-evolving landscape of enterprise integration, staying ahead means aligning with the best solutions. We at SnapLogic are thrilled … The post Elevating Generative Integration Puts SnapLogic in the Spotlight in Latest tPaaS Analyst Report appeared first on SnapLogic. Read MoreSnapLogic ..read more

Kubernetes Operators A Kubernetes Operator is a method of packaging, deploying, and managing a Kubernetes application. Conceptually, an Operator takes human operational knowledge and encodes it into software that is packaged with the application. This could include how to deploy a complex application, how to handle failing nodes or persistent storage, and how to upgrade […] Source CloudTweaksRead More ..read more