Category: Storage

This blog post was last reviewed/updated August, 2022. The updated version shown below is based on working backwards from a customer need to ensure data consistency post migration, to a modernized microservice architecture. A queuing system is composed of producers and consumers. A producer enqueues messages (writes messages to a database) and a consumer dequeues […]

Organizations in all industries are innovating their application stack through modernization. Developers have found that modular architecture patterns, serverless operational models, and agile development processes provide great benefits. They offer faster innovation, reduced risk, and reduction in total cost of ownership. Security organizations must evolve and innovate as well. But security practitioners often find themselves […]

Many AWS services have features to help you build and manage a multi-Region architecture, but identifying those capabilities across 200+ services can be overwhelming. In this 3-part blog series, we filter through those 200+ services and focus on those that have specific features to assist you in building multi-Region applications. In Part 1, we’ll build […]

Many aspects of autonomous driving (AD) system development are based on data that capture real-life driving scenarios. Therefore, research and development professionals working on AD systems need to handle an ever-changing array of interesting datasets composed from the real-life driving data.  In this blog post, we address a key problem in AD system development, which […]

With the increased adoption of critical applications running in the cloud, customers often find themselves revisiting traditional strategies that were adopted for on-premises workloads. When it comes to IBM DB2, one of the first decisions to make is to decide what backup and restore method will be used. In this blog post, we will show […]

In process manufacturing, it’s important to fetch real-time data from data historians to support decisions-based analytics. Most manufacturing use cases require real-time data for early identification and mitigation of manufacturing issues. A limited set of commercial off-the-shelf (COTS) tools integrate with OSIsoft’s PI Historian for real-time data. However, each integration requires months of development effort, […]

Organizations have been collecting text data for years. Text data can help you intelligently address a range of challenges, from customer experience to analytics. These mixed language, unstructured datasets can contain a wealth of information within business documents, emails, and webpages. If you’re able to process and interpret it, this information can provide insight that […]

Before cloud data warehouses (CDWs), many organizations used hyper-converged infrastructure (HCI) for data analytics. HCIs pack storage, compute, networking, and management capabilities into a single “box” that you can plug into your data centers. However, because of its legacy architecture, an HCI is limited in how much it can scale storage and compute and continue […]

Amenity Analytics develops enterprise natural language processing (NLP) platforms for the finance, insurance, and media industries that extract critical insights from mountains of documents. We provide a scalable way for businesses to get a human-level understanding of information from text. In this blog post, we will show how Amenity Analytics improved the continuous integration (CI) […]

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]