Author: David Matthews, Sr. Architect AWS cloud costs can quickly spiral out of control if not managed effectively. This blog post explores key areas to focus on for optimizing your cloud spend, including rightsizing resources, leveraging reserved instances and savings plans, and implementing cost management strategies.
Author: Paul Kurzawinski, Cloud Engineer Introduction AWS Elastic Disaster Recovery (AWS DRS) is a service provided and delivered by Amazon Web Services that helps companies ensure business continuity in an unexpected disaster or downtime. The primary goal of AWS DRS is to replicate critical data and applications using affordable storage, minimal compute, and point-in-time recovery [...]
Author: Wend Tarpaga, Cloud Engineer Introduction Kubernetes, often abbreviated as k8s, has emerged as the de facto system for orchestrating containerized applications. Within this ecosystem, the concepts of "pods" and "nodes" are fundamental to understanding how Kubernetes manages and schedules applications. A pod is the smallest deployable unit created and managed by Kubernetes, while a [...]
Author: Cyprian Moye, Cloud Engineer Introduction Unmatched agility and efficiency in managing workloads can be achieved by integrating HorizontalPodAutoscaler (HPA) with Kubernetes deployments to ensure seamless performance. HPA can automatically adjust workload resources such as Deployments or StatefulSets, aligning application scaling with demand fluctuations without manual intervention. HPA offers the flexibility to scale resources up [...]
With enterprise-grade security and privacy, access to industry-leading foundation models, and generative AI-powered applications, AWS makes it easy to build and scale your generative AI applications, customized for your data, your use cases, and your customers.
With enterprise-grade security and privacy, access to industry-leading foundation models, and generative AI-powered applications, AWS makes it easy to build and scale your generative AI applications, customized for your data, your use cases, and your customers.
AWS provides a variety of services to construct solutions for Real-Time use cases. Understanding whether to use streams or queues, Lambda functions, Spark or Flink, can be difficult, as each of these technologies has strengths, peculiarities, cost structures, and different scaling approaches.
Machine learning expands the intelligent capabilities of your organization. The Uturn MLOps Build Lab steps your data engineers through the creation and deployment of your ML pipelines, delivering your real world use cases as the output of the engagement.
The story of your organization is written in the data generated by your customers, ledgers, CRM, application logs, partner files, and countless other sources. To understand that story, the data needs to be presented in a way that can be digested by the minds of your decision makers, whether through BI reporting, GenAI, or other natural language processing tools.
Amount, a leading-edge provider of software based financial solutions located in Chicago Illinois has developed and launched an application platform that seamlessly enables banks and financial institutions to traverse the digital divide, unify data, and gain insight to improve the consumer experience.