Visionet redesigned the biotech company’s BI infrastructure and deployed their existing 10-node Qlik cluster on AWS to ensure scalability and pull their data together into one simple, easy-to-analyze dashboard.
Our client is one of the leading pharmaceutical and biotechnology companies in the US. It relies on the use of massive amounts of data to develop new products, solutions, and cures. However, the company faced the following challenges:
The client is a global retailer of vitamins and nutritional supplements that operates over 300 stores across the US.
The client was looking for a streamlined and mobile-friendly eCommerce experience with fully integrated omnichannel capabilities.
Using a carefully crafted digital strategy, Visionet delivered an omnichannel customer experience in record time. We implemented and unified their eCommerce and ERP platforms to create a seamless, consistent, and personalized experience across platforms and call center.
Visionet performed a comprehensive cloud analysis, identified significant overprovisioning of Azure resources, and recommended VM right-sizing and reduction of premium SSD storage for lower cloud spend.
Visionet developed an end-to-end, scalable digital asset management platform that solidified Tenovos’s marketing and creative ecosystems as well as improved their team’s efficiency, reduced costs, increased flexibility, and ensured seamless customizability.
Tenovos is a leading digital asset management company that transforms the way brands connect with their customers. Their platform enables consumer brands to augment their content with intelligence using transformative data.
Our client is a leading global luxury apparel and accessories brand, selling its products in prestige locations worldwide via retail stores, factory outlet stores, and its eCommerce website.
Due to poor management of IT infrastructure hosted on Azure, the client’s website faced a myriad of outages and security concerns.
Business processes were also fragmented across three ERP systems, which made it difficult to integrate information. This led to high cost of ownership, operational inefficiencies, and order fulfillment times.
The imminent shift to cloud and microservice application architectures has spurred on a rapid increase in scale and complexity. Legacy monitoring tools simply can’t keep up with the explosive amounts of data these environments generate and can’t deliver the required system-wide visibility to ensure optimal cloud application performance. This very purpose is served by observability.
Today’s IT teams thrive in dynamic environments leveraging agile methodologies, continuous integration/continuous delivery, and distributed services across the multi-cloud realm. With a sprawl of microservices and containers, and increased release velocity, it becomes impossible for the human eye to cope with the complexity that defines these environments. The increasingly digital landscape of today stipulates a seamless user experience, demanding IT and DevOps teams to resolve issues before they escalate.
Product engineering and software development are intricate processes. Companies rely on efficient development methodologies such as Agile development to seamlessly govern the software development lifecycle. In each Agile sprint, developers build new features, and quality assurance engineers have to test the application. However, in such cases, manual testing is inefficient and more time-consuming. Therefore, to make the entire process more efficient, businesses are leveraging test automation best practices to cope with continuous product development and delivery.
Why is container observability so important in today’s cloud native environments?