Technology juggernauts–despite their larger staffs and budgets–still face the “cognitive load” for DevOps that many organizations deal with day-to-day. That’s what led Spotify to build Backstage, which supports DevOps and platform engineering practices for the creation of developer portals.
Contact centers (or call centers) are crucial touchpoints for customer interactions across various channels, including phone, email, SMS, live chat, and more. As businesses strive to deliver exceptional customer experiences (particularly in high-volume consumer-facing industries such as financial services, telecom, travel, insurance, healthcare, online retail, etc.), it’s imperative to optimize contact center performance. How imperative?
HAProxy Fusion Control Plane gives you power to simplify, scale, and secure your HAProxy Enterprise infrastructure using a centralized orchestration solution, making it easier to extend HAProxy Enterprise’s security and performance across on-premises and cloud-hosted applications. With the release of version 1.1, HAProxy Fusion is more secure, more flexible, and even easier to use.
HAProxy 2.8 is now available, and HAProxy Enterprise 2.8 will be released later this year. Register for the live webinar HAProxy 2.8 Feature Roundup to learn more about this release and participate in a live Q&A with our experts.
When people hear the word “migration,” they typically think about migrating from on-prem to the cloud. In reality, companies do migrations of varying types and sizes all the time. However, many teams delay making critical migrations or technical upgrades because they don’t have the proper tools and frameworks to de-risk the process.
In a previous blog post, we built a small Python application that queries Elasticsearch using a mix of vector search and BM25 to help find the most relevant results in a proprietary data set. The top hit is then passed to OpenAI, which answers the question for us. In this blog, we will instrument a Python application that uses OpenAI and analyze its performance, as well as the cost to run the application.
In a recent blog post, we discussed how ChatGPT and Elasticsearch® can work together to help manage proprietary data more effectively. By utilizing Elasticsearch's search capabilities and ChatGPT's contextual understanding, we demonstrated how the resulting outcomes can be improved. In this post, we discuss how users’ experience can be further enhanced with the addition of facets, filtering, and additional context.
