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In this blog post, VGS will walk you through a real-world scenario where our team resolved persistent Kafka consumer group rebalancing problems for a high-throughput application.

The spotlight has intensified on VGS's innovative approach to empowering merchants to take control of their payment strategy.

Agentic commerce represents a transformative opportunity for companies poised to usher in the next era of e-commerce by using conversational AI. Especially when it comes to the payment process of agentic commerce.

The last few months have been a whirlwind of activity in the AI realm, with agentic commerce being a hot topic. We’re starting to slide towards calling this agentic payments, where agentic (being capable of acting independently) is really just a fancy word for an AI model acting on behalf of a user.

At VGS, we firmly believe that building closer, stronger relationships with our customers is the key to unlocking true success. Today, we are thrilled to announce a major milestone that embodies our core beliefs: VGS is expanding into the Asia-Pacific (APAC) geography with the launch of its Singapore region.

Agentic commerce is a term we have been using a lot lately at VGS. But what does agentic commerce mean? How do payments fit into the agentic commerce space? We broke it down for you so you can better understand agentic commerce as a whole and where payments fall into the AI commerce landscape.

AI is clearly mainstream. The skyrocketing user growth on the big AI platforms, the threat to Web 2.0 household names like Google and Meta, the roller coaster of the AI chip makers: AI has filled headlines for a few years now.

Today, one of the biggest payment challenges that exists is solving the last-mile of a purchase made using an AI agent. In agentic commerce, a truly universal platform needs to ensure a consumer can buy any product, from any merchant, using any payment method – and VGS has one of the only platforms that can make this possible.

For a long time VGS services have utilized common tools such as rate limiting and autoscaling to help meet the needs of our customers and elevate our infrastructure's resilience to meet the increasing demands of our customers. This has meant tackling a crucial challenge: implementing a robust workload partitioning architecture that both improves developer velocity and provides improved resiliency.

In the last few years, we’ve recognized the need to invest and elevate our infrastructure's resilience to meet the increasing demands of our customers such as building a platform that is able to recover when region level failure events occur.