Systems | Development | Analytics | API | Testing

In a previous blog post (How To Survive an Apache Kafka® Outage) I outlined the effects on applications during partial or total Kafka cluster outages and proposed some architectural strategies to handle these types of service interruptions. The applications most heavily impacted by this type of outage are external interfaces that receive data, do not control request flow, and possibly perform some form of business transaction with the outside world before producing to Kafka.

With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI.

Explore how you can create a GraphQL API using BigQuery and open-source software Hasura.

In one of our recent blog posts, about six key predictions for Enterprise AI in 2024, we noted that while businesses will know which use cases they want to test, they likely won’t know which ones will deliver ROI against their AI and ML investments. That’s problematic, because in our first survey this year, we found that 57% of respondents’ boards expect a double-digit increase in revenue from AI/ML investments in the coming fiscal year, while 37% expect a single-digit increase.

2024 is going to be an important transition year for artificial intelligence. 2023 was the public debut of generative AI and large language models (LLMs), a year of amazement, excitement, occasional panic and, yes, more than a little bit of hype. The year ahead is when businesses begin to make the promise of advanced artificial intelligence real, and we’ll begin seeing the effects on how we work and live.