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Monitoring

Using BigQuery Administrator for real-time monitoring

When doing analytics at scale with BigQuery, understanding what is happening and being able to take action in real-time is critical. To that end, we are happy to announce Resource Charts for BigQuery Administrator. Resources Charts provide a native, out-of-the-box experience for real-time monitoring and troubleshooting of your BigQuery environments.

Picking up the pieces of your monolith breakdown

A decade ago, all developers could talk about was breaking down the monolith and event-driven architectures. Especially in the financial services industry, to become more nimble and accelerate their application delivery. They leveraged messaging systems to decouple the application, and specifically Apache Kafka has transitioned from being a data integration technology to the leading messaging system for microservices.

How to accelerate digital transformation with Automated Business Monitoring

With automation becoming more user-friendly and streamlined than ever before, it's understandable organizations across sectors are examining how it can enhance their analytics capability and accelerate their business shift toward digital transformation.

Kafka infrastructure, monitoring, data - Which is your priority?

At the heart of Kafka is real-time data. With data at the center of any Kafka environment, it should be the area that gets the most attention, but typically it gets the least. This happens because we see most organizations split their Kafka efforts into three areas: infrastructure, monitoring, and data operations.

Automated business monitoring: Why you need it now

One of the things we've done a lot of work on at Yellowfin is automated business monitoring (ABM), specifically with our product Yellowfin Signals. It can truly transform organizations and help them to deliver insights faster, ones they can react on. ABM has been in the market for about five years but we haven't seen it take off just yet. One reason is that automated business monitoring challenges the status quo of the data analyst.