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Observability for Your Kubernetes Microservices Using Kuma and Prometheus

A year ago, Harry Bagdi wrote an amazingly helpful blog post on observability for microservices. And by comparing titles, it becomes obvious that my blog post draws inspiration from his work. To be honest, that statement on drawing inspiration from Harry extends well beyond this one blog post – but enough about that magnificent man and more on why I chose to revisit his blog. When he published it, our company was doing an amazing job at one thing: API gateways.

Difference Between Microservices and Web Services

The differences between microservices and web services deal with different concepts in modern application design. A microservice is a small, independent, application that performs a highly focused service as well as possible. A web service is an internet-based interface that makes the “services” of one application available to applications running on different platforms.

Machine learning in production: Human error is inevitable, here's how to prepare.

You did it. You have machine learning capabilities up and running in your organization. Success! What started as a few nascent experiments (and maybe a few failures) are now carefully constructed models racing along in full production—with the ability to scale into the hundreds or thousands of productional models in sight. Assembling your expert team of data scientists and custodians seems like a distant memory. Now you’re looking ahead to the future—growth, innovation, revenue!

Augmented Analytics - How Associative and AI Technologies Are Changing the Face of Analytics

It’s hard to believe that we are now over 30 years into data warehousing. In that time, we have seen major changes in tools to help user report on and analyse data. In the last twenty years, we have seen the evolution from reporting, ad hoc analysis and advanced analytics. Today, BI/Analytics is a mature market with self-service BI and visual analysis standards in most organisations with self-service data preparation also widely deployed.

For Business Agility, Focus on Data - Not on Data Management

Effectively managing data in an edge-to-cloud world is becoming increasingly complex. Enterprises need data management simplicity and agility to maximize the benefits they can get from their data. The enterprise that will succeed will shift resources away from mundane data management tasks to focus on using data to innovate and add business value.

Fresh Features: The beautiful, flexible design experience

Yellowfin 9 is defined by the belief that design matters. The ability to create a cohesive design look and feel across analytics dashboards and reports is particularly crucial for independent software vendors (ISVs) that embed analytics into their applications. Interestingly, when you take a look at the wider analytics market, few vendors are providing the toolkit that designers and developers need to build the analytical experiences they want.

How to choose your ETL tool

ETL tools help companies to streamline and enhance their data operations. They automate the repetitive tasks involved in extracting raw data from sources, transforming data into a consumable format and loading into data warehouses, where it is ready to be analyzed. With so many offerings available to you, all of which do the heavy lifting ‘out of the box’, it is hard to discern which ETL tool is best suited to your needs.