Systems | Development | Analytics | API | Testing

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What is new in Cloudera Streaming Analytics 1.4?

At the end of March, we released the first version of Cloudera SQL StreamBuilder as part of CSA 1.3. It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. Since then, we have been working hard to expose the full power of Apache Flink SQL and the existing Data Warehousing tools in CDP to combine it into a state-of-the-art real-time analytics platform.

Cloudera named a Strong Performer in The Forrester Wave: Streaming Analytics, Q2 2021

Cloudera has been named as a Strong Performer in the Forrester Wave for Streaming Analytics, Q2 2021. We are excited to be recognized in this wave at, what we consider to be, such a strong position. We are proud to have been named as one of “The 14 providers that matter most” in streaming analytics. The report states that richness of analytics, development tool options and near-effortless scalability are what streaming analytics customers should look for in a provider.

Cloudera Streaming Analytics 1.4: the unification of SQL batch and streaming

In October of 2020 Cloudera acquired Eventador and Cloudera Streaming Analytics (CSA) 1.3.0 was released early in 2021. It was the first release to incorporate SQL Stream Builder (SSB) from the acquisition, and brought rich SQL processing to the already robust Apache Flink offering. The team’s focus turned to bringing Flink Data Definition Language (DDL) and the batch interface into SSB with that completed.

How to Turn Your Data Into Insights: the Art and Science of E-Discovery

The thing about data is there’s no end to how much of it you can collect and keep. Each day, if you’re like most of the global banks I work with, you’re generating oceans of the stuff. Yet the bulk of it will never be very helpful or even relevant to your day-to-day business decisions.

Iguazio Product tutorial 2021

The Iguazio Data Science Platform enables you to develop, deploy and manage real-time AI applications at scale. It provides data science, data engineering and DevOps teams with one platform to operationalize machine learning and rapidly deploy operational ML pipelines. The platform includes an online and offline feature store, fully integrated with automated model monitoring and drift detection, model serving and dynamic scaling capabilities, all packaged in an open and managed platform.

Making k6 extensions using xk6, with Iván Szkiba and Mihail Stoykov (k6 Office Hours)

In this office hours, Nicole and Simme are joined by Iván Szkiba, a system architect at NNG LCC, and Mihail Stoikov, a software engineer at k6, to talk about how to make a k6 extension. We also discuss the rationale behind extensions Iván has created and how to get started if you're thinking about making an extension as well.

What is the best way for automated mobile browser testing on real devices?

Mobiles have become a part and parcel of our lives. Smartphone penetration has seen an increase for the past decade with some countries such as the UK leading the race with as high as 82%. In a world with a 7.5 billion population, 4.3 billion people are projected (by 2023) to keep this small device in their pockets and use it daily. Although the pandemic slowed down this growth, Gartner projects the sales would be up 11% in 2021. Surprised by these stats?

How to reduce the risk of missing bugs before deploying on production?

It’s very common to have a handful of issues when deploying a software change to production because you are replacing a working version of your software or application with the one having the desired changes. Your testing team might have thoroughly tested the new version of the software, but still, the doubt of whether it will work as intended or not is always there.