Cloudera Data Platform 7.2.1 introduces fine-grained authorization for access to Azure Data Lake Storage using Apache Ranger policies. Cloudera and Microsoft have been working together closely on this integration, which greatly simplifies the security administration of access to ADLS-Gen2 cloud storage.
Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Data architects deal with constantly evolving workloads and business analysts must balance the urgency and importance of a concurrent user population that continues to grow.
More and more companies are beginning to turn to Development and the cloud as a way to improve their software teams. Whilst it used to be that development and operations were seen as separate, that view has now changed. Linking the two leads to better communication, faster development times, and the ability to stay on top of things.
In our last two posts, we talked with Deloitte’s Marc Beierschoder and Martin Mannion respectively about the requirement organizations have to deploy their data and analytics, quickly, into a hybrid environment. On top of that, there is the fundamental aspect of consistent security and governance of your enterprise data cloud and need for multiple users with different requirements to access data flexibly.
This blog post will present a simple “hello world” kind of example on how to get data that is stored in S3 indexed and served by an Apache Solr service hosted in a Data Discovery and Exploration cluster in CDP. For the curious: DDE is a pre-templeted Solr-optimized cluster deployment option in CDP, and recently released in tech preview. We will only cover AWS and S3 environments in this blog.
Recently, Cloudera announced the release of Cloudera CDP Private Cloud, delivering the final component of our hybrid cloud strategy. There’s nothing comparable to it in the industry. CDP Private Cloud offers benefits of a public cloud architecture—autoscaling, isolation, agile provisioning, etc.—in an on-premise environment.
There’s no doubt that cloud has become ubiquitous, and thank goodness for that in 2020. We wouldn’t have survived the challenges of this year without cloud. It’s supported everything, from the sudden changes in the way we work to the way we access healthcare and even shop for vital goods. While cloud is the vehicle, it’s what sits on it that makes it so valuable — data.
In the last blog with Deloitte’s Marc Beierschoder, we talked about what the hybrid cloud is, why it can benefit a business and what the key blockers often are in implementation. You can read it here.
We recently Googled the manufacturing use case “predictive maintenance” and was astonished by the results there were 82 MILLION results returned. Next, we Googled “process optimization” and it yielded even more results – 302 MILLION. Clearly, these use cases are top of mind in today’s manufacturing landscape, considering digital transformation will deliver $11 Trillion USD in economic value by 2025.
In support of our partnership with AWS and the AWS DevOps Competency program, we’re re-examining how some of our major customers are using Kong with AWS. To this end, let’s look at our popular case study with TUNE.
