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DNS Zone Setup Best Practices on Azure

Cloudera

Customers can request this entitlement to be set either through a JIRA ticket or have their Cloudera solution engineer to make the request on their behalf. The sole drawback of this option is that it does not apply to data engineering, since that data service will create and use a MySQL private DNS zone on the fly.

Azure 52
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Network Traffic Intelligence for ISPs

Kentik

With the advent of open source big data engines, the power of big data network analytics has seemed tantalizingly close. So they innovated a purpose-built big data engine for network flows and related data. The skills and resources required for open source don’t match core ISP priorities.

Network 40
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Now Available: Cloudera Data Science Workbench Release 1.4

Cloudera

With Models, data scientists can simply select a Python or R function within a project file, and Cloudera Data Science Workbench will: create a snapshot of model code, saved model parameters, and dependencies. deploy and start a specified number of model API replicas, automatically load balanced.

Data 41
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Practical Steps for Enhancing Reliability in Cloud Networks - Part I

Kentik

Highly available networks are resistant to failures or interruptions that lead to downtime and can be achieved via various strategies, including redundancy, savvy configuration, and architectural services like load balancing. Resiliency. Resilient networks can handle attacks, dropped connections, and interrupted workflows.

Network 104
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The Why and How of Interface Classification

Kentik

The flow metadata stored in the Kentik Data Engine (our backend) isn’t simply what comes to us from network devices; instead it is enhanced with a variety of derived or externally acquired information (e.g. The multiple-count issue has (naturally) been anticipated in Kentik Detect from the outset. BGP, GeoIP, SNMP, etc.)

Network 40
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Building Cloud Native Data Apps on Premises

Cloudera

It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment. The platform offers advanced capabilities for data warehousing (DW), data engineering (DE), and machine learning (ML), with built-in data protection, security, and governance.

Cloud 63
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When Reliability Goes Wrong in Cloud Networks

Kentik

Here are a few examples of potential unintended side effects of relying on multizonal infrastructure for resiliency: Split-brain scenario : In a multizonal deployment with redundant components, such as load balancers or routers, a split-brain scenario can occur.

Network 52