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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

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What is IT automation?

Dynatrace

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. When monitoring tools release a stream of alerts, teams can easily identify which ones are false and assess whether an event requires human intervention.

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A case for ELT

Abhishek Tiwari

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. In addition, this approach is more tailored for both structured as well unstructured data sets. Classic ETL.