Abhishek Tiwari
DECEMBER 27, 2017
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.
Dynatrace
OCTOBER 4, 2022
Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. However, organizations must structure and store data inputs in a specific format to enable extract, transform, and load processes, and efficiently query this data. Massively parallel processing.
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Dynatrace
APRIL 20, 2023
-based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data. To grasp the challenges of multifeatured, cross-team cooperation dealing with observability data, consider the content of the logs generated. Dissolving data silos.
The Netflix TechBlog
MARCH 4, 2024
Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. In this way, no human intervention is required in the remediation process. Multi-objective optimizations. user name).
Percona
JANUARY 19, 2023
Compression: Compression is the process of restructuring the data by changing its encoding in order to store it in fewer bytes. There are many compression tools and algorithms for data out there. It was developed for optimizing data storage and access for big data sets. 1 mysql mysql 592K Dec 30 02:48 tb1.ibd
Testsigma
MAY 14, 2021
It provides better and simple disaster recovery because the process is automated. Definitely, cloud testing will involve some new technology and the testers will need to learn them. When we decide to start cloud-based testing in a project then we need to decide how we are going to manage the whole process of cloud-based testing.
The Netflix TechBlog
MARCH 2, 2021
I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. My academic credentials definitely helped on the technical side.
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