Analysis Architecture Big Data Storage 
Scalegrid
FEBRUARY 8, 2024
A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.
Dynatrace
OCTOBER 4, 2022
Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Still, it is critical to collect, store, and make easily accessible these massive amounts of log data for analysis.
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Dynatrace
APRIL 20, 2023
Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. Traditional log analysis evaluates logs and enables organizations to mitigate myriad risks and meet compliance regulations.
Dynatrace
OCTOBER 4, 2022
While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data management.
The Netflix TechBlog
MAY 4, 2023
When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.
Dynatrace
JANUARY 11, 2023
As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. Cloud storage monitoring. Hybrid cloud combines an on-premises or private data center with public cloud infrastructure.
Dynatrace
FEBRUARY 16, 2023
As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. This creates such high cardinality that it blows up existing metrics databases.”
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