Highly Scalable
AUGUST 20, 2013
The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility. Pipelining. In-Stream Processing Patterns.
Dynatrace
MAY 1, 2023
In addition to improved IT operational efficiency at a lower cost, ITOA also enhances digital experience monitoring for increased customer engagement and satisfaction. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.
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Dynatrace
OCTOBER 4, 2022
Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Traditional solutions and approaches are inefficient given the number of manual tasks that are required for effective log data ingest.
Dynatrace
APRIL 20, 2023
With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.
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. These next-generation cloud monitoring tools present reports — including metrics, performance, and incident detection — visually via dashboards.
Dynatrace
FEBRUARY 16, 2023
How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.
Dynatrace
JULY 5, 2022
AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. But AIOps also improves metrics that matter to the bottom line. For example: Greater IT staff efficiency. What is AIOps, and how does it work?
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