Dynatrace
JULY 6, 2022
IT automation, DevOps, and DevSecOps go together. DevOps and DevSecOps methodologies are often associated with automating IT processes because they have standardized procedures that organizations should apply consistently across teams and organizations. AI that is based on machine learning needs to be trained.
O'Reilly
FEBRUARY 18, 2020
Also: infrastructure and operations is trending up, while DevOps is trending down. These trends are also implicated in the rise of infrastructure and ops, which reflects both the limitations of DevOps and the challenges posed by the shift to cloud native design. A drill-down into data, AI, and ML topics. Coincidence?
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Percona Community
OCTOBER 14, 2020
(next day) Abstract Not so long ago, operations specialists worked much like today’s data engineers do: with specialized skills, they were the people who kept sites running, who responded to emergencies, and who—unfortunately—spent much of their time dealing with incidents and other “fires.”
High Scalability
MARCH 17, 2020
Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.
High Scalability
MARCH 3, 2020
Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.
High Scalability
FEBRUARY 18, 2020
Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.
Abhishek Tiwari
FEBRUARY 26, 2020
Skills++: Induct DevOps, People Leadership 31-50 Engineers Focus: Maintain growth trajectory of product in the market and start growing multi-layer people and technical leadership. Now building data-driven apps and data services and where necessary incorporating machine learning web service offered by public cloud providers.
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