Dynatrace
FEBRUARY 4, 2021
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Organizations can then integrate these skilled engineers at key points in the DevOps life cycle.
Dynatrace
FEBRUARY 24, 2021
SRE is the transformation of traditional operations practices by using software engineering and DevOps principles to improve the availability, performance, and scalability of releases by building resiliency into apps and infrastructure. Encouraging a shift-left approach , testing earlier in the development lifecycle. Efficiency.
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Dynatrace
NOVEMBER 6, 2023
In a recent webinar , Dynatrace DevOps activist Andi Grabner and senior software engineer Yarden Laifenfeld explored developer observability. Dynatrace enables teams to specify SLOs, such as latency, uptime, availability, and more. How do you know if this problem has business impact?
Dynatrace
FEBRUARY 4, 2021
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Organizations can then integrate these skilled engineers at key points in the DevOps life cycle.
Dynatrace
JANUARY 18, 2023
Site reliability engineering (SRE) is a software operations methodology that enables organizations to create highly reliable and scalable applications. SRE applies software engineering principles to operations and infrastructure processes. Site reliability engineers, or SREs, lead these efforts.
The Morning Paper
MARCH 3, 2020
The core algorithms (chain-replication, Paxos-based consensus) aren’t the stars of the show here, instead the paper focuses on how these algorithms are deployed, and the software engineering practices behind the creation of a mission-critical production system employing them. A guiding principle. Cells have seven nodes.
The Morning Paper
JULY 4, 2019
The ‘controlled’ part is important here because given the scale and complexity of the environment under test, the only meaningful place to do this is in production with real users. a bug fix, configuration change, new feature, or A/B test). Netflix’s system is deployed on the public cloud as complex set of interacting microservices.
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