Remove Infrastructure Remove Latency Remove Software Engineering
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.

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SRE vs DevOps: What you need to know

Dynatrace

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. Reduced latency. Investing in automation and tooling to avoid toil. SRE vs DevOps?

DevOps 268
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Site reliability engineering: 5 things you need to know

Dynatrace

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. A major goal of SRE is to reduce duplication or redundancy of effort as much as possible.

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Site reliability engineering: 5 things to you need to know

Dynatrace

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. A major goal of SRE is to reduce duplication or redundancy of effort as much as possible.

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Site reliability done right: 5 SRE best practices that deliver on business objectives

Dynatrace

How site reliability engineering affects organizations’ bottom line SRE applies the disciplines of software engineering to infrastructure management, both on-premises and in the cloud. However, cloud complexity has made software delivery challenging. But the transition to SRE maturity is not always easy.

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Designing Instagram

High Scalability

FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency. Optimization.

Design 334
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Automated observability, security, and reliability at scale

Dynatrace

While infrastructure has historically been treated as a bottleneck where proper scaling and compute power are applied to improve performance, these aspects are now typically addressed by hyperscalers that offer cloud-based infrastructure and infrastructure as a service.