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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

Traditional computing models rely on virtual or physical machines, where each instance includes a complete operating system, CPU cycles, and memory. There is no need to plan for extra resources, update operating systems, or install frameworks. The provider is essentially your system administrator.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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What is AWS Lambda?

Dynatrace

You will likely need to write code to integrate systems and handle complex tasks or incoming network requests. As a bonus, operations staff never needs to update operating systems or hardware, because AWS manages servers with no stoppage of application functionality. Optimizing Lambda for performance.

Lambda 179
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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., The paper examines the implications of microservices at the hardware, OS and networking stack, cluster management, and application framework levels, as well as the impact of tail latency.

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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. We formulate the problem as a Mixed Integer Program (MIP).

Cache 251
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A tale of two abstractions: the case for object space

The Morning Paper

. …software operating on persistent data structures requires "global" pointers that remain valid after a process terminates, while hardware requires that a diverse set of devices all have the same mappings they need for bulk transfers to and from memory, and that they be able to do so for a potentially heterogeneous memory system.

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Monitoring Distributed Systems

Dotcom-Montior

With the rapid advancements in web application technologies, programming languages, cloud computing services, microservices, hybrid environments, etc., monitoring distributed systems becomes much more difficult to carry out and manage. Software and hardware components are autonomous and execute tasks concurrently.

Systems 74