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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. offers the Software Watchdog specifically designed for this purpose.

Metrics 130
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Container security: What it is, why it’s tricky, and how to do it right

Dynatrace

Many good security tools provide that function, and benchmarks from the Center for Internet Security (CIS) are clear and prescriptive. These products see systems from the “outside” perspective—which is to say, the attacker’s perspective. Harden the host operating system. Why is container security tricky?

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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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What Is a Workload in Cloud Computing

Scalegrid

While managing cloud workloads offers numerous benefits, it also presents several challenges such as security risks, compliance issues, and resource optimization, which can be addressed effectively with tools like ScaleGrid, offering features like encryption, disaster recovery, and real-time resource optimization for diverse databases.

Cloud 130
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The Surprising Effectiveness of Non-Overlapping, Sensitivity-Based Performance Models

John McCalpin

This was a keynote presentation at the “2nd International Workshop on Performance Modeling: Methods and Applications” (PMMA16), June 23, 2016, Frankfurt, Germany (in conjunction with ISC16 ). This data is from the 2007 presentation.

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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., A typical architecture diagram for one of these services looks like this: Suitably armed with a set of benchmark microservices applications, the investigation can begin! ASPLOS’19.

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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

on Myths and Legends of High Performance Computing  — it’s a somewhat light-hearted look at some of the same issues by the leader of the team that built the Fugaku system I mention below. HPCG is led by Japan’s RIKEN Fugaku system at 16 petaflops, which is 3% of it’s peak capacity. petaflops, which is 0.8% of peak capacity.