Remove Benchmarking Remove Engineering Remove Latency Remove Systems
article thumbnail

Implementing service-level objectives to improve software quality

Dynatrace

Instead, they can ensure that services comport with the pre-established benchmarks. SLOs can be a great way for DevOps and infrastructure teams to use data and performance expectations to make decisions, such as whether to release and where engineers should focus their time. Latency is the time that it takes a request to be served.

Software 259
article thumbnail

The evolution of single-core bandwidth in multicore processors

John McCalpin

For most high-end processors these values have remained in the range of 75% to 85% of the peak DRAM bandwidth of the system over the past 15-20 years — an amazing accomplishment given the increase in core count (with its associated cache coherence issues), number of DRAM channels, and ever-increasing pipelining of the DRAMs themselves.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Maximizing Performance of AWS RDS for MySQL with Dedicated Log Volumes

Percona

DLVs are particularly advantageous for databases with large allocated storage, high I/O per second (IOPS) requirements, or latency-sensitive workloads. Amazon RDS extends support for DLVs across various database engines: MariaDB: 10.6.7 Who can benefit from DLV? and later v10 versions MySQL: 8.0.28 and later v13 versions, 14.7

AWS 99
article thumbnail

Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

article thumbnail

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

The Morning Paper

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook , Cao et al., Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads.

article thumbnail

Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

article thumbnail

Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which which is difficult when troubleshooting distributed systems. We needed to increase engineering productivity via distributed request tracing.