Remove Benchmarking Remove Latency Remove Metrics
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Implementing service-level objectives to improve software quality

Dynatrace

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. Instead, they can ensure that services comport with the pre-established benchmarks. This process includes benchmarking realistic SLO targets based on statistical and probabilistic analysis from Dynatrace.

Software 276
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Performance and Scalability Analysis of Redis and Memcached

DZone

This article takes a plunge into the comparative analysis of these two cult technologies, highlights the critical performance metrics concerning scalability considerations, and, through real-world use cases, gives you the clarity to confidently make an informed decision.

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Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Using this approach, we observed latencies ranging from 1 to 10 seconds, averaging 7.4 Blame The Notebook Now that we have an objective metric for the slowness, let’s officially start our investigation. Examining the code, we see that this function call stack is triggered when an API endpoint /metrics/v1 is called from the UI.

Latency 217
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PostgreSQL Benchmark: ScaleGrid vs. Amazon RDS

Scalegrid

Performance Benchmarking of PostgreSQL on ScaleGrid vs. AWS RDS Using Sysbench This article evaluates PostgreSQL’s performance on ScaleGrid and AWS RDS, focusing on versions 13, 14, and 15. This study benchmarks PostgreSQL performance across two leading managed database platforms—ScaleGrid and AWS RDS—using versions 13, 14, and 15.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

You will need to know which monitoring metrics for Redis to watch and a tool to monitor these critical server metrics to ensure its health. Redis returns a big list of database metrics when you run the info command on the Redis shell. You can pick a smart selection of relevant metrics from these.

Metrics 130
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

ShuffleBench i s a benchmarking tool for evaluating the performance of modern stream processing frameworks. Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. This significantly increases event latency.

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Edgar: Solving Mysteries Faster with Observability

The Netflix TechBlog

Tracing as a foundation Logs, metrics, and traces are the three pillars of observability. Metrics communicate what’s happening on a macro scale, traces illustrate the ecosystem of an isolated request, and the logs provide a detail-rich snapshot into what happened within a service. Is this an anomaly or are we dealing with a pattern?

Latency 299