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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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Implementing service-level objectives to improve software quality

Dynatrace

As more organizations embrace microservices-based architecture to deliver goods and services digitally, maintaining customer satisfaction has become exponentially more challenging. Instead, they can ensure that services comport with the pre-established benchmarks. Latency is the time that it takes a request to be served.

Software 264
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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Choosing a cloud DBMS: architectures and tradeoffs Tan et al., use the TPC-H benchmark to assess Redshift, Redshift Spectrum, Athena, Presto, Hive, and Vertica to find out what works best and the trade-offs involved. Each systems begins from a cold start unless explicitly stated otherwise in the results. VLDB’19.

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Plan Your Multi Cloud Strategy

Scalegrid

They can also bolster uptime and limit latency issues or potential downtimes. Register now for free and experience the seamless operation of your databases across multi-cloud and hybrid-cloud systems. By spreading your data and apps around, you can get your systems to work together more smoothly and make the most out of your budget.

Strategy 130
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Five Data-Loading Patterns To Improve Frontend Performance

Smashing Magazine

On your first try, you can use it as a benchmark for optimizations later. On design systems, UX, web performance and CSS/JS. Server caches help lower the latency between a Frontend and Backend; since key-value databases are faster than traditional relational SQL databases, it will significantly increase an API’s response time.

Cache 128
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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways.

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Why OpenStack is like a Crowdfunded Viking Movie

VoltDB

Telcos and Fortune 500 corporations used to spend years defining custom systems, down to the last cable. These systems were designed to have a lifetime of half a decade or more, and rapidly changing hardware meant that the initial deployment had to be sized for 5-7 years out. The “Public Private Cloud” folks.