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Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98
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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

The mean and percentile measurements hide this structure, but the rest of this post will show how the structure can be measured and analyzed so that you can figure out a useful model of your system, understand what is driving the long tail of latencies and come up with better SLAs and measures of capacity.

Lambda 98
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Fast key-value stores: an idea whose time has come and gone

The Morning Paper

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. The network latency of fetching data over the network, even considering fast data center networks. Oh, you mean a cache?

Cache 79
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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Which I’m quite happy to see as my most recent data pipeline is based around Lambda, S3, and Athena, and it’s been working great for my use case. For query executors that can be frequently started and stopped the authors explore performance with cold and warm caches (where applicable), and also the horizontal and vertical scaling performance.

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Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

All Things Distributed

I am excited to share with you that today we are expanding DynamoDB with streams, cross-region replication, and database triggers. Streams provide you with the underlying infrastructure to create new applications, such as continuously updated free-text search indexes, caches, or other creative extensions requiring up-to-date table changes.

Database 167
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In-Stream Big Data Processing

Highly Scalable

This article is an effort to explore techniques used by developers of in-stream data processing systems, trace the connections of these techniques to massive batch processing and OLTP/OLAP databases, and discuss how one unified query engine can support in-stream, batch, and OLAP processing at the same time.

Big Data 154
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A one size fits all database doesn't fit anyone

All Things Distributed

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167