The TidalScale Blog

Ike Nassi

Ike Nassi
http://www.computerhistory.org/trustee/dr-ike-nassi
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Recent Posts

Achieving Painless Reliability - an Alternate View

software-defined server, resilience

Failures

Computers fail. We wish it weren’t so, but it is. Personal computers fail more often than we would like. Maybe it’s because of a hardware failure (e.g. “I dropped my laptop”, or “the dog chewed on my iPhone”) or a component failure, like a memory or battery failure.

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Containers, DevOps and Software-Defined Servers: The Solution for High-Velocity Service Delivery

linux containers, software-defined server, in-memory, devops, composable infrastructure, TidalScale

Every day, more data center administrators are embracing DevOps best practices as a way to achieve high-velocity delivery of applications and services while optimizing the use of their IT assets. It makes sense: By extracting more utilization from resources you already own (or are already leasing in the cloud), you're lowering your TCO and gaining the flexibility you need to adapt to fluctuating workflows and exploding data volumes.

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Containers and Software-Defined Servers: A Win-Win

linux containers, software-defined server, in-memory, devops, composable infrastructure, TidalScale

Background

TidalScale has introduced a new concept in the computing fabric: Software-Defined Servers, which allow users to aggregate off -the-shelf commodity servers together in such a way that they form a virtual machine that spans the hardware servers but looks like a single large server to an operating system.  This large virtual server can run a single guest operating system like Linux and can then run application programs on that system.  

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Predicting Yesterday’s Weather

in-memory performance, Large memory, software-defined server

While it’s true that we can never predict tomorrow’s weather with 100 percent reliability (at least not yet), at the same time it’s true that we can predict yesterday’s weather with 100 percent certainty.

What does this have to do with anything?

Well, it turns out that meteorologists aren’t the only people who use historical data in an attempt to predict reasonable futures. 

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Application Programming When Memory Is No Longer A Constraint

application programming, big data, Large memory

We recently came across a problem that illustrates how software might be reconsidered in this new, software-defined-server environment.

Customer Problem Statement:

  • Consider two tables of historical data for each of, for example 3,000 securities. One table is called “Left” and one “Right”.
  • Each table for each security has a column of timestamps, and a column containing the name of the security its represents (e.g. “AAPL”), and additional data. The Left table might have, for example, 150 additional columns of data, and the Right table might have, for example, 100 columns of additional data.
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