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Cassandra 3.x High Availability

You're reading from   Cassandra 3.x High Availability Achieve scalability and high availability without compromising on performance

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Product type Paperback
Published in Aug 2016
Publisher
ISBN-13 9781786462107
Length 196 pages
Edition 2nd Edition
Languages
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Author (1):
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Robbie Strickland Robbie Strickland
Author Profile Icon Robbie Strickland
Robbie Strickland
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Table of Contents (10) Chapters Close

Preface 1. Cassandras Approach to High Availability 2. Data Distribution FREE CHAPTER 3. Replication 4. Data Centers 5. Scaling Out 6. High Availability Features in the Native Java Client 7. Modeling for Availability 8. Anti-Patterns 9. Failing Gracefully

Scaling out versus scaling up


So you know it's time to add more muscle to your cluster, but how do you know whether to scale up or out?

If you're not familiar with the difference, scaling up refers to converting existing infrastructure to better or more robust hardware (or instance types in cloud environments). This could mean adding storage capacity, increasing memory, moving to newer machines with more cores, and so on.

Scaling out simply means adding more machines that roughly match the specifications of the existing machines. Since Cassandra scales linearly with its peer-to-peer architecture, scaling out is often more desirable.

Tip

In general, it is better to replace physical hardware components incrementally rather than all at one time. This is because in large systems failures tend to come after hardware ages to a certain point, which is statistically likely to happen simultaneously for some subset of your nodes. For example, purchasing a large lot of drives from a single source at one...

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