Learn how to build an effective storage layer for a variety of workloads. With changing trends in system and storage hardware, understanding design trade-offs can be a challenge. This webinar will focus on cutting through the noise and diving into the choices that matter when designing for scale and performance.
Video: https://youtu.be/uEL8vyVSIis
6. Basic System Topology
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Every modern system is
essentially a network of
components.
The language of message
delivery applies at every
level of design.
System Topology Example (high level)
HDD SSD
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It’s a bad idea.
SANs for distributed databases...
Have strong skepticism when anybody tells you otherwise.
Perhaps they haven’t tried it yet, or are ignoring the obvious.
You don’t have to suffer the pains of others in order to learn
from their experiences. Still, some insist on trying.
23. HDD vs. SSD
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Type Pro Con
HDD ● Cheap? ● All concurrent operations are contended
● Random access is slow - drive seek
● Power usage
● Lower latencies come with much higher
costs
● Little room for further improvement
SSD ● Cheap? (1TB ~ $300)
● Fast
● Low internal contention
● Runs cooler / lower
wattage
● Faster transport
technology available
● Initial capacities available - encouraged
RAID shenanigans → No longer an issue
for reasonable data densities with
Cassandra/DSE.
● MTBF of earlier designs → No longer an
issue as SSDs have made huge strides in
reliability and DWPD limits
● Initial cost - No longer an issue
25. Selecting SSD vs. HDD
Favor modern SSDs by default.
Use HDDs only if you must for:
● High-write applications with low read concurrency
● Archival or Logging systems with low read concurrency
● Commit log storage, if you have the option
● Persistent messaging systems
● Non-latency sensitive batch/analytics workloads
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28. In Conclusion...
• Provision with headroom to avoid unnecessary contention.
• Select hardware to support user and workload requirements.
• Keep the storage path as simple as possible.
• Consider SSDs by default for your data directories.
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