APSys2021 云笔记（三）

Evaluating Reliability and Usage Characteristics of Flash-Based Storage in Production Systems

Speaker: Bianca Schroeder (Professor at University of Toronto, Canada)

With rapid development of SSDs

Motivation

• Storage landscape has changed
• Stora

Focus on another angke, This talk: the Storage(SSD) reliability.

This talk

• Take a look at flash reliability in the wild.
• How can we protect against flash failures?

Take a look at flash reliability

Issue 1: ARR Annual replacement rates

• [FAST' 20] Drives in Netapp Enterprise Systems.
• AVG ARR 0.22%, but rates vary widely
• much lower than HDDs

Issue 2: Rate of uncorrectable errors

• All SSDs experience bit errors.
• ECC to correct them, but sometimes uncorrectable
  • if no data redundancy, lost

Keynote_2_01

Role of Type

SLC, MLC, eMLC and TLC

differenct ARR, shows TLC has the most replacement rates.

Role of Age

• Usage affects the reliability of SSDs, due to wear-out of their cells.
• Hardware Failure ('Bathtub Curve') means SSDs has higher failure rate in their early life and wear-out.

Role of Firmware Version

• Compare individual firmware versions within the same family

FV has a tremendous impact on reliability (by a factor of 3-10x)!

Data protection in enterprise systems

RAID

• Single parity rapid -> up to two failures

• How common double failures

• RAID group size

Failure correlations within a RAID group

• How frequency do double failures occur?
• How quickly after the first
  • From CDF(Time Difference in days - Cumulative Probability), 46% successive failures occur on the same day!
• How are they related to RAID group size?

Keynote_2_02

How do file systems detect and recover from errors?

• ext4
• BtrFS
• ...

Keynote_2_03

Using prediction to improve reliability

• Prediction: model (NN, Random Forest...)
• Usage: improve scrubbing
  • Standard (fixed) -> dynamically add factor X with prediction

Interesting thing: the simple model (Random Forest) better than NN. Also mentioned as Question 3 from Zekai Sun in HKU.

DiLOS: Adding Performance to Paging-based Memory Disaggregation

Q&A

• Major difference between DiLOS and LegoOS which also uses memory disaggregagion

uniKernel ?

Coalescent Computing

Speaker: Kyle C. Hale (Illinois Institute of Technology)

Composable Infrastructure

Disaggregation at the Edge ->

Cyber Foraging

• In Cyber Foraging, use devices would "live off the land"
• Applications would be modified to parition into disjoint components, offloaded, sometimes using VMs
• Cloud offload, but with mobility

This might be a "chicken or the egg" problem: ...

Ref J.Flinn Cyber Foraging Fifteen Years Later IEEE Pervasive Computing

What's Changed?

• ...
• Wireless latency continues to drop

Coalescent Computing

Disaggregation resources at the Edge -> Ephemeral Single-System Image at the Edge

Principles and Characteristics

• Transparency: user no aware of coalescence
• Performance: offload shold only occur so as to improve
• Resilience: nodes come and go often
• Customizability: typesof resoucrces, when at what cost...
• Privacy and Security: same problems in IaaS

Lessons Learned from Migrating Complex Stateful Applications onto Serverless Platforms

Gap and Motivation

• Manually migrated 4 microservice applications
  • complex and stateful

Sanity Test - Scalability

Increase the load until saturated

Conclusions

• An automatic tool is helpful if it can
  • locate the call sites of the caller
  • locate the inner handlers

Future: automatic tools instead manually adapt the microservice to serverless