PostNord: Copy On Write

•

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This document discusses using a copy-on-write cache accelerator pattern and Varnish cache to optimize a microservice that allows customers to specify a favorite delivery location. Implementing a persistent cache with Varnish Cache Plus and transaction logging would make the solution robust and scalable by handling cache updates asynchronously and repopulating the cache if needed. This caching approach is well-suited for services with an expected low cache hit rate and improves performance by consuming fewer resources than directly calling the microservice.

Technology

A copy on write cache
accelerator pattern
or
A cache close to you

Me
● Anders Håål
● Software engineer consultant
● anders.haal@ingby.com
● @thenodon
● Currently PostNord Logistics
● Developing customer and recipient services

Customer facing servics @PostNord
Logistic production systems
Predictive load → ∫(parcels)
“Low” change rate
Enterprise software solutions
Internet facing services
Microservice design
Polyglot strategy
Continues delivery
Push
data

Favorite ServicePoint
● 25% of the parcel volume is
delivered to Servicepoints
● Enable a recipient to specify a
favorite Servicepoint
● Change the default Servicepoint,
based on postal code, to recipients
favorite
700 000 – 1 000 000 parcels/day
10-15% yearly increase

Solution
● Change the default to favorite before sorting and
processing
● During validation of EDI
● Lookup
– recipient mobile or email has
chosen a favorite
● Replace
– Servicepoint in EDI
if match
UNA:+.? '
UNB+UNOC:3+000X5766:30+00012306:30+160331:0759+1042++SendIT'
UNH+123456+IFTMIN:S:93A:UN+PLE101'
BGM+++9'
DTM+10:201604051530:203'
TSR+57+73 '
RFF+CU:Ordernummer1'
RFF+FLW:ABSOIDD'
TDT+20'
NAD+CZ+0206700700++Avsändarnamn+Testgatan 2+Nacka++13135+SE'
CTA+IC+Sven Svensson'
NAD+OS+++Webshop+Testgatan 2+Nacka++13135+SE'
NAD+CN+++Mottagarnamn+Hedlunds backe 1+Lerum++44338+SE'
CTA+IC'
COM+0700000000:AL'
COM+sven@gmail.com:EM'
GID+1+1:PC'
PCI+24+00373500454584614380'
UNT+17+123456'
UNZ+1+1042'

Favorite Servicepoint
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
PUT GET DELETE
GET

Favorite Servicepoint
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
PUT GET DELETE
GET
Service operation ~2 ms
Network latency ~110 ms
Total time > 110 ms

Adding Varnish Plus
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
GET

Adding Varnish Plus
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
GET
Expected hit rate is low
What is the right TTL?

Adding COW
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
GET
GET
PURGE
Async
call
On PUT →
Cache GET
On DELETE →
Cache PURGE

Adding COW
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
GET
On PUT →
Cache GET
On DELETE →
Cache PURGE
GET
Header X-force-fetch:true
PURGE
Async
call

Completed!
Service
FavoriteSP
EDI validation
system
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
GET
On PUT →
Cache GET
On DELETE →
Cache PURGE
GET
Header X-force-fetch:true
PURGE
Async
call
{
~90 ms
{
~4 ms

What about data consistency
Network down?
Varnish down?
Varnish out of space?
Everything can go wrong!

“Transactions”
● Persistent cache
● Varnish Cache Plus – massive storage engine
● Transaction log to enable resending and preserve
transaction order
● Acknowledge/commit the call to Varnish
● Operation to re-populate cache

Benefits
● Robust
●
Scalable
● Improved speed
● Consumes the “right” resources
● Cache updates are done out of EDI validation service
execution scope
● Effective for use cases with expected “low” hit rate
● Route to a specific cache based on request parameters

Nordic Favorite Servicepoint
Service
FavoriteSP
EDI validation
system
Sweden
API
Internal
API
Public API
(auth)
Varnish
Cache Plus
PUT GET DELETE
Async
call
PUT
EDI validation
system
Denmark
Varnish
Cache Plus
If SE
If DK

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PostNord: Copy On Write

1. COW's, microservices and Varnish

2. A copy on write cache accelerator pattern or A cache close to you

3. Me ● Anders Håål ● Software engineer consultant ● anders.haal@ingby.com ● @thenodon ● Currently PostNord Logistics ● Developing customer and recipient services

4. Customer facing servics @PostNord Logistic production systems Predictive load → ∫(parcels) “Low” change rate Enterprise software solutions Internet facing services Microservice design Polyglot strategy Continues delivery Push data

5. Favorite ServicePoint ● 25% of the parcel volume is delivered to Servicepoints ● Enable a recipient to specify a favorite Servicepoint ● Change the default Servicepoint, based on postal code, to recipients favorite 700 000 – 1 000 000 parcels/day 10-15% yearly increase

6. Solution ● Change the default to favorite before sorting and processing ● During validation of EDI ● Lookup – recipient mobile or email has chosen a favorite ● Replace – Servicepoint in EDI if match UNA:+.? ' UNB+UNOC:3+000X5766:30+00012306:30+160331:0759+1042++SendIT' UNH+123456+IFTMIN:S:93A:UN+PLE101' BGM+++9' DTM+10:201604051530:203' TSR+57+73 ' RFF+CU:Ordernummer1' RFF+FLW:ABSOIDD' TDT+20' NAD+CZ+0206700700++Avsändarnamn+Testgatan 2+Nacka++13135+SE' CTA+IC+Sven Svensson' NAD+OS+++Webshop+Testgatan 2+Nacka++13135+SE' NAD+CN+++Mottagarnamn+Hedlunds backe 1+Lerum++44338+SE' CTA+IC' COM+0700000000:AL' COM+sven@gmail.com:EM' GID+1+1:PC' PCI+24+00373500454584614380' UNT+17+123456' UNZ+1+1042'

7. Favorite Servicepoint Service FavoriteSP EDI validation system API Internal API Public API (auth) PUT GET DELETE GET

8. Favorite Servicepoint Service FavoriteSP EDI validation system API Internal API Public API (auth) PUT GET DELETE GET Service operation ~2 ms Network latency ~110 ms Total time > 110 ms

9. Favorite Servicepoint Service FavoriteSP EDI validation system API Internal API Public API (auth) PUT GET DELETE GET Service operation ~2 ms Network latency ~110 ms Total time > 110 ms Normal EDI validation per parcel 10-20 ms TAKES TOO LONG

10. Adding Varnish Plus Service FavoriteSP EDI validation system API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE GET

11. Adding Varnish Plus Service FavoriteSP EDI validation system API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE GET Expected hit rate is low What is the right TTL?

12. Adding COW Service FavoriteSP EDI validation system API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE GET GET PURGE Async call On PUT → Cache GET On DELETE → Cache PURGE

13. Adding COW Service FavoriteSP EDI validation system API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE GET On PUT → Cache GET On DELETE → Cache PURGE GET Header X-force-fetch:true PURGE Async call

14. Completed! Service FavoriteSP EDI validation system API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE GET On PUT → Cache GET On DELETE → Cache PURGE GET Header X-force-fetch:true PURGE Async call { ~90 ms { ~4 ms

15.

16. What about data consistency Network down? Varnish down? Varnish out of space? Everything can go wrong!

17. “Transactions” ● Persistent cache ● Varnish Cache Plus – massive storage engine ● Transaction log to enable resending and preserve transaction order ● Acknowledge/commit the call to Varnish ● Operation to re-populate cache

18. Benefits ● Robust ● Scalable ● Improved speed ● Consumes the “right” resources ● Cache updates are done out of EDI validation service execution scope ● Effective for use cases with expected “low” hit rate ● Route to a specific cache based on request parameters

19. Nordic Favorite Servicepoint Service FavoriteSP EDI validation system Sweden API Internal API Public API (auth) Varnish Cache Plus PUT GET DELETE Async call PUT EDI validation system Denmark Varnish Cache Plus If SE If DK

20. Thanks for listening! Questions?

PostNord: Copy On Write

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