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- that offers low-latency, high-reliability caching and storage
- in many occasions it is termed as “the hidden microservice”
- performing trillions of operations per day
- has the ability to persist the data to the disk
- With the advent of Netflix global cloud architecture
- The diagram below shows the logical structure of
- As we started moving towards the Global Cloud
- we had a three times increase in the data that needed to be replicated
- Supporting these features came at a considerable increase in cost and complexities
- Our motivation was to provide a global caching solution which was not only fast but was also cost effective.
- are providing fast access to data but at a much lower cost when compared to RAM
- we wanted to move part of the data out of memory without sacrificing availability or performance
- storing the same amount in RAM.
- RAM random read latencies were rarely higher than 1 microsecond
- whereas typical SSD random read speeds are between 100–500 microseconds
- is around 1 millisecond
- we noticed that we were able to perform over
- thus meeting our throughput goals with latency rarely exceeding 1 millisecond
- This meant that
- EVCache Moneta was our first venture at using SSD
- The approach we chose
- This approach reduced the size of most Moneta based clusters over 60% as compared to their corresponding RAM-only clusters
- This enabled us to achieve
- a significant reduction in cost
- However, we were unable to move some of the large online and customer facing clusters
- We would also exceed the desired SLA at times
- As we were working towards solving these issues
- which had taken a different approach
- shim called extstore
- extstore is efficient in terms of cost & storage device utilization
- without compromising the speed and throughput
- All the metadata (key & other metadata) is stored in RAM whereas the actual data is stored on flash.
- which we could not do achieve with Moneta
- we could use at most 50% of the disc capacity
- as we had to ensure an old item could be deleted
- only after it was written again
- This meant we had could end up with a copy of new and old data
- Since we did not have need for storing duplicate records
- are scaled to meet network demands rather than storage demands
- This has been quite a remarkable achievement.
- By moving from
- which allows us to iterate through all of the keys in an instance
- By taking advantage of this command
- at regular intervals
- This ensures data in EVCache is durable and highly available in case of a disaster.
- which is used to store users personalized recommendations.
- The majority of reads are around
- Below is the average read latency of one of cache
- extstore latencies are consistently lower than Moneta for similar load across both the instances.
- we are able to handle all types of workloads
- whether it is a read heavy, write heavy or balanced
- ranging from gigabytes to petabytes
- It has been quite a journey to move from Moneta to extstore
- as of now we have moved all our production clusters running Moneta to extstore
- We have also been able to move
- The new architecture for EVCache Server running extstore
- is allowing us to continue to innovate in ways that matter
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