Skip to content

cedrickchee/testing-distributed-systems

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

List of resources on testing distributed systems curated by Andrey Satarin (@asatarin). If you are interested in my other stuff, checkout talks page. For any questions or suggestions you can reach out to me on Twitter (@asatarin) or LinkedIn.

Contents

Overview of testing approaches

Research Papers

Technologies for Testing Distributed Systems by Colin Scott

Colin Scott shares his viewpoint from academia on testing distributed systems, specifically regression testing for correctness and performance bugs.

Testing in a Distributed World by Ines Sombra (RICON 2014)

Great overview of techniques for testing distributed systems from practitioner, the video did age well and still extremely good overview of the landscape. Additional materials could be found in this Github repo

Resilience In Complex Adaptive Systems

These materials are not directly related to testing distributed systems, but they greatly contribute to general understanding of such systems.

Jepsen

State of the art approach to testing stateful distributed systems.

Elle transactional consistency checker for black-box databases:

Some notable Jepsen analyses:

Jepsen is used by CockroachDB, VoltDB, Cassandra, ScyllaDB and others.

Formal Methods

Companies using TLA+ to verify correctness of algorithms:

Lineage-driven Fault Injection

Netflix adopted lineage-driven fault injection techniques for testing microservices.

Chaos Engineering

Netflix pioneered chaos engineering discipline.

Fuzzing

There are two flavors of fuzzing. First, randomized concurrency testing, where the ordering of messages is fuzzed:

And input fuzzing, where message contents or user inputs are fuzzed:

Microservices

Amazing and comprehensive overview of different strategies to test systems built with microservices by Cindy Sridharan.

Series of blog posts specifically on testing in production — best practices, pitfaults, etc:

Game Days

Performance and Benchmarking

See also benchmarking tools.

Test Case Reduction

Misc

Specific approaches in different distributed systems

Amazon Web Services

See also formal methods section.

Netflix

Automated failure injection (see also Lineage-driven Fault Injection):

Random/manual failure injection testing:

See also Chaos Engineering.

Twitter

Cassandra

ScyllaDB

They published series of blog posts on testing ScyllaDB:

VoltDB

Series of post on testing at VoltDB:

Additional resources:

MemSQL

CockroachLabs (CockroachDB)

PingCap (TiDB)

See also formal methods section.

MongoDB

See also formal methods section.

Cloudera

FoundationDB

Wallaroo Labs

There is also talk from Sean T. Allen on testing stream processing system at Wallaroo Labs (ex. Sendence)

Google

Microsoft

See also formal methods section.

Dropbox

  • Mysteries of Dropbox Property-Based Testing of a Distributed Synchronization Service — example of how to use QuickCheck to test synchronisation in Dropbox and similar tools (Google Drive). John Hughes gave a talk on this. See also QuickCheck.
  • Data Checking at Dropbox — If you have lots of data, you have to verify that is doesn't bit rot and protect it against rare bugs (e.g. race conditions) to guarantee long term durability. This talks explains intricacies of building data consistency checker(s) at Dropbox scale.
  • Dropbox's Exabyte Storage System (aka Magic Pocket) talk by James Cowling — describes number of strategies to achieve exteremely high durability. This includes:
    • guard against faulty disks,
    • guard against software defects,
    • guard against black swan events,
    • operational safeguards to reduce blast radius,
    • safeguards against deletes with multi stage soft-delete,
    • comprehensive testing strategy in-depth with increased scale,
    • redundancy across varios axis in software and hardware stacks,
    • continuous data integrity validation on many levels,
    • etc
  • Testing sync at Dropbox — comprehensive overview of two test frameworks at Dropbox for new sync engine implementation. CanopyCheck — single threaded and fully deterministic randomized testing framework with minimization for synchronization planner component of the engine. The other framework Trinity focuses on concurrency and larger surface area of componenents. Great discussion on tradeoffs between determinism, strengh of test oracles vs width of coverage and size of the system under test.

Atomix Copycat

Onyx

LinkedIn

Druid.io

Salesforce

InfluxDB

Shopify

Confluent (Kafka)

See also formal methods section.

Elastic (Elasticsearch)

YugabyteDB

FaunaDB

Hazelcast

Basho (Riak)

CoreOS (etcd)

Red Planet Labs

Coil (TigerBeetle)

Single node systems

These examples are not about distributed systems, but they demostrate testing concurrency and level of sofistication required in distributed systems.

SQLite

SQLite is not a distributed system by any stretch of the imagination, but provides good example of comprehensive testing of a database implementation.

Sled

Clickhouse

Tools

Network Simulation

QuickCheck

Benchmarking

Linkbench

YCSB

Releases

No releases published

Packages

No packages published

Languages

  • HTML 62.5%
  • SCSS 37.5%