DataStax: Ramping up Cassandra QA

Oct 3, 20152 likes670 views

Learn what DataStax is doing to ensure Cassandra releases are of high quality through functional test engineering and performance testing. Learn about the public testing resources that are available to the open source community that offer a common self-service experience to Cassandra contributors. A part of this talk will show cassandra-dtest, the integration test suite for Cassandra functional testing, cstar_perf the Cassandra performance testing framework, CVH a rigourous data validation harness, and CassCI the Cassandra Continuous Integration service for running any developer branch of Cassandra and applying a common test suite. We will offer a glimpse at what testing will look like under the new Tick-Tock Cassandra release process.

Ramping up Cassandra QA
with Test Engineering
Ryan McGuire, DataStax

Why are we building Cassandra?
Take a step back for one minute..

The Magnum Opus - Cassandra plays a role in it

That’s why I work on Cassandra.
Now let me tell you how.

Cassandra Test Engineering Team @
Ryan McGuire
EnigmaCurry
Russ Hatch
knifewine
Michael Shuler
exlt
Philip Thompson
ptnapoleon
Andrew Hust
nutbunnies
Jim Witschey
mambocab
Alan Boudreault
aboudreault

We are a group of developers focused on
identifying the present and future requirements
of OSS Cassandra and developing automated
tests to prove the fitness of releases and the
development of tools that enable DataStax
and the Cassandra Community to engage and
contribute to this process.
What is Cassandra Test Eng?

What we create
● ccm - the Cassandra Cluster Manager, tool to quickly bootstrap
Cassandra locally for development or testing purposes.
● cassandra-dtest - The integration test suite for the OSS Cassandra
project
● CassCI - cassci.datastax.com - Continuous Integration service for
developers of Cassandra
● cstar_perf - An open-source performance testing tool for Cassandra
● CVH - the Cassandra Validation Harness - next-gen kitchen sink
testing tool currently under development.

ccm - Powerful C* State Machine - Just Copy / Paste

cassandra_dtest
Script ccm clusters with Python to test features and detect regressions.
We have about 800 such dtests.

CassCI
Cassandra Continuous Integration cassci.datastax.com
4 Apache branches
27 developer repos
55k tests per day

● To run cassandra_dtest one time: 5 hours 35 minutes (ooof!)
● Knapsack Solution:
○ Query Jenkins for previous runtimes
○ Split tests into equal sized buckets based
on the expected test runtimes
○ Run each bucket on a separate instance
○ Merge results
○ New runtime:
30 Minutes
Scaling CassCI On Demand

Scaling CassCI On Demand
CassCI workerpool turns on and off Amazon EC2
nodes depending on test load. This is efficient and
keeps our costs low.

Use CassCI On Your Own Code
Are you adding features to Cassandra or fixing bugs?
We offer automated testing services to the community for free.
Join 27 other devs, and test your changes on CassCI!
Talk to us in #cassandra-dev on FreeNode for details.

cstar_perf - Driving Performance of Cassandra
Benchmarking is hard.
Automation makes it less hard.

Test Results Archive
View Performance Graph
Create new test based on this one
All artifacts are stored in Cassandra itself:
● Console - Bootstrap and Stress logs
● All Cassandra logs from each node
● Garbage collection logs
● Performance Metrics in JSON
● Any cstar_perf error messages
Hotlink to this page from JIRA.

Don’t like GUIs? Use JSON!
You can HTTP POST this to the REST backend API

Want to try it out? It’s Open Source!
Full instructions online: http://datastax.github.io/cstar_perf
It’s easy with native docker integration (for testing / development purposes):
Full local staging environment: http://localhost:8000

Thanks!
Contact me:
ryan@datastax.com
Twitter: @EnigmaCurry
IRC: EnigmaCurry on #cassandra-dev on FreeNode
Links:
github.com/pcmanus/ccm
github.com/riptano/cassandra-dtest
cassci.datastax.com
github.com/datastax/cstar_perf

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Software Development with Apache Cassandrazznate

Tracing allows you to see the path a query takes through the Cassandra cluster. It shows details like which nodes are queried, how long each step takes, and can help identify performance bottlenecks. The tracing information can be accessed via the Java driver, cqlsh, or DevCenter and provides a detailed timeline of query execution. Reviewing traces is recommended during development to catch unexpected query behavior.

Successful Software Development with Apache CassandraDataStax Academy

The document provides an overview of software development with Cassandra, including data modeling, writing code, testing, reviewing code, and managing environments. It discusses using the Java driver for writing code, preparing statements, batches, and lightweight transactions. Testing recommendations include using naming schemes, grouping tests into logical suites, and integrating unit and integration tests. The document also covers tracing queries, instrumentation with metrics, and reviewing code.

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MongoDB is a great NoSQL database, it’s very flexible and easy to use, but would it handle massive Read / Write throughput? actually, what happens when you need to scale everything out and easily? We will lay out the reasons and the steps of migrating our data pipeline to Apache Cassandra in a short period without having any prior knowledge. We’ll list our lessons learned as well. Bio: Demi Ben-Ari, Sr. Data Engineer @Windward, I have over 9 years of experience in building various systems both from the field of near real time applications and Big Data distributed systems. Co-Organizer of the “Big Things” Big Data community:http://somebigthings.com/big-things-intro/

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We will dissect the world famous todo app that provides a REST API (which is the foundation of microservices) with data backed by Apache Cassandra. We will leverage the TODO MVC and the TODO backend projects with the back end that we will build with Quarkus and Cassandra. Attendees will get an overview of Cassandra, including the driver for Quarkus. Through live coding (that attendees can try out later) in a cloud-based environment, primarily in Quarkus and Cassandra, attendees will understand how to implement and connect the APIs to the backend and leverage the generic client(s)provided. After attending this session attendees will walk away with a good understanding of implementing microservices using Cassandra and Quarkus. They will also get a working knowledge of how Astra (Cassandra as a service) can be leveraged in other solutions.

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Cassandra at PollfishPollfish

Pollfish is a survey platform which provides access to millions of targeted users. Pollfish allows easy distribution and targeting of surveys through existing mobile apps. (https://www.pollfish.com/). At pollfish we use Cassandra for difference use cases, eg. for application data store to maximize write throughput when appropriate and for our analytics project to find insights in application generated data. As a medium to accomplish our success so far, we use the Datastax's DSE 4.6 environment which integrates Appache Cassadra, Spark and a hadoop compatible file system (CFS). We will discuss how we started, how the journey was and the impressions gained so far along with some tips learned the hard way. This is a result of joint work of an excellent team here at Pollfish.

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Velocity NYC 2016 - Containers @ Netflixaspyker

Netflix uses containers to run both batch jobs and services. For batch jobs, containers simplify resource management and allow jobs like model training and media encoding to easily share resources. Services are more complex to run in containers due to challenges like constant resizing, statefulness, and networking. Netflix addresses these challenges through solutions like a VPC networking driver and reusing existing infrastructure services for containers. Looking ahead, Netflix aims to run more containers at larger scale for areas like developer experience, continuous integration, and internal resource optimization.

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performance_tuning.pdfAlexadiaz52

The document summarizes a study that benchmarked the performance of Cassandra, Couchbase, and MongoDB as more hardware was added to clusters. The study found that: - Couchbase performed the best in terms of throughput, scaling nearly linearly as nodes were added for workloads where the majority of data fit in RAM. - Throughput increased for all databases as nodes were added, but Couchbase significantly outperformed Cassandra and MongoDB, particularly for the 95% read/5% write workload. - The study was designed to test how the databases scaled their key-value storage capabilities in a RAM-heavy use case, which favored Couchbase's performance given its origins in Membase and memcached.

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Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts! 📕 Agenda Welcome & Introductions Orchestrator API Overview Exploring the Swagger Interface Test Manager API Highlights Streamlining Automation & Testing with APIs (Demo) Q&A and Open Discussion Perfect for developers, testers, and automation enthusiasts! 👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/ This session streamed live on April 29, 2025, 18:00 CET. Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.

Cybersecurity Identity and Access Solutions using Azure ADVICTOR MAESTRE RAMIREZ