Apache Cassandra® 5.0: Behind the Scenes

4 September 2024, 3:53 am by Apache Cassandra - Instaclustr

Here at NetApp, our Instaclustr product development team has spent nearly a year preparing for the release of Apache Cassandra 5.  

Starting with one engineer tinkering at night with the Apache Cassandra 5 Alpha branch, and then up to 5 engineers working on various monitoring, configuration, testing and functionality improvements to integrate the release with the Instaclustr Platform.  

It’s been a long journey to the point we are at today, offering Apache Cassandra 5 Release Candidate 1 in public preview on the Instaclustr Platform. 

Note: the Instaclustr team has a dedicated open source committer to the Apache Cassandra project. His changes are not included in this document as there were too many for us to include here. Instead, this blog primarily focuses on the engineering effort to release Cassandra 5.0 onto the Instaclustr Managed Platform. 

August 2023: The Beginning

We began experimenting with the Apache Cassandra 5 Alpha 1 branches using our build systems. There were several tools we built into our Apache Cassandra images that were not working at this point, but we managed to get a node to start even though it immediately crashed with errors.  

One of our early achievements was identifying and fixing a bug that impacted our packaging solution; this resulted in a small contribution to the project allowing Apache Cassandra to be installed on Debian systems with non-OpenJDK Java. 

September 2023: First Milestone 

The release of the Alpha 1 version allowed us to achieve our first running Cassandra 5 cluster in our development environments (without crashing!).  

Basic core functionalities like user creation, data writing, and backups/restores were tested successfully. However, several advanced features, such as repair and replace tooling, monitoring, and alerting were still untested.  

At this point we had to pause our Cassandra 5 efforts to focus on other priorities and planned to get back to testing Cassandra 5 after Alpha 2 was released. 

November 2023:  Further Testing and Internal Preview 

The project released Alpha 2. We repeated the same build and test we did on alpha 1. We also tested some more advanced procedures like cluster resizes with no issues.  

We also started testing with some of the new 5.0 features: Vector Data types and Storage-Attached Indexes (SAI), which resulted in another small contribution.  

We launched Apache Cassandra 5 Alpha 2 for internal preview (basically for internal users). This allowed the wider Instaclustr team to access and use the Alpha on the platform.  

During this phase we found a bug in our metrics collector when vectors were encountered that ended up being a major project for us. 

If you see errors like the below, it’s time for a Java Cassandra driver upgrade to 4.16 or newer: 

java.lang.IllegalArgumentException: Could not parse type name vector<float, 5>  
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.DataTypeCqlNameParser.parse(DataTypeCqlNameParser.java:233)  
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.TableMetadata.build(TableMetadata.java:311)
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.SchemaParser.buildTables(SchemaParser.java:302)
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.SchemaParser.refresh(SchemaParser.java:130)
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.ControlConnection.refreshSchema(ControlConnection.java:417)  
Nov 15 22:41:04 ip-10-0-39-7 process[1548]: at com.datastax.driver.core.ControlConnection.refreshSchema(ControlConnection.java:356)  
<Rest of stacktrace removed for brevity>

December 2023: Focus on new features and planning 

As the project released Beta 1, we began focusing on the features in Cassandra 5 that we thought were the most exciting and would provide the most value to customers. There are a lot of awesome new features and changes, so it took a while to find the ones with the largest impact.  

 The final list of high impact features we came up with was: 

  • A new data type – Vectors 
  • Trie memtables/Trie Indexed SSTables (BTI Formatted SStables) 
  • Storage-Attached Indexes (SAI) 
  • Unified Compaction Strategy 

A major new feature we considered deploying was support for JDK 17. However, due to its experimental nature, we have opted to postpone adoption and plan to support running Apache Cassandra on JDK 17 when it’s out of the experimentation phase. 

Once the holiday season arrived, it was time for a break, and we were back in force in February next year. 

February 2024: Intensive testing 

In February, we released Beta 1 into internal preview so we could start testing it on our Preproduction test environments. As we started to do more intensive testing, we discovered issues in the interaction with our monitoring and provisioning setup. 

We quickly fixed the issues identified as showstoppers for launching Cassandra 5. By the end of February, we initiated discussions about a public preview release. We also started to add more resourcing to the Cassandra 5 project. Up until now, only one person was working on it.  

Next, we broke down the work we needed to do.  This included identifying monitoring agents requiring upgrade and config defaults that needed to change. 

From this point, the project split into 3 streams of work: 

  1. Project Planning – Deciding how all this work gets pulled together cleanly, ensuring other work streams have adequate resourcing to hit their goals, and informing product management and the wider business of what’s happening.  
  2. Configuration Tuning – Focusing on the new features of Apache Cassandra to include, how to approach the transition to JDK 17, and how to use BTI formatted SSTables on the platform.  
  3. Infrastructure Upgrades – Identifying what to upgrade internally to handle Cassandra 5, including Vectors and BTI formatted SSTables. 

A Senior Engineer was responsible for each workstream to ensure planned timeframes were achieved. 

March 2024: Public Preview Release 

In March, we launched Beta 1 into public preview on the Instaclustr Managed Platform. The initial release did not contain any opt in features like Trie indexed SSTables. 

However, this gave us a consistent base to test in our development, test, and production environments, and proved our release pipeline for Apache Cassandra 5 was working as intended. This also gave customers the opportunity to start using Apache Cassandra 5 with their own use cases and environments for experimentation.  

See our public preview launch blog for further details. 

There was not much time to celebrate as we continued working on infrastructure and refining our configuration defaults. 

April 2024: Configuration Tuning and Deeper Testing 

The first configuration updates were completed for Beta 1, and we started performing deeper functional and performance testing. We identified a few issues from this effort and remediated. This default configuration was applied for all Beta 1 clusters moving forward.  

This allowed users to start testing Trie Indexed SSTables and Trie memtables in their environment by default. 

"memtable": 
  { 
    "configurations": 
      { 
        "skiplist": 
          { 
            "class_name": "SkipListMemtable" 
          }, 
        "sharded": 
          { 
            "class_name": "ShardedSkipListMemtable" 
          }, 
        "trie": 
          { 
            "class_name": "TrieMemtable" 
          }, 
        "default": 
          { 
            "inherits": "trie" 
          } 
      } 
  }, 
"sstable": 
  { 
    "selected_format": "bti" 
  }, 
"storage_compatibility_mode": "NONE",

The above graphic illustrates an Apache Cassandra YAML configuration where BTI formatted sstables are used by default (which allows Trie Indexed SSTables) and defaults use of Trie for memtables.  You can override this per table: 

CREATE TABLE test WITH memtable = {‘class’ : ‘ShardedSkipListMemtable’};

Note that you need to set storage_compatibility_mode to NONE to use BTI formatted sstables. See Cassandra documentation for more information. 

You can also reference the cassandra_latest.yaml  file for the latest settings (please note you should not apply these to existing clusters without rigorous testing). 

May 2024: Major Infrastructure Milestone 

We hit a very large infrastructure milestone when we released an upgrade to some of our core agents that were reliant on an older version of the Apache Cassandra Java driver. The upgrade to version 4.17 allowed us to start supporting vectors in certain keyspace level monitoring operations.  

At the time, this was considered to be the riskiest part of the entire project as we had 1000s of nodes to upgrade across may different customer environments. This upgrade took a few weeks, finishing in June. We broke the release up into 4 separate rollouts to reduce the risk of introducing issues into our fleet, focusing on single key components in our architecture in each release. Each release had quality gates and tested rollback plans, which in the end were not needed. 

June 2024: Successful Rollout New Cassandra Driver 

The Java driver upgrade project was rolled out to all nodes in our fleet and no issues were encountered. At this point we hit all the major milestones before Release Candidates became available. We started to look at the testing systems to update to Apache Cassandra 5 by default. 

July 2024: Path to Release Candidate 

We upgraded our internal testing systems to use Cassandra 5 by default, meaning our nightly platform tests began running against Cassandra 5 clusters and our production releases will smoke test using Apache Cassandra 5. We started testing the upgrade path for clusters from 4.x to 5.0. This resulted in another small contribution to the Cassandra project.  

The Apache Cassandra project released Apache Cassandra 5 Release Candidate 1 (RC1), and we launched RC1 into public preview on the Instaclustr Platform. 

The Road Ahead to General Availability 

We’ve just launched Apache Cassandra 5 Release Candidate 1 (RC1) into public preview, and there’s still more to do before we reach General Availability for Cassandra 5, including: 

  • Upgrading our own preproduction Apache Cassandra for internal use to Apache Cassandra 5 Release Candidate 1. This means we’ll be testing using our real-world use cases and testing our upgrade procedures on live infrastructure. 

At Launch: 

When Apache Cassandra 5.0 launches, we will perform another round of testing, including performance benchmarking. We will also upgrade our internal metrics storage production Apache Cassandra clusters to 5.0, and, if the results are satisfactory, we will mark the release as generally available for our customers. We want to have full confidence in running 5.0 before we recommend it for production use to our customers.  

For more information about our own usage of Cassandra for storing metrics on the Instaclustr Platform check out our series on Monitoring at Scale.  

What Have We Learned From This Project? 

  • Releasing limited, small and frequent changes has resulted in a smooth project, even if sometimes frequent releases do not feel smooth. Some thoughts: 
    • Releasing to a small subset of internal users allowed us to take risks and break things more often so we could learn from our failures safely.
    • Releasing small changes allowed us to more easily understand and predict the behaviour of our changes: what to look out for in case things went wrong, how to more easily measure success, etc. 
    • Releasing frequently built confidence within the wider Instaclustr team, which in turn meant we would be happier taking more risks and could release more often.  
  • Releasing to internal and public preview helped create momentum within the Instaclustr business and teams:  
    • This turned the Apache Cassandra 5.0 release from something that “was coming soon and very exciting” to “something I can actually use.”
  • Communicating frequently, transparently, and efficiently is the foundation of success:  
    • We used a dedicated Slack channel (very creatively named #cassandra-5-project) to discuss everything. 
    • It was quick and easy to go back to see why we made certain decisions or revisit them if needed. This had a bonus of allowing a Lead Engineer to write a blog post very quickly about the Cassandra 5 project. 

This has been a long–running but very exciting project for the entire team here at Instaclustr. The Apache Cassandra community is on the home stretch for this massive release, and we couldn’t be more excited to start seeing what everyone will build with it.  

You can sign up today for a free trial and test Apache Cassandra 5 Release Candidate 1 by creating a cluster on the Instaclustr Managed Platform.  

More Readings 

 

The post Apache Cassandra® 5.0: Behind the Scenes appeared first on Instaclustr.

Will Your Cassandra Database Project Succeed?: The New Stack

3 September 2024, 12:45 am by Apache Cassandra - Instaclustr

Open source Apache Cassandra® continues to stand out as an enterprise-proven solution for organizations seeking high availability, scalability and performance in a NoSQL database. (And hey, the brand-new 5.0 version is only making those statements even more true!) There’s a reason this database is trusted by some of the world’s largest and most successful companies.

That said, effectively harnessing the full spectrum of Cassandra’s powerful advantages can mean overcoming a fair share of operational complexity. Some folks will find a significant learning curve, and knowing what to expect is critical to success. In my years of experience working with Cassandra, it’s when organizations fail to anticipate and respect these challenges that they set the stage for their Cassandra projects to fall short of expectations.

Let’s look at the key areas where strong project management and following proven best practices will enable teams to evade common pitfalls and ensure a Cassandra implementation is built strong from Day 1.

Accurate Data Modeling Is a Must

Cassandra projects require a thorough understanding of its unique data model principles. Teams that approach Cassandra like a relationship database are unlikely to model data properly. This can lead to poor performance, excessive use of secondary indexes and significant data consistency issues.

On the other hand, teams that develop familiarity with Cassandra’s specific NoSQL data model will understand the importance of including partition keys, clustering keys and denormalization. These teams will know to closely analyze query and data access patterns associated with their applications and know how to use that understanding to build a Cassandra data model that matches their application’s needs step for step.

The post Will Your Cassandra Database Project Succeed?: The New Stack appeared first on Instaclustr.

Use Your Data in LLMs With the Vector Database You Already Have: The New Stack

6 August 2024, 7:08 am by Apache Cassandra - Instaclustr

Open source vector databases are among the top options out there for AI development, including some you may already be familiar with or even have on hand.

Vector databases allow you to enhance your LLM models with data from your internal data stores. Prompting the LLM with local, factual knowledge can allow you to get responses tailored to what your organization already knows about the situation. This reduces “AI hallucination” and improves relevance.

You can even ask the LLM to add references to the original data it used in its answer so you can check yourself. No doubt vendors have reached out with proprietary vector database solutions, advertised as a “magic wand” enabling you to assuage any AI hallucination concerns.

But, ready for some good news?

If you’re already using Apache Cassandra 5.0, OpenSearch or PostgreSQL, your vector database success is already primed. That’s right: There’s no need for costly proprietary vector database offerings. If you’re not (yet) using these free and fully open source database technologies, your generative AI aspirations are a good time to migrate — they are all enterprise-ready and avoid the pitfalls of proprietary systems.

For many enterprises, these open source vector databases are the most direct route to implementing LLMs — and possibly leveraging retrieval augmented generation (RAG) — that deliver tailored and factual AI experiences.

Vector databases store embedding vectors, which are lists of numbers representing spatial coordinates corresponding to pieces of data. Related data will have closer coordinates, allowing LLMs to make sense of complex and unstructured datasets for features such as generative AI responses and search capabilities.

RAG, a process skyrocketing in popularity, involves using a vector database to translate the words in an enterprise’s documents into embeddings to provide highly efficient and accurate querying of that documentation via LLMs.

Let’s look closer at what each open source technology brings to the vector database discussion:

Apache Cassandra 5.0 Offers Native Vector Indexing

With its latest version (currently in preview), Apache Cassandra has added to its reputation as an especially highly available and scalable open source database by including everything that enterprises developing AI applications require.

Cassandra 5.0 adds native vector indexing and vector search, as well as a new vector data type for embedding vector storage and retrieval. The new version has also added specific Cassandra Query Language (CQL) functions that enable enterprises to easily use Cassandra as a vector database. These additions make Cassandra 5.0 a smart open source choice for supporting AI workloads and executing enterprise strategies around managing intelligent data.

OpenSearch Provides a Combination of Benefits

Like Cassandra, OpenSearch is another highly popular open source solution, one that many folks on the lookout for a vector database happen to already be using. OpenSearch offers a one-stop shop for search, analytics and vector database capabilities, while also providing exceptional nearest-neighbor search capabilities that support vector, lexical, and hybrid search and analytics.

With OpenSearch, teams can put the pedal down on developing AI applications, counting on the database to deliver the stability, high availability and minimal latency it’s known for, along with the scalability to account for vectors into the tens of billions. Whether developing a recommendation engine, generative AI agent or any other solution where the accuracy of results is crucial, those using OpenSearch to leverage vector embeddings and stamp out hallucinations won’t be disappointed.

The pgvector Extension Makes Postgres a Powerful Vector Store

Enterprises are no strangers to Postgres, which ranks among the most used databases in the world. Given that the database only needs the pgvector extension to become a particularly performant vector database, countless organizations are just a simple deployment away from harnessing an ideal infrastructure for handling their intelligent data.

pgvector is especially well-suited to provide exact nearest-neighbor search, approximate nearest-neighbor search and distance-based embedding search, and at using cosine distance (as recommended by OpenAI), L2 distance and inner product to recognize semantic similarities. Efficiency with those capabilities makes pgvector a powerful and proven open source option for training accurate LLMs and RAG implementations, while positioning teams to deliver trustworthy AI applications they can be proud of.

Was the Answer to Your AI Challenges in Front of You All Along?

The solution to tailored LLM responses isn’t investing in some expensive proprietary vector database and then trying to dodge the very real risks of vendor lock-in or a bad fit. At least it doesn’t have to be. Recognizing that available open source vector databases are among the top options out there for AI development — including some you may already be familiar with or even have on hand — should be a very welcome revelation.

Read more at The New Stack!

The post Use Your Data in LLMs With the Vector Database You Already Have: The New Stack appeared first on Instaclustr.

easy-cass-lab v5 released

5 August 2024, 12:00 am by Posts on RustyRazorblade Consulting

I’ve got some fun news to start the week off for users of easy-cass-lab: I’ve just released version 5. There are a number of nice improvements and bug fixes in here that should make it more enjoyable, more useful, and lay groundwork for some future enhancements.

  • When the cluster starts, we wait for the storage service to reach NORMAL state, then move to the next node. This is in contrast to the previous behavior where we waited for 2 minutes after starting a node. This queries JMX directly using Swiss Java Knife and is more reliable than the 2-minute method. Please see packer/bin-cassandra/wait-for-up-normal to read through the implementation.
  • Trunk now works correctly. Unfortunately, AxonOps doesn’t support trunk (5.1) yet, and using the agent was causing a startup error. You can test trunk out, but for now the AxonOps integration is disabled.
  • Added a new repl mode. This saves keystrokes and provides some auto-complete functionality and keeps SSH connections open. If you’re going to do a lot of work with ECL this will help you be a little more efficient. You can try this out with ecl repl.
  • Power user feature: Initial support for profiles in AWS regions other than us-west-2. We only provide AMIs for us-west-2, but you can now set up a profile in an alternate region, and build the required AMIs using easy-cass-lab build-image. This feature is still under development and requires using an easy-cass-lab build from source. Credit to Jordan West for contributing this work.
  • Power user feature: Support for multiple profiles. Setting the EASY_CASS_LAB_PROFILE environment variable allows you to configure alternate profiles. This is handy if you want to use multiple regions or have multiple organizations.
  • The project now uses Kotlin instead of Groovy for Gradle configuration.
  • Updated Gradle to 8.9.
  • When using the list command, don’t show the alias “current”.
  • Project cleanup, remove old unused pssh, cassandra build, and async profiler subprojects.

The release has been released to the project’s GitHub page and to homebrew. The project is largely driven by my own consulting needs and for my training. If you’re looking to have some features prioritized please reach out, and we can discuss a consulting engagement.

easy-cass-lab updated with Cassandra 5.0 RC-1 Support

23 July 2024, 12:00 am by Posts on RustyRazorblade Consulting

I’m excited to announce that the latest version of easy-cass-lab now supports Cassandra 5.0 RC-1, which was just made available last week! This update marks a significant milestone, providing users with the ability to test and experiment with the newest Cassandra 5.0 features in a simplified manner. This post will walk you through how to set up a cluster, SSH in, and run your first stress test.

For those new to easy-cass-lab, it’s a tool designed to streamline the setup and management of Cassandra clusters in AWS, making it accessible for both new and experienced users. Whether you’re running tests, developing new features, or just exploring Cassandra, easy-cass-lab is your go-to tool.

easy-cass-lab now available in Homebrew

18 July 2024, 12:00 am by Posts on RustyRazorblade Consulting

I’m happy to share some exciting news for all Cassandra enthusiasts! My open source project, easy-cass-lab, is now installable via a homebrew tap. This powerful tool is designed to make testing any major version of Cassandra (or even builds that haven’t been released yet) a breeze, using AWS. A big thank-you to Jordan West who took the time to make this happen!

What is easy-cass-lab?

easy-cass-lab is a versatile testing tool for Apache Cassandra. Whether you’re dealing with the latest stable releases or experimenting with unreleased builds, easy-cass-lab provides a seamless way to test and validate your applications. With easy-cass-lab, you can ensure compatibility and performance across different Cassandra versions, making it an essential tool for developers and system administrators. easy-cass-lab is used extensively for my consulting engagements, my training program, and to evaluate performance patches destined for open source Cassandra. Here are a few examples:

Cassandra Training Signups For July and August Are Open!

25 April 2024, 12:00 am by Posts on RustyRazorblade Consulting

I’m pleased to announce that I’ve opened training signups for Operator Excellence to the public for July and August. If you’re interested in stepping up your game as a Cassandra operator, this course is for you. Head over to the training page to find out more and sign up for the course.

Streaming My Sessions With Cassandra 5.0

28 February 2024, 12:00 am by Posts on RustyRazorblade Consulting

As a long time participant with the Cassandra project, I’ve witnessed firsthand the evolution of this incredible database. From its early days to the present, our journey has been marked by continuous innovation, challenges, and a relentless pursuit of excellence. I’m thrilled to share that I’ll be streaming several working sessions over the next several weeks as I evaluate the latest builds and test out new features as we move toward the 5.0 release.

Streaming Cassandra Workloads and Experiments

26 February 2024, 12:00 am by Posts on RustyRazorblade Consulting

Streaming

In the world of software engineering, especially within the realm of distributed systems, continuous learning and experimentation are not just beneficial; they’re essential. As a software engineer with a focus on distributed systems, particularly Apache Cassandra, I’ve taken this ethos to heart. My journey has led me to not only explore the intricacies of Cassandra’s distributed architecture but also to share my experiences and findings with a broader audience. This is why my YouTube channel has become an active platform where I stream at least once a week, engaging with viewers through coding sessions, trying new approaches, and benchmarking different Cassandra workloads.

Live Streaming On Tuesdays

1 February 2024, 12:00 am by Posts on RustyRazorblade Consulting

As I promised in December, I redid my presentation from the Cassandra Summit 2023 on a live stream. You can check it out at the bottom of this post.

Going forward, I’ll be live-streaming on Tuesdays at 10AM Pacific on my YouTube channel.

Next week I’ll be taking a look at tlp-stress, which is used by the teams at some of the biggest Cassandra deployments in the world to benchmark their clusters. You can find that here.

Cassandra Summit Recap: Performance Tuning and Cassandra Training

11 January 2024, 12:00 am by Posts on RustyRazorblade Consulting

Hello, friends in the Apache Cassandra community!

I recently had the pleasure of speaking at the Cassandra Summit in San Jose. Unfortunately, we ran into an issue with my screen refusing to cooperate with the projector, so my slides were pretty distorted and hard to read. While the talk is online, I think it would be better to have a version with the right slides as well as a little more time. I’ve decided to redo the entire talk via a live stream on YouTube. I’m scheduling this for 10am PST on Wednesday, January 17 on my YouTube channel. My original talk was done in 30 minute slot, this will be a full hour, giving plenty of time for Q&A.

Cassandra Summit, YouTube, and a Mailing List

6 December 2023, 12:00 am by Posts on RustyRazorblade Consulting

I am thrilled to share some significant updates and exciting plans with my readers and the Cassandra community. As we draw closer to the end of the year, I’m preparing for an important speaking engagement and mapping out a year ahead filled with engaging and informative activities.

Cassandra Summit Presentation: Mastering Performance Tuning

I am honored to announce that I will be speaking at the upcoming Cassandra Summit. My talk, titled “Cassandra Performance Tuning Like You’ve Been Doing It for Ten Years,” is scheduled for December 13th, from 4:10 pm to 4:40 pm. This session aims to equip attendees with advanced insights and practical skills for optimizing Cassandra’s performance, drawing from a decade’s worth of experience in the field. Whether you’re new to Cassandra or a seasoned user, this talk will provide valuable insights to enhance your database management skills.

Uncover Cassandra's Throughput Boundaries with the New Adaptive Scheduler in tlp-stress

31 October 2023, 12:00 am by Posts on RustyRazorblade Consulting

Introduction

Apache Cassandra remains the preferred choice for organizations seeking a massively scalable NoSQL database. To guarantee predictable performance, Cassandra administrators and developers rely on benchmarking tools like tlp-stress, nosqlbench, and ndbench to help them discover their cluster’s limits. In this post, we will explore the latest advancements in tlp-stress, highlighting the introduction of the new Adaptive Scheduler. This brand-new feature allows users to more easily uncover the throughput boundaries of Cassandra clusters while remaining within specific read and write latency targets. First though, we’ll take a brief look at the new workload designed to stress test the new Storage Attached Indexes feature coming in Cassandra 5.

AxonOps Review - An Operations Platform for Apache Cassandra

24 October 2023, 12:00 am by Posts on RustyRazorblade Consulting

Note: Before we dive into this review of AxonOps and their offerings, it’s important to note that this blog post is part of a paid engagement in which I provided product feedback. AxonOps had no influence or say over the content of this post and did not have access to it prior to publishing.

In the ever-evolving landscape of data management, companies are constantly seeking solutions that can simplify the complexities of database operations. One such player in the market is AxonOps, a company that specializes in providing tooling for operating Apache Cassandra.

Benchmarking Apache Cassandra with tlp-stress

20 July 2023, 12:00 am by Posts on RustyRazorblade Consulting

This post will introduce you to tlp-stress, a tool for benchmarking Apache Cassandra. I started tlp-stress back when I was working at The Last Pickle. At the time, I was spending a lot of time helping teams identify the root cause of performance issues and needed a way of benchmarking. I found cassandra-stress to be difficult to use and configure, so I ended up writing my own tool that worked in a manner that I found to be more useful. If you’re looking for a tool to assist you in benchmarking Cassandra, and you’re looking to get started quickly, this might be the right tool for you.

Back to Consulting!

22 March 2023, 12:00 am by Posts on RustyRazorblade Consulting

Saying “it’s been a while since I wrote anything here” would be an understatement, but I’m back, with a lot to talk about in the upcoming months.

First off - if you’re not aware, I continued writing, but on The Last Pickle blog. There’s quite a few posts there, here are the most interesting ones:

Now the fun part - I’ve spent the last 3 years at Apple, then Netflix, neither of which gave me much time to continue my writing. As of this month, I’m officially no longer at Netflix and have started Rustyrazorblade Consulting!

Building a 100% ScyllaDB Shard-Aware Application Using Rust

15 February 2023, 12:00 am by Ultrabug

Building a 100% ScyllaDB Shard-Aware Application Using Rust

I wrote a web transcript of the talk I gave with my colleagues Joseph and Yassir at [Scylla Su...

Learning Rust the hard way for a production Kafka+ScyllaDB pipeline

21 February 2022, 12:00 am by Ultrabug

Learning Rust the hard way for a production Kafka+ScyllaDB pipeline

This is the web version of the talk I gave at [Scylla Summit 2022](https://www.scyllad...

On Scylla Manager Suspend & Resume feature

6 May 2021, 12:00 am by Ultrabug

On Scylla Manager Suspend & Resume feature

!!! warning "Disclaimer" This blog post is neither a rant nor intended to undermine the great work that...

Renaming and reshaping Scylla tables using scylla-migrator

6 November 2020, 12:00 am by Ultrabug

We have recently faced a problem where some of the first Scylla tables we created on our main production cluster were not in line any more with the evolved s...

Python scylla-driver: how we unleashed the Scylla monster's performance

24 August 2020, 12:00 am by Ultrabug

At Scylla summit 2019 I had the chance to meet Israel Fruchter and we dreamed of working on adding **shard...

Scylla Summit 2019

28 December 2019, 12:00 am by Ultrabug

I've had the pleasure to attend again and present at the Scylla Summit in San Francisco and the honor to be awarded the...

A Small Utility to Help With Extracting Code Snippets

10 August 2019, 12:00 am by Posts on RustyRazorblade Consulting

It’s been a while since I’ve written anything here. Part of the reason has been due to the writing I’ve done over on the blog at The Last Pickle. In the lsat few years, I’ve written about our tlp-stress tool, tips for new Cassandra clusters, and a variety of performance posts related to Compaction, Compression, and GC Tuning.

The other reason is the eight blog posts I’ve got in the draft folder. One of the reasons why there are so many is the way I write. If the post is programming related, I usually start with the post, then start coding, pull snippets out, learn more, rework the post, then rework snippets. It’s an annoying, manual process. The posts sitting in my draft folder have incomplete code, and reworking the code is a tedious process that I get annoyed with, leading to abandoned posts.

Scylla: four ways to optimize your disk space consumption

29 March 2019, 12:00 am by Ultrabug

We recently had to face free disk space outages on some of our scylla clusters and we learnt some very interesting things while outlining some improvements t...

Scylla Summit 2018 write-up

6 December 2018, 12:00 am by Ultrabug

It's been almost one month since I had the chance to attend and speak at Scylla Summit 2018 so I'm reliev...

Authenticating and connecting to a SSL enabled Scylla cluster using Spark 2

19 July 2018, 12:00 am by Ultrabug

This quick article is a wrap up for reference on how to connect to ScyllaDB using Spark 2 when authentication and SSL are enforced for the clients on the...

A botspot story

6 July 2018, 12:00 am by Ultrabug

I felt like sharing a recent story that allowed us identify a bot in a haystack thanks to Scylla.

...

Evaluating ScyllaDB for production 2/2

28 February 2018, 12:00 am by Ultrabug

In my previous blog post, I shared [7 lessons on our experience in evaluating Scylla](https://www.ultrabug.fr...

Accessing Private Variables in the JVM

25 February 2018, 12:00 am by Posts on RustyRazorblade Consulting

In this I’ll discuss a uncommonly used but useful technique of accessing variables and methods which have been declared as private in the JVM, using the Apache Commons Lang library to work around the restriction. The description from the project page reads:

The standard Java libraries fail to provide enough methods for manipulation of its core classes. Apache Commons Lang provides these extra methods.

A couple weeks ago I was working on a project that required parsing some CQL statements. There isn’t a standard parser separate from the Cassandra project at the moment, so I decided to pull in the entirety of cassandra-all from maven central. The parser in Cassandra isn’t really designed to be used as a library. In particular, the org.apache.cassandra.cql3.QueryProcessor has a parseStatement(String) call, but the ParsedStatement that’s returned doesn’t expose any of the private variables via getters. I felt particularly determined for some reason, so I decided to investigate a workaround.

Migration to Hugo

10 February 2018, 12:00 am by Posts on RustyRazorblade Consulting

After almost five years of using Pelican as my static site generator, I’ve migrated to the Hugo tool. While I enjoyed Pelican and it’s flexibility, it’s performance started to bother me when building a site from scratch. Depending on what else was running on my laptop, a full build could take 15-20 seconds. This isn’t the end of the world, but in comparison Hugo takes less than 100 milliseconds.

If it was simply a matter of build time, I may not have really cared that much, but I’ve been using Hugo to build the site and documentation for Reaper, the open source repair tool we maintain at The Last Pickle.

Evaluating ScyllaDB for production 1/2

23 January 2018, 12:00 am by Ultrabug

I have recently been conducting a quite deep evaluation of ScyllaDB to find out if we could benefit from this database in some of...

Working with gRPC, Kotlin and Gradle

9 October 2017, 12:00 am by Posts on RustyRazorblade Consulting

Edit: The source code for this post is located on GitHub

Sometimes when I travel I end up trying to learn something completely new. For a while I was playing with Rust, Capn Proto, Scala, or I’d start a throwaway project at an airport and just tinker.

My passion is and has always been databases. I’ve maintained this blog for roughly a decade, starting with MySQL for the first part of my career but moving to Apache Cassandra several years ago, and am now a committer and member of the PMC.

I Am Still Writing!

18 April 2017, 12:00 am by Posts on RustyRazorblade Consulting

If you were to take a look at my blog, you’d think I’d flipped a table and left the tech industry. Not the case at all. I’m still writing, but less frequently, and on the TLP blog. I intend to start writing here again, but the material will likely focus around topics other than Cassandra, since I’m already writing about it elsewhere. Here are the posts I’ve authored in the last 6 months or so:

Instaclustr Now Supporting Apache Cassandra 3.7 as LTS

20 October 2016, 12:00 am by Posts on RustyRazorblade Consulting

Instacluster announced on the Apache Cassandra user list that they are making their supported branch of the Cassandra 3.7 tick tock release publicly available (see GitHub repo). Bug fixes that go into 3.8, 3.9, etc will be back ported to the Instacluster LTS. You can read the blog post about the decision.

Some people I’ve talked to are concerned about having different commercial entities doing long term supported releases, and this concern is understandable. The obvious preference is for the project maintainers to handle this and make an official LTS available. The big concern here is that third party LTS could fracture the project in the long term.

Rustyrazorblade Radio, A Distributed System Podcast

13 September 2016, 12:00 am by Posts on RustyRazorblade Consulting

I haven’t blogged in a while, which is a bummer because I was determined to write an article a week for the entire year. I haven’t even come remotely close to that goal.

I’ve recently switched jobs from DataStax to Consulting with The Last Pickle, which has been pretty hectic. Add to that 3 presentations at the Cassandra Summit and the end result is very little time for personal projects.

Working Relationally With Cassandra

11 May 2016, 12:00 am by Posts on RustyRazorblade Consulting

I’ve spent the last 4 years working in the big data world with Cassandra because it’s the only practical solution if you have a requirement to scale out, uptime is a priority, and you need predictable performance. I’ve heard different ways of describing where Cassandra fits in your architecture, but I think the best way to think of it is close to your customer. Think of the servers your mobile apps communicate with or what holds your product inventory.

Cassandra Dataset Manager Preview 1 Released

29 April 2016, 12:00 am by Posts on RustyRazorblade Consulting

One of the problems of learning a new database is getting used to a new way of data modeling. PostgreSQL looks different from Redis, which is different from a graph, and is different from Cassandra.

Cassandra Dataset Manager aims to reduce the time spent in a frustrating trial and error process trying to learn proper data modeling techniques for Apache Cassandra and Datastax Enterprise by providing curated data models which have been designed by professionals with years of experience. Think of it as a package manager for Cassandra data models and sample data.

Cassandra Dataset Manager Video Preview

6 April 2016, 12:00 am by Posts on RustyRazorblade Consulting

I posted a short preview showing off some of the work I’ve been doing recently on Cassandra Dataset Manager, a tool to help new Cassandra users learn how to create proper data models.

There’s documentation, but it’s still under heavy development.

Cassandra 3.3 Released

18 February 2016, 12:00 am by Posts on RustyRazorblade Consulting

Apache Cassandra 3.3 was released last week. As per the Tick Tock release schedule, this release is focused on bug fixes and no new features were introduced. For practical purposes, consider this a bug fix release to Cassandra 3.2. All told there were almost 50 bugs fixed in this release. Many of the bugs fixed in this version also applied to Cassandra 3.0.3, which was also released last week.

Cassandra Secondary Index Preview #1

8 February 2016, 12:00 am by Posts on RustyRazorblade Consulting

If you’ve looked into using Cassandra at all, you probably have heard plenty of warnings about its secondary indexes. If you’ve come from a relational background, you may have been surprised when you were told to create multiple tables (materialized views) instead of relying on indexes. This is because Cassandra is a distributed database, and the impact of doing a query that hits your entire cluster is you lose your linear scalability. If you’re capped at 25K queries per second per server, it doesn’t matter if you have one or a thousand servers, you’re still only able to handle 25k queries per second, total.