SlideShare a Scribd company logo
1 of 19
Version 1.0
Guardrails - Apache Cassandra
In Cassandra lunch #107, we will discuss how Guardrails
work in Apache Cassandra
Dipan Shah
Engineer @ Anant
Topics
● What are guardrails?
● What is the purpose of guardrails?
● How they work?
● Guardrails options for production
● Guardrails demo
● Upcoming developments
● Q&A
Guardrails in Apache Cassandra
● A framework that allows operators to restrict certain functionalities in Cassandra
● Available from Apache Cassandra V 4.1
● Has been available in Datastax Enterprise from V 6.8 in some form
What problems does it solve?
● Operators have faced cluster stability problems due to improper usage of Cassandra
● Best practices and Anti-patterns are difficult to communicate and enforce
● Guardrails allow to restrict some of these functionalities
● Options like below have been available since earlier versions but this is different
○ Tombstone limits
○ Batch limits
○ Materialized views usage
How it works?
The new framework allows operators to restrict how Cassandra is used by:
● Disabling certain features
● Disallowing some specific values
● Defining soft and hard limits to certain database magnitudes
How it works?
Guardrail violation are validated at:
● CQL Layer
● In the background
CQL Guardrails Examples
● allow_filtering_enabled : false
○ Will not allow queries with “Allow filtering” if set to false
○ CQL error is reported
CQL Guardrails Examples
● tables_warn_threshold : 20
○ Raises a CQL client warning and logs a server-side warning message
○ CQL operation is not aborted
CQL Guardrails Examples
● tables_fail_threshold : 30
○ CQL operation will be aborted
Monitoring Guardrail events
● The triggering of a guardrail will emit a diagnostic log with guardrail event in it
● Check logs for WARN and ERROR messages related to guardrails
● Set alerts for such messages in log aggregation tools like Splunk, ELK stack, Graylog,
etc.
More Guardrail examples
● Secondary Indexes
○ secondary_indexes_enabled: true
○ secondary_indexes_per_table_warn_threshold: 5
○ secondary_indexes_per_table_fail_threshold: 10
● Number of fields in a UDT
○ fields_per_udt_warn_threshold: -1
○ fields_per_udt_fail_threshold: -1
Background Guardrails
● Some guardrails are checked in the background
● They are not associated with any specific query
● To avoid a costly read-before-write operation
● Examples:
○ Disk space usage
○ Number of items in a non-frozen collection
Additional Guardrails for Production
● Replication factor
○ minimum_replication_factor_warn_threshold
○ minimum_replication_factor_fail_threshold
● Read and write consistency levels
○ read_consistency_levels_warned: []
○ read_consistency_levels_disallowed: []
○ write_consistency_levels_warned: []
○ write_consistency_levels_disallowed: []
Additional Guardrails for Production
● IN restrictions
○ partition_keys_in_select_warn_threshold
○ partition_keys_in_select_fail_threshold
● Materialized views
○ materialized_views_per_table_warn_threshold
○ materialized_views_per_table_fail_threshold
Exceptions
● Guardrails are only applied to the operations of regular users
● They will neither be checked for superuser queries nor internal queries
● The configuration for guardrails is an extensible API
● Third-party alternative implementations could provide different guardrail
configurations depending on the user, or on some other factors
Demo
Upcoming developments
● New features are being developed
● Can be tracked at: https://issues.apache.org/jira/browse/CASSANDRA-
17189?jql=project%20%3D%20CASSANDRA%20AND%20text%20~%20%22guard
rail%22
Questions
Strategy: Scalable Fast Data
Architecture: Cassandra, Spark, Kafka
Engineering: Node, Python, JVM,CLR
Operations: Cloud, Container
Rescue: Downtime!! I need help.
www.anant.us | solutions@anant.us | (855) 262-6826
3 Washington Circle, NW | Suite 301 | Washington, DC 20037

More Related Content

Similar to Apache Cassandra Lunch #107: Guardrails

Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...
 Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F... Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...
Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...Databricks
 
MySQL backup and restore performance
MySQL backup and restore performanceMySQL backup and restore performance
MySQL backup and restore performanceVinicius M Grippa
 
Truemotion Adventures in Containerization
Truemotion Adventures in ContainerizationTruemotion Adventures in Containerization
Truemotion Adventures in ContainerizationRyan Hunter
 
Load testing in Zonky with Gatling
Load testing in Zonky with GatlingLoad testing in Zonky with Gatling
Load testing in Zonky with GatlingPetr Vlček
 
What to expect from MariaDB Platform X5, part 1
What to expect from MariaDB Platform X5, part 1What to expect from MariaDB Platform X5, part 1
What to expect from MariaDB Platform X5, part 1MariaDB plc
 
PL22 - Backup and Restore Performance.pptx
PL22 - Backup and Restore Performance.pptxPL22 - Backup and Restore Performance.pptx
PL22 - Backup and Restore Performance.pptxVinicius M Grippa
 
Best Practices for Developing & Deploying Java Applications with Docker
Best Practices for Developing & Deploying Java Applications with DockerBest Practices for Developing & Deploying Java Applications with Docker
Best Practices for Developing & Deploying Java Applications with DockerEric Smalling
 
Migrating to Apache Spark at Netflix
Migrating to Apache Spark at NetflixMigrating to Apache Spark at Netflix
Migrating to Apache Spark at NetflixDatabricks
 
Eko10 Workshop Opensource Database Auditing
Eko10  Workshop Opensource Database AuditingEko10  Workshop Opensource Database Auditing
Eko10 Workshop Opensource Database AuditingJuan Berner
 
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst IT
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst ITThings You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst IT
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst ITOpenStack
 
Crikeycon 2019 Velociraptor Workshop
Crikeycon 2019 Velociraptor WorkshopCrikeycon 2019 Velociraptor Workshop
Crikeycon 2019 Velociraptor WorkshopVelocidex Enterprises
 
Journey through high performance django application
Journey through high performance django applicationJourney through high performance django application
Journey through high performance django applicationbangaloredjangousergroup
 
OpenNebula and StorPool: Building Powerful Clouds
OpenNebula and StorPool: Building Powerful CloudsOpenNebula and StorPool: Building Powerful Clouds
OpenNebula and StorPool: Building Powerful CloudsOpenNebula Project
 
Eko10 workshop - OPEN SOURCE DATABASE MONITORING
Eko10 workshop - OPEN SOURCE DATABASE MONITORINGEko10 workshop - OPEN SOURCE DATABASE MONITORING
Eko10 workshop - OPEN SOURCE DATABASE MONITORINGPablo Garbossa
 
Monitoring hybrid container environments
Monitoring hybrid container environments Monitoring hybrid container environments
Monitoring hybrid container environments Samuel Vandamme
 
Software Profiling: Java Performance, Profiling and Flamegraphs
Software Profiling: Java Performance, Profiling and FlamegraphsSoftware Profiling: Java Performance, Profiling and Flamegraphs
Software Profiling: Java Performance, Profiling and FlamegraphsIsuru Perera
 
MariaDB Security Best Practices
MariaDB Security Best PracticesMariaDB Security Best Practices
MariaDB Security Best PracticesFederico Razzoli
 
Introduction to Akka Serverless
Introduction to Akka ServerlessIntroduction to Akka Serverless
Introduction to Akka ServerlessKnoldus Inc.
 
How to keep maintainability of long life Scala applications
How to keep maintainability of long life Scala applicationsHow to keep maintainability of long life Scala applications
How to keep maintainability of long life Scala applicationstakezoe
 

Similar to Apache Cassandra Lunch #107: Guardrails (20)

Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...
 Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F... Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...
Scalable Monitoring Using Prometheus with Apache Spark Clusters with Diane F...
 
MySQL backup and restore performance
MySQL backup and restore performanceMySQL backup and restore performance
MySQL backup and restore performance
 
Truemotion Adventures in Containerization
Truemotion Adventures in ContainerizationTruemotion Adventures in Containerization
Truemotion Adventures in Containerization
 
Load testing in Zonky with Gatling
Load testing in Zonky with GatlingLoad testing in Zonky with Gatling
Load testing in Zonky with Gatling
 
What to expect from MariaDB Platform X5, part 1
What to expect from MariaDB Platform X5, part 1What to expect from MariaDB Platform X5, part 1
What to expect from MariaDB Platform X5, part 1
 
PL22 - Backup and Restore Performance.pptx
PL22 - Backup and Restore Performance.pptxPL22 - Backup and Restore Performance.pptx
PL22 - Backup and Restore Performance.pptx
 
Best Practices for Developing & Deploying Java Applications with Docker
Best Practices for Developing & Deploying Java Applications with DockerBest Practices for Developing & Deploying Java Applications with Docker
Best Practices for Developing & Deploying Java Applications with Docker
 
Migrating to Apache Spark at Netflix
Migrating to Apache Spark at NetflixMigrating to Apache Spark at Netflix
Migrating to Apache Spark at Netflix
 
Eko10 Workshop Opensource Database Auditing
Eko10  Workshop Opensource Database AuditingEko10  Workshop Opensource Database Auditing
Eko10 Workshop Opensource Database Auditing
 
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst IT
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst ITThings You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst IT
Things You MUST Know Before Deploying OpenStack: Bruno Lago, Catalyst IT
 
Crikeycon 2019 Velociraptor Workshop
Crikeycon 2019 Velociraptor WorkshopCrikeycon 2019 Velociraptor Workshop
Crikeycon 2019 Velociraptor Workshop
 
Running Cassandra in AWS
Running Cassandra in AWSRunning Cassandra in AWS
Running Cassandra in AWS
 
Journey through high performance django application
Journey through high performance django applicationJourney through high performance django application
Journey through high performance django application
 
OpenNebula and StorPool: Building Powerful Clouds
OpenNebula and StorPool: Building Powerful CloudsOpenNebula and StorPool: Building Powerful Clouds
OpenNebula and StorPool: Building Powerful Clouds
 
Eko10 workshop - OPEN SOURCE DATABASE MONITORING
Eko10 workshop - OPEN SOURCE DATABASE MONITORINGEko10 workshop - OPEN SOURCE DATABASE MONITORING
Eko10 workshop - OPEN SOURCE DATABASE MONITORING
 
Monitoring hybrid container environments
Monitoring hybrid container environments Monitoring hybrid container environments
Monitoring hybrid container environments
 
Software Profiling: Java Performance, Profiling and Flamegraphs
Software Profiling: Java Performance, Profiling and FlamegraphsSoftware Profiling: Java Performance, Profiling and Flamegraphs
Software Profiling: Java Performance, Profiling and Flamegraphs
 
MariaDB Security Best Practices
MariaDB Security Best PracticesMariaDB Security Best Practices
MariaDB Security Best Practices
 
Introduction to Akka Serverless
Introduction to Akka ServerlessIntroduction to Akka Serverless
Introduction to Akka Serverless
 
How to keep maintainability of long life Scala applications
How to keep maintainability of long life Scala applicationsHow to keep maintainability of long life Scala applications
How to keep maintainability of long life Scala applications
 

More from Anant Corporation

QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137
QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137
QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137Anant Corporation
 
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdf
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdfKono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdf
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdfAnant Corporation
 
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache Pinot
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache PinotData Engineer's Lunch 96: Intro to Real Time Analytics Using Apache Pinot
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache PinotAnant Corporation
 
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...Anant Corporation
 
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPTAutomate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPTAnant Corporation
 
Episode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
Episode 2: The LLM / GPT / AI Prompt / Data Engineer RoadmapEpisode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
Episode 2: The LLM / GPT / AI Prompt / Data Engineer RoadmapAnant Corporation
 
Machine Learning Orchestration with Airflow
Machine Learning Orchestration with AirflowMachine Learning Orchestration with Airflow
Machine Learning Orchestration with AirflowAnant Corporation
 
Cassandra Lunch 130: Recap of Cassandra Forward Talks
Cassandra Lunch 130: Recap of Cassandra Forward TalksCassandra Lunch 130: Recap of Cassandra Forward Talks
Cassandra Lunch 130: Recap of Cassandra Forward TalksAnant Corporation
 
Data Engineer's Lunch 90: Migrating SQL Data with Arcion
Data Engineer's Lunch 90: Migrating SQL Data with ArcionData Engineer's Lunch 90: Migrating SQL Data with Arcion
Data Engineer's Lunch 90: Migrating SQL Data with ArcionAnant Corporation
 
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...Anant Corporation
 
Cassandra Lunch 129: What’s New: Apache Cassandra 4.1+ Features & Future
Cassandra Lunch 129: What’s New:  Apache Cassandra 4.1+ Features & FutureCassandra Lunch 129: What’s New:  Apache Cassandra 4.1+ Features & Future
Cassandra Lunch 129: What’s New: Apache Cassandra 4.1+ Features & FutureAnant Corporation
 
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...Anant Corporation
 
Data Engineer's Lunch #85: Designing a Modern Data Stack
Data Engineer's Lunch #85: Designing a Modern Data StackData Engineer's Lunch #85: Designing a Modern Data Stack
Data Engineer's Lunch #85: Designing a Modern Data StackAnant Corporation
 
Data Engineer's Lunch #83: Strategies for Migration to Apache Iceberg
Data Engineer's Lunch #83: Strategies for Migration to Apache IcebergData Engineer's Lunch #83: Strategies for Migration to Apache Iceberg
Data Engineer's Lunch #83: Strategies for Migration to Apache IcebergAnant Corporation
 
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOps
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOpsApache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOps
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOpsAnant Corporation
 
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache Cassandra
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache CassandraApache Cassandra Lunch 119: Desktop GUI Tools for Apache Cassandra
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache CassandraAnant Corporation
 
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...Anant Corporation
 
Data Engineer's Lunch #60: Series - Developing Enterprise Consciousness
Data Engineer's Lunch #60: Series - Developing Enterprise ConsciousnessData Engineer's Lunch #60: Series - Developing Enterprise Consciousness
Data Engineer's Lunch #60: Series - Developing Enterprise ConsciousnessAnant Corporation
 

More from Anant Corporation (20)

QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137
QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137
QLoRA Fine-Tuning on Cassandra Link Data Set (1/2) Cassandra Lunch 137
 
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdf
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdfKono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdf
Kono.IntelCraft.Weekly.AI.LLM.Landscape.2024.02.28.pdf
 
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache Pinot
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache PinotData Engineer's Lunch 96: Intro to Real Time Analytics Using Apache Pinot
Data Engineer's Lunch 96: Intro to Real Time Analytics Using Apache Pinot
 
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...
NoCode, Data & AI LLM Inside Bootcamp: Episode 6 - Design Patterns: Retrieval...
 
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPTAutomate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
Automate your Job and Business with ChatGPT #3 - Fundamentals of LLM/GPT
 
YugabyteDB Developer Tools
YugabyteDB Developer ToolsYugabyteDB Developer Tools
YugabyteDB Developer Tools
 
Episode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
Episode 2: The LLM / GPT / AI Prompt / Data Engineer RoadmapEpisode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
Episode 2: The LLM / GPT / AI Prompt / Data Engineer Roadmap
 
Machine Learning Orchestration with Airflow
Machine Learning Orchestration with AirflowMachine Learning Orchestration with Airflow
Machine Learning Orchestration with Airflow
 
Cassandra Lunch 130: Recap of Cassandra Forward Talks
Cassandra Lunch 130: Recap of Cassandra Forward TalksCassandra Lunch 130: Recap of Cassandra Forward Talks
Cassandra Lunch 130: Recap of Cassandra Forward Talks
 
Data Engineer's Lunch 90: Migrating SQL Data with Arcion
Data Engineer's Lunch 90: Migrating SQL Data with ArcionData Engineer's Lunch 90: Migrating SQL Data with Arcion
Data Engineer's Lunch 90: Migrating SQL Data with Arcion
 
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...
Data Engineer's Lunch 89: Machine Learning Orchestration with AirflowMachine ...
 
Cassandra Lunch 129: What’s New: Apache Cassandra 4.1+ Features & Future
Cassandra Lunch 129: What’s New:  Apache Cassandra 4.1+ Features & FutureCassandra Lunch 129: What’s New:  Apache Cassandra 4.1+ Features & Future
Cassandra Lunch 129: What’s New: Apache Cassandra 4.1+ Features & Future
 
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...
Data Engineer's Lunch #86: Building Real-Time Applications at Scale: A Case S...
 
Data Engineer's Lunch #85: Designing a Modern Data Stack
Data Engineer's Lunch #85: Designing a Modern Data StackData Engineer's Lunch #85: Designing a Modern Data Stack
Data Engineer's Lunch #85: Designing a Modern Data Stack
 
CL 121
CL 121CL 121
CL 121
 
Data Engineer's Lunch #83: Strategies for Migration to Apache Iceberg
Data Engineer's Lunch #83: Strategies for Migration to Apache IcebergData Engineer's Lunch #83: Strategies for Migration to Apache Iceberg
Data Engineer's Lunch #83: Strategies for Migration to Apache Iceberg
 
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOps
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOpsApache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOps
Apache Cassandra Lunch 120: Apache Cassandra Monitoring Made Easy with AxonOps
 
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache Cassandra
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache CassandraApache Cassandra Lunch 119: Desktop GUI Tools for Apache Cassandra
Apache Cassandra Lunch 119: Desktop GUI Tools for Apache Cassandra
 
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...
Data Engineer's Lunch #82: Automating Apache Cassandra Operations with Apache...
 
Data Engineer's Lunch #60: Series - Developing Enterprise Consciousness
Data Engineer's Lunch #60: Series - Developing Enterprise ConsciousnessData Engineer's Lunch #60: Series - Developing Enterprise Consciousness
Data Engineer's Lunch #60: Series - Developing Enterprise Consciousness
 

Recently uploaded

GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]📊 Markus Baersch
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Seán Kennedy
 
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...ssuserf63bd7
 
PKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPramod Kumar Srivastava
 
Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Cathrine Wilhelmsen
 
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一F sss
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our WorldEduminds Learning
 
Easter Eggs From Star Wars and in cars 1 and 2
Easter Eggs From Star Wars and in cars 1 and 2Easter Eggs From Star Wars and in cars 1 and 2
Easter Eggs From Star Wars and in cars 1 and 217djon017
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样vhwb25kk
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanMYRABACSAFRA2
 
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Jack DiGiovanna
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxMike Bennett
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfchwongval
 
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSINGmarianagonzalez07
 
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhijennyeacort
 
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改yuu sss
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...Boston Institute of Analytics
 
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一fhwihughh
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsVICTOR MAESTRE RAMIREZ
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectBoston Institute of Analytics
 

Recently uploaded (20)

GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...
 
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...
Statistics, Data Analysis, and Decision Modeling, 5th edition by James R. Eva...
 
PKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptxPKS-TGC-1084-630 - Stage 1 Proposal.pptx
PKS-TGC-1084-630 - Stage 1 Proposal.pptx
 
Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)Data Factory in Microsoft Fabric (MsBIP #82)
Data Factory in Microsoft Fabric (MsBIP #82)
 
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
办理学位证中佛罗里达大学毕业证,UCF成绩单原版一比一
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our World
 
Easter Eggs From Star Wars and in cars 1 and 2
Easter Eggs From Star Wars and in cars 1 and 2Easter Eggs From Star Wars and in cars 1 and 2
Easter Eggs From Star Wars and in cars 1 and 2
 
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
1:1定制(UQ毕业证)昆士兰大学毕业证成绩单修改留信学历认证原版一模一样
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population Mean
 
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
Building on a FAIRly Strong Foundation to Connect Academic Research to Transl...
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptx
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdf
 
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
2006_GasProcessing_HB (1).pdf HYDROCARBON PROCESSING
 
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
 
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改
专业一比一美国俄亥俄大学毕业证成绩单pdf电子版制作修改
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
 
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business Professionals
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis Project
 

Apache Cassandra Lunch #107: Guardrails

  • 1. Version 1.0 Guardrails - Apache Cassandra In Cassandra lunch #107, we will discuss how Guardrails work in Apache Cassandra Dipan Shah Engineer @ Anant
  • 2. Topics ● What are guardrails? ● What is the purpose of guardrails? ● How they work? ● Guardrails options for production ● Guardrails demo ● Upcoming developments ● Q&A
  • 3. Guardrails in Apache Cassandra ● A framework that allows operators to restrict certain functionalities in Cassandra ● Available from Apache Cassandra V 4.1 ● Has been available in Datastax Enterprise from V 6.8 in some form
  • 4. What problems does it solve? ● Operators have faced cluster stability problems due to improper usage of Cassandra ● Best practices and Anti-patterns are difficult to communicate and enforce ● Guardrails allow to restrict some of these functionalities ● Options like below have been available since earlier versions but this is different ○ Tombstone limits ○ Batch limits ○ Materialized views usage
  • 5. How it works? The new framework allows operators to restrict how Cassandra is used by: ● Disabling certain features ● Disallowing some specific values ● Defining soft and hard limits to certain database magnitudes
  • 6. How it works? Guardrail violation are validated at: ● CQL Layer ● In the background
  • 7. CQL Guardrails Examples ● allow_filtering_enabled : false ○ Will not allow queries with “Allow filtering” if set to false ○ CQL error is reported
  • 8. CQL Guardrails Examples ● tables_warn_threshold : 20 ○ Raises a CQL client warning and logs a server-side warning message ○ CQL operation is not aborted
  • 9. CQL Guardrails Examples ● tables_fail_threshold : 30 ○ CQL operation will be aborted
  • 10. Monitoring Guardrail events ● The triggering of a guardrail will emit a diagnostic log with guardrail event in it ● Check logs for WARN and ERROR messages related to guardrails ● Set alerts for such messages in log aggregation tools like Splunk, ELK stack, Graylog, etc.
  • 11. More Guardrail examples ● Secondary Indexes ○ secondary_indexes_enabled: true ○ secondary_indexes_per_table_warn_threshold: 5 ○ secondary_indexes_per_table_fail_threshold: 10 ● Number of fields in a UDT ○ fields_per_udt_warn_threshold: -1 ○ fields_per_udt_fail_threshold: -1
  • 12. Background Guardrails ● Some guardrails are checked in the background ● They are not associated with any specific query ● To avoid a costly read-before-write operation ● Examples: ○ Disk space usage ○ Number of items in a non-frozen collection
  • 13. Additional Guardrails for Production ● Replication factor ○ minimum_replication_factor_warn_threshold ○ minimum_replication_factor_fail_threshold ● Read and write consistency levels ○ read_consistency_levels_warned: [] ○ read_consistency_levels_disallowed: [] ○ write_consistency_levels_warned: [] ○ write_consistency_levels_disallowed: []
  • 14. Additional Guardrails for Production ● IN restrictions ○ partition_keys_in_select_warn_threshold ○ partition_keys_in_select_fail_threshold ● Materialized views ○ materialized_views_per_table_warn_threshold ○ materialized_views_per_table_fail_threshold
  • 15. Exceptions ● Guardrails are only applied to the operations of regular users ● They will neither be checked for superuser queries nor internal queries ● The configuration for guardrails is an extensible API ● Third-party alternative implementations could provide different guardrail configurations depending on the user, or on some other factors
  • 16. Demo
  • 17. Upcoming developments ● New features are being developed ● Can be tracked at: https://issues.apache.org/jira/browse/CASSANDRA- 17189?jql=project%20%3D%20CASSANDRA%20AND%20text%20~%20%22guard rail%22
  • 19. Strategy: Scalable Fast Data Architecture: Cassandra, Spark, Kafka Engineering: Node, Python, JVM,CLR Operations: Cloud, Container Rescue: Downtime!! I need help. www.anant.us | solutions@anant.us | (855) 262-6826 3 Washington Circle, NW | Suite 301 | Washington, DC 20037

Editor's Notes

  1. https://cassandra.apache.org/_/blog/Apache-Cassandra-4.1-Features-Guardrails-Framework.html For example, on the schema side, users can create too many tables or secondary indexes, leading to excessive use of resources. On the query side, users can run queries touching too many partitions that might involve all nodes in the cluster. Even worse, they can simply run a query using costly replica-side filtering, potentially reading all the table contents into memory on all nodes across the cluster. https://docs.datastax.com/en/dse/6.8/dse-dev/datastax_enterprise/config/configCassandra_yaml.html#configCassandra_yaml__guardrailsYaml