SlideShare uma empresa Scribd logo
1 de 37
Cassandra Tools and Distributed Administration
Dr. Jeffrey Berger
Lead Database Engineer
Knewton
1 Introduction
2 Why command-line tools?
3 cassandra-stat
4 cassandra-tracing
5 Ansible ad-hoc commands
2© DataStax, All Rights Reserved.
Knewton
© DataStax, All Rights Reserved. 3
Leader in adaptive learning
● Partners with publishers and institutions in Europe, US,
and Asia
● Provides unique recommendations to students based on
previous behavior
● Advanced content ingestion, curation, and calibration
● Runs in AWS with many different storage backends
● Check us out: www.knewton.com/about/careers/
Cassandra at Knewton
© DataStax, All Rights Reserved. 4
Cassandra is the main datastore at Knewton
EU ProductionDevelopment US ProductionUser AcceptanceQA
Clusters: 5
Nodes: 15
Clusters: 6
Nodes: 69
Clusters: 6
Nodes: 18
Clusters: 6
Nodes: 24
Clusters: 2
Nodes: 6
Clusters: 25 Nodes: 132
Cassandra Challenges
© DataStax, All Rights Reserved. 5
• Monitoring
– Historical measures are important
• Triage
– Immediate answers in a distributed system
• Provisioning
– Keep configurations consistent
• Scaling
– Elastically scale Cassandra 'out' or 'in'
Cassandra Challenges
© DataStax, All Rights Reserved. 6
• Monitoring
– Historical measures are important
• Triage
– Immediate answers in a distributed system
• Provisioning
– Keep configurations consistent
• Scaling
– Elastically scale Cassandra 'out' or 'in'
Solutions as Software
© DataStax, All Rights Reserved. 7
If you magnify your surface area,
magnify your tools
● Easy to use
● Fast and responsive
● Distributed
1 Introduction
2 Why command-line tools?
3 cassandra-stat
4 cassandra-tracing
5 Ansible ad-hoc commands
8© DataStax, All Rights Reserved.
Why command line tools?
© DataStax, All Rights Reserved. 9
Always consider the operator!
Systems people like the command line!
● Few moving parts
● Local
● Immediate
Why not graphs?
© DataStax, All Rights Reserved. 10
Graphs are great, I love graphs
● Not immediate
● Can be overloaded
● Remote
● Fixed metrics
● Averages rather than values
Why not nodetool?
© DataStax, All Rights Reserved. 11
Nodetool is great..
Why not nodetool?
© DataStax, All Rights Reserved. 12
Until it is time to cook dinner...
Jolokia ( jolokia.org )
© DataStax, All Rights Reserved. 13
Exposes JMX endpoints by HTTP
• Open source (Apache2)
• Lets you script with full access to JMX endpoints
• Agent runs with cassandra
• Lightweight, fast, easy to install
Installing Jolokia is painless
© DataStax, All Rights Reserved. 14
2) Add this line to cassandra-env.sh
# added to activate the jolokia agent
JVM_OPTS="$JVM_OPTS -javaagent:/opt/cassandra/jolokia-jvm-agent.jar"
(Or whatever the path is to your Jolokia JVM jar!)
1) Download the Jolokia JVM agent from their site / maven
What to do with Jolokia?
© DataStax, All Rights Reserved. 15
Build some monitoring tools!
• Use jconsole to find metrics you are interested in
• Make some programs with your favorite language
• Get the metrics from Jolokia to feed it
Check out the tools we have already made!
cassandra-toolbox
© DataStax, All Rights Reserved. 16
Python package of cassandra tools developed at Knewton
• Pip installable
– pip install cassandra-toolbox
• Open source (Apache2)
• Interacts with C* via Jolokia
• github.com/Knewton/cassandra-toolbox
• 2 scripts right now, more soon
1 Introduction
2 Why command-line tools?
3 cassandra-stat
4 cassandra-tracing
5 Ansible ad-hoc commands
17© DataStax, All Rights Reserved.
cassandra-stat
© DataStax, All Rights Reserved. 18
A real-time feed of Cassandra operations
Like iostat for Cassandra
• Interacts with Jolokia agent
• Diffs metrics on a configurable time scale
• Overall / Keyspace / CF granularity
• Easy to use, easy to read
cassandra-stat
© DataStax, All Rights Reserved. 19
$cassandra-stat
Reads Writes Reads (99%) ms Writes (99%) ms Compactions Time ns
1 111 91.462 17.4 0 20:15:36 total
2 113 91.4 17.98 0 20:15:37 total
0 117 91.4 17.17 0 20:15:38 total
0 72 91.4 17.34 0 20:15:39 total
0 69 91.4 17.3 0 20:15:40 total
*Not all fields shown
Some metrics are summed
across CFs and the difference
from the last iteration reported
Some report the maximum
value from all CFs
Some metrics are summed
across CFs
cassandra-stat
20
metrics = [
{
"metric_name": "ReadLatency",
"metric_key": "Count",
"display_name": "Reads",
"sum": True,
"diff": True,
"nonzero": True
},
...
● Metrics are not hardcoded
● Easy to add/remove
● Flexible
○ sum
○ diff
○ nonzero
● Configuration is moving to
a YAML file
cassandra-stat
© DataStax, All Rights Reserved. 21
Benefits:
• Traffic monitoring
– Real time load can be read off easily
• Performance debugging
– All vital metrics are on a single line at each time
• High granularity
– Metrics every second
• Diverse metrics
– Metrics can be configured and read out immediately
1 Introduction
2 Why command-line tools?
3 cassandra-stat
4 cassandra-tracing
5 Ansible ad-hoc commands
22© DataStax, All Rights Reserved.
cassandra-tracing
© DataStax, All Rights Reserved. 23
Sampling a percent of all queries is a great tool*
$nodetool settraceprobability 0.001
But if you ever queried the CFs in system_traces you
might be bewildered..
* Don't set this percent too high!
cassandra-tracing
© DataStax, All Rights Reserved. 24
cqlsh:system_traces> SELECT request,parameters FROM sessions LIMIT 4;
request | parameters
--------------------+---------------------------------------
Execute CQL3 query |
{'consistency_level': 'LOCAL_ONE', 'page_size': '5000', 'query': 'SELECT * FROM test2 WHERE
key=''XXXXXXXXXXXXXXXXX''', 'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'select cluster_name from system.local',
'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'select cluster_name from system.local',
'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'SELECT * FROM system.schema_columnfamilies',
'serial_consistency_level': 'SERIAL'}
cassandra-tracing
© DataStax, All Rights Reserved. 25
cqlsh:system_traces> SELECT request,parameters FROM sessions LIMIT 4;
request | parameters
--------------------+---------------------------------------
Execute CQL3 query |
{'consistency_level': 'LOCAL_ONE', 'page_size': '5000', 'query': 'SELECT * FROM test2 WHERE
key=''XXXXXXXXXXXXXXXXX''', 'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'select cluster_name from system.local',
'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'select cluster_name from system.local',
'serial_consistency_level': 'SERIAL'}
Execute CQL3 query |
{'consistency_level': 'ONE', 'query': 'SELECT * FROM system.schema_columnfamilies',
'serial_consistency_level': 'SERIAL'}
cassandra-tracing
© DataStax, All Rights Reserved. 26
$ cassandra-tracing `hostname -I `
100% Complete: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX|100
Total skipped due to null duration: 0
Total skipped due to error: 0
175 sessions satisfying criteria.
Showing 100 longest running results.
Session Id Duration(us) Query
UUID 19696 SELECT * FROM system.schema_columnfamilies
UUID 20569 Executing single-partition query on ColumnFamilyA
UUID 20905 SELECT * FROM system.schema_columnfamilies
UUID 21056 Executing single-partition query on ColumnFamilyB
UUID 21397 Executing single-partition query on ColumnFamilyB
UUID 21992 Executing single-partition query on ColumnFamilyC
...
Longest duration queries shown lastSession id allows introspection into
individual operations in system_traces
*Not all fields shown
cassandra-tracing
© DataStax, All Rights Reserved. 27
cqlsh:system_traces> select activity,source_elapsed from events WHERE session_id=UUID;
activity | source_elapsed
---------------------------------------------------------------+---------------
Parsing SELECT * FROM system.schema_columnfamilies | 21
Preparing statement | 31
Computing ranges to query | 73
Submitting range requests on 1 ranges with a concurrency of 1 | 88
Submitted 1 concurrent range requests covering 1 ranges | 96
Executing seq scan across 3 sstables for [min(-1), min(-1)] | 382
Read 7 live and 0 tombstone cells | 2057
Read 2 live and 0 tombstone cells | 2495
Read 1 live and 0 tombstone cells | 3066
Read 17 live and 32 tombstone cells | 16892
Read 7 live and 0 tombstone cells | 18757
Scanned 5 rows and matched 5 | 19172
cassandra-tracing
© DataStax, All Rights Reserved. 28
Benefits:
• High level view of traffic passing through the node
– Does a single query type take a long time?
– Are you hitting a lot of tombstones with a query type?
– Index usage? Timeouts?
• Meaningful introspection
– Isolate the sessions that are interesting cases and
spend your time on the queries driving up your %99.9.
1 Introduction
2 Why command-line tools?
3 cassandra-stat
4 cassandra-tracing
5 Ansible ad-hoc commands
29© DataStax, All Rights Reserved.
Ansible (www.ansible.com)
An agentless, open source, ssh-based, configuration
management tool.
We use it for backups / provisioning / distributed commands.
Go check out: Cassandra backups and restorations using Ansible
Joshua Wickman
4:10 PM – 4:45 PM Room 210B
© DataStax, All Rights Reserved. 30
Ad Hoc commands
Ad hoc commands are one-off command line processes
ansible cassandra -i ips.txt -m shell -a "hostname"
© DataStax, All Rights Reserved. 31
Yaml file of groups of ips
Using the shell module
Command to execute on
the remote hostName of ip group to
execute on
IP List can be a script that returns the IPs, so it can tie
into any inventory management
Ad Hoc commands
Output looks like:
172.ip.ip.ip| success | rc=0 >>
cassandra-i-962LMNOP
172.ip.ip.ip | success | rc=0 >>
cassandra-i-dbfLMNOP
172.ip.ip.ip | success | rc=0 >>
cassandra-i-450LMNOP
© DataStax, All Rights Reserved. 32
Success or failure of command
Return code of command
Able to be piped through grep or other
processes on your local machine
Distributed Arbitrary Commands
function dcmd(){
if [[ $# < 2 ]]; then
echo "USAGE dcmd <GROUP> <SHELL COMMAND>
Ex: dcmd qa-cass 'tail /var/log/cassandra/system.log'";
else
ansible "${1}" -i ips.txt -m shell -a "${2}" --sudo;
fi
}
© DataStax, All Rights Reserved. 33
Make a wrapper function - make it easy on your team!
dcmd = distributed command
Distributed Commands
© DataStax, All Rights Reserved. 34
Benefits:
• Get immediate status on distributed systems
– Output reflects the current state
• Execute operations on all nodes
– If you need to bounce a whole cluster, this is great
• Easy to see differences between node output
– Cassandra is distributed so all nodes might not
agree on the state of the cluster. It can be hard to
find the dissenting node(s).
Distributed Nodetool Commands
$dcmd qa-cass 'nodetool tpstats | egrep "AntiEntropy|Name"'
172.ip.ip.ip | success | rc=0 >>
Pool Name Active Pending Completed Blocked All time blocked
AntiEntropyStage 0 0 0 0 0
172.ip.ip.ip | success | rc=0 >>
Pool Name Active Pending Completed Blocked All time blocked
AntiEntropyStage 0 0 0 0 0
172.ip.ip.ip | success | rc=0 >>
Pool Name Active Pending Completed Blocked All time blocked
AntiEntropySessions 0 0 1536 0 0
AntiEntropyStage 0 0 126720 0 0
© DataStax, All Rights Reserved. 35
Conclusions
● Cassandra exposes a lot of metrics if you know where
to find them - don't be afraid to dig them out!
● Programs can analyze bulk output a lot faster and better
than people - save your time for the things programs
aren't good at.
● Have distributed commands in your arsenal and don't
be afraid to use them.
© DataStax, All Rights Reserved. 36
Thank You

Mais conteúdo relacionado

Mais procurados

Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...
Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...
Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...DataStax
 
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...DataStax
 
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...DataStax
 
Processing 50,000 events per second with Cassandra and Spark
Processing 50,000 events per second with Cassandra and SparkProcessing 50,000 events per second with Cassandra and Spark
Processing 50,000 events per second with Cassandra and SparkBen Slater
 
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016DataStax
 
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016DataStax
 
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...What We Learned About Cassandra While Building go90 (Christopher Webster & Th...
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...DataStax
 
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016DataStax
 
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016DataStax
 
Real time data pipeline with spark streaming and cassandra with mesos
Real time data pipeline with spark streaming and cassandra with mesosReal time data pipeline with spark streaming and cassandra with mesos
Real time data pipeline with spark streaming and cassandra with mesosRahul Kumar
 
Engineering fast indexes
Engineering fast indexesEngineering fast indexes
Engineering fast indexesDaniel Lemire
 
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...DataStax
 
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...DataStax
 
Large partition in Cassandra
Large partition in CassandraLarge partition in Cassandra
Large partition in CassandraShogo Hoshii
 
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...DataStax
 
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...DataStax
 
How We Used Cassandra/Solr to Build Real-Time Analytics Platform
How We Used Cassandra/Solr to Build Real-Time Analytics PlatformHow We Used Cassandra/Solr to Build Real-Time Analytics Platform
How We Used Cassandra/Solr to Build Real-Time Analytics PlatformDataStax Academy
 
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...DataStax
 
Cassandra CLuster Management by Japan Cassandra Community
Cassandra CLuster Management by Japan Cassandra CommunityCassandra CLuster Management by Japan Cassandra Community
Cassandra CLuster Management by Japan Cassandra CommunityHiromitsu Komatsu
 

Mais procurados (20)

Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...
Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...
Using Approximate Data for Small, Insightful Analytics (Ben Kornmeier, Protec...
 
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...
SASI: Cassandra on the Full Text Search Ride (DuyHai DOAN, DataStax) | C* Sum...
 
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...
Lessons Learned From Running 1800 Clusters (Brooke Jensen, Instaclustr) | Cas...
 
Processing 50,000 events per second with Cassandra and Spark
Processing 50,000 events per second with Cassandra and SparkProcessing 50,000 events per second with Cassandra and Spark
Processing 50,000 events per second with Cassandra and Spark
 
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016
From Postgres to Cassandra (Rimas Silkaitis, Heroku) | C* Summit 2016
 
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016
Cassandra at Instagram 2016 (Dikang Gu, Facebook) | Cassandra Summit 2016
 
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...What We Learned About Cassandra While Building go90 (Christopher Webster & Th...
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...
 
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016
Storing Cassandra Metrics (Chris Lohfink, DataStax) | C* Summit 2016
 
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016
Monitoring Cassandra at Scale (Jason Cacciatore, Netflix) | C* Summit 2016
 
Real time data pipeline with spark streaming and cassandra with mesos
Real time data pipeline with spark streaming and cassandra with mesosReal time data pipeline with spark streaming and cassandra with mesos
Real time data pipeline with spark streaming and cassandra with mesos
 
Engineering fast indexes
Engineering fast indexesEngineering fast indexes
Engineering fast indexes
 
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...
 
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...
DataStax | Building a Spark Streaming App with DSE File System (Rocco Varela)...
 
Large partition in Cassandra
Large partition in CassandraLarge partition in Cassandra
Large partition in Cassandra
 
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...
Develop Scalable Applications with DataStax Drivers (Alex Popescu, Bulat Shak...
 
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...
An Effective Approach to Migrate Cassandra Thrift to CQL (Yabin Meng, Pythian...
 
How We Used Cassandra/Solr to Build Real-Time Analytics Platform
How We Used Cassandra/Solr to Build Real-Time Analytics PlatformHow We Used Cassandra/Solr to Build Real-Time Analytics Platform
How We Used Cassandra/Solr to Build Real-Time Analytics Platform
 
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...
 
Apache Cassandra at Macys
Apache Cassandra at MacysApache Cassandra at Macys
Apache Cassandra at Macys
 
Cassandra CLuster Management by Japan Cassandra Community
Cassandra CLuster Management by Japan Cassandra CommunityCassandra CLuster Management by Japan Cassandra Community
Cassandra CLuster Management by Japan Cassandra Community
 

Semelhante a Cassandra Tools and Distributed Administration (Jeffrey Berger, Knewton) | C* Summit 2016

iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...
iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...
iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...DataStax Academy
 
Leveraging Cassandra for real-time multi-datacenter public cloud analytics
Leveraging Cassandra for real-time multi-datacenter public cloud analyticsLeveraging Cassandra for real-time multi-datacenter public cloud analytics
Leveraging Cassandra for real-time multi-datacenter public cloud analyticsJulien Anguenot
 
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)Apache Apex
 
A Dataflow Processing Chip for Training Deep Neural Networks
A Dataflow Processing Chip for Training Deep Neural NetworksA Dataflow Processing Chip for Training Deep Neural Networks
A Dataflow Processing Chip for Training Deep Neural Networksinside-BigData.com
 
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)Cédrick Lunven
 
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...DataStax
 
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...DataStax
 
Top 10 Best Practices for Apache Cassandra and DataStax Enterprise
Top 10 Best Practices for Apache Cassandra and DataStax EnterpriseTop 10 Best Practices for Apache Cassandra and DataStax Enterprise
Top 10 Best Practices for Apache Cassandra and DataStax EnterpriseDataStax
 
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...Daniel Cohen
 
Declarative benchmarking of cassandra and it's data models
Declarative benchmarking of cassandra and it's data modelsDeclarative benchmarking of cassandra and it's data models
Declarative benchmarking of cassandra and it's data modelsMonal Daxini
 
Macy's: Changing Engines in Mid-Flight
Macy's: Changing Engines in Mid-FlightMacy's: Changing Engines in Mid-Flight
Macy's: Changing Engines in Mid-FlightDataStax Academy
 
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...Florian Lautenschlager
 
제3회난공불락 오픈소스 인프라세미나 - MySQL Performance
제3회난공불락 오픈소스 인프라세미나 - MySQL Performance제3회난공불락 오픈소스 인프라세미나 - MySQL Performance
제3회난공불락 오픈소스 인프라세미나 - MySQL PerformanceTommy Lee
 
Apache Big Data 2016: Next Gen Big Data Analytics with Apache Apex
Apache Big Data 2016: Next Gen Big Data Analytics with Apache ApexApache Big Data 2016: Next Gen Big Data Analytics with Apache Apex
Apache Big Data 2016: Next Gen Big Data Analytics with Apache ApexApache Apex
 
Benchmarking Solr Performance at Scale
Benchmarking Solr Performance at ScaleBenchmarking Solr Performance at Scale
Benchmarking Solr Performance at Scalethelabdude
 
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014Johnny Miller
 

Semelhante a Cassandra Tools and Distributed Administration (Jeffrey Berger, Knewton) | C* Summit 2016 (20)

iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...
iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...
iland Internet Solutions: Leveraging Cassandra for real-time multi-datacenter...
 
Leveraging Cassandra for real-time multi-datacenter public cloud analytics
Leveraging Cassandra for real-time multi-datacenter public cloud analyticsLeveraging Cassandra for real-time multi-datacenter public cloud analytics
Leveraging Cassandra for real-time multi-datacenter public cloud analytics
 
Apache cassandra v4.0
Apache cassandra v4.0Apache cassandra v4.0
Apache cassandra v4.0
 
Devops kc
Devops kcDevops kc
Devops kc
 
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)
GE IOT Predix Time Series & Data Ingestion Service using Apache Apex (Hadoop)
 
A Dataflow Processing Chip for Training Deep Neural Networks
A Dataflow Processing Chip for Training Deep Neural NetworksA Dataflow Processing Chip for Training Deep Neural Networks
A Dataflow Processing Chip for Training Deep Neural Networks
 
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)
Top 10 present and future innovations in the NoSQL Cassandra ecosystem (2022)
 
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...
Cassandra Tuning - Above and Beyond (Matija Gobec, SmartCat) | Cassandra Summ...
 
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
Webinar: Dyn + DataStax - helping companies deliver exceptional end-user expe...
 
Top 10 Best Practices for Apache Cassandra and DataStax Enterprise
Top 10 Best Practices for Apache Cassandra and DataStax EnterpriseTop 10 Best Practices for Apache Cassandra and DataStax Enterprise
Top 10 Best Practices for Apache Cassandra and DataStax Enterprise
 
Large scale, distributed access management deployment with aruba clear pass
Large scale, distributed access management deployment with aruba clear passLarge scale, distributed access management deployment with aruba clear pass
Large scale, distributed access management deployment with aruba clear pass
 
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...
DataStax Enterprise & Apache Cassandra – Essentials for Financial Services – ...
 
BigData Developers MeetUp
BigData Developers MeetUpBigData Developers MeetUp
BigData Developers MeetUp
 
Declarative benchmarking of cassandra and it's data models
Declarative benchmarking of cassandra and it's data modelsDeclarative benchmarking of cassandra and it's data models
Declarative benchmarking of cassandra and it's data models
 
Macy's: Changing Engines in Mid-Flight
Macy's: Changing Engines in Mid-FlightMacy's: Changing Engines in Mid-Flight
Macy's: Changing Engines in Mid-Flight
 
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...
Chronix: Long Term Storage and Retrieval Technology for Anomaly Detection in ...
 
제3회난공불락 오픈소스 인프라세미나 - MySQL Performance
제3회난공불락 오픈소스 인프라세미나 - MySQL Performance제3회난공불락 오픈소스 인프라세미나 - MySQL Performance
제3회난공불락 오픈소스 인프라세미나 - MySQL Performance
 
Apache Big Data 2016: Next Gen Big Data Analytics with Apache Apex
Apache Big Data 2016: Next Gen Big Data Analytics with Apache ApexApache Big Data 2016: Next Gen Big Data Analytics with Apache Apex
Apache Big Data 2016: Next Gen Big Data Analytics with Apache Apex
 
Benchmarking Solr Performance at Scale
Benchmarking Solr Performance at ScaleBenchmarking Solr Performance at Scale
Benchmarking Solr Performance at Scale
 
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014
Apache Cassandra For Java Developers - Why, What and How. LJC @ UCL October 2014
 

Mais de DataStax

Is Your Enterprise Ready to Shine This Holiday Season?
Is Your Enterprise Ready to Shine This Holiday Season?Is Your Enterprise Ready to Shine This Holiday Season?
Is Your Enterprise Ready to Shine This Holiday Season?DataStax
 
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...DataStax
 
Running DataStax Enterprise in VMware Cloud and Hybrid Environments
Running DataStax Enterprise in VMware Cloud and Hybrid EnvironmentsRunning DataStax Enterprise in VMware Cloud and Hybrid Environments
Running DataStax Enterprise in VMware Cloud and Hybrid EnvironmentsDataStax
 
Best Practices for Getting to Production with DataStax Enterprise Graph
Best Practices for Getting to Production with DataStax Enterprise GraphBest Practices for Getting to Production with DataStax Enterprise Graph
Best Practices for Getting to Production with DataStax Enterprise GraphDataStax
 
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyWebinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyDataStax
 
Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...
Webinar  |  How to Understand Apache Cassandra™ Performance Through Read/Writ...Webinar  |  How to Understand Apache Cassandra™ Performance Through Read/Writ...
Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...DataStax
 
Webinar | Better Together: Apache Cassandra and Apache Kafka
Webinar  |  Better Together: Apache Cassandra and Apache KafkaWebinar  |  Better Together: Apache Cassandra and Apache Kafka
Webinar | Better Together: Apache Cassandra and Apache KafkaDataStax
 
Introduction to Apache Cassandra™ + What’s New in 4.0
Introduction to Apache Cassandra™ + What’s New in 4.0Introduction to Apache Cassandra™ + What’s New in 4.0
Introduction to Apache Cassandra™ + What’s New in 4.0DataStax
 
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...DataStax
 
Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud Realities
Webinar  |  Aligning GDPR Requirements with Today's Hybrid Cloud RealitiesWebinar  |  Aligning GDPR Requirements with Today's Hybrid Cloud Realities
Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud RealitiesDataStax
 
Designing a Distributed Cloud Database for Dummies
Designing a Distributed Cloud Database for DummiesDesigning a Distributed Cloud Database for Dummies
Designing a Distributed Cloud Database for DummiesDataStax
 
How to Power Innovation with Geo-Distributed Data Management in Hybrid Cloud
How to Power Innovation with Geo-Distributed Data Management in Hybrid CloudHow to Power Innovation with Geo-Distributed Data Management in Hybrid Cloud
How to Power Innovation with Geo-Distributed Data Management in Hybrid CloudDataStax
 
How to Evaluate Cloud Databases for eCommerce
How to Evaluate Cloud Databases for eCommerceHow to Evaluate Cloud Databases for eCommerce
How to Evaluate Cloud Databases for eCommerceDataStax
 
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...DataStax
 
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...DataStax
 
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...DataStax
 
Datastax - The Architect's guide to customer experience (CX)
Datastax - The Architect's guide to customer experience (CX)Datastax - The Architect's guide to customer experience (CX)
Datastax - The Architect's guide to customer experience (CX)DataStax
 
An Operational Data Layer is Critical for Transformative Banking Applications
An Operational Data Layer is Critical for Transformative Banking ApplicationsAn Operational Data Layer is Critical for Transformative Banking Applications
An Operational Data Layer is Critical for Transformative Banking ApplicationsDataStax
 
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design Thinking
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design ThinkingBecoming a Customer-Centric Enterprise Via Real-Time Data and Design Thinking
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design ThinkingDataStax
 
Innovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud DetectionInnovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud DetectionDataStax
 

Mais de DataStax (20)

Is Your Enterprise Ready to Shine This Holiday Season?
Is Your Enterprise Ready to Shine This Holiday Season?Is Your Enterprise Ready to Shine This Holiday Season?
Is Your Enterprise Ready to Shine This Holiday Season?
 
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...
 
Running DataStax Enterprise in VMware Cloud and Hybrid Environments
Running DataStax Enterprise in VMware Cloud and Hybrid EnvironmentsRunning DataStax Enterprise in VMware Cloud and Hybrid Environments
Running DataStax Enterprise in VMware Cloud and Hybrid Environments
 
Best Practices for Getting to Production with DataStax Enterprise Graph
Best Practices for Getting to Production with DataStax Enterprise GraphBest Practices for Getting to Production with DataStax Enterprise Graph
Best Practices for Getting to Production with DataStax Enterprise Graph
 
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyWebinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey
 
Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...
Webinar  |  How to Understand Apache Cassandra™ Performance Through Read/Writ...Webinar  |  How to Understand Apache Cassandra™ Performance Through Read/Writ...
Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...
 
Webinar | Better Together: Apache Cassandra and Apache Kafka
Webinar  |  Better Together: Apache Cassandra and Apache KafkaWebinar  |  Better Together: Apache Cassandra and Apache Kafka
Webinar | Better Together: Apache Cassandra and Apache Kafka
 
Introduction to Apache Cassandra™ + What’s New in 4.0
Introduction to Apache Cassandra™ + What’s New in 4.0Introduction to Apache Cassandra™ + What’s New in 4.0
Introduction to Apache Cassandra™ + What’s New in 4.0
 
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...
 
Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud Realities
Webinar  |  Aligning GDPR Requirements with Today's Hybrid Cloud RealitiesWebinar  |  Aligning GDPR Requirements with Today's Hybrid Cloud Realities
Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud Realities
 
Designing a Distributed Cloud Database for Dummies
Designing a Distributed Cloud Database for DummiesDesigning a Distributed Cloud Database for Dummies
Designing a Distributed Cloud Database for Dummies
 
How to Power Innovation with Geo-Distributed Data Management in Hybrid Cloud
How to Power Innovation with Geo-Distributed Data Management in Hybrid CloudHow to Power Innovation with Geo-Distributed Data Management in Hybrid Cloud
How to Power Innovation with Geo-Distributed Data Management in Hybrid Cloud
 
How to Evaluate Cloud Databases for eCommerce
How to Evaluate Cloud Databases for eCommerceHow to Evaluate Cloud Databases for eCommerce
How to Evaluate Cloud Databases for eCommerce
 
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...
 
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...
 
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...
 
Datastax - The Architect's guide to customer experience (CX)
Datastax - The Architect's guide to customer experience (CX)Datastax - The Architect's guide to customer experience (CX)
Datastax - The Architect's guide to customer experience (CX)
 
An Operational Data Layer is Critical for Transformative Banking Applications
An Operational Data Layer is Critical for Transformative Banking ApplicationsAn Operational Data Layer is Critical for Transformative Banking Applications
An Operational Data Layer is Critical for Transformative Banking Applications
 
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design Thinking
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design ThinkingBecoming a Customer-Centric Enterprise Via Real-Time Data and Design Thinking
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design Thinking
 
Innovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud DetectionInnovation Around Data and AI for Fraud Detection
Innovation Around Data and AI for Fraud Detection
 

Último

Leveraging AI for Mobile App Testing on Real Devices | Applitools + Kobiton
Leveraging AI for Mobile App Testing on Real Devices | Applitools + KobitonLeveraging AI for Mobile App Testing on Real Devices | Applitools + Kobiton
Leveraging AI for Mobile App Testing on Real Devices | Applitools + KobitonApplitools
 
How to submit a standout Adobe Champion Application
How to submit a standout Adobe Champion ApplicationHow to submit a standout Adobe Champion Application
How to submit a standout Adobe Champion ApplicationBradBedford3
 
SoftTeco - Software Development Company Profile
SoftTeco - Software Development Company ProfileSoftTeco - Software Development Company Profile
SoftTeco - Software Development Company Profileakrivarotava
 
What’s New in VictoriaMetrics: Q1 2024 Updates
What’s New in VictoriaMetrics: Q1 2024 UpdatesWhat’s New in VictoriaMetrics: Q1 2024 Updates
What’s New in VictoriaMetrics: Q1 2024 UpdatesVictoriaMetrics
 
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...OnePlan Solutions
 
Best Angular 17 Classroom & Online training - Naresh IT
Best Angular 17 Classroom & Online training - Naresh ITBest Angular 17 Classroom & Online training - Naresh IT
Best Angular 17 Classroom & Online training - Naresh ITmanoharjgpsolutions
 
Not a Kubernetes fan? The state of PaaS in 2024
Not a Kubernetes fan? The state of PaaS in 2024Not a Kubernetes fan? The state of PaaS in 2024
Not a Kubernetes fan? The state of PaaS in 2024Anthony Dahanne
 
Osi security architecture in network.pptx
Osi security architecture in network.pptxOsi security architecture in network.pptx
Osi security architecture in network.pptxVinzoCenzo
 
Keeping your build tool updated in a multi repository world
Keeping your build tool updated in a multi repository worldKeeping your build tool updated in a multi repository world
Keeping your build tool updated in a multi repository worldRoberto Pérez Alcolea
 
Simplifying Microservices & Apps - The art of effortless development - Meetup...
Simplifying Microservices & Apps - The art of effortless development - Meetup...Simplifying Microservices & Apps - The art of effortless development - Meetup...
Simplifying Microservices & Apps - The art of effortless development - Meetup...Rob Geurden
 
VictoriaMetrics Anomaly Detection Updates: Q1 2024
VictoriaMetrics Anomaly Detection Updates: Q1 2024VictoriaMetrics Anomaly Detection Updates: Q1 2024
VictoriaMetrics Anomaly Detection Updates: Q1 2024VictoriaMetrics
 
Amazon Bedrock in Action - presentation of the Bedrock's capabilities
Amazon Bedrock in Action - presentation of the Bedrock's capabilitiesAmazon Bedrock in Action - presentation of the Bedrock's capabilities
Amazon Bedrock in Action - presentation of the Bedrock's capabilitiesKrzysztofKkol1
 
VK Business Profile - provides IT solutions and Web Development
VK Business Profile - provides IT solutions and Web DevelopmentVK Business Profile - provides IT solutions and Web Development
VK Business Profile - provides IT solutions and Web Developmentvyaparkranti
 
Powering Real-Time Decisions with Continuous Data Streams
Powering Real-Time Decisions with Continuous Data StreamsPowering Real-Time Decisions with Continuous Data Streams
Powering Real-Time Decisions with Continuous Data StreamsSafe Software
 
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full Recording
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full RecordingOpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full Recording
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full RecordingShane Coughlan
 
Understanding Flamingo - DeepMind's VLM Architecture
Understanding Flamingo - DeepMind's VLM ArchitectureUnderstanding Flamingo - DeepMind's VLM Architecture
Understanding Flamingo - DeepMind's VLM Architecturerahul_net
 
Ronisha Informatics Private Limited Catalogue
Ronisha Informatics Private Limited CatalogueRonisha Informatics Private Limited Catalogue
Ronisha Informatics Private Limited Catalogueitservices996
 
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...OnePlan Solutions
 
A healthy diet for your Java application Devoxx France.pdf
A healthy diet for your Java application Devoxx France.pdfA healthy diet for your Java application Devoxx France.pdf
A healthy diet for your Java application Devoxx France.pdfMarharyta Nedzelska
 
Precise and Complete Requirements? An Elusive Goal
Precise and Complete Requirements? An Elusive GoalPrecise and Complete Requirements? An Elusive Goal
Precise and Complete Requirements? An Elusive GoalLionel Briand
 

Último (20)

Leveraging AI for Mobile App Testing on Real Devices | Applitools + Kobiton
Leveraging AI for Mobile App Testing on Real Devices | Applitools + KobitonLeveraging AI for Mobile App Testing on Real Devices | Applitools + Kobiton
Leveraging AI for Mobile App Testing on Real Devices | Applitools + Kobiton
 
How to submit a standout Adobe Champion Application
How to submit a standout Adobe Champion ApplicationHow to submit a standout Adobe Champion Application
How to submit a standout Adobe Champion Application
 
SoftTeco - Software Development Company Profile
SoftTeco - Software Development Company ProfileSoftTeco - Software Development Company Profile
SoftTeco - Software Development Company Profile
 
What’s New in VictoriaMetrics: Q1 2024 Updates
What’s New in VictoriaMetrics: Q1 2024 UpdatesWhat’s New in VictoriaMetrics: Q1 2024 Updates
What’s New in VictoriaMetrics: Q1 2024 Updates
 
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...
Tech Tuesday - Mastering Time Management Unlock the Power of OnePlan's Timesh...
 
Best Angular 17 Classroom & Online training - Naresh IT
Best Angular 17 Classroom & Online training - Naresh ITBest Angular 17 Classroom & Online training - Naresh IT
Best Angular 17 Classroom & Online training - Naresh IT
 
Not a Kubernetes fan? The state of PaaS in 2024
Not a Kubernetes fan? The state of PaaS in 2024Not a Kubernetes fan? The state of PaaS in 2024
Not a Kubernetes fan? The state of PaaS in 2024
 
Osi security architecture in network.pptx
Osi security architecture in network.pptxOsi security architecture in network.pptx
Osi security architecture in network.pptx
 
Keeping your build tool updated in a multi repository world
Keeping your build tool updated in a multi repository worldKeeping your build tool updated in a multi repository world
Keeping your build tool updated in a multi repository world
 
Simplifying Microservices & Apps - The art of effortless development - Meetup...
Simplifying Microservices & Apps - The art of effortless development - Meetup...Simplifying Microservices & Apps - The art of effortless development - Meetup...
Simplifying Microservices & Apps - The art of effortless development - Meetup...
 
VictoriaMetrics Anomaly Detection Updates: Q1 2024
VictoriaMetrics Anomaly Detection Updates: Q1 2024VictoriaMetrics Anomaly Detection Updates: Q1 2024
VictoriaMetrics Anomaly Detection Updates: Q1 2024
 
Amazon Bedrock in Action - presentation of the Bedrock's capabilities
Amazon Bedrock in Action - presentation of the Bedrock's capabilitiesAmazon Bedrock in Action - presentation of the Bedrock's capabilities
Amazon Bedrock in Action - presentation of the Bedrock's capabilities
 
VK Business Profile - provides IT solutions and Web Development
VK Business Profile - provides IT solutions and Web DevelopmentVK Business Profile - provides IT solutions and Web Development
VK Business Profile - provides IT solutions and Web Development
 
Powering Real-Time Decisions with Continuous Data Streams
Powering Real-Time Decisions with Continuous Data StreamsPowering Real-Time Decisions with Continuous Data Streams
Powering Real-Time Decisions with Continuous Data Streams
 
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full Recording
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full RecordingOpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full Recording
OpenChain Education Work Group Monthly Meeting - 2024-04-10 - Full Recording
 
Understanding Flamingo - DeepMind's VLM Architecture
Understanding Flamingo - DeepMind's VLM ArchitectureUnderstanding Flamingo - DeepMind's VLM Architecture
Understanding Flamingo - DeepMind's VLM Architecture
 
Ronisha Informatics Private Limited Catalogue
Ronisha Informatics Private Limited CatalogueRonisha Informatics Private Limited Catalogue
Ronisha Informatics Private Limited Catalogue
 
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...
Revolutionizing the Digital Transformation Office - Leveraging OnePlan’s AI a...
 
A healthy diet for your Java application Devoxx France.pdf
A healthy diet for your Java application Devoxx France.pdfA healthy diet for your Java application Devoxx France.pdf
A healthy diet for your Java application Devoxx France.pdf
 
Precise and Complete Requirements? An Elusive Goal
Precise and Complete Requirements? An Elusive GoalPrecise and Complete Requirements? An Elusive Goal
Precise and Complete Requirements? An Elusive Goal
 

Cassandra Tools and Distributed Administration (Jeffrey Berger, Knewton) | C* Summit 2016

  • 1. Cassandra Tools and Distributed Administration Dr. Jeffrey Berger Lead Database Engineer Knewton
  • 2. 1 Introduction 2 Why command-line tools? 3 cassandra-stat 4 cassandra-tracing 5 Ansible ad-hoc commands 2© DataStax, All Rights Reserved.
  • 3. Knewton © DataStax, All Rights Reserved. 3 Leader in adaptive learning ● Partners with publishers and institutions in Europe, US, and Asia ● Provides unique recommendations to students based on previous behavior ● Advanced content ingestion, curation, and calibration ● Runs in AWS with many different storage backends ● Check us out: www.knewton.com/about/careers/
  • 4. Cassandra at Knewton © DataStax, All Rights Reserved. 4 Cassandra is the main datastore at Knewton EU ProductionDevelopment US ProductionUser AcceptanceQA Clusters: 5 Nodes: 15 Clusters: 6 Nodes: 69 Clusters: 6 Nodes: 18 Clusters: 6 Nodes: 24 Clusters: 2 Nodes: 6 Clusters: 25 Nodes: 132
  • 5. Cassandra Challenges © DataStax, All Rights Reserved. 5 • Monitoring – Historical measures are important • Triage – Immediate answers in a distributed system • Provisioning – Keep configurations consistent • Scaling – Elastically scale Cassandra 'out' or 'in'
  • 6. Cassandra Challenges © DataStax, All Rights Reserved. 6 • Monitoring – Historical measures are important • Triage – Immediate answers in a distributed system • Provisioning – Keep configurations consistent • Scaling – Elastically scale Cassandra 'out' or 'in'
  • 7. Solutions as Software © DataStax, All Rights Reserved. 7 If you magnify your surface area, magnify your tools ● Easy to use ● Fast and responsive ● Distributed
  • 8. 1 Introduction 2 Why command-line tools? 3 cassandra-stat 4 cassandra-tracing 5 Ansible ad-hoc commands 8© DataStax, All Rights Reserved.
  • 9. Why command line tools? © DataStax, All Rights Reserved. 9 Always consider the operator! Systems people like the command line! ● Few moving parts ● Local ● Immediate
  • 10. Why not graphs? © DataStax, All Rights Reserved. 10 Graphs are great, I love graphs ● Not immediate ● Can be overloaded ● Remote ● Fixed metrics ● Averages rather than values
  • 11. Why not nodetool? © DataStax, All Rights Reserved. 11 Nodetool is great..
  • 12. Why not nodetool? © DataStax, All Rights Reserved. 12 Until it is time to cook dinner...
  • 13. Jolokia ( jolokia.org ) © DataStax, All Rights Reserved. 13 Exposes JMX endpoints by HTTP • Open source (Apache2) • Lets you script with full access to JMX endpoints • Agent runs with cassandra • Lightweight, fast, easy to install
  • 14. Installing Jolokia is painless © DataStax, All Rights Reserved. 14 2) Add this line to cassandra-env.sh # added to activate the jolokia agent JVM_OPTS="$JVM_OPTS -javaagent:/opt/cassandra/jolokia-jvm-agent.jar" (Or whatever the path is to your Jolokia JVM jar!) 1) Download the Jolokia JVM agent from their site / maven
  • 15. What to do with Jolokia? © DataStax, All Rights Reserved. 15 Build some monitoring tools! • Use jconsole to find metrics you are interested in • Make some programs with your favorite language • Get the metrics from Jolokia to feed it Check out the tools we have already made!
  • 16. cassandra-toolbox © DataStax, All Rights Reserved. 16 Python package of cassandra tools developed at Knewton • Pip installable – pip install cassandra-toolbox • Open source (Apache2) • Interacts with C* via Jolokia • github.com/Knewton/cassandra-toolbox • 2 scripts right now, more soon
  • 17. 1 Introduction 2 Why command-line tools? 3 cassandra-stat 4 cassandra-tracing 5 Ansible ad-hoc commands 17© DataStax, All Rights Reserved.
  • 18. cassandra-stat © DataStax, All Rights Reserved. 18 A real-time feed of Cassandra operations Like iostat for Cassandra • Interacts with Jolokia agent • Diffs metrics on a configurable time scale • Overall / Keyspace / CF granularity • Easy to use, easy to read
  • 19. cassandra-stat © DataStax, All Rights Reserved. 19 $cassandra-stat Reads Writes Reads (99%) ms Writes (99%) ms Compactions Time ns 1 111 91.462 17.4 0 20:15:36 total 2 113 91.4 17.98 0 20:15:37 total 0 117 91.4 17.17 0 20:15:38 total 0 72 91.4 17.34 0 20:15:39 total 0 69 91.4 17.3 0 20:15:40 total *Not all fields shown Some metrics are summed across CFs and the difference from the last iteration reported Some report the maximum value from all CFs Some metrics are summed across CFs
  • 20. cassandra-stat 20 metrics = [ { "metric_name": "ReadLatency", "metric_key": "Count", "display_name": "Reads", "sum": True, "diff": True, "nonzero": True }, ... ● Metrics are not hardcoded ● Easy to add/remove ● Flexible ○ sum ○ diff ○ nonzero ● Configuration is moving to a YAML file
  • 21. cassandra-stat © DataStax, All Rights Reserved. 21 Benefits: • Traffic monitoring – Real time load can be read off easily • Performance debugging – All vital metrics are on a single line at each time • High granularity – Metrics every second • Diverse metrics – Metrics can be configured and read out immediately
  • 22. 1 Introduction 2 Why command-line tools? 3 cassandra-stat 4 cassandra-tracing 5 Ansible ad-hoc commands 22© DataStax, All Rights Reserved.
  • 23. cassandra-tracing © DataStax, All Rights Reserved. 23 Sampling a percent of all queries is a great tool* $nodetool settraceprobability 0.001 But if you ever queried the CFs in system_traces you might be bewildered.. * Don't set this percent too high!
  • 24. cassandra-tracing © DataStax, All Rights Reserved. 24 cqlsh:system_traces> SELECT request,parameters FROM sessions LIMIT 4; request | parameters --------------------+--------------------------------------- Execute CQL3 query | {'consistency_level': 'LOCAL_ONE', 'page_size': '5000', 'query': 'SELECT * FROM test2 WHERE key=''XXXXXXXXXXXXXXXXX''', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'select cluster_name from system.local', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'select cluster_name from system.local', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'SELECT * FROM system.schema_columnfamilies', 'serial_consistency_level': 'SERIAL'}
  • 25. cassandra-tracing © DataStax, All Rights Reserved. 25 cqlsh:system_traces> SELECT request,parameters FROM sessions LIMIT 4; request | parameters --------------------+--------------------------------------- Execute CQL3 query | {'consistency_level': 'LOCAL_ONE', 'page_size': '5000', 'query': 'SELECT * FROM test2 WHERE key=''XXXXXXXXXXXXXXXXX''', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'select cluster_name from system.local', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'select cluster_name from system.local', 'serial_consistency_level': 'SERIAL'} Execute CQL3 query | {'consistency_level': 'ONE', 'query': 'SELECT * FROM system.schema_columnfamilies', 'serial_consistency_level': 'SERIAL'}
  • 26. cassandra-tracing © DataStax, All Rights Reserved. 26 $ cassandra-tracing `hostname -I ` 100% Complete: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX|100 Total skipped due to null duration: 0 Total skipped due to error: 0 175 sessions satisfying criteria. Showing 100 longest running results. Session Id Duration(us) Query UUID 19696 SELECT * FROM system.schema_columnfamilies UUID 20569 Executing single-partition query on ColumnFamilyA UUID 20905 SELECT * FROM system.schema_columnfamilies UUID 21056 Executing single-partition query on ColumnFamilyB UUID 21397 Executing single-partition query on ColumnFamilyB UUID 21992 Executing single-partition query on ColumnFamilyC ... Longest duration queries shown lastSession id allows introspection into individual operations in system_traces *Not all fields shown
  • 27. cassandra-tracing © DataStax, All Rights Reserved. 27 cqlsh:system_traces> select activity,source_elapsed from events WHERE session_id=UUID; activity | source_elapsed ---------------------------------------------------------------+--------------- Parsing SELECT * FROM system.schema_columnfamilies | 21 Preparing statement | 31 Computing ranges to query | 73 Submitting range requests on 1 ranges with a concurrency of 1 | 88 Submitted 1 concurrent range requests covering 1 ranges | 96 Executing seq scan across 3 sstables for [min(-1), min(-1)] | 382 Read 7 live and 0 tombstone cells | 2057 Read 2 live and 0 tombstone cells | 2495 Read 1 live and 0 tombstone cells | 3066 Read 17 live and 32 tombstone cells | 16892 Read 7 live and 0 tombstone cells | 18757 Scanned 5 rows and matched 5 | 19172
  • 28. cassandra-tracing © DataStax, All Rights Reserved. 28 Benefits: • High level view of traffic passing through the node – Does a single query type take a long time? – Are you hitting a lot of tombstones with a query type? – Index usage? Timeouts? • Meaningful introspection – Isolate the sessions that are interesting cases and spend your time on the queries driving up your %99.9.
  • 29. 1 Introduction 2 Why command-line tools? 3 cassandra-stat 4 cassandra-tracing 5 Ansible ad-hoc commands 29© DataStax, All Rights Reserved.
  • 30. Ansible (www.ansible.com) An agentless, open source, ssh-based, configuration management tool. We use it for backups / provisioning / distributed commands. Go check out: Cassandra backups and restorations using Ansible Joshua Wickman 4:10 PM – 4:45 PM Room 210B © DataStax, All Rights Reserved. 30
  • 31. Ad Hoc commands Ad hoc commands are one-off command line processes ansible cassandra -i ips.txt -m shell -a "hostname" © DataStax, All Rights Reserved. 31 Yaml file of groups of ips Using the shell module Command to execute on the remote hostName of ip group to execute on IP List can be a script that returns the IPs, so it can tie into any inventory management
  • 32. Ad Hoc commands Output looks like: 172.ip.ip.ip| success | rc=0 >> cassandra-i-962LMNOP 172.ip.ip.ip | success | rc=0 >> cassandra-i-dbfLMNOP 172.ip.ip.ip | success | rc=0 >> cassandra-i-450LMNOP © DataStax, All Rights Reserved. 32 Success or failure of command Return code of command Able to be piped through grep or other processes on your local machine
  • 33. Distributed Arbitrary Commands function dcmd(){ if [[ $# < 2 ]]; then echo "USAGE dcmd <GROUP> <SHELL COMMAND> Ex: dcmd qa-cass 'tail /var/log/cassandra/system.log'"; else ansible "${1}" -i ips.txt -m shell -a "${2}" --sudo; fi } © DataStax, All Rights Reserved. 33 Make a wrapper function - make it easy on your team! dcmd = distributed command
  • 34. Distributed Commands © DataStax, All Rights Reserved. 34 Benefits: • Get immediate status on distributed systems – Output reflects the current state • Execute operations on all nodes – If you need to bounce a whole cluster, this is great • Easy to see differences between node output – Cassandra is distributed so all nodes might not agree on the state of the cluster. It can be hard to find the dissenting node(s).
  • 35. Distributed Nodetool Commands $dcmd qa-cass 'nodetool tpstats | egrep "AntiEntropy|Name"' 172.ip.ip.ip | success | rc=0 >> Pool Name Active Pending Completed Blocked All time blocked AntiEntropyStage 0 0 0 0 0 172.ip.ip.ip | success | rc=0 >> Pool Name Active Pending Completed Blocked All time blocked AntiEntropyStage 0 0 0 0 0 172.ip.ip.ip | success | rc=0 >> Pool Name Active Pending Completed Blocked All time blocked AntiEntropySessions 0 0 1536 0 0 AntiEntropyStage 0 0 126720 0 0 © DataStax, All Rights Reserved. 35
  • 36. Conclusions ● Cassandra exposes a lot of metrics if you know where to find them - don't be afraid to dig them out! ● Programs can analyze bulk output a lot faster and better than people - save your time for the things programs aren't good at. ● Have distributed commands in your arsenal and don't be afraid to use them. © DataStax, All Rights Reserved. 36