Percona’s Open Source Data Management Software Survey

PerconaSurvey

Click Here to Complete our New Survey!

Last year we informally surveyed the open source community and our conference attendees.
The results revealed that:

  • 48% of those in the cloud choose to self-manage their databases, but 52% were comfortable relying on the DBaaS offering of their cloud vendor.
  • 49% of people said “performance issues” when asked, “what keeps you up at night?”
  • The major decision influence for buying services was price, with 42% of respondents keen to make the most of their money.

We found this information so interesting that we wanted to find out more! As a result, we are pleased to announce the launch of our first annual Open Source Data Management Software Survey.

The final results will be 100% anonymous, and will be made freely available on Creative Commons.

How Will This Survey Help The Community?

Unlimited access to accurate market data is important. Millions of open source projects are in play, and most are dependent on databases. Accurate market data helps you track the popularity of different databases, as well as seeing how and where these databases are run. This helps us all build better software and take advantage of shifting trends.

Thousands of vendors are focused on helping SysAdmins, DBAs, and Developers get the most out of their database infrastructure. Insightful market data enables them to create better tools that meet current demands and grow the open source database market.

We want to assist companies who are still deciding what, how, and where to run their systems. This information will help them understand the industry direction and allow them to make an informed decision on the software and services they choose.

How Can You Help Make This Survey A Success?

Firstly, please share your insight into current trends and new developments in open source data management software.

Secondly, please share this survey with other people who work in the industry, and encourage them to contribute.

The more responses we receive, the more useful this will be to the whole open source community. If we missed anything, or you would like to ask other questions in future, let us know!

So tell us; who are the big fish, and which minnows are nibbling at their tails?! Is the cloud giving you altitude sickness, or are you flying high? What is the next big thing and is everyone on board, or is your company lagging behind?

Preliminary results will be presented at our annual Percona Live Conference in Austin, Texas (May 28-30, 2019) by our CEO, Peter Zaitsev and released to the open source community when finalized.

Click Here to Have Your Say!

Read more at: http://www.mysqlperformanceblog.com/

Percona Server for MongoDB 3.6.11-3.1 Is Now Available

Percona Server for MongoDB

Percona Server for MongoDB

Percona announces the release of Percona Server for MongoDB 3.6.11-3.1 on March 15, 2019. Download the latest version from the Percona website or the Percona software repositories.

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 3.6 Community Edition. It supports MongoDB 3.6 protocols and drivers.

Percona Server for MongoDB extends Community Edition functionality by including the Percona Memory Engine storage engine, as well as several enterprise-grade features. Also, it includes MongoRocks storage engine, which is now deprecated. Percona Server for MongoDB requires no changes to MongoDB applications or code.

Release 3.6.11-3.1 extends the buildInfo command with the psmdbVersion key to report the version of Percona Server for MongoDB. If this key exists then Percona Server for MongoDB is installed on the server. This key not available from MongoDB.

Improvements

  • PSMDB-216: The database command buildInfo provides the psmdbVersion key to report the version of Percona Server for MongoDB. If this key exists then Percona Server for MongoDB is installed on the server. This key is not available from MongoDB.

The Percona Server for MongoDB 3.6.11-3.1 release notes are available in the official documentation.

Read more at: http://www.mysqlperformanceblog.com/

MongoDB on ARM Processors

reads updates transactions per hour per $

ARM processors have been around for a while. In mid-2015/2016 there were a couple of attempts by the community to port MongoDB to work with this architecture. At the time, the main storage engine was MMAP and most of the available ARM boards were 32-bits. Overall, the port worked, but the fact is having MongoDB running on a Raspberry Pi was more a hack than a setup. The public cloud providers didn’t yet offer machines running with these processors.

The ARM processors are power-efficient and, for this reason, they are used in smartphones, smart devices and, now, even laptops. It was just a matter of time to have them available in the cloud as well. Now that AWS is offering ARM-based instances you might be thinking: “Hmmm, these instances include the same amount of cores and memory compared to the traditional x86-based offers, but cost a fraction of the price!”.

But do they perform alike?

In this blog, we selected three different AWS instances to compare: one powered by  an ARM processor, the second one backed by a traditional x86_64 Intel processor with the same number of cores and memory as the ARM instance, and finally another Intel-backed instance that costs roughly the same as the ARM instance but carries half as many cores. We acknowledge these processors are not supposed to be “equivalent”, and we do not intend to go deeper in CPU architecture in this blog. Our goal is purely to check how the ARM-backed instance fares in comparison to the Intel-based ones.

These are the instances we will consider in this blog post.

Methodology

We will use the Yahoo Cloud Serving Benchmark (YCSB, https://github.com/brianfrankcooper/YCSB) running on a dedicated instance (c5d.4xlarge) to simulate load in three distinct tests:

  1. a load of 1 billion documents in one collection having only the primary key (which we’ll call Inserts).
  2. a workload comprised of exclusively reads (Reads)
  3. a workload comprised of a mix of 75% reads with 5% scans plus 25% updates (Reads/Updates)

We will run each test with a varying number of concurrent threads (32, 64, and 128), repeating each set three times and keeping only the second-best result.

All instances will run the same MongoDB version (4.0.3, installed from a tarball and running with default settings) and operating system, Ubuntu 16.04. We chose this setup because MongoDB offer includes an ARM version for Ubuntu-based machines.

All the instances will be configured with:

  • 100 GB EBS with 5000 PIOPS and 20 GB EBS boot device
  • Data volume formatted with XFS, 4k blocks
  • Default swappiness and disk scheduler
  • Default kernel parameters
  • Enhanced cloud watch configured
  • Free monitoring tier enabled

Preparing the environment

We start with the setup of the benchmark software we will use for the test, YCSB. The first task was to spin up a powerful machine (c5d.4xlarge) to run the software and then prepare the environment:

The YCSB program requires Java, Maven, Python, and pymongo which doesn’t come by default in our Linux version – Ubuntu server x86. Here are the steps we used to configure our environment:

Installing Java

sudo apt-get install java-devel

Installing Maven

wget http://ftp.heanet.ie/mirrors/www.apache.org/dist/maven/maven-3/3.1.1/binaries/apache-maven-3.1.1-bin.tar.gz
sudo tar xzf apache-maven-*-bin.tar.gz -C /usr/local
cd /usr/local
sudo ln -s apache-maven-* maven
sudo vi /etc/profile.d/maven.sh

Add the following to maven.sh

export M2_HOME=/usr/local/maven
export PATH=${M2_HOME}/bin:${PATH}

Installing Python 2.7

sudo apt-get install python2.7

Installing pip to resolve the pymongo dependency

sudo apt-get install python-pip

Installing pymongo (driver)

sudo pip install pymongo

Installing YCSB

curl -O --location https://github.com/brianfrankcooper/YCSB/releases/download/0.5.0/ycsb-0.5.0.tar.gz
tar xfvz ycsb-0.5.0.tar.gz
cd ycsb-0.5.0

YCSB comes with different workloads, and also allows for the customization of a workload to match our own requirements. If you want to learn more about the workloads have a look at https://github.com/brianfrankcooper/YCSB/blob/master/workloads/workload_template

First, we will edit the workloads/workloada file to perform 1 billion inserts (for our first test) while also preparing it to later perform only reads (for our second test):

recordcount=1000000
operationcount=1000000
workload=com.yahoo.ycsb.workloads.CoreWorkload
readallfields=true
readproportion=1
updateproportion=0.0

We will then change the workloads/workloadb file so as to provide a mixed workload for our third test.  We also set it to perform 1 billion reads, but we break it down into 70% of read queries and 30% of updates with a scan ratio of 5%, while also placing a cap on the maximum number of scanned documents (2000) in an effort to emulate real traffic – workloads are not perfect, right?

recordcount=10000000
operationcount=10000000
workload=com.yahoo.ycsb.workloads.CoreWorkload
readallfields=true
readproportion=0.7
updateproportion=0.25
scanproportion=0.05
insertproportion=0
maxscanlength=2000

With that, we have the environment configured for testing.

Running the tests

With all instances configured and ready, we run the stress test against our MongoDB servers using the following command :

./bin/ycsb [load/run] mongodb -s -P workloads/workload[ab] -threads [32/64/128] 
 -p mongodb.url=mongodb://xxx.xxx.xxx.xxx.:27017/ycsb0000[0-9] 
 -jvm-args="-Dlogback.configurationFile=disablelogs.xml"

The parameters between brackets varied according to the instance and operation being executed:

  • [load/run] load means insert data while run means perform action (update/read)
  • workload[a/b] reference the different workloads we’ve used
  • [32/64/128] indicate the number of concurrent threads being used for the test
  • ycsb0000[0-9] is the database name we’ve used for the tests (for reference only)

Results

Without further ado, the table below summarizes the results for our tests:

 

 

 

Performance cost

Considering throughput alone – and in the context of those tests, particularly the last one – you may get more performance for the same cost. That’s certainly not always the case, which our results above also demonstrate. And, as usual, it depends on “how much performance do you need” – a matter that is even more pertinent in the cloud. With that in mind, we had another look at our data under the “performance cost” lens.

As we saw above, the c5.4xlarge instance performed better than the other two instances for a little over 50% more (in terms of cost). Did it deliver 50% more (performance) as well? Well, sometimes it did even more than that, but not always. We used the following formula to extrapolate the OPS (Operations Per Second) data we’ve got from our tests into OPH (Operations Per Hour), so we could them calculate how much bang (operations) for the buck (US$1) each instance was able to provide:

transactions/hour/US$1 = (OPS * 3600) / instance cost per hour

This is, of course, an artificial metric that aims to correlate performance and cost. For this reason, instead of plotting the raw values, we have normalized the results using the best performer instance as baseline(100%):

 

 

The intent behind these was only to demonstrate another way to evaluate how much we’re getting for what we’re paying. Of course, you need to have a clear understanding of your own requirements in order to make a balanced decision.

Parting thoughts

We hope this post awakens your curiosity not only about how MongoDB may perform on ARM-based servers, but also by demonstrating another way you can perform your own tests with the YCSB benchmark. Feel free to reach out to us through the comments section below if you have any suggestions, questions, or other observations to make about the work we presented here.

Read more at: http://www.mysqlperformanceblog.com/

Upcoming Webinar Wed 2/6: Percona Software News and Roadmap Update

Percona Software News and Roadmap Update Webinar

Percona Software News and Roadmap Update WebinarJoin Percona CEO Peter Zaitsev as he presents Percona Software News and Roadmap Update on Wednesday, February 6, 2019, at 11:00 AM PST (UTC-8) / 2:00 PM EST (UTC-5).

Register Now

Come and listen to Percona CEO Peter Zaitsev discuss what’s new in Percona open source software. Topics include Percona Server for MySQL and MongoDB, Percona XtraBackup, Percona Toolkit, Percona XtraDB Cluster and Percona Monitoring and Management.

During this webinar, Peter will talk about newly released features in Percona software. He will also show a few quick demos and share with you highlights from the Percona open source software roadmap.

Peter will also talk about new developments in Percona commercial services and finish with a Q&A.

Register today to join Peter for his Percona Software News and Roadmap Update.

Read more at: http://www.mysqlperformanceblog.com/

Percona Server for MongoDB 3.6.10-3.0 Is Now Available

Percona Server for MongoDB

Percona Server for MongoDB

Percona announces the release of Percona Server for MongoDB 3.6.10-3.0 on February 6, 2019. Download the latest version from the Percona website or the Percona Software Repositories. This
release is also available for Ubuntu 18.10 (Cosmic Cuttlefish).

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 3.6 Community Edition. It supports MongoDB 3.6 protocols and drivers.

Percona Server for MongoDB extends Community Edition functionality by including the Percona Memory Engine storage engine, as well as several enterprise-grade features. It also includes MongoRocks storage engine (which is now deprecated). Percona Server for MongoDB requires no changes to MongoDB applications or code.

In Percona Server for MongoDB 3.6.10-3.0, data at rest encryption becomes GA. The data at rest encryption feature now covers the temporary files used for external sorting and the rollback files. You can decrypt and examine the contents of the rollback files using the new perconadecrypt command line tool.

In this release, Percona Server for MongoDB supports the ngram full-text search engine. Thanks to Sunguck Lee (@SunguckLee) for this contribution. To enable the ngram full-text search engine, create an index passing ngram to the default_language parameter:

mongo > db.collection.createIndex({name:"text"}, {default_language: "ngram"})

New Features

  • PSMDB-276perconadecrypt tool is now available for decrypting the encrypted rollback files.
  • PSMDB-250: The Ngram full-text search engine has been added to Percona Server for MongoDB. Thanks to @SunguckLee on GitHub

Bugs Fixed

  • PSMDB-234: It was possible to use a key file for encryption the owner of which was not the owner of the mongod process.
  • PSMDB-269: In some cases, a hot backup was not using the correct path to the keydb directory designated for data encryption.
  • PSMDB-273: When using data at rest encryption, temporary files for external sorting and rollback files were not encrypted
  • PSMDB-272mongos could crash when running the createBackup command.
  • PSMDB-233: WiredTiger encryption options were silently ignored at server startup, although a storage engine different from WiredTiger was used.
  • PSMDB-257: MongoDB could not be started with a group-readable key file owned by root.
  • PSMDB-266: In some cases, it was possible to add arbitrary collections to the keydb directory which may only store encryption data.

Other bugs fixed: PSMDB-239PSMDB-243

The Percona Server for MongoDB 3.6.10-3.0 release notes are available in the official documentation.

Read more at: http://www.mysqlperformanceblog.com/

Percona Server for MongoDB 4.0.5-2 Is Now Available

Percona Server for MongoDB

Percona Server for MongoDB

Percona announces the release of Percona Server for MongoDB 4.0.5-2 on February 18, 2019. Download the latest version from the Percona website or the Percona Software Repositories.

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 4.0 Community Edition. It supports MongoDB 4.0 protocols and drivers.

Percona Server for MongoDB extends Community Edition functionality by including the Percona Memory Engine storage engine, as well as several enterprise-grade features. It also includes MongoRocks storage engine (which is now deprecated). Percona Server for MongoDB requires no changes to MongoDB applications or code.

This release includes all features of MongoDB 4.0 Community Edition. Most notable among these are:

Note that the MMAPv1 storage engine is deprecated in MongoDB 4.0 Community Edition.

In Percona Server for MongoDB 4.0.5-2, data at rest encryption becomes GA. The data at rest encryption feature now covers the temporary files used for external sorting and the rollback files. You can decrypt and examine the contents of the rollback files using the new perconadecrypt command line tool.

In this release, Percona Server for MongoDB supports the ngram full-text search engine. Thanks to Sunguck Lee (@SunguckLee) for this contribution. To enable the ngram full-text search engine, create an index passing ngram to the default_language parameter:

mongo > db.collection.createIndex({name:"text"}, {default_language: "ngram"})

New Features

  • PSMDB-276perconadecrypt tool is now available for decrypting the encrypted rollback files.
  • PSMDB-250: The Ngram full-text search engine has been added to Percona Server for MongoDB.Thanks to Sunguck Lee (@SunguckLee) for this contribution.

Bugs Fixed

  • PSMDB-234: It was possible to use a key file for encryption the owner of which was not the owner of the mongod process.
  • PSMDB-273: When using data at rest encryption, temporary files for external sorting and rollback files were not encrypted
  • PSMDB-257: MongoDB could not be started with a group-readable key file owned by root.
  • PSMDB-272mongos could crash when running the createBackup command.

Other bugs fixed: PSMDB-247

The Percona Server for MongoDB 4.0.5-2 release notes are available in the official documentation.

Read more at: http://www.mysqlperformanceblog.com/

Percona Server for MongoDB 3.4.19-2.17 Is Now Available

Percona Server for MongoDB

Percona Server for MongoDB

Percona announces the release of Percona Server for MongoDB 3.4.19-2.17 on February 19, 2019. Download the latest version from the Percona website or the Percona Software Repositories.

Percona Server for MongoDB 3.4 is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 3.4 Community Edition. It supports MongoDB 3.4 protocols and drivers.

Percona Server for MongoDB extends MongoDB Community Edition functionality by including the Percona Memory Engine and MongoRocks storage engines, as well as several enterprise-grade features:

Percona Server for MongoDB requires no changes to MongoDB applications or code. This release is based on MongoDB 3.4.19.

In this release, Percona Server for MongoDB supports the ngram full-text search engine. Thanks to Sunguck Lee (@SunguckLee) for this contribution. To enable the ngram full-text search engine, create an index passing ngram to the default_language parameter:

mongo > db.collection.createIndex({name:"text"}, {default_language: "ngram"})

New Features

  • PSMDB-250: The ngram full-text search engine has been added to Percona Server for MongoDB.Thanks to Sunguck Lee (@SunguckLee) for this contribution.

Bugs Fixed

  • PSMDB-272mongos could crash when running the createBackup command.

Other bugs fixed: PSMDB-247

The Percona Server for MongoDB 3.4.19-2.17 release notes are available in the official documentation.

Read more at: http://www.mysqlperformanceblog.com/

Percona Monitoring and Management (PMM) 1.17.1 Is Now Available

Percona Monitoring and Management 1.17.0

Percona Monitoring and Management

Percona Monitoring and Management (PMM) is a free and open-source platform for managing and monitoring MySQL®, MongoDB®, and PostgreSQL performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL®, MongoDB®, and PostgreSQL® servers to ensure that your data works as efficiently as possible.

In this release, we are introducing support for detection of our upcoming PMM 2.0 release in order to avoid potential version conflicts in the future, as PMM 1.x will not be compatible with PMM 2.x.

Another improvement in this release is we have updated the Tooltips for Dashboard MySQL Query Response Time by providing a description of what the graphs display, along with links to related documentation resources. An example of Tooltips in action:

PMM 1.17.1 release provides fixes for CVE-2018-16492 and CVE-2018-16487 vulnerabilities, related to Node.js modules. The authentication system used in PMM is not susceptible to the attacks described in these CVE reports. PMM does not use client-side data objects to control user-access.

In release 1.17.1 we have included two improvements and fixed nine bugs.

Improvements

  • PMM-1339: Improve tooltips for MySQL Query Response Time dashboard
  • PMM-3477: Add Ubuntu 18.10 support

Fixed Bugs

  • PMM-3471: Fix global status metric names in mysqld_exporter for MySQL 8.0 compatibility
  • PMM-3400: Duplicate column in the Query Analytics dashboard Explain section
  • PMM-3353: postgres_exporter does not work with PostgreSQL 11
  • PMM-3188: Duplicate data on Amazon RDS / Aurora MySQL Metrics dashboard
  • PMM-2615: Fix wrong formatting in log which appears if pmm-qan-agent process fails to start
  • PMM-2592: MySQL Replication Dashboard shows error with multi-source replication
  • PMM-2327: Member State Uptime and Max Member Ping time charts on the MongoDB ReplSet dashboard return an error
  • PMM-955: Fix format of User Time and CPU Time Graphs on MySQL User Statistics dashboard
  • PMM-3522: CVE-2018-16492 and CVE-2018-16487

Help us improve our software quality by reporting any Percona Monitoring and Management bugs you encounter using our bug tracking system.

Read more at: http://www.mysqlperformanceblog.com/

Percona Server for MongoDB 4.0.6-3 Is Now Available

Percona Server for MongoDB

Percona Server for MongoDB

Percona announces the release of Percona Server for MongoDB 4.0.6-3 on February 28, 2019. Download the latest version from the Percona website or the Percona software repositories.

Percona Server for MongoDB is an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB 4.0 Community Edition. It supports MongoDB 4.0 protocols and drivers.

Percona Server for MongoDB extends the functionality of the MongoDB 4.0 Community Edition by including the Percona Memory Engine storage engine, encrypted WiredTiger storage engineaudit loggingSASL authenticationhot backups, and enhanced query profilingPercona Server for MongoDB requires no changes to MongoDB applications or code.

Release 4.0.6-3 extends the buildInfo command with the psmdbVersion key to report the version of Percona Server for MongoDB. If this key exists then Percona Server for MongoDB is installed on the server. This key not available from MongoDB.

This release includes all features of MongoDB 4.0 Community Edition 4.0. Most notable among these are:

Note that the MMAPv1 storage engine is deprecated in MongoDB 4.0 Community Edition 4.0.

Improvements

  • PSMDB-216: The database command buildInfo provides the psmdbVersion key to report the version of Percona Server for MongoDB. If this key exists then Percona Server for MongoDB is installed on the server. This key is not available from MongoDB.

The Percona Server for MongoDB 4.0.6-3 release notes are available in the official documentation.

Read more at: http://www.mysqlperformanceblog.com/

Does Percona Monitoring and Management (PMM) Support External Monitoring Services? Yes It Does!

External Monitoring Services

Percona Monitoring and Management (PMM) is a free and open-source platform for managing and monitoring MySQL and MongoDB performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL and MongoDB servers to ensure that your data works as efficiently as possible.

Starting with version 1.4.0 and improved in 1.7.0, PMM supports external monitoring services. This means you can plug in Prometheus exporters for technologies not directly provided by Percona. For example, you can start monitoring the metrics of your PostgreSQL database host, Memcached or Redis.

Exporters Overview

Applications store their metrics in arbitrary formats, and Prometheus exporters collect them and produce (or export to) a consistent format of key-value pairs. The keys refer to metric types and values are numbers in the float 64 format. Due to the diversity of formats that applications may use, you should program a specific exporter for each format. However, if you decide to make the metrics of your application available via PMM you may consider using one of existing Prometheus exporters.

Currently, PMM offers exporters for MySQL (mysqld_exporter) and MongoDB (mongodb_exporter) database management systems. Built-in exporters also exist for Percona XtraDBCluster, MariaDB, RDS and Aurora via mysqld_exporter and for ProxySQL (via proxysql_exporter). These exporters are made available as monitoring services that you can add or remove as necessary. In addition, PMM includes the node_exporter to capture the host level Linux metrics such as CPU, Load, and disk resources.

Using Exporters

On the computer where the PMM client is installed and connected to a PMM server, make use of the pmm-admin utility to add any built-in monitoring service directly. There is no extra effort in this case: the added monitoring service will run its exporter and all required configuration updates are made automatically to make the metrics available in the web interface for further analysis in Query analytics and Metrics monitor.

In case of external monitoring services, you need to locate, download, set up and run the specific Prometheus exporter to collect metrics. When it is ready, you can add it as a monitoring service:

pmm-admin add external:service job_name [instance] --service-port=PORT_NUMBER

This command adds an external monitoring service bound to the Prometheus job that you specify as the job_name parameter. You should also provide the port associated with this Prometheus job as the value of the service-port parameter. The instance parameter is optional. By default, it is assigned the name of the host where you run pmm-admin.

Example 1: Adding a PostgreSQL Monitoring Service

In order to add an external monitoring service for a PostgreSQL database server, make sure to install and configure your PostgreSQL server. Then, select a PostgreSQL Prometheus exporter from the list available from the  Prometheus site, such as PostgreSQL metric exporter for Prometheus. Refer to the documentation for this exporter for details about how to install and set it up.

As soon as your Prometheus exporter can collect metrics from your PostgreSQL database server,  you are ready to add this exporter as a monitoring service. Make sure that you have access to a configured PMM server and your PMM client has been set up to use it. Use the pmm-admin utility, which is part of PMM client, to add the PostgreSQL monitoring service. Assuming postgresql is the name of this monitoring service, your command should look like this:

pmm-admin add external:service --service-port=PORT_NUMBER postgresql

It is time now to display the metrics on the PMM Server. Open Metrics Monitor and check the Advanced Data Exploration dashboard. This can dashboard visualize a lot of metrics including those exposed by external monitoring services. In the Host field select your host. Use the Metric field to select a metric.

External Monitoring Services
Viewing a metric exposed by a PostgreSQL exporter.

Setting up an external monitoring service requires extra work compared to adding built-in monitoring services. However, by using external monitoring services you can considerably extend the capabilities of your PMM installation.

Note that running the pmm-admin list command lists the added external monitoring services. They also appear in the JSON output, too. To remove an external service use the remove (or its short form rm) command:

pmm-admin rm external:service --service-port=PORT_NUMBER NAME_OF_EXTERNAL_MONITORING_SERVICE

$ sudo pmm-admin list
pmm-admin 1.7.0
PMM Server      | 192.0.2.2 (password-protected)
Client Name     | postgres01
Client Address  | 192.0.2.3
Service Manager | unix-systemv
Job name    Scrape interval  Scrape timeout  Metrics path  Scheme  Target         Labels                   Health
postgresql  1s               1s              /metrics      http    192.0.2.3:9187 instance="postgres01"      UP

Example 2: Adding a Redis Monitoring Service

To start with, you must install a Prometheus exporter for Redis (this exporter is listed on the Prometheus Exporters and Integrations page) on the machine where your PMM client runs. The following command adds this exporter as an external monitoring service (run it as a superuser or use sudo). This time the command has an extra parameter:

$ sudo pmm-admin add external:service redis --service-port 9121 redis01
External service added.

Notice that we use Redis Server as the last parameter passed to pmm-admin add external:service command. The last positional parameter is a label that you assign to this particular instance.

pmm-admin add external:service --service-port=PORT_NUMBER NAME_OF_EXTERNAL_MONITORING_SERVICE [INSTANCE_LABEL]

You may choose any name for this purpose. Make sure to use quotes if you decide to use a label made of two or more words.

$ sudo pmm-admin list
pmm-admin 1.7.0
PMM Server | 127.0.0.1
Client Name | percona
Client Address | 172.17.0.1
Service Manager | linux-systemd
No services under monitoring.
Job name Scrape interval Scrape timeout Metrics path Scheme Target          Labels                  Health
redis    1m0s            10s            /metrics     http   172.17.0.1:9121 instance="redis01"      UP

To view Redis related metrics you need to open the Advanced Data Exploration dashboard on your PMM Server. The redis01 label automatically appears in the Host field in the Advanced Data Exploration dashboard. In the Host field, select the redis01 option and choose a metric to view from the Metric field, such as redis_exporter_scrapes_total.

Other Ways to Add External Services

The pmm-admin add external:service command is the recommended way to add an external monitoring service. There exist other, more specific, methods. The pmm-admin add external:metrics adds external Prometheus exporters job to metrics monitoring.

Read more at: http://www.mysqlperformanceblog.com/