If you are serious about monitoring your cluster health with real-time alerts, analyzing your cluster configuration, rebalance as necessary, managing addition of nodes, re-sharding, node deletion, and master-replica configuration, you must try out RedisInSight. It’s pretty cool and officially supported by Redis Labs. It works quite good if you are using Redis Enterprise. But what if you want to monitor and access UI for Redis Open Source?
Rebrow comes to rescue..
One of the promising tool I came across was Rebrow. It is a Python-Flask-based Browser for Redis Content. It is built for the developer who needs to look into a Redis store. It allows for inspection and deletion of keys and follows PubSub messages. It also displays some runtime and configuration information.
Tested Infrastructure
- Play with Docker Environment
- Docker 19.03.4
- Docker Compose 1.23.2, build 1110ad0
- Redis 6.0 Release Candidate 1
We will be using Docker Swarm, hence one of the quickest way to get Docker Swarm up and running is through “Play with Docker”, aka PWD. It’s free of cost and open for all. You get maximum of 5 instances of Linux system to play around with Docker.
- Open Play with Docker labs on your browser
- Click on Icon near to Instance to choose 3 Managers & 2 Worker Nodes
- Wait for few seconds to bring up 5-Node Swarm Cluster
Clone the Repository
I have created a docker-compose file with the below contents:
version: "3"
services:
web:
# replace username/repo:tag with your name and image details
image: ajeetraina/redis-flask
build:
context: ./stackdemo
dockerfile: Dockerfile
deploy:
replicas: 5
restart_policy:
condition: on-failure
resources:
limits:
cpus: "0.1"
memory: 50M
ports:
- "8000:8000"
networks:
- webnet
visualizer:
image: dockersamples/visualizer:stable
ports:
- "8080:8080"
volumes:
- "/var/run/docker.sock:/var/run/docker.sock"
deploy:
placement:
constraints: [node.role == manager]
networks:
- webnet
redis:
image: redis:6.0-rc1
ports:
- "6379:6379"
volumes:
- data:/home/docker/data
deploy:
placement:
constraints: [node.role == manager]
command: redis-server --appendonly yes
networks:
- webnet
networks:
webnet:
volumes:
data:I have put the above code under Collabnix repository which you can pull and leverage it directly. Do follow the below steps:
git clone https://github.com/collabnix/dockerlabs
cd dockerlabs/solution/redis/viz-web-redis
docker stack deploy -c docker-compose.yml myredis
Verifying the Services
$ docker service ls
ID NAME MODE REPLICAS IMAGE PORTS
ydgp8j56apek myredis_redis replicated 1/1 redis:3.0.6 *:6379->6379/tcp
ofqnb4282zo1 myredis_visualizer replicated 1/1 dockersamples/visualizer:stable *:8080->8080/tcp
bkxd3aklxhj7 myredis_web replicated 5/5 ajeetraina/redis-flask:latest *:8000->8000/tcp
Verifying if Redis is running successfully
$ docker service ps myredis_redis
ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
robvimouagqj myredis_redis.1 redis:6.0-rc1 manager1 Running Running about a minute ago
Verifying the Redis Volume
$ docker volume inspect myredis_data
[
{
"CreatedAt": "2019-12-29T02:18:00Z",
"Driver": "local",
"Labels": {
"com.docker.stack.namespace": "myredis"
},
"Mountpoint": "/var/lib/docker/volumes/myredis_data/_data",
"Name": "myredis_data",
"Options": null,
"Scope": "local"
}
]
Checking the Redis logs
[manager1] (local) root@192.168.0.45 ~/dockerlabs/solution/redis/viz-web-redis
$ docker service ps myredis_redis
ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
robvimouagqj myredis_redis.1 redis:6.0-rc1 manager1 Running Running about a minute ago
[manager1] (local) root@192.168.0.45 ~/dockerlabs/solution/redis/viz-web-redis
$ docker service ps myredis_redis
ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
robvimouagqj myredis_redis.1 redis:6.0-rc1 manager1 Running Running about a minute ago
[manager1] (local) root@192.168.0.45 ~/dockerlabs/solution/redis/viz-web-redis
$ docker service logs -f myredis_redis
myredis_redis.1.robvimouagqj@manager1 | 1:C 29 Dec 2019 02:35:54.400 # oO0OoO0OoO0Oo Redis is starting oO0OoO0OoO0Oo
myredis_redis.1.robvimouagqj@manager1 | 1:C 29 Dec 2019 02:35:54.400 # Redis version=5.9.101, bits=64, commit=00000000, modified=0, pid=1, just started
myredis_redis.1.robvimouagqj@manager1 | 1:C 29 Dec 2019 02:35:54.400 # Configuration loaded
myredis_redis.1.robvimouagqj@manager1 | 1:M 29 Dec 2019 02:35:54.402 * Running mode=standalone, port=6379.
myredis_redis.1.robvimouagqj@manager1 | 1:M 29 Dec 2019 02:35:54.402 # WARNING: The TCP backlog setting of 511 cannot be enforced because /proc/sys/net/core/somaxconn is set to the lower value of 128.
myredis_redis.1.robvimouagqj@manager1 | 1:M 29 Dec 2019 02:35:54.402 # Server initialized
myredis_redis.1.robvimouagqj@manager1 | 1:M 29 Dec 2019 02:35:54.402 # WARNING you have Transparent Huge Pages (THP) support enabled in your kernel. This will create latency and memory usage issues with Redis. To fix this issue run the command 'echo never > /sys/kernel/mm/transparent_hugepage/enabled' as root, and add it to your /etc/rc.local in order to retain the setting after a reboot. Redis must be restarted after THP is disabled.
myredis_redis.1.robvimouagqj@manager1 | 1:M 29 Dec 2019 02:35:54.402 * Ready to accept connectionsWhere is my Redis service running?
$ docker service ps myredis_redis
ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
robvimouagqj myredis_redis.1 redis:6.0-rc1 manager1 Running Running 3 minutes ago
Inspecting Redis Service
$ docker service inspect myredis_redis
[
{
"ID": "hmistkdxnirdm5vq2f41aaqr9",
"Version": {
"Index": 127
},
"CreatedAt": "2019-12-29T02:35:47.7810801Z",
"UpdatedAt": "2019-12-29T02:35:47.78773254Z",
"Spec": {
"Name": "myredis_redis",
"Labels": {
"com.docker.stack.image": "redis:6.0-rc1",
"com.docker.stack.namespace": "myredis"
},
"TaskTemplate": {
"ContainerSpec": {
"Image": "redis:6.0-rc1@sha256:c2227b1e5c4755cb94f18eef10b34fb4eac116ce8c5ea0a40d0ca806927b8311",
"Labels": {
"com.docker.stack.namespace": "myredis"
},
"Args": [
"redis-server",
"--appendonly",
"yes"
],
"Privileges": {
"CredentialSpec": null,
"SELinuxContext": null
},
"Mounts": [
{
"Type": "volume",
"Source": "myredis_data",
"Target": "/home/docker/data",
"VolumeOptions": {
"Labels": {
"com.docker.stack.namespace": "myredis"
}
}
}
],
"StopGracePeriod": 10000000000,
"DNSConfig": {},
"Isolation": "default"
},
"Resources": {},
"RestartPolicy": {
"Condition": "any",
"Delay": 5000000000,
"MaxAttempts": 0
},
"Placement": {
"Constraints": [
"node.role == manager"
],
"Platforms": [
{
"Architecture": "amd64",
"OS": "linux"
},
{
"Architecture": "386",
"OS": "linux"
},
{
"Architecture": "ppc64le",
"OS": "linux"
},
{
"Architecture": "s390x",
"OS": "linux"
}
]
},
"Networks": [
{
"Target": "rolenrgn8nqibx2h16wd2tac6",
"Aliases": [
"redis"
]
}
],
"ForceUpdate": 0,
"Runtime": "container"
},
"Mode": {
"Replicated": {
"Replicas": 1
}
},
"UpdateConfig": {
"Parallelism": 1,
"FailureAction": "pause",
"Monitor": 5000000000,
"MaxFailureRatio": 0,
"Order": "stop-first"
},
"RollbackConfig": {
"Parallelism": 1,
"FailureAction": "pause",
"Monitor": 5000000000,
"MaxFailureRatio": 0,
"Order": "stop-first"
},
"EndpointSpec": {
"Mode": "vip",
"Ports": [
{
"Protocol": "tcp",
"TargetPort": 6379,
"PublishedPort": 6379,
"PublishMode": "ingress"
}
]
}
},
"Endpoint": {
"Spec": {
"Mode": "vip",
"Ports": [
{
"Protocol": "tcp",
"TargetPort": 6379,
"PublishedPort": 6379,
"PublishMode": "ingress"
}
]
},
"Ports": [
{
"Protocol": "tcp",
"TargetPort": 6379,
"PublishedPort": 6379,
"PublishMode": "ingress"
}
],
"VirtualIPs": [
{
"NetworkID": "sl1ecujt79razdyhjvmbohhjo",
"Addr": "10.255.0.26/16"
},
{
"NetworkID": "rolenrgn8nqibx2h16wd2tac6",
"Addr": "10.0.1.15/24"
}
]
}
}
]
$ docker exec -it 2db redis-cli --cluster help
Cluster Manager Commands:
create host1:port1 ... hostN:portN
--cluster-replicas <arg>
check host:port
--cluster-search-multiple-owners
info host:port
fix host:port
--cluster-search-multiple-owners
reshard host:port
--cluster-from <arg>
--cluster-to <arg>
--cluster-slots <arg>
--cluster-yes
--cluster-timeout <arg>
--cluster-pipeline <arg>
--cluster-replace
rebalance host:port
--cluster-weight <node1=w1...nodeN=wN>
--cluster-use-empty-masters
--cluster-timeout <arg>
--cluster-simulate
--cluster-pipeline <arg>
--cluster-threshold <arg>
--cluster-replace
add-node new_host:new_port existing_host:existing_port
--cluster-slave
--cluster-master-id <arg>
del-node host:port node_id
call host:port command arg arg .. arg
set-timeout host:port milliseconds
import host:port
--cluster-from <arg>
--cluster-copy
--cluster-replace
backup host:port backup_directory
help
For check, fix, reshard, del-node, set-timeout you can specify the host and port of any working node in the cluster.
$ curl localhost:8000
Hello World! I have been seen 6 times.
$ curl localhost:8000
Hello World! I have been seen 7 times.Let’s try to run Rebrow as Docker Swarm service and see if it really works.
$ docker service create --name myrebrow --publish 5001:5001 --replicas 2 marian/rebrow
p9qfx8bfmk7doamfxwy65eicu
overall progress: 2 out of 2 tasks
1/2: running
2/2: running
verify: Service converged
Wow ! It was really fast. Let’s open up web browser to see if it works without any issue. Just supply your Manager IP address and port as 6379. By now, it should connect to Redis server and show up the server status as shown below:
Click on “Keys” to find “hits” with a type “string”.
Once you click on “hits”, it should show you the total number of hits for the webpage.
Conclusion:
Rebrow is a promising Web UI for redis database content. Its completely open source and built for the developer who needs to look into a Redis store. It allows for inspection and deletion of keys and follows PubSub messages too. It also displays some runtime and configuration information.
Older Posts:
Building 3-Node Active-Active Redis Enterprise Cluster for Developers using Docker Desktop for Mac
Running Redis Enterprise inside Docker Container in 5 Minutes
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