In order to connect to Redis Memorystore on GCP, we can either use “redis-py” or other alternative methods offered in this article. Bobcares, as a part of our Google Cloud Platform Support Service offers solutions to every query that comes our way.

Overview

1. How to Connect to Redis Memorystore on GCP?
2. Connecting to Redis Memorystore Using redis-py Client
3. Other Methods

How to Connect to Redis Memorystore on GCP?

To connect to Redis Memorystore on GCP, we need to obtain the Discovery Endpoint from the GCP Console and use redis-cli or a client library like redis-py on a Compute Engine VM within the same VPC network. Here, we’ll look into the details of the process:

Connecting to Redis Memorystore Using redis-py Client

Using redis-py Client

i. Install the redis-py library:

pip install redis-py-cluster

ii. Connect to the Redis Cluster:

from rediscluster import RedisCluster

endpoints = [{"host": "IPADDRESS", "port": "6379"}]

rdb = RedisCluster(
startup_nodes=endpoints,
skip_full_coverage_check=True, # Required for Memorystore
decode_responses=True
)

print(rdb.set('PYTHON', 'CLUSTER'))
print(rdb.get('PYTHON'))
print(rdb.unlink('PYTHON'))

Getting the Cluster’s Discovery Endpoint

i. Go to the Memorystore for Redis Cluster page in the Google Cloud Console.

ii. Click the Cluster ID.

iii. In the Connect to this instance section, note the IP address and port number next to Discovery Endpoint.

Connecting from a Compute Engine VM

i. Create or use an existing Linux Compute Engine VM in the authorized network.

ii. Install redis-cli (version 6.0 or newer) on the VM.

iii. Install the instance’s certificate authority on the VM.

iv. Connect to the instance:

redis-cli -h DISCOVERY_ENDPOINT_ADDRESS -p PORT_NUMBER -c

v. View cluster topology:

redis-cli -h DISCOVERY_ENDPOINT_ADDRESS -p PORT_NUMBER -c
CLUSTER SHARDS

vi. Connect to a node:

redis-cli -h NODE_IP_ADDRESS -p NODE_PORT -a ACCESS_TOKEN -c

Other Methods

Method 1: Port Forwarding

i. Create a forwarding VM:

gcloud compute instances create redis-forwarder --machine-type=f1-micro

ii. Setup port forwarding:

gcloud compute ssh redis-forwarder -- -N -L 6379:10.0.0.3:6379

iii. Connect locally:

redis-cli -h localhost -p 6379

Method 2: Using HAProxy

i. Setup HAProxy with Docker:

frontend redis_frontend
bind *:6379
mode tcp
option tcplog
timeout client 1m
default_backend redis_backend
backend redis_backend
mode tcp
option tcplog
option log-health-checks
option redispatch
log global
balance roundrobin
timeout connect 10s
timeout server 1m
server redis_server 10.0.0.12:6379 check

ii. Connect via HAProxy:

redis-cli -h -p 6379

Method 3: Using a Jumpbox

i. Create a firewall rule:

gcloud compute firewall-rules create default-allow-ssh --project=my-project --network my-network --allow tcp:22 --source-ranges 0.0.0.0/0

ii. Create a jumpbox:

gcloud compute instances create jump-box --machine-type=f1-micro --project my-project --zone europe-west1-b --network my-network

iii. Setup port forwarding:

gcloud compute ssh jump-box --project my-project --zone europe-west1-b -- -N -L 6379:10.177.174.179:6379

iv. Connect locally:

redis-cli -h localhost -p 6379

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Conclusion

To sum up, our Tech team explains different methods to connect to to Redis Memorystore on GCP. The first method involves use of redis-py Client. Alternative methods to create the connection is also explained.