DOCKER @ FLUX7 LABS

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Who am I?

● Aater Suleman○ Part-time UT Professor ○ Geek, Architect, Developer, Ops, DevOps …

● Co-founder & CEO Flux7 Labs ○ DevOps Solutions

■ Deployments■ Cost/performance optimized large scale

website (Ruby on rails, node.js, Django) and Hadoop deployments

VyScale Dev Flow

Docker's impact on performance (whitepaper WIP)

Multi-tenancy

Live process migration using CRIU (criu.org)

Four projects:

Application: Single Service Provider

Receive Sensor Data

Report Generation

based on data

Report sent to End User

Internet of Things -- Solar Panel Monitoring

XML Data over TCP

Big Data Analytics

Single Provider System

Provider Span

Location1 Location2Location3

Gateway1 Gateway2

Gateway3sensors

A provider has Mifi routers installed at multiple Locations which collect data from sensors and sends it to a remote TCP server via the internet.

TCP serverPort 6000

Cassandra port 9160

Flask AppPort 80

BrowserUses the Flask app at port 80Internet

COMPONENTS

1. Cassandra for data persistence which we later use for generating reports for each gateway.

2. A Twisted TCP server listening at PORT 6000, for data ingestion from multiple gateways owned by the provider.

3. A Flask app serving at PORT 80 as the admin panel for setting customizations and viewing reports.

GG G

G

Customer NCustomer 2 …Customer 1 Each customer can have multiple gateways

commissioned to them.

Remote Twister TCP Server (Non–Blocking I/O)

Cassandra NoSQL data store(High Volume High Velocity Write which scales Linearly across the

cluster )

Power consumption status on website and

mails

*G - Gateway

Web App

Mailer

SINGLE PROVIDER LAUNCH

For launching the single provider version, the following was done:

1. nohup python tcp_server.py & # For firing up the TCP server.

2. nohup python flask_app.py & # For firing up the admin panel

Both these code bases houses hard-coded Cassandra KEYSPACE

Success!

Application: Multiple Service Providers

…

Provider 1 sends data to port 6001

and accesses flask app at port 8081

Provider 2 sends data to port 6002 and accesses flask app at

port 8082

Flask container-runs flask app at port 80. Exposes port 80 and

published it to port 8081 for provider 1

Flask container-runs flask app at port 80. Exposes

port 80 and published it to port 8082 for provider 2

TCP server container-runs at port 6000.

Exposes port 6000 and published it to port 6001

for provider 1

TCP server container-runs at port 6000. Exposes

port 6000 and published it to port 6002 for provider 2

Cassandra

Internet

KNEE-JERK APPROACH

Sprinkle Tenant ID everywhere in the code and DB

Time consuming

Expensive

Poor isolation

Security

Maintenance

Rigidity

An alternate solution is to use Virtual Machine (VM)

Hosts are expensive ($)VMs are expensive (high overhead)

MULTIPLE HOST/VMS

AND THE SOLUTION

How: Isolated environments for running multiple instances of the app

WHY DOCKER?

Docker containers provide isolation that is

Fast

Inexpensive

Create a docker container for the new version of the app

PLAN

Setup environments/dependencies correctly

Start a Cassandra container.

# start a docker container for consuming gateway data at gateway_portstart_command = 'python software/remote_server.py ' + provider_idremote_server = docker_client.create_container('flux7/labs', # docker imagecommand=start_command, # start command contains the keyspace parameter, keyspace is the provider_idname='remote_server_' + provider_id, # name the container, name is provider_idports=[(6000, 'tcp'),]) # open port for binding, remote_server.py listens at 6000docker_client.start(remote_server, port_bindings={6000: ('0.0.0.0', gateway_port)}, links={'db': 'cassandra'})

AUTOMATION

# start a docker container for serving admin panel at admin_portstart_command = 'python software/flask_app.py ' + provider_idremote_server = docker_client.create_container('flux7/labs', # docker imagecommand=start_command, # start command contains the keyspace parameter, keyspace is the provider_idname='admin_panel_' + provider_id, # name the container, name is provider_idports=[(80, 'tcp'),]) # open port for binding, remote_server.py listens at 6000docker_client.start(remote_server, port_bindings={80: ('0.0.0.0',admin_port)}, links={'db': 'cassandra'})

An automation was the next foreseeable step, and for that we found Docker-py extremely useful. We used something like:

# Yes. We love Python!def start_provider(provider_id, gateway_port, admin_port ):docker_client = docker.Client(base_url='unix://var/run/docker.sock', version='1.6', timeout=100)

For now, a locally running container serving at PORT 9160 using the command

similar to this:

docker run -d -p 9160:9160 -name db flux7/cassandra

OUR SOLUTION- EXPLAINED

▪ Create a keyspace ‘provider1’ using pycassaShell.

We fired up our two code bases on two separate containers like this:

OUR SOLUTION- EXPLAINED

docker run -name remote_server_1 -link db:cassandra -

p 6000:6000 flux7/labs python software/remote_server.

py provider1

docker run -name flask_app_1 -link db:cassandra -p

6000:6000 flux7/labs python software/flask_app.py

provider1

DOCKER ISSUES DISCOVERED

Docker does not support multiple instances of Cassandra running on the

same machine.

Hosting multiple database instances on a single machine can quickly

cause resource shortages

❑ Followed the traditional solution to make an application multi-tenant

OUR SOLUTION

Code Changes •• To data ingestion server and web server by adding the keyspace parameter to the DB accesses.

Cassandra KEYSPACE /

provider ID •• Passed to each instance of the app on the

command line.

❑ Each provider in the data store gets a separate namespace without making

any changes to the column family schema.

Use of KEYSPACE as the namespace for each provider in the data store

LESSONS WE LEARNED

1. Docker is an extremely fast and elegant isolation framework: easy to port, cheap to run, easy to orchestrate

2. Multi-tenancy != changing the app to support multiple tenants

3. Docker orchestration frameworks are not at par with Docker today. What we have written is yet another one but for multi-tenancy.

4. Dockerfiles still need work -- we used shell scripts in some places

5. We can run multiple commands/container

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