Portainer Helps Simplify Complex Infrastructure Management

This large technology company builds a lot of internal applications using containers and container orchestration platforms like Docker and Kubernetes. They are running these containerized workloads on internal datacenter infrastructure.

Managing and monitoring these containerized applications is the main opportunity for their 7 person quality assurance team. The hardware engineering teams building the applications often lack expertise with command line configuration and YAML templates required for container deployments and management.

Managing containers and orchestrators like Docker and Kubernetes introduced complexity for the hardware engineers. The Senior QA Engineer told us: 

“There’s a lot of hardware engineers and they don’t want to think about the infrastructure. Getting them to build a container, was probably the most I was ever going to really be able to do.”

Facing a skill gap adopting container technology, the team needed to simplify management for those focused on building applications.

Troubleshooting issues with logging or coordinating deployments has been cumbersome and time consuming across teams. In order to implement a solution like Portainer in this large, data-driven organization, the team leader had to build a business case to defend bringing Portainer on as a new vendor. 

The question from management was: 

“Now that we think that we should buy that, are we sure that Portainer produces the best of what we’re trying to buy ”

The team leader had to prove they could solve these business critical issues with Portainer: 

• Let hardware engineers innovate
• Standardize and centralize management 
• Improve productivity and deployment 
• Manage demand and scale. 

With Portainer the team leader can now get everything including network configurations set up in a stack and defined. Now he can tell somebody to change only one number, removing the need for his team to learn command line interfaces and configuration file formats.

Standardizing and Centralizing Management

Rather than having separate engineers developing their own logging solution, Portainer delivers consistent container management. As the team leader explains, Portainer provides a unified way for engineers to do logging. This also aids troubleshooting the frequent proof of concept type applications which have a high chance of not working on the first run. It used to mean “hours coordinating between folks.”

Engineering time is expensive, so reducing coordination efforts between teams has major financial implications. Beyond the financial implications it often surprises management how long it actually takes to diagnose issues.

Improving Productivity and Deployments

To convince management about Portainer’s value, the team leader sized productivity gains as equal to “the hiring of an engineer” for the 7 person team. Proving Portainer could eliminate the equivalent of 1 full time engineer’s salary in efficiency gains.

Quantifying how much time is spent on deployments, the team leader showed how Portainer simplifies updating containers: “everybody then has to learn the command line version of that.” With a visual interface, “somebody else can pick it up” allowing tasks to be transferred between team members.

Standard troubleshooting also benefits their culture of inquiry where leadership demands data around outages. By providing consistent logs and views, Portainer ensures “everybody has the same starting point” when triaging production issues. Employees no longer waste time piecing together what went wrong.

Managing Demand and Scale

While they run Portainer on internal infrastructure, the team leader notes how visibility aids capacity planning:

“I visit the cluster status or the pages pretty often just to even see how things are getting balanced out because it gives me a very good quick look at what’s going on.”

As for scale, this team far surpasses typical workloads: “In the last 24 hours, we’ve brought 500 containers up and down” doing “a lot of data analysis” and “proof of concept” tests. Retrieving logs on 20-30 containers concurrently has been achieved.