openstack-manuals/doc/arch-design/source/massively-scalable-operatio...

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Operational considerations

In order to run efficiently at massive scale, automate as many of the operational processes as possible. Automation includes the configuration of provisioning, monitoring and alerting systems. Part of the automation process includes the capability to determine when human intervention is required and who should act. The objective is to decrease the ratio of operational staff to running systems as much as possible in order to reduce maintenance costs. In a massively scaled environment, it is very difficult for staff to give each system individual care.

Configuration management tools such as Puppet and Chef enable operations staff to categorize systems into groups based on their roles and thus create configurations and system states that the provisioning system enforces. Systems that fall out of the defined state due to errors or failures are quickly removed from the pool of active nodes and replaced.

At large scale the resource cost of diagnosing failed individual systems is far greater than the cost of replacement. It is more economical to replace the failed system with a new system, provisioning and configuring it automatically and adding it to the pool of active nodes. By automating tasks that are labor-intensive, repetitive, and critical to operations, cloud operations teams can work more efficiently because fewer resources are required for these common tasks. Administrators are then free to tackle tasks that are not easy to automate and that have longer-term impacts on the business, for example, capacity planning.

The bleeding edge

Running OpenStack at massive scale requires striking a balance between stability and features. For example, it might be tempting to run an older stable release branch of OpenStack to make deployments easier. However, when running at massive scale, known issues that may be of some concern or only have minimal impact in smaller deployments could become pain points. Recent releases may address well known issues. The OpenStack community can help resolve reported issues by applying the collective expertise of the OpenStack developers.

The number of organizations running at massive scales is a small proportion of the OpenStack community, therefore it is important to share related issues with the community and be a vocal advocate for resolving them. Some issues only manifest when operating at large scale, and the number of organizations able to duplicate and validate an issue is small, so it is important to document and dedicate resources to their resolution.

In some cases, the resolution to the problem is ultimately to deploy a more recent version of OpenStack. Alternatively, when you must resolve an issue in a production environment where rebuilding the entire environment is not an option, it is sometimes possible to deploy updates to specific underlying components in order to resolve issues or gain significant performance improvements. Although this may appear to expose the deployment to increased risk and instability, in many cases it could be an undiscovered issue.

We recommend building a development and operations organization that is responsible for creating desired features, diagnosing and resolving issues, and building the infrastructure for large scale continuous integration tests and continuous deployment. This helps catch bugs early and makes deployments faster and easier. In addition to development resources, we also recommend the recruitment of experts in the fields of message queues, databases, distributed systems, networking, cloud, and storage.

Growth and capacity planning

An important consideration in running at massive scale is projecting growth and utilization trends in order to plan capital expenditures for the short and long term. Gather utilization meters for compute, network, and storage, along with historical records of these meters. While securing major anchor projects can lead to rapid jumps in the utilization rates of all resources, the steady adoption of the cloud inside an organization or by consumers in a public offering also creates a steady trend of increased utilization.

Skills and training

Projecting growth for storage, networking, and compute is only one aspect of a growth plan for running OpenStack at massive scale. Growing and nurturing development and operational staff is an additional consideration. Sending team members to OpenStack conferences, meetup events, and encouraging active participation in the mailing lists and committees is a very important way to maintain skills and forge relationships in the community. For a list of OpenStack training providers in the marketplace, see: http://www.openstack.org/marketplace/training/.