TACTIC: a Scalable Solution

A data management system to grow along with your expanding data needs TACTIC software meets the complex content demands of today’s large-scale production environment:

  • Based on existing web technologies, it is easy to maintain and scale

  • Easy to load-balance and scale across cores and across multiple machines

What Makes TACTIC Scalable?

The TACTIC platform uses web technologies in its underlying architecture. As proven by many popular web sites today, web technologies are able to scale to a large number of users—to levels far beyond the size of any large installation today requiring TACTIC.

The TACTIC user interface and its API (Application Programmer Interface) are both built on web technologies. A web server controls as the user front end, and accesses a back-end database. Web servers can handle high volumes, so scalability is not an issue — especially for the relatively manageable volume seen in even the largest of digital productions.

Web server technology

TACTIC uses a web server to deliver static content to users, who are able to access TACTIC over the web. Web servers are capable of delivering enormous numbers of requests, and will remain stable during heavy loads. Web servers by definition are the most efficient vehicles for web delivery, and TACTIC technology is optimized to take advantage of this technology for fast execution and scalability.

Leading database technology

TACTIC supports a variety of databases, including PostgreSQL, MySQL, and SQLServer.

Today’s databases coupled with today’s hardware are sufficiently powerful to handle any of today’s production needs. The largest of digital productions cannot come close to exceeding the data limits of a typical database.

Optimized requests

With digital productions, the amount of data required is seldom the issue. Rather, bottlenecks are typically caused by complex requests slowing down database response time. Digital productions tend to use deeply nested and enormously complex relationships between various pieces of data. It is this complexity that tends to slow down applications that try to parse this data in a meaningful human way, creating complex requests that slow down database response.

TACTIC is designed from the ground up to master the complexities of digital productions. For every request, it builds a unique object-relational mapper specifically designed for the needs of high volume, large scale digital production asset management solutions.

TACTIC is flexible enough to handle the complex relationships between any part of the production pipeline, and has proven itself in large-scale projects using extremely complex data.

Easy code maintenance

The Python programming language is used for TACTIC application development. Python has many strengths that contribute to ease of maintenance (courtesy of www.python.org):

  • clear, readable syntax

  • strong introspection capabilities

  • intuitive object orientation

  • natural expression of procedural code

  • full modularity supporting hierarchical packages

  • exception-based error handling

  • very high-level dynamic data types

  • extensive standard libraries and third party modules for virtually every task

  • extensions and modules easily written in C, C++ (or Java for Jython, or .NET languages for IronPython)

  • embeddable within applications as a scripting interface

Load balancing

Load balancing the distribution of requests across TACTIC processes is possible across cores and across multiple machines, and enables TACTIC to scale to large enterprise environments.

(For details and examples, see TACTIC Scalable Configuration Examples.)

Segregating services

The various TACTIC services can be segregated to run independently of each other. This allows important services, such as user interface requests, to access their own resources and not be slowed down by other more resource-intensive services such as render farms.

(For details and examples, see Scalable TACTIC Deployments.)

Types of Scalability

There are several types of scalability that are considerations with the use of Python as the TACTIC programming language:

  • Code scalability: TACTIC contains thousands of classes and many hundreds of thousands of lines of code which are facilitated by use of the Python language. There has been no reason to believe that the code base cannot continue to scale to meet software needs for the foreseeable future.

  • Memory scalability: Python is known for large memory requirements when compared to other languages, but the required memory for TACTIC code is much smaller than that found on typical servers, and has seldom been an issue.

  • Performance scalability: Python’s GIL (Global Interpreter Lock) limits Python’s scalability across multiple threads. This limitation has been long discussed in newsgroups, with the general consensus that scalability is achieved much more easily by load-balancing across processes rather than across threads. TACTIC enables easy load balancing across processes to achieve full linear scalability.

  • Maintenance scalability: Clean and clear syntax makes it easy to refactor and maintain code over the long term. Experience has shown that our code base is very accessible to new developers, providing confidence that code base knowledge can be maintained over the years.

Overall, very few limitations with the Python language itself have been encountered and have easily circumvented its lack of scalability across multiple threads by optimizing proper load balancing across processes.

Additional Scalability Considerations


TACTIC has been designed to be highly stable even under extremely heavy stress. It has been tested and tuned on several projects in environments of high stress and high load and has been proven to run under duress without going down.

As with any piece of software, there is always a point a failure—there are a number of legitimate reasons for a TACTIC server becoming unresponsive or even going down:

  • network cutoff

  • power failure

  • physical memory failure

  • overloaded requests for the available resources

For projects that require high availability even in the event of catastrophic failure, there are a number of hardware solutions to provide failover should the primary resource fail. These hardware solutions will instantly redirect requests to a redundant resource, thereby providing continuous service to the users.

Memory requirements

Each available process will use a certain amount of memory, so a balance must be struck between the number of processes and the size of the complete in-memory TACTIC footprint on the server. In other words, adding more processes may or may not increase the availability of TACTIC if memory is an issue. If processes start running into swap space, performance will be severely affected.

As memory usage becomes an issue, the choice will be to load balance over multiple machines (see Scalable TACTIC Deployments).