Recommendations from the principles of Green Software Engineering applied to an N-Tier architecture

The N-tier architecture organizes your application into distinct logical layers based on their responsibility. Layers run on a series of physically separated tiers that represent compute resources.

Applying the principles of Green Software Engineering, the following are examples of changes you can make to your N-tier architecture to optimize it for sustainability.

Optimize your network traffic permalink

Reduce the amount of traffic your architecture creates per operation as well as the distance each request and response travels.

  • Consider using caching headers, which allows browser caches and proxy caches to have enough information to confidently cache static assets. Caching static assets at the browser or proxy level allows future requests for those assets to be handled by those caches and reduces network traffic to your application.
  • Consider using a CDN to distribute your application's static assets closer to the source of a request. This distribution of assets reduces the distance all requests for static assets has to travel over the network.
  • Where possible, reduce the size and optimize your bundles and static assets.
    • Consider using compression and decompression for data you transmit over the network. Compression and decompression is usually takes less overall energy than transmitting uncompressed data over the network.

Increase your compute utilization permalink

Update your workload distribution and compute resources so that you use less resources at a higher utilization. This reduces the amount of energy your compute resources spend in an idle state, or using energy without doing work.

  • If using virtual machines for compute resources and they have low utilization, consider reducing the size of those virtual machines to increase utilization. Smaller virtual machines with higher utilization usually use less energy than larger virtual machines with lower utilization given the same workload.
  • Evaluate migrating your workload to a PaaS where possible. Typically, PaaS solutions are sized more appropriately for their workload and can run those workloads at a high utilization on their underlying compute resources.
  • Consider using auto-scaling or burst capabilities for your compute resources over statically allocating compute resources for maximum capacity at all times. These capabilities allow you to increase and decrease your compute resources based on demand while keeping the utilization high on those compute resources.
  • If you have many logical layers in a physical tier, consider increasing your physical tiers and reorganizing where your logical layers run. The increased physical tiers with a more granular organization of logical layers allows you more flexibility to scale the logical layers independently. This flexibility allows you to keep utilization high on your compute resources and avoid idle logical layers.

Optimize your database permalink

Optimizing which database you use as well as how the data is stored can reduce the energy used to run the database as well decrease idle time waiting for queries to complete.

  • Ensure you are using the best database for interacting with your data set. For example, if you are running many relational queries on your data set, a relational database is better suited and likely more efficient to use than NoSQL database.
  • If no single database is designed to handle all the ways you interact with you data set, consider keeping redundant copies of your data in different databases and using each database for the subset of interactions best suited for that database.
  • Consider using index if your database offers it.
  • Consider evaluating and optimizing your queries.
  • Consider using a database cache. In some cases, caching can reduce redundant queries to the database and decrease energy usage by the database, especially for complex or compute-intensive queries.