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Performance

Storage Performance Principles tips​

Efficient Resource Utilization

  • Serverless storage services that are built to scale on demand, such as Amazon S3
  • Auto-scaling of storage resources
  • Utilize virtualization to maximize utilization of resources
  • Utilize resource pooling to minimize workloads
  • Automate processes and create alerts for resource utilization
  • Utilize a streamlined storage architecture.
  • Consolidate hardware to reduce maintenance and power costs
  • Resource usage monitoring system

Efficient Logic, queries

  • Proper indexing of data to improve query performance
  • Database indexes to optimize query performance
  • Stored procedures to improve query performance
  • Multi-threading or parallel processing to improve query performance
  • Utilize query optimization techniques such as query rewrite and query optimization tools
  • Query optimization techniques like query rewriting, query optimization and query caching
  • Database query tuning tools like EXPLAIN PLAN or SQL Profiler to identify inefficient logic
  • Serverless compute services like AWS Lambda or Azure Functions to implement custom logic

Efficient Storage, read/write

  • Solid-state drive (SSD) technology to improve storage performance
  • Utilize RAID technology to improve storage performance
  • Caching techniques such as read and write ahead to reduce I/O operations
  • Compression techniques to reduce storage space
  • Services that are optimized for read/write performance such as Amazon S3 or Azure Blob Storage
  • Storage services that use compression and deduplication techniques to reduce storage costs
  • Built-in replication for redundancy and fault tolerance
  • Amazon ElastiCache or Azure Redis Cache to reduce read/write latency

Concurrency (Hardware/Software)

  • Distributed storage to improve concurrency
  • Multi-threaded storage transfers to improve concurrency
  • Message queues, semaphores, and locks to improve concurrency
  • Storage load balancing technologies to improve concurrency
  • Task scheduling system
  • Intelligent thread pooling system
  • Intelligent task synchronization system
  • Distributed computing frameworks such as Hadoop or Spark to process large datasets in parallel
  • Serverless compute services such as AWS Lambda or Azure Functions to run tasks in parallel
  • Messaging services such as Amazon SQS or Azure Service Bus to queue requests for asynchronous processing

Caching (Hardware/Software)

  • Object storage services such as Amazon S3 or Azure Blob Storage to enable caching of objects
  • Hardware-based caching like write-back caching
  • Software-based caching like memcached or Redis
  • Application-level caching techniques such as object caching
  • Content delivery networks (CDNs) to improve caching performance
  • Intelligent caching system
  • Eviction policy to ensure data is being cached in the most efficient manner
  • Ensure queries are being cached
  • Cache audit system

Capacity

  • Object storage services such as Amazon S3 or Azure Blob Storage to store unstructured data
  • Use cloud storage to increase capacity
  • Utilize disk striping or disk mirroring to increase capacity
  • Use disk replication or disk pooling to increase capacity
  • Distributed file systems such as HDFS or GlusterFS to store and manage large amounts of data
  • Disk striping with parity to increase capacity and improve data availability
  • Utilize an intelligent capacity planning system to ensure resources are being provisioned efficiently
  • Intelligent storage monitoring system to ensure data is being stored in the most efficient manner
  • Capacity audit system
  • Intelligent capacity forecasting system
  • Use a capacity optimization system

Performance Tips - AWS​

  • Use Amazon EBS-optimized instances.
  • Enable EC2 instance I/O credits.
  • Use multiple small I/O operations instead of fewer large I/O operations.
  • Striped EBS volumes for increased IOPS.
  • Consider using provisioned IOPS SSDs.

S3 latency/speed tips​

  • Use Amazon S3 Transfer Acceleration for uploads.
  • Use Amazon S3 multipart uploads for large objects.
  • Use Amazon CloudFront for content delivery.
  • Use S3 Transfer Acceleration with Amazon CloudFront.
  • Use AWS Snowball for large data transfers.
  • Use AWS Snowball Edge for local data processing and transfer.
  • Use AWS Direct Connect to reduce network latency and improve data transfer speeds.
  • Use Amazon S3 Transfer Manager for automated, large-scale data transfers.

S3 cost optimization tips​

  • Use Amazon S3 Intelligent-Tiering for data with unknown or changing access patterns..
  • Use Amazon S3 object tagging for better organization and cost optimization.
  • Enable Amazon S3 Transfer Acceleration for faster uploads.
  • Consider using Amazon S3 One Zone for infrequently accessed data.
  • Consider using Amazon S3 Lifecycle policies to transition data to other storage classes.

Organization and security tips​

  • Use Amazon S3 Inventory to track changes in your objects.
  • Use Amazon S3 Select to retrieve only the data you need.
  • Use Amazon S3 Lifecycle to automatically move objects to the appropriate storage class.
  • Use Amazon S3 Select and S3 Glacier Select for efficient data retrieval.
  • Use Amazon S3 presigned URLs for secure data access.
  • Use AWS Key Management Service (KMS) for encryption of S3 data.
  • Consider using Amazon S3 storage class analysis to optimize storage costs.
  • Use Amazon S3 batch operations to process large numbers of objects.