Optimizing compute resource allocation to achieve performance goals while controlling costs can be a challenging balance to strike especially for database workloads with complex usage patterns. To help address these challenges, we are pleased to announce the preview of Azure SQL Database serverless. SQL Database serverless (preview) is a new compute tier that optimizes price-performance and simplifies performance management for databases with intermittent and unpredictable usage. Line-of-business applications, dev/test databases, content management and e-commerce systems are just some examples across a range of applications that often fit the usage pattern ideal for SQL Database serverless. SQL Database serverless is also well-suited for new applications with compute sizing uncertainty or workloads requiring frequent rescaling in order to reduce costs. The serverless compute tier enjoys all the fully managed, built-in intelligence benefits of SQL Database and helps accelerate application development, minimize operational complexity, and lower total costs.
SQL Database serverless automatically scales compute for single databases based on workload demand and bills for compute used per second. Serverless contrasts with the provisioned compute tier in SQL Database which allocates a fixed amount of compute resources for a fixed price and is billed per hour. Over short time scales, provisioned compute databases must either over-provision resources at a cost in order to accommodate peak usage or under-provision and risk poor performance. Over longer time scales, provisioned compute databases can be rescaled, but this solution may require predicting usage patterns or writing custom logic to trigger rescaling operations based on a schedule or performance metrics. This adds to development and operational complexity. In serverless, compute scaling within configurable limits is managed by the service to continuously right-size resources. Serverless also provides an option to automatically pause the database during inactive usage periods and automatically resume when activity returns.
In SQL Database serverless, compute is only billed based on the amount of CPU and memory used per second. While the database is paused only storage is billed, providing additional price optimization benefit.
For example, consider a line-of-business application or a dev/test database that is idle at night, but needs multi-core bursting headroom throughout the day. Suppose the application is using a serverless database configured to allow auto-pausing and auto-scaling up to 4 vcores and has the following usage pattern over a 24 hour period:
Compute auto-scaling
SQL Database serverless automatically scales compute for single databases based on workload demand and bills for compute used per second. Serverless contrasts with the provisioned compute tier in SQL Database which allocates a fixed amount of compute resources for a fixed price and is billed per hour. Over short time scales, provisioned compute databases must either over-provision resources at a cost in order to accommodate peak usage or under-provision and risk poor performance. Over longer time scales, provisioned compute databases can be rescaled, but this solution may require predicting usage patterns or writing custom logic to trigger rescaling operations based on a schedule or performance metrics. This adds to development and operational complexity. In serverless, compute scaling within configurable limits is managed by the service to continuously right-size resources. Serverless also provides an option to automatically pause the database during inactive usage periods and automatically resume when activity returns.
Pay only for compute used
In SQL Database serverless, compute is only billed based on the amount of CPU and memory used per second. While the database is paused only storage is billed, providing additional price optimization benefit.
For example, consider a line-of-business application or a dev/test database that is idle at night, but needs multi-core bursting headroom throughout the day. Suppose the application is using a serverless database configured to allow auto-pausing and auto-scaling up to 4 vcores and has the following usage pattern over a 24 hour period:
As can be seen, database usage corresponds to the amount of compute billed which is measured in units of vcore seconds and sums to around 46k vcore seconds over the 24 hour period. Suppose the compute unit price for the serverless database is around $0.000073/vcore/second. Then the compute bill for this one day period is just under $3.40. This is calculated by multiplying the compute unit price by the total number of vcore seconds accumulated. During this time period, the database was auto-paused while idle and enjoyed the benefit of bursting episodes up to 80 percent of 4 vcores without customer intervention. In this example, the price savings using serverless is significant compared to a provisioned compute database configured with the same 4 vcore limit.
Price-performance trade-offs
When using SQL Database serverless there are price-performance trade-offs to consider. These trade-offs are related to the compute unit price and the impact on application performance due to compute warm-up after periods of low or idle usage.
Compute unit price
The compute unit price is higher for a serverless database than for a provisioned compute database since serverless is optimized for workloads with intermittent usage patterns. If CPU or memory usage is high enough and sustained for long enough, then the provisioned compute tier may be less expensive.
Compute warm-up after low usage
While a serverless database is online, memory is gradually reclaimed if CPU or memory usage is low enough for long enough. When workload activity returns, disk IO may be required to rehydrate data pages into the SQL buffer pool or query plans may need to be recompiled. This memory management policy to reclaim cache based on low usage is unique to SQL Database serverless and done to control customer costs, but can impact performance. Memory reclamation based on low usage does not occur in the provisioned compute tier for single databases or elastic pools where this kind of impact can be avoided.
Compute warm-up after pausing
The latency to pause and resume a serverless database is usually around one minute or less during which time the database is offline. After the database is resumed, memory caches need to be rehydrated which adds additional latency before optimal performance conditions return. The idle period that must elapse before auto-pausing occurs can be configured to compensate for this performance impact. Alternatively, auto-pausing can be disabled for workloads sensitive to this impact and still benefit from auto-scaling. Compute minimums are billed while the database is online regardless of usage, and so disabling auto-pausing can increase costs.
Thanks for sharing Very Use ful Blog..
ReplyDeleteAzure DevOps Online Training
Microsoft Azure DevOps Training Courses
Microsoft Azure DevOps online Training in Hyderabad
Microsoft Azure DevOps Training
Azure DevOps Online Training in Hyderabad
ReplyDeleteGreat blog!! Thanks for sharing
Azure DevOps online training
Microsoft Azure DevOps Training
Microsoft Azure DevOps Online Training
Microsoft Azure DevOps training hyderabad
Azure DevOps online training in hyderabad
Thanks for sharing Very Useful Blog
ReplyDeleteAWS Training
AWS Online Training
AWS certification training
Hi, This is a great article. Loved your efforts on it buddy. Thanks for sharing this with us. Azure training.
ReplyDelete