PASS Summit 13, Day 1 keynote by Quentin Clarke and we’re hearing about “redefiniing mission critical in the cloud”.
With a move to the Windows Azure cloud comes the promise of capacity on demand, automatic HA, backups, patching and so on, as well as passing responsibility to MS for managing hardware, upgrades and so on. However, for many databases and applications the best route to the cloud is not necessarily obvious. For most, the path of least resistance is IaaS – SQL Server in a Azure VM. It removes the hardware burden but you still have to manage your databases and implementing HA for SQL Server is your responsibility. Also, scaling up comes at quite a cost – the biggest VM (8 CPU cores, 56 GB RAM, 16 1TB drives with 500 IOPS each) weighs in at over over $4500 per month.
With PaaS, in the form of Windows SQL Database, you get a “3-copies replica set” so HA comes out-of the box, and removes the majority of the administration burden, but you are moving your database into a very different environment. For a start, it’s a shared environment, with other customers using the same compute nodes in the cluster, and potentially even sharing the same database (multi-tenancy). Unless you pay for SQL DB Premium edition, the resources available for your workload will depends on how nicely others “play” in the shared environment. You’ll potentially need to do a lot of tuning, and application rewriting to avoid throttling issues, optimising application-database communication to deal with increased latency between the two, and so on. You’ll need aggressive application caching. You’ll also need retry logic and to deal with (expected) node failure and the need to reconnect.
In Tuesday’s PASS Summit pre-con from the SQLCAT team, they spent a lot of time covering some of the telemetric techniques (collect into Azure storage the necessary monitoring data) to perform capacity planning, work out the hotspots and bottlenecks in your cloud applications. Tools like WAD (Windows Azure Diagnostics), performance counters SQL Database DMVs, and others, will be essential.
Of course, to truly exploit the vast horizontal scaling that is available from the existence of thousands of compute nodes, you’ll also need to need to consider how to “shard” your data so Azure can move it between nodes at will.
Finding the right path to the Cloud isn’t easy, but it’s coming. I spoke to people one year ago who saw no real benefit in trying to move their infrastructure and databases to the cloud, but now at their company, it’s the conversation that won’t go away.