In this blog post, we’re going to work on deploying a SQL Server Availability Group in a Kubernetes Cluster in on-premises virtual machines. I’m going to walk you through the process as it’s documented by Microsoft at this link [here]. This document is very good but only shows you how to do it in Azure, we’re going to do it in VMs. I’m going to follow Microsoft’s documentation as much as possible, deviating only when necessary for on-premises deployments.
I’m proud to announce that I will be speaking at SQL Saturday Pensacola on June 3rd 2017! Check out the amazing schedule! If you don’t know what SQLSaturday is, it’s a whole day of free SQL Server training available to you at no cost! If you haven’t been to a SQLSaturday, what are you waiting for! Sign up now! My presentation is **“Designing High Availability Database Systems using AlwaysOn Availability Groups” **
Availability Groups are a fantastic way to provide high availability and disaster recovery for your databases, but it isn’t exactly the easiest thing in the world to pull off correctly. To do it right there’s a lot of planning and effort that goes into your Availability Group topology. The funny thing about AGs is as hard as they are to plan…they’re pretty easy to implement…but sometimes things can go wrong. In this post I’m going to show you how to look into things when creating your AGs fails.
Proactive Reporting for SQL Server If you’re a return reader of this blog you know I write often about monitoring and performance of Availability Groups. I’m a very big proponent of using monitoring techniques to ensure you’re meeting your service level agreements in terms of recovery time objective and recovery point objective. In my in person training sessions on “Performance Monitoring AlwaysOn Availability Groups”, I emphasize the need for knowing what your system’s baseline for healthy replication and knowing when your system deviates from that baseline.
When designing Availability Group systems one of the first pieces of information I ask clients for is how much transaction log their databases generate. *Roughly*, this is going to account for how much data needs to move between their Availability Group Replicas. With that number we can start working towards the infrastructure requirements for their Availability Group system. I do this because I want to ensure the network has a sufficient amount of bandwidth to move the transaction log generated between all the replicas .
SQL 2014 Service Pack 2 was recently released by Microsoft and there is a ton of great new features and enhancements in this release.This isn’t just a collection of bug fixes…there’s some serious value in this Service Pack. Check out the full list here. One of the key things added in this Service Pack is an enhancement of the Extended Events for AlwaysOn Availability Group replication. Why are the new Availability Group Extended Event interesting?
In my opinion one of the key features of SQL Server 2016 is the rebuilt and optimized log redo mechanism for AlwaysOn Availability Groups. Check out the many new AG features here. Check out my posts here and here to learn about how Availability Groups move data. Early last week I was conducting a load test using SQL Server 2016 and wanted to compare the performance of the log redo thread with that of SQL Server 2014.
In previous posts here and here we discussed AlwaysOn Availability Group replication latency and monitoring concepts, specifically the importance of monitoring the send_queue and redo_queue. In this post I’m going to show you a technique for monitoring Availability Group replication latency with Redgate SQL Monitor and its Custom Metric functionality. Here’s the rub, monitoring AGs is a little interesting for the following reasons We’re interested in trending and monitoring and that isn’t built into SQL Server or SSMS’s AlwaysOn Dashboard.
AlwaysOn Availability Groups have made a big splash in the SQL world and are quickly becoming the HA and DR technology of choice for many SQL Server environments. Crucial to their success is the ability to move data between the replicas in the Availability Group quickly and efficiently. In the previous [post] we discussed design concepts for offloaded backups in AlwaysOn Availability Groups, specifically we focused on how data is moved between AGs and the potential impact on backups and recovery.
AlwaysOn Availability Groups made their initial appearance in SQL 2012 and have generated a lot of buzz, HA and DR in one! Even with AGs, still integral to your DR strategy are backups and with AGs you’re given the option to offload backups to a secondary replica. In this blog we’re going to talk about offloaded log backups the potential impact to your databases’ recoverability under certain conditions, we’ll begin with some preliminaries on data movement in AGs.