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 . Basically are the pipes big enough to handle the generated workload. But bandwidth is only part of the story, we also need to ensure latency is low. Why, well we’re going to explore that together in this post!
Network Latency Defined
First, let’s define network latency. It’s how long it takes for a piece of information to move from source to destination. In computer networks, latency is often measured in milliseconds, sometimes microseconds on really fast networks. The most common way we measure network latency is with ping. The measurement ping provides measures from the time the ICMP request is send until the time it was replied to. This is how long it takes to move a piece of information from source to destination. But, the size of the data sent by default is only 64 bytes…that’s not very much data. So really ping isn’t a good way to measure latency for data intensive applications. As you add more data to the transmission, your latency will increase due to fact that the payload being transmitted is larger and those bytes have to be placed on the wire and read from the wire on the other side. This all contributes to your network latency. So we really want to measure what our network latency is with our data transmission size.
server0:~ demo$ ping 192.168.1.1
PING 192.168.1.1 (192.168.1.1): 56 data bytes
64 bytes from 192.168.1.1: icmp_seq=0 ttl=64 time=0.072 ms
Network Latency and Availability Groups
Now let’s talk about Availability Group replication and network latency. Availability Groups replicate data over your network using Database Mirroring Endpoints which are TCP sockets used to move data between the primary and it’s replicas. When designing Availability Groups, we often think about things in terms of bandwidth…how much data do I need to move between my replicas. But there’s another design factor your need to consider, network latency. Why? Hint, it’s not going to have anything to do with synchronous availability mode and HADR_SYNC_COMMIT waits. Let’s talk about some fundamentals of TCP for a second.
How TCP Moves Data
The unit of transfer in TCP is called a TCP Segment. TCP requires positive acknowledgement. This means each segment sent, must be acknowledged by the receiver by sending an acknowledgement back to the sender confirming receipt of the segment. From that acknowledgement, TCP tracks how long it takes for a receiver to acknowledge each segment. How long? That’s where network latency comes in…acknowledgements will take at least as long as your network’s latency.
Now if TCP waited for each and every TCP segment to be acknowledged before sending the next segment, our system would never fully realize the network link’s capacity. We’d only consume the bandwidth of one segment at a time, which isn’t very much. To overcome this, TCP has a concept called “Congestion Window” what this means is that TCP can have several unacknowledged segments in flight at a point in time and thus consume more of our network connection’s capacity. The number of unacknowledged segments in-flight depends on our network’s conditions, specifically latency and reliability. If our network latency is high…TCP will reduce the number of segments in the Congestion Window. Which means our effective bandwidth utilization will be low. If the network latency is low, TCP will increase the number of unacknowledged segments in our Congestion Window and our effective bandwidth utilization will be high. If the link isn’t very reliable TCP will decrease the Congestion Window’s size in response to unacknowledged segments, i.e. “dropped packets” so if your network line is dropping packets for some reason…expect a reduction in throughput. The Congestion Window is also variable, as conditions change TCP will increase and decrease based on changing network conditions.
Determining your maximum throughput is pretty easy, check out this calculator here. Enter your physical link bandwidth, your round trip latency time, and the size of your TCP Window and you’ll get the maximum throughput of a single TCP stream, in other words…how fast a single TCP connection and transmit data.
Here’s a practical example, if you have a 1Gb link to your DR site and it has 40ms of latency a single TCP stream will only use 13Mb/sec. Wow…huh? CIOs everywhere just cringed reading that.
Now this is just the maximum for a single TCP stream, we can of course potentially have multiple streams sending, In AGs each database mirroring endpoint uses a TCP stream between the primary and each secondary replica in a standard Availability Group (not Distributed)
How Does Network Latency Impact My Availability Group’s Availability?
- Effective bandwidth can decrease – As network latency increases, effective bandwidth decreases…this means our transaction log throughput is reduced.
- Availability Group Flow Control – AGs track the number of unacknowledged messages sent from primary to secondary and if this gets too high the primary will enter flow control mode and will slow down or stop sending messages to the secondary. What can cause the number of unacknowledged AG messages to increase…network latency. A secondary can initialize flow control too, if it’s experiencing resource contention, it will message the primary and say slow down.
In both of these cases our ability to move transaction log between replicas is reduced due to network latency and this can impact availability. If you want to know more about how AGs move data check out this post and this one. Also it’s important to note, these issues are present regardless of AG availability mode. Synchronous-commit or asynchronous-commt this will impact your replication latency. In fact this just doesn’t apply to AGs, it’s ANY single TCP stream.
Where do we go from here?
Well, if you’re designing or operating high availability systems using Availability Groups, make sure you understand your network infrastructure and its performance characteristics. If you have AG replicas in a remote data center and it’s across a high latency link…test your workload to ensure you’re getting the throughput you need for your transaction log volume. You may have to tune your TCP settings on your operating system to better handle high latency connections or even have to make network changes to support your workload.
If you want to dive deeper into how TCP works check out my Pluralsight course – LFCE: Advanced Linux Networking. While it’s not a SQL Server course, the TCP concepts are the same.
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