Introduction
502 and 504 errors could be a nuisance for Rockset and our customers. For a lot of customers operating customer-facing purposes on Rockset, availability and uptime are crucial, so even a single 5xx error is trigger for concern. As a cloud service, Rockset deploys code to our manufacturing clusters a number of instances every week, which signifies that any part of our distributed system has to cease and restart with new code in an error-free means.
Not too long ago, we launched into a product high quality push to diagnose and treatment most of the causes of 502 and 504 errors that customers could encounter. It was not instantly apparent what these points had been since our logging appeared to point these error-producing queries didn’t attain our HTTP endpoints. Nevertheless, as product high quality and person expertise are at all times high of thoughts for us, we determined to research this challenge totally to eradicate these errors.
Cluster setup
To diagnose the issue, we first want to know the setup of our cluster. Within the instance above, N1, N2, and N3 are the EC2 cases at the moment in our cluster. P1, P2 and P3 are Kubernetes pods which can be scheduled in these cases. Particularly, P1 and P2 are scheduled in N1, and P3 is scheduled in N2. There are not any pods which can be scheduled in N3.
HTTP requests from the online will first hit our AWS Software Load Balancer (ALB), which can then ahead these requests to our cluster. The companies that obtain these HTTP requests from the ALB are arrange with NodePort sort. What which means is, when a request hits the ALB, it would get routed to a random node, for instance, N3. N3 will then route this request to a pod P3, which may reside in a very completely different node.
We run kube-proxy in iptables mode. This implies the routing described above is finished by way of a part referred to as iptables, which is fairly environment friendly. Our HTTP servers are written in Java utilizing jetty.
With this setup, there are a number of points we uncovered as we investigated the random 502/504 errors.
Connection idle timeout misconfiguration
Connection idle timeout, or keep-alive timeout, is outlined because the period of time after which the connection shall be terminated if there is no such thing as a information. This act of termination will be initiated from each ends of the connection. Within the diagram above, each ALB and P3 can terminate the connection relying on the idle timeout setting. Meaning if one finish has a smaller timeout, it is going to be the one who terminates the connection.
The difficulty lay with the actual fact our HTTP server (P3) had smaller connection idle timeout than the ALB. That meant it was doable that whereas there was an inflight request from ALB to P3, P3 terminates the connection. This can lead to a 502 error as a result of the TCP connection has been closed.
The answer is that the facet that sends the request should be the facet with smaller idle timeout. On this case, it is the ALB. We elevated the idle timeout in Jetty with ServerConnector::setIdleTimeout to repair this challenge.
Draining is just not arrange correctly
The ALB employs HTTP persistent connection when sending HTTP requests to our servers. What which means is the ALB will reuse the TCP connection that was established in earlier HTTP requests in an effort to keep away from the price of TCP handshake.
The difficulty comes when the server (P3 on this case) desires to empty, probably resulting from our periodic code-push, and it doesn’t wish to settle for any extra requests. Nevertheless, the ALB is unaware of this reality due to the NodePort sort of service. Recall that ALB is barely conscious of the node N3, not the pod P3. Meaning the ALB would nonetheless ship requests to N3. Because the TCP connection is reused, these requests would get routed to the draining pod P3. As soon as the draining interval completes, 502s will happen.
One strategy to repair that is to have each response from P3 embrace a particular header, referred to as Connection: shut, when P3 is draining. This header will instruct the ALB to not reuse the previous TCP connections and create new ones as an alternative. On this state of affairs, the brand new connections will not be routed to the draining pods.
One tough half is that the draining interval should be bigger than your service’s readiness probe interval, in order that kube-proxy from different nodes (together with N3) are conscious of P3 draining and replace their iptables guidelines accordingly.
Node abruptly faraway from cluster
When a brand new assortment is created, Rockset employs a mode referred to as bulk-ingest in an effort to conduct an preliminary dump of the supply information into the gathering. This mode is usually very CPU intensive, so we want a particular sort of EC2 machine that’s compute-optimized. Internally, we name these bulk nodes. Since these machines are dearer, we solely spin them up when crucial and terminate after we now not want them. This turned out to trigger 502s as properly.
Bear in mind from earlier sections, requests are routed to a random node within the cluster, together with, on this case, the majority nodes. So when the majority nodes be a part of the cluster, they’re obtainable for receiving and forwarding the requests as properly. When the bulk-ingest is accomplished, we terminate these nodes in an effort to save on prices. The issue is we terminate these nodes too abruptly, closing the connection between this node and the ALB, inflicting the inflight requests to fail and producing 502 errors. We recognized this downside by noticing that the 502 graph aligned with the graph of the variety of bulk nodes at the moment within the system. Each time variety of bulk nodes decreased, 502s occurred.
The repair for us was to make use of AWS lifecycle hooks to gracefully terminate these nodes, by ready for the inflight requests to complete earlier than truly terminating them.
Node is just not able to route requests
Much like the earlier issues, this challenge entails the node simply becoming a member of the cluster and never able to ahead requests. When a node joins the cluster, a number of set-up steps must occur earlier than site visitors can circulation between this new node and different nodes. For instance, kube-proxy on this new node must arrange iptables guidelines. Different nodes must replace the firewall to simply accept the site visitors from the brand new node. These steps are finished asynchronously.
Meaning, the ALB would oftentimes timeout whereas attempting to determine the connection to this new node, as this node would fail to ahead the TCP handshake request to different pods. This may trigger 504 errors.
We recognized this downside by trying on the ALB log from AWS. By inspecting the goal node (the node that ALB determined to ahead the request to), we will see {that a} 504 error occurs when the goal node simply joins the cluster.
There are 2 methods to repair this: delay the node becoming a member of the ALB goal group by a couple of minutes or simply have a static set of nodes for routing. We don’t wish to introduce pointless delays, so we go together with the latter method. We do that by making use of the label alpha.service-controller.kubernetes.io/exclude-balancer=true to the nodes we don’t need the ALB to path to.
Kubernetes bug
Having resolved the problems above, a couple of 502s would nonetheless happen. Understandably, a k8s bug is the very last thing we might consider. Fortunately, a colleague of mine identified this text on a k8s bug inflicting intermittent connection resets, which matched our downside. It is mainly a k8s bug from earlier than model 1.15. The workaround for that is to set ip_conntrack_tcp_be_liberal to keep away from marking packets as INVALID.
echo 1 > /proc/sys/internet/ipv4/netfilter/ip_conntrack_tcp_be_liberal
Conclusion
There will be many causes 502 and 504 errors can occur. Some are unavoidable, attributable to AWS eradicating nodes abruptly or your service OOMing or crashing. On this publish, I describe the problems that may be fastened by way of correct configuration.
Personally, this has been an ideal studying expertise. I realized lots about k8s networking and k8s on the whole. At Rockset, there are numerous comparable challenges, and we’re aggressively hiring. In case you’re , please drop me a message!
