Cases36 cases

29 to 33 of 36

1. IL-0033 Uneven load across kube-dns pods and a DNS packets-per-second limit pushed service latency to 20 seconds

   Airbnb2019

   Symptoms

   On May 10 the latency graphs of several services showed a few spikes of up to about one second, then latency climbed to five seconds and then to 20 seconds, and it stayed there for a long time. The same pattern appeared on many services, not just one.

   High latencyIntermittent timeoutsLoad imbalanceDNS resolution failures

   Trigger

   Several services sent a high volume of external DNS queries, all of which went through kube-dns.

   Root cause

   Capacity exhaustion

   Component

   kube-dnskube-proxyClient-side DNS resolver and cache

   Contributing factor

   Unreviewed defaults

   Detection

   Latency graphs of several services showed the rise; engineers then looked at load per kube-dns pod.

   Lessons

   By default a pod discovers DNS through the kube-dns cluster IP and uses the ClusterFirst policy, so even external lookups go through kube-dns. If a pod does not need cluster DNS, set its dnsPolicy to Default or None. Check the DNS policy early and often. iptables picks backends at random and is not a load balancer, so pods behind a cluster IP, kube-dns included, can carry very different loads.

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2. IL-0189 A JVM service moved from EC2 to Kubernetes answered up to ten times slower because KIAM's 15-minute credentials made the AWS Java SDK fetch new credentials on every request

   Adevinta2019

   Symptoms

   After a Spring-based JVM microservice was deployed to Kubernetes and part of production traffic was routed to it, request latency there was up to 10 times higher than on EC2. Behind the NGINX ingress controller the backend took 100 to 200 ms to answer, where the EC2 instances took about 20 ms.

   High latency

   Trigger

   Moving the service onto the Kubernetes platform, where KIAM served IAM credentials to pods with its default 15-minute lifetime.

   Root cause

   Configuration change

   Component

   Credential broker for pods

   Contributing factor

   Unreviewed defaults

   Detection

   After part of production traffic was routed to the Kubernetes deployment, its request latency was seen to be up to 10 times higher than on EC2.

   Remediation

   • reconfigured KIAM to request IAM credentials with a longer expiration period

   Lessons

   KIAM's short credential lifetime for pods and the AWS Java SDK's eager refresh of any credential within 15 minutes of expiry are each reasonable, but together they force a metadata round trip on every request. When latency rises after a move to Kubernetes, the cause is often the interaction of components that never ran together before rather than Kubernetes itself. Here a packet capture from inside the container found what latency metrics and DNS tests had not.

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3. IL-0057 Higher p99 latency after moving a reverse proxy to EKS, from outgoing connections delayed by a SNAT conntrack race

   Prezi2019

   Symptoms

   Prometheus alerts fired on tail latency: from 7/24, the p99 response time of a few services went up after Prezi moved its Nginx-based reverse proxy, smartgateway, from dedicated Elastic Beanstalk machines onto shared Kubernetes worker nodes. The bump affected only the tail, so the earlier monitoring of average response times would most certainly have missed it.

   High latencyIntermittent timeouts

   Trigger

   Moving the reverse proxy onto shared EKS worker nodes, where its outgoing connections went through source NAT on the node and some SYN packets were dropped by a race in Netfilter's conntrack.

   Root cause

   DNS or network fault

   Component

   conntrack tableAWS VPC CNILinux kernelNode operating system image

   Contributing factor

   Unreviewed defaultsUnpatched known bug

   Detection

   Prometheus alerts on p99 latency fired after the reverse proxy migration.

   Remediation

   • added AWS X-Ray tracing and an $upstream_connect_time trace attribute to locate the delay
   • ran more pods of the service on more nodes, which reduced but did not end the delays
   • set AWS_VPC_K8S_CNI_EXTERNALSNAT=true on the AWS VPC CNI to turn off SNAT on the nodes

   Lessons

   Alerting on tail latency instead of averages caught a problem that would otherwise have gone unnoticed, and tracing turned a vague slowdown into a measured connect delay. Delays of exactly 1 or 3 seconds on new outgoing connections point to dropped SYN packets, and on EKS the SNAT done by the VPC CNI is where to look.

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4. IL-0047 Pod-to-pod requests delayed by 5, 10 or 15 seconds because of DNS lookups lost to a conntrack race

   MindTickle2019

   Symptoms

   Pod-to-pod calls were intermittently slow and the web application felt slow overall. A request that pod A sent at time x reached pod B at x + 5s, x + 10s or x + 15s, always a multiple of five seconds.

   Intermittent timeoutsHigh latencyDNS resolution failures

   Trigger

   The C library resolver sent the A and AAAA queries for each lookup on the same port; where DNAT or SNAT translation takes place, a race condition in conntrack sometimes left one of the queries unanswered, and the resolver waited 5 seconds before retrying.

   Root cause

   DNS or network fault

   Component

   conntrack tableClient-side DNS resolver and cacheLinux kernel

   Contributing factor

   Unreviewed defaults

   Detection

   The team noticed intermittent delays in pod-to-pod calls and slowness in the web application, and that the delays were always multiples of five seconds.

   Remediation

   • added the single-request-reopen option to dnsConfig in the deployment specs
   • set GRPC_DNS_RESOLVER=native in the Dockerfiles of gRPC applications so they used the libc resolver
   • checked with tcpdump port 53 that A and AAAA queries left from different ports

   Lessons

   Delays that are exact multiples of five seconds point to DNS lookups being retried after the resolver's 5-second timeout. A resolver option set in the pod spec only helps processes that use the libc resolver; runtimes with their own resolver, such as gRPC with c-ares, ignore it.

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5. IL-0011 HAProxy ingress piled requests onto the same pods because a Go template visited the backend map in sorted pod IP order

   Skyscanner2019

   Symptoms

   On a Sunday, a team using one of Skyscanner's Kubernetes clusters manually paged the out-of-hours Kubernetes support because their service showed elevated latency, worst at the p90 and maximum levels.

   High latencyLoad imbalanceOOMKilledIntermittent connection failures

   Trigger

   Upgrading the HAProxy ingress controller to v0.6 and going back from Service virtual IPs to individual pod IPs as backends, on the understanding that the sort-backends flag introduced in v0.5, false by default, meant backends were randomly shuffled.

   Root cause

   Software defect

   Component

   Ingress controllerHAProxyConfiguration templating

   Contributing factor

   Unrepresentative stagingUnverified assumptionIgnored early signal

   Detection

   A cluster user manually paged the out-of-hours Kubernetes support about elevated latency; Prometheus queries then showed the uneven request distribution across pods.

   Remediation

   • switched the affected service from pod IPs back to the Service virtual IP through a config change in the internal deployment tool Slingshot
   • patched the controller to keep each backend's servers in an insertion-ordered slice and changed the template to iterate over that slice
   • tested the patch in sandbox clusters and rolled it out to the production clusters

   Action items

   • Run the internal controller patch in production and return to pod IPs as the default backends
   • Raise the problem upstream with a GitHub issue and pull request
   • Test changes to cluster components against the specific behaviour and conditions that matter

   Lessons

   The team already knew that sorted backends cause hot-podding and still did not test the new flag well enough to see that it did not work; changes to cluster components need tests aimed at the exact behaviour that matters, under conditions like production. A keyword can behave differently in different parts of a language: range over a map is unordered in Go code but sorted in text/template. A small cluster component can do outsized harm to every user of the cluster and, in the end, to customers.

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