confluent-kafka-dotnet is derived from Andreas Heider's rdkafka-dotnet. by confluent-kafka-dotnet. When there is no Blockade cluster up and running I run the following commands: After that, to recreate the cluster between each scenario I run: In this scenario well send 100000 messages with acks=0, meaning that the client does not require any acknowledgements back. librdkafka, a finely tuned C to avoid stop-the-world rebalancing operations and unnecessary reloading of state when you add or remove processing nodes. This should be similar to scenario 4 with full isolation of the leader. Isolating a Kafka leader node should lead to greater message loss than a downed node as the leader does not realize it cannot talk to Zookeeper until after it has already acknowledged messages during a short period, a few seconds. The fail-over will occur and the client will detect the changes within a minute and start publishing to the new leader. (kafka.zookeeper.ZooKeeperClient). We get them right in one place (librdkafka) and leverage this work use the Produce method instead: The Web example demonstrates how to integrate My on-premise Sentry server installed on an Ubuntu 18.04.5 machine running through apache SSL proxy does receive events and replies to all HTTPS requests with code 200 and an event ID in JSON response body, but the dashboard wont show any event. RAM : 4GB total, 1.9GB used So we see that a completely isolated node is worse than a node failure with acks=1, as it takes a while for the broker to detect that it has lost its Zookeeper connection. Wed also need to know about which version of Sentry you are using. client. We see that we lost 6764 messages that the producer had sent. Prints out the broker id of the leader at the start and when it changes. Schema Registry's REST API. Its a Microsoft Azure VM. Thanks Andreas! Again we can combine the slow-producer.py and the docker logs to get confirmation of what is happening. and confluent-kafka-go). 4GB should be enough for light loads but I dont know your load. This is due to a combination of a connection failure and a leader fail-over. Previous Leader Epoch was: 0 (kafka.cluster.Partition). Next we kick off the publishing of the messages. Once publishing is complete we run a script to get the current high watermark of the topic. (kafka.controller.KafkaController), [2018-09-16 19:20:26,148] INFO [RequestSendThread controllerId=1] Controller 1 connected to kafka2:19093 (id: 2 rack: null) for sending state change requests (kafka.controller.RequestSendThread), [2018-09-16 19:20:26,171] INFO [RequestSendThread controllerId=1] Controller 1 connected to kafka1:19092 (id: 1 rack: null) for sending state change requests (kafka.controller.RequestSendThread), [2018-09-16 19:20:26,180] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions test1-0 (kafka.server.ReplicaFetcherManager), [2018-09-16 19:20:26,181] INFO [Partition test1-0 broker=1] test1-0 starts at Leader Epoch 1 from offset 20. You can see which commit a particular build number corresponds to by looking at the for example in the context of handling web requests. Chaos testing Apache Kafka with Blockade, Docker, Python and Bash. They have many similarities. In our case we dont want duplicates interfering with the numbers. In this scenario I send 100000 messages at roughly a rate of 10000 second and at about the 30000 message mark I isolate the leader using Blockade. Key/Value store (similar to RocksDb) to materialize working state that may be larger than available memory, and incremental rebalancing So when the followers are still in the ISR, well not get an ack because theyll never confirm receipt and once the attempt to shrink the ISR has occurred no more writes will be accepted. We see that the new leader is kafka1 and that we did not lose a message. Then we get the long period with nothing, followed by thousands of Local: Message timed out errors.In the end we get 37640 acknowledged messages. available via the Error and ConsumeResult fields. 2016-2019 Confluent Inc. confluent-kafka-dotnet has no affiliation with and is not endorsed by We still have more failures to introduce to the cluster that well cover in part 2. In the end you see that still no acknowledged messages were lost, though the number of acknowledged messages was very low. Lets run it again with the ten concurrent producers that will attempt to send 1 million messages in total. Well repeat the same actions as in scenario 6 except well set acks to all. Whats kafka ? [2018-09-15 19:20:31,244] INFO Opening socket connection to server zk1/172.17.0.2:2181. will be thrown. [2018-09-16 19:20:26,024] INFO [Controller id=1] Newly added brokers: , deleted brokers: 3, all live brokers: 1,2 (kafka.controller.KafkaController), [2018-09-16 19:20:26,025] INFO [RequestSendThread controllerId=1] Shutting down (kafka.controller.RequestSendThread), [2018-09-16 19:20:26,029] INFO [RequestSendThread controllerId=1] Stopped (kafka.controller.RequestSendThread), [2018-09-16 19:20:26,031] INFO [RequestSendThread controllerId=1] Shutdown completed (kafka.controller.RequestSendThread), [2018-09-16 19:20:26,069] INFO [Controller id=1] Broker failure callback for 3 (kafka.controller.KafkaController), [2018-09-16 19:20:26,074] INFO [Controller id=1] Removed ArrayBuffer() from list of shutting down brokers. Those were the messages sent during this brief 15 second window where kafka1 was still accepting writes even though a new leader had been elected. Future proof - Confluent, founded by the I have a slow-producer.py script that publishes one message per second and prints out more information. Because Kafka has more components and more configurations than RabbitMQ, well do this in two parts. I dont see any DNS issue, for instance ping sentry.io works perfectly. It didnt send the request as it believed the node was offline because it had expired in Zookeeper. In this scenario we will isolate the leader from Zookeeper but not from the other Kafka nodes.
All Consume errors will result in a ConsumeException with further information about the error and context Although calling most methods on the clients will result in a fatal error if the client is in an un-recoverable The producer config request.required.acks=1 or its alias acks=1 tells the broker that the producers wants an acknowledgement once the leader partition has written the message to its local log.
Wed also need to know about which version of Sentry you are using. Meanwhile the leader should fail-over to a follower and the client should detect that change within 60 seconds and start sending messages to the new leader instead. Shows the broker 1 cannot connect to Zookeeper (for 7 seconds), then shortly afterwards it tries shrinks the ISR to itself, though it cannot update zookeeper with that information. Below we see that the leader failed over to kafka3 and the high watermark is 34669 which means we lost 31784 acknowledged messages. Protobuf and JSON both have great support in .NET. Copyright (c) So we see that acks=all helped guarantee no message loss during a leader fail-over. This scenario should still lose messages, but less messages than acks=0 as we should lose zero messages due to the connection failure, only due to the leader fail-over. The Apache Software Foundation. Will not attempt to authenticate using SASL (unknown error) (org.apache.zookeeper.ClientCnxn), [2018-09-16 19:20:43,991] WARN Client session timed out, have not heard from server in 6005ms for sessionid 0x165e8aa663e0005 (org.apache.zookeeper.ClientCnxn), [2018-09-16 19:20:43,991] INFO Client session timed out, have not heard from server in 6005ms for sessionid 0x165e8aa663e0005, closing socket connection and attempting reconnect (org.apache.zookeeper.ClientCnxn), [2018-09-16 19:20:44,095] INFO [ZooKeeperClient] Waiting until connected. Thats new. Supported - Commercial support is offered by register a producer as a singleton service, and how to bind configuration from an injected IConfiguration instance. Note: All three serialization formats are supported across Confluent Platform. It sends 100000 messages to the topic test1 at a rate of 10000 messages a second. I ran the script and after 10 seconds I started the network partition. In each scenario well publish messages to a topic called test1 while introducing failures. The reason is that the leader will be isolated from Zookeeper and so when the fail-over occurs, the controller wont bother to tell the original leader to stop being leader.
For more information, refer to the 3rd Party Libraries page. client. Wed need to see the logs for relay and kafka to make any speculations. Zookeeper seems fine unless it is killed The final count showed of the 89027 acknowledged messages, with only 45518 making it to the topic meaning 43509 we lost. Will not attempt to authenticate using SASL (unknown error) (org.apache.zookeeper.ClientCnxn), [2018-09-15 19:20:43,991] WARN Client session timed out, have not heard from server in 6004ms for sessionid 0x165e83d8e870005 (org.apache.zookeeper.ClientCnxn), [2018-09-15 19:20:44,095] INFO [ZooKeeperClient] Waiting until connected. Will not attempt to authenticate using SASL (unknown error) (org.apache.zookeeper.ClientCnxn), [2018-09-15 19:20:37,884] WARN Client session timed out, have not heard from server in 7025ms for sessionid 0x165e83d8e870005 (org.apache.zookeeper.ClientCnxn), [2018-09-15 19:20:37,884] INFO Client session timed out, have not heard from server in 7025ms for sessionid 0x165e83d8e870005, closing socket connection and attempting reconnect (org.apache.zookeeper.ClientCnxn), [2018-09-15 19:20:39,034] INFO [Partition test1-0 broker=3] Shrinking ISR from 1,2,3 to 1 (kafka.cluster.Partition), [2018-09-15 19:20:43,991] INFO Opening socket connection to server zk1/172.17.0.2:2181. {{ 'https://github.com/confluentinc/confluent-kafka-dotnet/wiki' | no-protocol }}, {{ 'https://github.com/confluentinc/confluent-kafka-dotnet' | no-protocol }}, {{ 'https://confluentcommunity.slack.com/messages/clients' | no-protocol }}, https://ci.appveyor.com/nuget/confluent-kafka-dotnet, Getting Started with Apache Kafka and .NET. client. Acks=all is required to avoid data loss in leader fail-overs whether they are due to a network partition or failed node. Any messages acknowledged during this short window will be lost. Because, its very important to me that I get it working before week-end. This will tell us how many messages have been persisted to the topic. I killed the leader midway and summed the success numbers to 537722. Detects when the message offset drops to a lower value and warns of message loss. In this post well do exactly the same but with a Kafka cluster. I did a quick google search for docker-compose dns issues and found this one: https://github.com/moby/moby/issues/41003. Errors delivered to a client's error handler should be considered informational except when the IsFatal flag For a step-by-step guide and code samples, see Getting Started with Apache Kafka and .NET on Confluent Developer. I guess the issue is from kafka. You can also refer to the Confluent Cloud example which demonstrates how to configure the .NET client for use with The difference is that the reason they stop sending fetch requests is that leadership failed-over to another node.The leader is kafka2 and the controller node is kafka1. But the conclusions from this part are clear - use acks=all if message loss is unacceptable to you. In my previous post I used Blockade, Python and some Bash scripts to test a RabbitMQ cluster under various failure conditions such as failed nodes, network partitions, packet loss and a slow network. The .NET Client has full support for transactions and idempotent message production, allowing you to write horizontally scalable stream Tagged: Kafka, Fault Tolerance, Chaos Testing, How to Lose Messages on a Kafka Cluster - Part 2, How to Lose Messages on a RabbitMQ Cluster, How to Lose Messages on a Kafka Cluster - Part 1, Tweaking the BookKeeper protocol - Unbounded Ledgers, Tweaking the BookKeeper protocol - Guaranteeing write quorum, Learn about TLA+ and the formal verification of Apache BookKeeper, Posts I wrote on the RabbitMQ blog in 2020, Kafka and RabbitMQ blog posts I wrote elsewhere in 2019, With Great Observation Comes Great Insight, Why I'm Not Writing Much On My Blog These Days, A Look at Multi-Topic Subscriptions with Apache Pulsar, Building A "Simple" Distributed System - It's the Logs Stupid, Building A "Simple" Distributed System - The Implementation, Building A "Simple" Distributed System - Formal Verification, Building A "Simple" Distributed System - The Protocol, Building a "Simple" Distributed System - The What, Quorum Queues - Making RabbitMQ More Competitive in Reliable Messaging, Why I Am Not a Fan of the RabbitMQ Sharding Plugin, Testing Producer Deduplication in Apache Kafka and Apache Pulsar, How to (not) Lose Messages on an Apache Pulsar Cluster, RabbitMQ vs Kafka Part 6 - Fault Tolerance and High Availability with Kafka, RabbitMQ vs Kafka Part 5 - Fault Tolerance and High Availability with RabbitMQ Clustering, AWS Security - Securing Your Use of the AWS CLI and Automation Tools, RabbitMQ Work Queues: Avoiding Data Inconsistency with Rebalanser, Creating Consumer Groups in RabbitMQ with Rebalanser - Part 1, .NET Core AWS Lambda Lifetime After Uncontrolled Exception.
502s arent happening anymore, but I noticed that none of relay, kafka and zookeeper generate logs at the time which Sentry replies to events with HTTP 200. snuba-consumer_1 | %3|1597288279.541|FAIL|rdkafka#producer-1| [thrd:kafka:9092/bootstrap]: kafka:9092/1001: Failed to resolve 'kafka:9092': Temporary failure in name resolution (after 125688ms in state CONNECT, 1 identical error(s) suppressed), snuba-transactions-consumer_1 | %3|1597291599.204|FAIL|rdkafka#consumer-2| [thrd:GroupCoordinator]: GroupCoordinator: Failed to resolve 'kafka:9092': Temporary failure in name resolution (after 446154ms in state CONNECT, 1 identical error(s) suppressed), snuba-outcomes-consumer_1 | %3|1597288470.794|FAIL|rdkafka#consumer-2| [thrd:GroupCoordinator]: GroupCoordinator: Failed to resolve 'kafka:9092': Temporary failure in name resolution (after 165000ms in state CONNECT, 1 identical error(s) suppressed), snuba-replacer_1 | %3|1597288605.389|FAIL|rdkafka#consumer-1| [thrd:kafka:9092/bootstrap]: kafka:9092/1001: Failed to resolve 'kafka:9092': Temporary failure in name resolution (after 157001ms in state CONNECT, 1 identical error(s) suppressed). (org.apache.kafka.clients.FetchSessionHandler), [2018-09-16 19:20:26,210] INFO [ReplicaFetcher replicaId=2, leaderId=3, fetcherId=0] Stopped (kafka.server.ReplicaFetcherThread), [2018-09-16 19:20:26,211] INFO [ReplicaFetcher replicaId=2, leaderId=3, fetcherId=0] Shutdown completed (kafka.server.ReplicaFetcherThread), [2018-09-16 19:20:26,245] INFO [Log partition=test1-0, dir=/var/lib/kafka/data] Truncating to 20 has no effect as the largest offset in the log is 19 (kafka.log.Log). confluent-kafka-dotnet is distributed via NuGet. Once the 10 second limit is reached the leader will shrink the ISR to itself but it cant update Zookeeper with the value and will stop accepting more writes. creators of Kafka, is building a streaming platform For an overview of configuration properties, refer to the librdkafka documentation. (kafka.zookeeper.ZooKeeperClient). In theory, once the leader is isolated we should not get any acknowledgements because no followers in the ISR are reachable. KAFKA is a registered trademark of The Apache Software Foundation and has been licensed for use Ultimately, you need to figure out whats going on. Just like in scenario 5 I dont expect to see message loss. Theres something else : after running docker-compose restart , I get HTTP 502 errors on developer endpoints but not on dashboard endpoints. For a step-by-step guide on using the .NET client with Confluent Cloud see Getting Started with Apache Kafka and .NET on Confluent Developer. Now I have a new problem : after entering my TOTP code Im being redirected back to e-mail/password form. Youll find the scripts in the Github repo. We see that kafka2 removes the existing fetcher and creates a new one, for the new leader, starting at offset 20. matches the appveyor build number. across all of our clients (also confluent-kafka-python With acks=all we did not lose any messages, in fact, 7 messages for which we never got an ack also got persisted. Behind the scenes, the client will manage with Apache Kafka at its core. Please read my post on Kafka fault tolerance as this post assumes you understand the basics of the acknowledgements and replication protocol. Seems like it is resolved in a recent version so maybe that would help? At the 30000 message mark more or less I killed broker 1 with the following command: With acks=1 only 89356 messages are acknowledged, but hopefully all or nearly all will have survived the fail-over. The errors on Kafka indicate a zookeeper failure so lets check its logs too? Thinking its still leader, it will see the other followers not sending fetch requests and try to remove them from the ISR, but it wont be able to. In Part 2 well take some of the scenarios from Part 1 and add a flaky/slow network. When using Produce, to determine whether a particular message has been successfully delivered to a cluster, Its not : Considering the emergency, I could give you access to it. processing applications with exactly once semantics. Note that a server round-trip is slow (3ms at a minimum; actual latency depends on many factors). The three "Serdes" packages provide serializers and deserializers for Avro, Protobuf and JSON with Confluent Schema Registry integration. Again at about the 30000 message mark I isolate the leader. At about the 30000 mark, I kill the node that hosts the leader partition. Im not a magician, just making some guesses here on a system I never have seen or touched. That will increase the bill. to integrate with Kafka. https://ci.appveyor.com/nuget/confluent-kafka-dotnet. Theres something else : after running docker-compose restart, I get HTTP 502 errors on developer endpoints but not on dashboard endpoints.
At about the 30000 message mark we tell Blockade to kill kafka3 which hosts the partition leader. At this point you may want to try running docker-compose down --remove-orphans, remove any zookeeper related volumes and then bring things back up and see if it fixes the issues. Lets rerun the scenario with ten producers, each sending 100000 messages at the same time. Shows kafka3 truncating its log to the new leaders high watermark (though no data is truncated as it is not ahead of the new leader). In Part 1 well concentrate on node failures and network partitions. So I rm-ed both volumes related to zonekeeper. [2018-09-15 19:20:26,181] INFO [Partition test1-0 broker=2] test1-0 starts at Leader Epoch 1 from offset 15. At this point you may want to try running docker-compose down --remove-orphans , remove any zookeeper related volumes and then bring things back up and see if it fixes the issues. The version suffix of these nuget packages The ExactlyOnce example demonstrates this capability by way Then finally I retrieved the high watermark for the topic. Confluent Platform. In the end it gets 66453 acknowledgements. the above approach, but there will be a delay on each await call. Do you really think its necessary ? and error via the DeliveryResult and Error fields. At some point the followers will stop sending fetch requests to the leader and the leader will try to shrink the ISR to itself. requests before proceeding. Soon after it tries to shrink the ISR to itself but cannot and declares it will wait to be connected. Remember that we are not retrying failed messages, which is what you would do in production. Acks=all is the equivalent of RabbitMQs publisher confirms and we have seen with both messaging systems that confirming replication to secondaries is critical for lossless fail-overs. The partition on kafka1 gets elected leader. For this I run the python script from a bash script, running concurrently as background jobs. You can see that the time out messages appear after 60000 messages have been acknowledged. Currently, this can only happen on Maybe you are having issue with you DNS provider, somehow affecting this? should specify it in the nuget package manager): Reliability - There are a lot of details to get right when writing an Apache Kafka (kafka.controller.ControllerChannelManager). If we look in the logs of the three brokers we see some interesting snippets. pace with core Apache Kafka and components of the Confluent Platform. Currently there are only 7 projects and all their history is empty. My docker version is 19.03.12, which is the latest one released in 2020-06-18, and my docker-compose version is 1.26.2, which is also the latest one released in 2020-07-02. Now we starting sending the 100000 messages, with acks=1. is set to true, indicating that the client is in an un-recoverable state. It uses acks mode 0 (fire-and-forget). You should use the ProduceAsync method if you would like to wait for the result of your produce In fact, there is a message in the topic for which we never received an ack. check the Error field of the DeliveryReport during the delivery handler callback. If you are on a different platform, you may need to build librdkafka manually (or acquire it via other means) and load it using the Library.Load method. Note that the fail-over occurred at 19:20:26 and that kafka3 was still thinking it was the leader at 19:20:39, stopping to receive messages at 19:20:40 - a whole 14 seconds after the fail-over. We provide five packages: To install Confluent.Kafka from within Visual Studio, search for Confluent.Kafka in the NuGet Package Manager UI, or run the following command in the Package Manager Console: To add a reference to a dotnet core project, execute the following at the command line: Note: Confluent.Kafka depends on the librdkafka.redist package which provides a number of different builds of librdkafka that are compatible with common platforms. 2015-2016 Andreas Heider. Acknowledgements came in right up to message 28, at which point is seemingly hung for 60 seconds. Well repeat the same concurrent ten producers sending 1 million messages over a period of a few seconds, killing the leader midway. This time soon after isolating the leader we get three Broker: request timed out errors due to the fact that the followers are out of contact. After 60 seconds the client detected the new leader was broker 2 and we got 60 seconds worth of message timeouts all at once. What do you mean by load ? At the end we see how many messages are lost. I have created a few helper bash scripts to perform tasks such as recreating the cluster between scenarios, creating topics etc. Lets dig a bit deeper and see what is going on. In the logs we see the following line straight after the fail-over: [2018-09-17 19:20:26,323] WARN [Channel manager on controller 1]: Not sending request (type=StopReplicaRequest, controllerId=1, controllerEpoch=1, deletePartitions=false, partitions=test1-0) to broker 3, since it is offline. We see that kafka1 sees that kafka3 is gone and that it stops its fetcher. Note: if you await the call, this means a ProduceException One last interesting thing is that the controller node could have stopped kafka3 from accepting writes if it had sent a request to it to stop being leader. Confluent. Midway I isolated kafka2 from Zookeeper only. Edit : thats a browser issue which happened on another computer, Ill check it out later. 40+ seconds of name resolution times are just ridiculous. Awesome .NET open source & community resources. Not too bad for a leader fail-over with acks=1. We're fans of his work and were very happy to have been able to leverage rdkafka-dotnet as the basis of this Disk : 30GB total, 6.3GB used Message loss due to a fail-over as a result of a node failure with acks=1 was surprisingly low and well see what affect slowing down the network has on that number. I mean, how would I know? 4GB should be enough for light loads but I dont know your load. I isolated the leader at about the 13-14 message mark. In the next part well start messing with the network speed and also contrast RabbitMQs queue synchronization to Kafkas replication protocol. When using ProduceAsync, any delivery result other than NoError will cause the returned Task to be in the So it declares that it will wait until connected to Zookeeper again. After about 10 seconds I executed the command to kill the leader like in previous scenarios. [2018-09-15 19:20:26,245] INFO [Log partition=test1-0, dir=/var/lib/kafka/data] Truncating to 15 has no effect as the largest offset in the log is 14 (kafka.log.Log). Shows it taking on leadership of partition 0, with offset 15. applications, where you would like to process many messages in rapid succession, you would typically It's high priority for us that client features keep In highly concurrent scenarios you will achieve high overall throughput out of the producer using [2018-09-16 19:20:26,154] INFO [ReplicaFetcherManager on broker 2] Removed fetcher for partitions test1-0 (kafka.server.ReplicaFetcherManager), [2018-09-16 19:20:26,185] INFO [ReplicaFetcherManager on broker 2] Added fetcher for partitions List([test1-0, initOffset 20 to broker BrokerEndPoint(1,kafka1,19092)] ) (kafka.server.ReplicaFetcherManager), [2018-09-16 19:20:26,186] INFO [ReplicaAlterLogDirsManager on broker 2] Added fetcher for partitions List() (kafka.server.ReplicaAlterLogDirsManager), [2018-09-16 19:20:26,192] INFO [ReplicaFetcher replicaId=2, leaderId=1, fetcherId=0] Starting (kafka.server.ReplicaFetcherThread), [2018-09-16 19:20:26,199] INFO [ReplicaFetcher replicaId=2, leaderId=3, fetcherId=0] Shutting down (kafka.server.ReplicaFetcherThread), [2018-09-16 19:20:26,209] INFO [ReplicaFetcher replicaId=2, leaderId=3, fetcherId=0] Error sending fetch request (sessionId=1307994263, epoch=10152) to node 3: java.nio.channels.ClosedSelectorException. On receipt of an acknowledgement, prints out the value of the message and that message offset. The Confluent.SchemaRegistry nuget package provides a client for interfacing with [2018-09-16 19:20:31,877] INFO Opening socket connection to server zk1/172.17.0.2:2181.
message timed out at confluent kafka producer
