Debezium & MySQL v8 : Public Key Retrieval Is Not Allowed
I started hitting problems when trying Debezium against MySQL v8. When creating the connector:
Using Kafka Connect and Debezium with Confluent Cloud
This is based on using Confluent Cloud to provide your managed Kafka and Schema Registry. All that you run yourself is the Kafka Connect worker.
Optionally, you can use this Docker Compose to run the worker and a sample MySQL database.
Skipping bad records with the Kafka Connect JDBC sink connector
The Kafka Connect framework provides generic error handling and dead-letter queue capabilities which are available for problems with [de]serialisation and Single Message Transforms. When it comes to errors that a connector may encounter doing the actual pull or put of data from the source/target system, it’s down to the connector itself to implement logic around that. For example, the Elasticsearch sink connector provides configuration (behavior.on.malformed.documents) that can be set so that a single bad record won’t halt the pipeline. Others, such as the JDBC Sink connector, don’t provide this yet. That means that if you hit this problem, you need to manually unblock it yourself. One way is to manually move the offset of the consumer on past the bad message.
TL;DR : You can use kafka-consumer-groups --reset-offsets --to-offset <x> to manually move the connector past a bad message
Kafka Connect and Elasticsearch
I use the Elastic stack for a lot of my talks and demos because it complements Kafka brilliantly. A few things have changed in recent releases and this blog is a quick note on some of the errors that you might hit and how to resolve them. It was inspired by a lot of the comments and discussion here and here.
Copying data between Kafka clusters with Kafkacat
kafkacat gives you Kafka super powers 😎
I’ve written before about kafkacat and what a great tool it is for doing lots of useful things as a developer with Kafka. I used it too in a recent demo that I built in which data needed manipulating in a way that I couldn’t easily elsewhere. Today I want share a very simple but powerful use for kafkacat as both a consumer and producer: copying data from one Kafka cluster to another. In this instance it’s getting data from Confluent Cloud down to a local cluster.
Kafka Summit GoldenGate bridge run/walk
Coming to Kafka Summit in San Francisco next week? Inspired by similar events at Oracle OpenWorld in past years, I’m proposing an unofficial run (or walk) across the GoldenGate bridge on the morning of Tuesday 1st October. We should be up and out and back in plenty of time to still attend the morning keynotes. Some people will run, some may prefer to walk, it’s open to everyone :)
Staying sane on the road as a Developer Advocate
I’ve been a full-time Developer Advocate for nearly 1.5 years now, and have learnt lots along the way. The stuff I’ve learnt about being an advocate I’ve written about elsewhere (here/here/here); today I want to write about something that’s just as important: staying sane and looking after yourself whilst on the road. This is also tangentially related to another of my favourite posts that I’ve written: Travelling for Work, with Kids at Home.
Where I’ll be on the road for the remainder of 2019
I’ve had a relaxing couple of weeks off work over the summer, and came back today to realise that I’ve got a fair bit of conference and meetup travel to wrap my head around for the next few months :)
If you’re interested in where I’ll be and want to come and say hi, hear about Kafka—or just grab a coffee or beer, herewith my itinerary as it currently stands.
Reset Kafka Connect Source Connector Offsets
Kafka Connect in distributed mode uses Kafka itself to persist the offsets of any source connectors. This is a great way to do things as it means that you can easily add more workers, rebuild existing ones, etc without having to worry about where the state is persisted. I personally always recommend using distributed mode, even if just for a single worker instance - it just makes things easier, and more standard.
Starting a Kafka Connect sink connector at the end of a topic
When you create a sink connector in Kafka Connect, by default it will start reading from the beginning of the topic and stream all of the existing—and new—data to the target. The setting that controls this behaviour is auto.offset.reset, and you can see its value in the worker log when the connector runs:
[2019-08-05 23:31:35,405] INFO ConsumerConfig values:
allow.auto.create.topics = true
auto.commit.interval.ms = 5000
auto.offset.reset = earliest
…