Jan 23, 2020

Notes on getting data into InfluxDB from Kafka with Kafka Connect

You can download the InfluxDB connector for Kafka Connect here. Documentation for it is here.

When a message from your source Kafka topic is written to InfluxDB the InfluxDB values are set thus:

  • Timestamp is taken from the Kafka message timestamp (which is either set by your producer, or the time at which it was received by the broker)

  • Tag(s) are taken from the tags field in the message. This field must be a map type - see below

  • Value fields are taken from the rest of the message, and must be numeric or boolean

  • Measurement name can be specified as a field of the message, or hardcoded in the connector config.

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Jan 21, 2020

Monitoring Sonos with ksqlDB, InfluxDB, and Grafana

I’m quite a fan of Sonos audio equipment but recently had some trouble with some of the devices glitching and even cutting out whilst playing. Under the covers Sonos stuff is running Linux (of course) and exposes some diagnostics through a rudimentary frontend that you can access at http://<sonos player IP>:1400/support/review: Whilst this gives you the current state, you can’t get historical data on it. It felt like the problems were happening "all the time", but were they actually?

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Jan 16, 2020

Changing the Logging Level for Kafka Connect Dynamically

Logs are magical things. They tell us what an application is doing—or not doing. They help us debug problems. As it happens, they also underpin the entire philosophy of Apache Kafka, but that’s a story for another day. Today we’re talking about logs written by Kafka Connect, and how we can change the amount of detail written. By default, Kafka Connect will write logs at INFO and above. So when it starts up, the settings that it’s using, and any WARN or ERROR messages along the way - a missing configuration, a broken connector, and so on.

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Jan 16, 2020

How to win [or at least not suck] at the conference abstract submission game

Just over a year ago, I put together the crudely-titled "Quick Thoughts on Not Writing a Crap Abstract" after reviewing a few dozen conference abstracts. This time around I’ve had the honour of being on a conference programme committee and with it the pleasure of reading 250+ abstracts—from which I have some more snarky words of wisdom to impart on the matter. Remind me…how does this conference game work? Before we really get into it, let’s recap how this whole game works, because plenty of people are new to conference speaking.

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Jan 9, 2020

Exploring ksqlDB window start time

Prompted by a question on StackOverflow I had a bit of a dig into how windows behave in ksqlDB, specifically with regards to their start time. This article shows also how to create test data in ksqlDB and create data to be handled with a timestamp in the past. For a general background to windowing in ksqlDB see the excellent docs. The nice thing about recent releases of ksqlDB/KSQL is that you can create and populate streams directly with CREATE STREAM and INSERT INTO respectively.

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Jan 8, 2020

Streaming messages from RabbitMQ into Kafka with Kafka Connect

This was prompted by a question on StackOverflow to which I thought the answer would be straightforward, but turned out not to be so. And then I got a bit carried away and ended up with a nice example of how you can handle schema-less data coming from a system such as RabbitMQ and apply a schema to it. Note This same pattern for ingesting bytes and applying a schema will work with other connectors such as MQTT What?

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Dec 20, 2019

Analysing network behaviour with ksqlDB and MongoDB

In this post I want to build on my previous one and show another use of the Syslog data that I’m capturing. Instead of looking for SSH attacks, I’m going to analyse the behaviour of my networking components. Note You can find all the code to run this on GitHub. Getting Syslog data into Kafka As before, let’s create ourselves a syslog connector in ksqlDB: CREATE SOURCE CONNECTOR SOURCE_SYSLOG_UDP_01 WITH ( 'tasks.

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Dec 18, 2019

Detecting and Analysing SSH Attacks with ksqlDB

I’ve written previously about ingesting Syslog into Kafka and using KSQL to analyse it. I want to revisit the subject since it’s nearly two years since I wrote about it and some things have changed since then. ksqlDB now includes the ability to define connectors from within it, which makes setting things up loads easier. You can find the full rig to run this on GitHub. Create and configure the Syslog connector To start with, create a source connector:

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Dec 17, 2019

Copy MongoDB collections from remote to local instance

This is revisiting the blog I wrote a while back, which showed using mongodump and mongorestore to copy a MongoDB database from one machine (a Unifi CloudKey) to another. This time instead of a manual lift and shift, I wanted a simple way to automate the update of the target with changes made on the source. The source is as before, Unifi’s CloudKey, which runs MongoDB to store its data about the network - devices, access points, events, and so on.

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Nov 29, 2019

Kafka Connect - Request timed out

A short & sweet blog post to help people Googling for this error, and me next time I encounter it.

The scenario: trying to create a connector in Kafka Connect (running in distributed mode, one worker) failed with the curl response

HTTP/1.1 500 Internal Server Error
Date: Fri, 29 Nov 2019 14:33:53 GMT
Content-Type: application/json
Content-Length: 48
Server: Jetty(9.4.18.v20190429)

{"error_code":500,"message":"Request timed out"}

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Nov 29, 2019

Using tcpdump With Docker

I was doing some troubleshooting between two services recently and wanting to poke around to see what was happening in the REST calls between them. Normally I’d reach for tcpdump to do this but imagine my horror when I saw:

root@ksqldb-server:/# tcpdump
bash: tcpdump: command not found

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Nov 22, 2019

Common mistakes made when configuring multiple Kafka Connect workers

Kafka Connect can be deployed in two modes: Standalone or Distributed. You can learn more about them in my Kafka Summit London 2019 talk. I usually recommend Distributed for several reasons: It can scale It is fault-tolerant It can be run on a single node sandbox or a multi-node production environment It is the same configuration method however you run it I usually find that Standalone is appropriate when:

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Nov 20, 2019

Streaming data from SQL Server to Kafka to Snowflake ❄️ with Kafka Connect

Snowflake is the data warehouse built for the cloud, so let’s get all ☁️ cloudy and stream some data from Kafka running in Confluent Cloud to Snowflake! What I’m showing also works just as well for an on-premises Kafka cluster. I’m using SQL Server as an example data source, with Debezium to capture and stream and changes from it into Kafka. I’m assuming that you’ve signed up for Confluent Cloud and Snowflake and are the proud owner of credentials for both.

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Nov 12, 2019

Running Dockerised Kafka Connect worker on GCP

I talk and write about Kafka and Confluent Platform a lot, and more and more of the demos that I’m building are around Confluent Cloud. This means that I don’t have to run or manage my own Kafka brokers, Zookeeper, Schema Registry, KSQL servers, etc which makes things a ton easier. Whilst there are managed connectors on Confluent Cloud (S3 etc), I need to run my own Kafka Connect worker for those connectors not yet provided. An example is the MQTT source connector that I use in this demo. Up until now I’d either run this worker locally, or manually build a cloud VM. Locally is fine, as it’s all Docker, easily spun up in a single docker-compose up -d command. I wanted something that would keep running whilst my laptop was off, but that was as close to my local build as possible—enter GCP and its functionality to run a container on a VM automagically.

You can see the full script here. The rest of this article just walks through the how and why.

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Oct 15, 2019

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

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