Which messaging system for a web dashboard? - apache-kafka

I would like to make a Web Dashboard system and I am facing a problem. I need to get an information that is in the cache of one of the instances of my program, for this I had thought of doing Pub/Sub with Kafka however I don't know how to do to Publish and get a response from one of my Subscriber. Do you know a pattern that allows this and a service that allows me to do this?
EDIT: I would like to design an infrastructure that follows this pattern:

Attached diagram is showing simple request->response flow, Kafka is designed for different types of architecture, so IMHO you should not focus on Kafka in this case.
However, if you still want to use Kafka for some other reasons I can suggest to you two options:
Stick with request->response flow and use ReplyingKafkaTemplate or AggregatingKafkaTemplate to handle it, second one is an extension of first one, this adds functionality to handle more responses then one. You can send a request to Kafka topic from the Dashboard application, then poll the message by one of the Bot instances, next, send reply to reply topic, and then process reply in Dashboard application.
Use Kafka to implement Event-Carried State Transfer pattern, move state (mutual guilds data) from Bot Instances directly to Dashboard application via Kafka topic. You can use several tools to implement this:
Bot applications send events to Kafka topic via simple KafkaProducer or KafkaTemplate, then use one of the Kafka Connect sink connectors to save data in Dashboards database.
Bot applications send events to Kafka topic via simple KafkaProducer or KafkaTemplate. Run Kafka Streams thread in Dashboard application and build a state using Kafka Streams functionalities - grouping, aggregating etc. Then read the state directly from Kafka Streams internal RocksDB database.

Related

Kafka for API gateway to store messages

I need to build a secure REST API for different services where client services can post and receive messages from other clients( like mail box. but messages are going to be in JSON form. and should be persistent. I am expecting around 5000 client services. With around 50 message per service per day).
My questions are:
Can I use Kafka for this(I think I will be needing some wrapper over
Kafka to manage other task) ?
If yes then outbox and inbox are going to be a separate topic for
each service?( 2 topics per service. 5000*2 topics. My plan is to
create them dynamically as new client joins in)
what are the alternative technologies to write this kind of gateway.
Any help will be appreciated.
You can't use Kafka to implement REST API because REST API implies request/response while Kafka is just a message queue (Kafka doesn't provide a mechanism to respond to messages). You can use Kafka to produce messages to be consumed by other services. The idea of message queues is to decouple producer from consumer and vice versa. When a consumer receives a message it acts on it, that's it. But when you say inbox/outbox you imply that there's a response for a message which means that producers and consumers pace should be similar which couples them which is against the nature of message queues.
It seems like in your case it makes more sense to use http requests/response or even websockets. If you want to save the request/response data (making it persistent) you can save it either in a database, object storage (like S3), log it or send each message to Kafka so that Kafka stores all of your messages, writes to Kafka will actually be very fast because Kafka is roughly-speaking an append-only log. You can then search messages values using ksqldb.

Keeping services in sync in a kafka event driven backbone

Say I am using Kafka as the event-driven backbone for all my microservices in my system design. Many microservices use the events data to populate their internal databases.
Now there is a requirement where I need to create a new service and it uses some events data. The service will only be able to consume events after the time it comes live and hence, won't have a lot of data that it missed. I want a strategy such that I don't have to backfill my internal databases by writing out scripts.
What are some cool strategies I can have which do not create a huge load on Kafka & does not account for a lot of scripting to backfill data in the new services that I ever create?
There are a few strategies you can have here, depending on how you publish data to a kafka topic. Here are a few ideas:
first, you can set the retention of a kafka topic to be forever, meaning that it will store all the data. This is OK as kafka is built for this purpose as well. See this. By doing this, any new service that come alive can start consuming data from the start.
if you are using kafka for latest state publishing for a given entity/aggregate, you can also consider configuring the topic to be a compacted. This will let you store at least the latest state of your entity/aggregate on the topic, and new consumers that starts listening on the topic will have less data to configure. However, your consumers still need to know how to process multiple messages per entity/aggregate as you cannot guarantee it will have exactly one message in the topic.

Kafka Messages Processing

I am using Kafka distributed system for message processing in spring boot application. Now my application are producing messages on even basic to three different different topics. There is one separate spring boot application which will be used by some data analysis team who will analysis the data. This application is a simple report type application with only one filter Topic.
Now I have to implement this but I am little bit confused how I will show the data to the UI. I have written listeners (Consumers) who are consuming the messages but how I will show the data to the UI on real time basic. Should I need to store it in some database like redis and then show this data to UI? Is this the correct way to deal with consumer in Kafka? Will it not be slow? As messages can grow drastically over the time.
In nutshell I want to know to how we can show messages on any UI in the efficient way and in real time.
Thanks
You can write a consumer to forward to a websocket.
Or you can use Kafka Connect to write to a database, then write a REST API
Or use Kafka Streams Interactive Queries feature + add a RPC layer on top for Javascript to call

Process messages pushed through Kafka

I haven't used Kafka before and wanted to know if messages are published through Kafka what are the possible ways to capture that info?
Is Kafka only way to receive that info via "Consumers" or can Rest APIs be also used here?
Haven't used Kafka before and while reading up I did find that Kafka needs ZooKeeper running too.
I don't need to publish info just process data received from Kafka publisher.
Any pointers will help.
Kafka is a distributed streaming platform that allows you to process streams of records in near real-time.
Producers publish records/messages to Topics in the cluster.
Consumers subscribe to Topics and process those messages as they are available.
The Kafka docs are an excellent place to get up to speed on the core concepts: https://kafka.apache.org/intro
Is Kafka only way to receive that info via "Consumers" or can Rest APIs be also used here?
Kafka has its own TCP based protocol, not a native HTTP client (assuming that's what you actually mean by REST)
Consumers are the only way to get and subsequently process data, however plenty of external tooling exists to make it so you don't have to write really any code if you don't want to in order to work on that data

Kafka user - project design advise

I am new to Kafka and data streaming and need some advice for the following requirement,
Our system is expecting close to 1 million incoming messages per day. The message carries a project identifier. The message should be pushed to users of only that project. For our case, lets say we have projects A, B and C. Users who opens project A's dashboard only sees / receives messages of project A.
This is my idea so far on implementing solution for the requirement,
The messages should be pushed to a Kafka Topic as they arrive, lets call this topic as Root Topic. The messages once pushed to the Root Topic, can be read by a Kafka Consumer/Listener and based on the project identifier in the message can push that message to a project specific Topic. So any message can end up at Topic A or B or C. Thinking of using websockets to update the message as they arrive on the project users' dashboards. There will be N Consumers/Listeners for the N project Topics. These consumers will push the project specific message to the project specifc websocket endpoints.
Please advise if I can make any improvements to the above design.
Chose Kafka as the messaging system here as it is highly scalable and fault tolerant.
There is no complex transformation or data enrichment before it gets sent to the client. Will it makes sense to use Apache Flink or Hazelcast Jet for the streaming or Kafka streaming is good enough for this simple requirement.
Also, when should I consider using Hazelcast Jet or Apache Flink in my project.
Should i use Flink say when I have to update few properties in the message based on a web service call or database lookup before sending it to the users?
Should I use Hazelcast Jet only when I need the entire dataset in memory to arrive at a property value? or will using Jet bring some benefits even for my simple use case specified above. Please advise.
Kafka Streams are a great tool to convert one Kafka topic to another Kafka topic.
What you need is a tool to move data from a Kafka topic to another system via web sockets.
Stream processor gives you a convenient tooling to build this data pipeline (among others connectors to Kafka and web sockets and scalable, fault-tolerant execution environment). So you might want use stream processor even if you don't transform the data.
The benefit of Hazelcast Jet is it's embedded scalable caching layer. You might want to cache your database/web service calls so that the enrichment is performed locally, reducing remote service calls.
See how to use Jet to read from Kafka and how to write data to a TCP socket (not websocket).
I would like to give you another option. I'm not Spark/Jet expert at all, but I've studying them for a few weeks.
I would use Pentaho Data Integration(kettle) to consume from the Kafka and I would write a kettle step (or User Defined Java Class step) to write the messages to a Hazelcast IMAP.
Then, would use this approach http://www.c2b2.co.uk/middleware-blog/hazelcast-websockets.php to provided the Websockets for the end-users.