Kpow for Apache Kafka (Annual)

My main use case for Kpow for Apache Kafka  is navigating and inspecting and checking out the message flow in the different applications that our system supports. Our team currently builds an application which consumes messages and also sends out messages. It has an inbound and also has an outbound. We also talk to external teams such as Salesforce  and Cerner, which listen to our messages. In the current stage, imagine a chain of applications wherein one listens and sends the message out, consuming an input and giving back an output. Checking that use case is mainly what we are doing with the different applications we support.

A specific example of how I use Kpow for Apache Kafka  is in my company, particularly in the group domain. We use Kpow for Apache Kafka to identify the topic. Based on the topic, we identify which domain the message belongs to. We query and filter out the messages by selecting the cluster, whether it is test, dev, or pre-prod. Then we select the topic and filter by the message unique reference or message ID and select the time window. We analyze results to validate the message headers and the JSON payload, and inspect the structure. We also use it for our data loads to check for the lags on a topic and the rate of reading the messages. In troubleshooting and debugging, if one application in the group domain had the group transformer send out messages to the group inbound app, but we see that the group inbound app did not receive the message, common use cases such as missing data, incorrect data, or delayed data are helpful to debug and filter with Kpow for Apache Kafka.

I find myself using Kpow for Apache Kafka very frequently. Just before deploying our application or deploying a feature, we usually do a round of testing, which usually involves an end-to-end test of the complete life cycle of a message. I use it on a weekly basis and in our company, it is split across five or six environments including dev, test, test batch, training, pre-prod, and prod. Performing data loads and debugging is pretty common, and I use it on a weekly basis.

I want to add two things about my main use case. One is a fun fact. I recently got to know what Kpow stands for; it stands for Kafka power, which aligns with the web UI tool that is really powerful and user-friendly and helps in monitoring and observability, and even fast debugging in a cross-team setting. The second thing I would mention is that we sometimes use Kpow for Apache Kafka to validate the schemas. On the menu, there is a section for schemas where we can inspect the message structure or the field structure and validate the payloads if it is the field level data structure. That is really helpful as well.

I believe that the best features Kpow for Apache Kafka offers include the monitoring and debugging aspect, which is a very handy feature, as well as object management or the life cycle of an object or message, starting from managing the topics, the partitions, the groups, consumer groups, and the schemas, all of which can be configured in Kpow for Apache Kafka. While browsing or inspecting the messages, it offers the KQuery, which can be really handy; you can just filter out based on writing the query, and then it does its magic.

The KQuery feature helps me in my daily work by allowing us to filter a life cycle of a message using an identifier called the message unique reference, which is our primary key. In all the applications, that particular ID is similar, so we know if the message went through a certain app, whether the next one received and processed it, and subsequently if it passed on till the end with a happy path. Adding querying based on the timestamps can be really helpful in which we can filter it down.

Kpow for Apache Kafka has positively impacted my organization and has been very beneficial. Having it across different environments has helped our team manage the project really well, especially working in a cross-functional team that has a dependency with Salesforce  and Cerner teams, and also as we work on modernizing a legacy app. Supporting different teams and having a tool that acts as a great UI for Kafka messages is wonderful.

To improve Kpow for Apache Kafka, I believe that even though the UI is really user-friendly, it can be made more intuitive. Sometimes I find it a bit laggy or it does not update itself properly, which could be due to the load or the number of messages being processed. There is definitely scope for improvement in terms of the loading or UI aspect. Nonetheless, the features it offers are really great compared to similar tools such as Kafdrop and AKHQ and Conductor .

I have been using Kpow for Apache Kafka for more than a year now, as part of my current project at VHI.

Kpow for Apache Kafka has certainly increased collaboration and reduced time in our team. For example, there are instances where we have to say that a certain message hits a particular topic, which in a usual path would go through the application when it runs or something is triggered. Kpow for Apache Kafka also has a feature where we can trigger messages or send out a message based on configuring it on the fly by updating certain configs. I can tweak a message that it received and send it again to debug and verify how the app processes it. That has been really handy, saving us time and helping find issues that could be fatal in a production environment, adding a security layer as well.

Regarding Kpow for Apache Kafka's AI capabilities, I think it is a nice tool in terms of security and authorization. I can only access it via certain roles that I need to be granted, and it is only through an in-house portal that I can access this tool. The data or the messages it supports are secured end to end, so I believe the security aspect is brilliant.

I have not explored Kpow for Apache Kafka's AI capabilities much regarding its accuracy and reliability of output.

My advice for others looking into using Kpow for Apache Kafka would be to get familiarized with the UI. On the menu, there are certain features it supports including topics, partitions, schemas, groups, and clusters. Selecting the clusters was tricky for me based on the different environment selector, whether it is dev, test, or prod. Starting off with browsing the different topics, listing and searching and viewing the partitions and offsets, then inspecting the messages would be helpful. You can filter by different options and view the message and headers, then view the lags to identify any downstream issues.

I would say that Kpow for Apache Kafka is a really powerful tool, as the name suggests, which offers fast visibility, and the debugging it provides makes it structured and organized. It can be handy for supporting different environments. I give Kpow for Apache Kafka a rating of 9 out of 10.

Private Cloud

Amazon Web Services (AWS)

Kpow for Apache Kafka  is used for persistent messages, payment-type messages, processing log-type messages, consuming data in general from different systems, part of an information infrastructure or an information architecture, consuming information from various sources, then storing that information in a database and processing that information. Processing payment messages is a big application, also for integration and storing the messages persistently, and processing them concurrently.

I have used Kpow for Apache Kafka  in partition mode where someone else has set it up with message partitions or topic partitions, and I then consume messages from specific partitions; however, I haven't set it up myself in that mode.

I have not used Kpow for Apache Kafka consumer lag insights; I've seen it and heard about it, but I haven't used that so far. I've only used it where the messages are consumed into some other system that does something with the messages.

I see benefits from the product in terms of cost; replacing IBM MQ  with Kpow for Apache Kafka is much cheaper. Using Kafka instead of something such as IBM MQ  is much cheaper, offering scalability and processing messages in parallel, which Kafka helps manage quite a lot, though you can have issues with duplicate processing. Cost-wise and in terms of simplicity in setup versus something such as IBM MQ , that tends to be a bit more complicated to set up.

The product's adaptability is quite important for my organization as that's the central part of how the information from external systems are processed.

I think Kpow for Apache Kafka could improve in the area of monitoring; you can change many parts of it, and it can run out of storage if you don't monitor it, which could cause issues. Having the monitoring perhaps on by default would be good, but besides space issues, I don't see anything else that could be improved.

I have been working with Kpow for Apache Kafka for around ten years, on and off, as I worked extensively on it about ten years ago and then again in the meantime.

I have not used Kpow for Apache Kafka consumer lag insights; I've seen it and heard about it, but I haven't used that so far. I've only used it where the messages are consumed into some other system that does something with the messages.

I can't really assess the product's ability to identify performance bottlenecks in Kafka clusters because I haven't managed the clusters myself too much. I would think it would be similar to how you scale and manage a Kubernetes  cluster, launching more pods or scaling out the cluster if the throughput is not high enough.

My thoughts on technical support involve finding a lot of information more from open-source forums and the internet; I think there is a company that does support, specifically Confluent , as a commercial provider for Kafka that could be used for support, but I haven't worked on any support issues. Most of the issues are what people find online regarding managing Kafka.

I would rate the work of support as typically a six or a seven based on open-source information.

The deployment for Kpow for Apache Kafka can take just minutes for local setup; setting it up in a clustered environment might take a couple of hours, but for anyone knowing how to do that, once you know how to set it up in a Kubernetes  cluster or just with a Kafka cluster, then that should take minutes.

One person can do it; it should be quite simple for one person to set up.

I am saying that the cloud version is quite expensive, and there's room for improvement since I've set up a test cluster on my own AWS  account, and within the first couple of days, it already accumulated a bill close to $200-$300 with no activity on the cluster. If I didn't stop it that month, I would have gotten a bill close to $1,000 and it wasn't doing much.

I am talking about the public cloud, AWS , which is quite expensive even if you don't run much on the topics or so, and so I shut it down there.

I understand it was not purchased through AWS Marketplace ; I just set up via the console, a test cluster, you set up a Kafka test cluster as you would set up an instance, and they bill you for that, which turned out to be quite expensive, as many of the latest services on AWS, especially database services also, RDS  or so.

I have thought of typical alternatives to Kpow for Apache Kafka, including RabbitMQ or IBM MQ  depending on whether an organization is using IBM MQ; ActiveMQ  is also a popular alternative, and AWS has Kinesis  that can be used for streaming of messages.

I did not face any challenges during deployment with Apache SkyWalking ; it was quite straightforward. I haven't worked with that.

I have not worked with telemetry tools, and I haven't used those.

The product's adaptability is quite important for my organization as that's the central part of how the information from external systems are processed.

I would rate this product nine out of ten overall.

On-premises

Amazon Web Services (AWS)

My main use case for Kpow for Apache Kafka  is that it functions as a monitoring tool. It was developed by Factor House and is used to observe, inspect, manage, and grow Kafka clusters. These are the capabilities you can view through a basic UI at an enterprise level where you can see your Apache Kafka  infrastructure.

A specific example of how I use Kpow for Apache Kafka  to monitor or manage my Kafka clusters includes real-time visibility for healthcare, broken state, consumer logs, under-replicated partitions, and Kafka stream topology. It also supports Prometheus metrics for integration and Grafana  data logs. These are the aspects I have checked in terms of observability and monitoring. Apart from that, I also use it for some inspection and debugging.

I generally use Kpow for Apache Kafka to inspect, debug, and automate some processes for security purposes as well. The underlying single UI is also very good. Because of these capabilities, it is very feasible to use.

The best features Kpow for Apache Kafka offers that I have checked include a single UI, no extra infrastructure, powerful message search, security and compliance, multi-cluster operations, and operation efficiency. The handling of queues is very critical for my day-to-day work. With Kpow for Apache Kafka, you can monitor your Apache Kafka  infrastructure and add some integration. The UI is very good. These are the capabilities that I use day by day.

Kpow for Apache Kafka has positively impacted my organization by being easy to manage. The development capabilities are very good, making it easy to integrate. You can also monitor data diagnostics. These aspects are beneficial to my organization. It makes development faster for this purpose.

I believe Kpow for Apache Kafka is already in a pretty good state. However, the default resource allocation is very limited. I would suggest they increase the best resource requirements. The default requires around 2 GB to 8 GB, which is relatively high for a UI tool that could be scaled through one CPU to 2 GB for a single cluster.

I chose the number eight because it has a very good GUI for handling Apache Kafka. However, there are some improvements that should be made. Since it is not a free tool and you have to pay for it, there is no testing possible without paying something. This is not ideal for those who want to try the free version.

There are no other improvements needed for Kpow for Apache Kafka that I haven't mentioned.

I have been using Kpow for Apache Kafka for the last eight months since I started using Apache Kafka. I have used Kafka before.

Kpow for Apache Kafka is stable.

Kpow for Apache Kafka's scalability is quite good.

I have not received customer support for Kpow for Apache Kafka. However, I believe there is a very good UI available to ask for help with customer support.

I did not previously use a different solution.

My experience with pricing, setup cost, and licensing for Kpow for Apache Kafka is that pricing is quite reasonable. However, it should be open source so that everybody can at least use a free trial. Running the enterprise edition requires managing license details, some ID code, and structure signature, which involve administrative setup compared to open source utilities. Because of this, I believe it is both good and challenging in different ways.

Before choosing Kpow for Apache Kafka, I did not evaluate other options.

Regarding governance and security features, Kpow for Apache Kafka provides very good capabilities. I have not used all of them extensively, but the features I have used are very good. However, I am not completely sure about all the security features because we have not yet integrated them with our main systems.

Regarding Kpow for Apache Kafka's security capabilities, I would say the security features are quite good. They have included RBAC and multi-tenancy, data masking, audit logging, and SSO  integration. These features make the security purpose very adequate for my needs.

The accuracy and reliability of Kpow for Apache Kafka's output is very good.

Kpow for Apache Kafka makes development faster because integration with Kafka can be quite complex and requires significant research and development effort. However, with Kpow for Apache Kafka, you can use a simple integration process to handle all of these aspects. It is very good for easy development.

My advice to others looking into using Kpow for Apache Kafka is that it is a paid tool, so you will need to purchase it. If your infrastructure is very good and there are multiple queues and multiple things to manage, Kpow for Apache Kafka is very effective for handling and maintaining the infrastructure. The UI is very good. These aspects make it a very good tool for this purpose. I would rate this product an eight out of ten.

Private Cloud

Amazon Web Services  (AWS )

What do you like best about the product?

The most helpful about Kpow for Apache Kafka is the easy setup, support for multiple types of schemas (Avro, Protobuf and more), fair price, nice to use and clean UI.

What do you dislike about the product?

The downside of Kpow for Apache Kafka is the topic data inspection of some topics where when we don't inform the key and/or value deserializer the response show those fields as null, making it hard to know why the values are not being show.

What problems is the product solving and how is that benefiting you?

The main problems that Kpow for Apache Kafka is solving for us is the support to query topic with different types of schemas (Avro, Protobuf, etc) and the ease to setup in multiple environments.
Another plus is the free community edition version to use on the local environments for testing/debugging.

What do you like best about the product?

What we appreciate with kPow is that it gives you all the good features available in the market in one tool :
- Beautiful UI/UX like Kowl
- Efficient topic message searching like Kafka UI
- Excellent to watch and edit topics configuration, even better than Kafka UI
- Able to browse and edit schema registry efficiently like Kafka UI

And in addition, you got multiple bonus features :
- Useful and beautiful monitoring of cluster, connectors, consumers, etc...
- Better consumer offset reset management
- Fully customizable auth mechanism from very simple to very complex
- Fully integrated Kafka Stream topology display and monitoring using kpow-streams-agent
- Human support with excellent technical understanding
- Open about feature requests that can bring value to the product, with a good following after suggestion is made
- Open-minded about license pricing for a small-sized company
- And so on...

What do you dislike about the product?

As for me, the only downside of this tool is that you have to launch it on your own, using docker container, AWS Marketplace, etc...

I would love to have managed cloud offer where you give a way to connect to your Kafka Cluster (through VPC Peering for example) and everything is handled on kPow side :
- Create a custom VPC for the customer
- Mount a kPow instance on the VPC
- Create the peering between this VPC managed by kPow and your VPC
- Manage authentication/authorization using kPow online dashboard

Such offer could open great opportunities with, for example, a free community version (run on your own) and a priced cloud managed version.

What problems is the product solving and how is that benefiting you?

Our objective was to :
- Monitor our Kafka brokers' state
- Browse our current topics and their contents
- Follow the state of our consumers and manage their offsets

All these in an easy-to-use HMI without learning how to do it through complex Kafka command lines.