The best Kafka UI tool for IBM Event Streams connects with the same SASL and TLS settings IBM asks of every Kafka client and reads schemas through the registry’s Confluent-compatible endpoint. It lets an engineer into production for a set task, holds risky changes for approval, keeps an audit trail that names each person rather than the tool’s own credential, and runs as one container beside the cluster, out of the data path. Kpow, IBM’s own Event Streams UI, Kafbat UI, AKHQ, Lenses, Redpanda Console and Conduktor each cover part of that. Scored on the six weighted criteria explained below the rankings, Kpow ranks first with 87 out of 100, ahead of the IBM Event Streams UI at 66 and Kafbat UI at 65; Conduktor, listed last, totals 56.
Tools compared
| Rank | Tool | Total (out of 100) | Out of the data path | Production access on request | Audit trail per person | Directory and Kafka sign-in | Many teams, shared clusters | Fit with IBM Event Streams | Cost a year, one cluster (modelled) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Kpow | 87 | One container, no external database, not a proxy | Temporary policies, staged approvals, masking | Every action and data read, by user | SAML, OpenID, LDAP | Tenants per team | Standard Kafka API and Confluent-compatible registries; no Event Streams guide | $7,380 |
| 2 | IBM Event Streams UI | 66 | Part of the instance, nothing to deploy | IAM roles and ACLs, no approvals or masking | IAM user or Kafka principal, read outside the UI | IBM Cloud IAM; Keycloak or SCRAM on Cloud Pak | One instance per UI | IBM's own interface to the service | $0, included |
| 3 | Kafbat UI | 65 | One container | Read-only clusters, no approvals | Opt-in log, no view in the product | OAuth2, OIDC, LDAP | Roles per resource | Kafka API and registry, no Event Streams guide | $8,640 |
| 4 | AKHQ | 57 | One container | Group roles, no approvals | Opt-in topic, no reads | LDAP, OIDC | Regex groups | Kafka API and registry, no Event Streams guide | $8,640 |
| 5 | Lenses | 52 | HQ on PostgreSQL plus an agent per cluster | Global masking, no approvals | In-product audit log | SSO from Team tier | Group roles | Any Kafka-compatible API | $6,880 for 15 users; custom above |
| 6 | Redpanda Console | 47 | One container | None in the free build; RBAC licensed | No record on non-Redpanda brokers | OIDC (Enterprise) | One cluster per deployment | Kafka API and registry, no Event Streams guide | $8,640 plus an unpublished licence for sign-in and RBAC |
| 7 | Conduktor | 56 | Console on PostgreSQL; Gateway, a proxy, for data-level controls | Masking exemptions, owner approval | 70+ event types in the UI | LDAP, OIDC | Groups; Virtual Clusters need Gateway | Any Kafka 2.5+; Gateway on Event Streams undocumented | $32,880; $122,880 with Gateway Core and Protect |
The tools, ranked for IBM Event Streams
Rank 1 Kpow
87 out of 100 Total
Try Kpow in the live demo No signup needed.
- Cost a year
- $4,500 per cluster with 100 users included, plus about $2,880 in operator time, so $7,380 on one cluster (modelled)
- On IBM Event Streams
- Standard Kafka client settings and Confluent-compatible registries; no Event Streams guide
- Deployment
- One container or JAR, no external database
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Directory and Kafka sign-in
- 9 out of 10
- Many teams, shared clusters
- 9 out of 10
- Fit with IBM Event Streams
- 6 out of 10
Why these scores for Kpow
- Out of the data path 9 out of 10
- It is one container or JAR whose snapshots, metrics and audit log live in topics on your own cluster, and it connects to Event Streams as an ordinary Kafka client, so nothing sits between your applications and the brokers.
- Production access on request 9 out of 10
- Temporary policies grant time-boxed access that an admin or a change system calling the Kpow API can create, staged mutations hold any action for approval, and data policies mask fields in inspection, though masking is per resource rather than per viewer.
- Audit trail per person 9 out of 10
- Every action is recorded with the user from the identity provider and the policy that allowed it, including data inspect queries, with a seven-day view in the product, the record written to an audit topic on your own cluster, and webhooks that send it to a SIEM for long-term retention.
- Directory and Kafka sign-in 9 out of 10
- People sign in with SAML, OpenID or LDAP, and Kpow connects to Event Streams with the SASL and TLS settings any Kafka client uses.
- Many teams, shared clusters 9 out of 10
- Tenants scope each team to its own topics, consumer groups and connectors on a shared cluster, and RBAC adds Allow, Deny or Stage per action.
- Fit with IBM Event Streams 6 out of 10
- Kpow’s documentation says it is compatible with Apache Kafka 1.0 and later and lists Confluent-compatible registries, Apicurio among them, as supported, which covers what Event Streams exposes for schemas; Event Streams is not on its tested-compatible list and has no provider page, so the fit is held at partial support that the reader verifies.
On IBM Event Streams. Kpow’s Kafka cluster documentation states compatibility with Apache Kafka 1.0 and later and takes the standard client security settings, such as SECURITY_PROTOCOL, SASL_MECHANISM and SASL_JAAS_CONFIG, which is how IBM’s own client configuration guide asks every Kafka client to connect. Its schema registry documentation supports Confluent-compatible registries, including Apicurio Registry, which Event Streams uses on Cloud Pak, while IBM Cloud exposes a Confluent-compatible endpoint. What the documentation does not cover: Event Streams is not on the list of platforms Kpow has been tested with, and there is no Event Streams provider page or worked example.
Where it falls short. Kpow works through the standard Kafka API and does not manage anything specific to Event Streams, such as IAM policies, geo-replication, Event Endpoint Management or the Event Streams custom resources, which stay with IBM’s own tooling. IBM Cloud’s registry implements only part of the Confluent API, so registry features beyond reading subjects and schemas are for a team to test. Kpow governs people working through Kpow, so applications keep their own credentials. RBAC, masking, staged mutations and the audit log need Kpow Enterprise; Community Edition is free for 3 clusters and 10 users.
Compare Kpow vs Kafbat UIKpow vs AKHQ
Rank 2 IBM Event Streams UI
ibm.com
66 out of 100 Total
- Cost a year
- $0 licence and nothing extra to run; included with Event Streams
- Sign-in
- IBM Cloud IAM on the managed service; Keycloak or SCRAM credentials on Cloud Pak
- Deployment
- Part of each Event Streams instance
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 10 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 3 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 5 out of 10
- Directory and Kafka sign-in
- 6 out of 10
- Many teams, shared clusters
- 4 out of 10
- Fit with IBM Event Streams
- 10 out of 10
Why these scores for IBM Event Streams UI
- Out of the data path 10 out of 10
- It comes with each Event Streams instance, so there is nothing separate to deploy and nothing between clients and brokers, which makes it the best on this criterion.
- Production access on request 3 out of 10
- Access follows IAM roles per cluster, topic and group on IBM Cloud, while on Cloud Pak a Keycloak user needs the eventstreams-admin or admin role to use the UI, which opens every panel, and IBM’s documentation describes no masking of fields, no approval step before a change and no access that expires on its own.
- Audit trail per person 5 out of 10
- IBM Cloud records management activity with the user ID or service ID, and message audit events can be switched on per topic on the Enterprise plan, aggregated per initiator over an hour; on Cloud Pak, broker audit records name the Kafka principal and are sent to a separate log aggregator, so neither record is read in the UI itself.
- Directory and Kafka sign-in 6 out of 10
- Engineers sign in with their own IBM Cloud identity on the managed service, and on Cloud Pak through Keycloak or with a Kafka user’s SCRAM credentials, which ties UI sign-in to Kafka credentials unless Keycloak is set up.
- Many teams, shared clusters 4 out of 10
- IAM policies and Kafka ACLs can be scoped to topic names, but each UI belongs to one Event Streams instance and there is no tenant view of a team’s own resources.
- Fit with IBM Event Streams 10 out of 10
- It is IBM’s own interface to the service, covering topics, message browsing, schemas, geo-replication and credentials, the widest coverage of Event Streams on this page.
What it covers. IBM’s Event Streams overview describes an administrative UI for managing production clusters that handles topic lifecycle control, message filtering and browsing, client metric analysis, schema and geo-replication management, and connection details and credentials generation. On IBM Cloud, the service’s access model assigns Reader, Writer and Manager roles per cluster, topic, consumer group and transaction ID.
Where it falls short. Each UI reaches the one Event Streams instance it belongs to, so a team that also runs Kafka elsewhere needs a second tool. IBM’s documentation describes no field masking, no approval in front of a destructive change and no access that expires, and the audit records live in IBM Cloud Logs or an external log aggregator rather than in the UI.
Rank 3 Kafbat UI
65 out of 100 Total
- Cost a year
- $0 licence, about $8,640 in operator time (modelled)
- On IBM Event Streams
- Kafka API and Confluent-compatible registry; no Event Streams guide
- Sign-in
- OAuth2, OIDC and LDAP, free
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 6 out of 10
- Fit with IBM Event Streams
- 5 out of 10
Why these scores for Kafbat UI
- Out of the data path 9 out of 10
- It is one stateless container with no database and no proxy, the same pass as Kpow.
- Production access on request 4 out of 10
- RBAC grants actions per resource and a cluster can be set read-only, but there is no approval step, no time-boxed grant, and its masking applies the same way to every viewer.
- Audit trail per person 6 out of 10
- Its audit log names the logged-in user and records reads when the level is set to ALL, but it writes to a topic or the console with no view in the product, so reading the trail is something you build.
- Directory and Kafka sign-in 7 out of 10
- It supports OAuth2 and OIDC, including Microsoft Entra ID, and LDAP or Active Directory, and its documentation does not list SAML.
- Many teams, shared clusters 6 out of 10
- Roles scope permissions per resource and list the clusters they apply to, with no tenant view of a team’s own resources.
- Fit with IBM Event Streams 5 out of 10
- It can reach Event Streams through the Kafka API with SASL settings and read a Confluent-compatible registry like any Kafka cluster, but publishes no Event Streams guidance, so the fit is yours to verify.
On IBM Event Streams. Kafbat UI treats Event Streams as one more Kafka cluster: a bootstrap address, SASL and TLS properties, and a Confluent-compatible schema registry. Its feature list covers topic and message browsing, consumer groups, schemas and Kafka Connect. The Kafbat UI review covers its RBAC and release history in detail.
Where it falls short. There is no way to grant production access for an hour and have it expire, no approval before a change runs, and masking cannot exempt the team that owns the data. No vendor is under contract to ship fixes. Its modelled running cost on one cluster is 6 engineer-hours a month, $8,640 a year at $120 an hour.
Rank 4 AKHQ
57 out of 100 Total
- Cost a year
- $0 licence, about $8,640 in operator time (modelled)
- On IBM Event Streams
- Kafka API and Confluent-compatible registry; no Event Streams guide
- Security default
- Disabled until you enable it
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 3 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Directory and Kafka sign-in
- 6 out of 10
- Many teams, shared clusters
- 5 out of 10
- Fit with IBM Event Streams
- 5 out of 10
Why these scores for AKHQ
- Out of the data path 9 out of 10
- It is one stateless container with no database and no proxy, the same pass as Kpow.
- Production access on request 3 out of 10
- Groups bind actions to resources by regex, but there is no approval step or time-boxed grant, masking is global, and without the JWT signing secret the restriction is in the UI only.
- Audit trail per person 4 out of 10
- Audit events are opt-in to a Kafka topic, reads are not recorded, and there is no view for the trail.
- Directory and Kafka sign-in 6 out of 10
- It supports LDAP, OIDC and header authentication from a proxy, does not list SAML, and ships with security disabled until you enable it.
- Many teams, shared clusters 5 out of 10
- Groups combine resource types with regex patterns on names and clusters, which limits what a role can reach, but there is no tenant view of a team’s own resources.
- Fit with IBM Event Streams 5 out of 10
- It connects to Event Streams as a named Kafka connection with ordinary client properties and reads a Confluent-compatible registry, with no Event Streams guidance of its own.
On IBM Event Streams. AKHQ connects to Event Streams as a named Kafka connection with the SASL and TLS properties IBM documents for every client, and the registry is configured as a Confluent-compatible endpoint. The AKHQ review covers the rest.
Where it falls short. Security is off until you configure it, the audit trail is an opt-in topic that does not record reads, and there is no approval step or time-boxed grant. Its modelled running cost on one cluster is 6 engineer-hours a month, $8,640 a year at $120 an hour.
Compare Kpow vs AKHQAKHQ review
Rank 5 Lenses
lenses.io
52 out of 100 Total
- Cost a year
- Team is $4,000 for up to 15 users on one cluster, $6,880 with operator time; 25 engineers needs a custom quote (modelled)
- On IBM Event Streams
- Any Kafka-compatible API, one agent per cluster
- Deployment
- HQ on PostgreSQL plus an agent and database per cluster
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 4 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 7 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 6 out of 10
- Fit with IBM Event Streams
- 5 out of 10
Why these scores for Lenses
- Out of the data path 4 out of 10
- It runs a central HQ on PostgreSQL plus an agent and an agent database beside every cluster, and HQ has no high-availability option.
- Production access on request 4 out of 10
- Its masking is the strictest view-time model, global with no escape even for admins, but no approval step or time-boxed grant is described.
- Audit trail per person 7 out of 10
- Audit logs can be read in the product, with no need to build a consumer first.
- Directory and Kafka sign-in 7 out of 10
- SSO spans Okta, Keycloak, OneLogin, Google and Entra ID, with basic authentication only on Community.
- Many teams, shared clusters 6 out of 10
- Roles attach to groups only, never to individuals, and no scoped view per team is described.
- Fit with IBM Event Streams 5 out of 10
- Lenses says it supports any Kafka-compatible API through its agent, and reads Confluent-compatible registries, but describes nothing specific to Event Streams.
On IBM Event Streams. Lenses connects to a Kafka cluster through an agent beside it, and SQL over topics is the centre of the product and the strongest query model on this page. The Lenses review covers its tiers and deployment.
Where it falls short. A central HQ on PostgreSQL plus an agent and an agent database for every cluster adds databases to run beside each Event Streams instance. The Team licence stops at 15 users on one cluster, so a larger team is on a custom quote.
Compare Kpow vs LensesLenses review
Rank 6 Redpanda Console
redpanda.com
47 out of 100 Total
- Cost a year
- $0 for the free build, about $8,640 in operator time (modelled); sign-in and RBAC need an unpublished Enterprise licence
- Licence
- Business Source License
- Clusters
- One broker cluster per deployment
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 2 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 2 out of 10
- Directory and Kafka sign-in
- 4 out of 10
- Many teams, shared clusters
- 3 out of 10
- Fit with IBM Event Streams
- 5 out of 10
Why these scores for Redpanda Console
- Out of the data path 9 out of 10
- It is a self-hosted container with no database, the same pass as Kpow.
- Production access on request 2 out of 10
- The free community build has no access control of any kind, and RBAC needs a Redpanda Enterprise licence, with no approval step or time-boxed grant described.
- Audit trail per person 2 out of 10
- Redpanda’s audit log is a feature of Redpanda’s own brokers, so on Event Streams Console keeps no record of who did what, with or without an Enterprise licence.
- Directory and Kafka sign-in 4 out of 10
- It connects to Kafka-compatible brokers over the standard SASL mechanisms, but OIDC sign-in for people requires an Enterprise licence and is its only single sign-on protocol.
- Many teams, shared clusters 3 out of 10
- RBAC is licence-gated and each deployment reaches one broker cluster, so there is no single policy across development, staging and production.
- Fit with IBM Event Streams 5 out of 10
- It reaches Event Streams through the Kafka API and a Confluent-compatible registry like any Kafka cluster, with no Event Streams guidance of its own.
On IBM Event Streams. Redpanda Console is Redpanda’s web console, source-available under the Business Source License, and it connects to Kafka-compatible brokers as well as Redpanda. Its message viewer is quick, with an observer mode that reads a topic without joining a consumer group. The Redpanda Console review covers the licence terms in detail.
Where it falls short. Governance is bought from Redpanda, a broker vendor, even on a cluster that runs no Redpanda broker: sign-in and RBAC need an Enterprise licence whose price is not published, and Redpanda’s audit log is a feature of its own brokers, so on Event Streams no licence gives Console a record of who did what. Each deployment reaches one broker cluster.
Rank 7 Conduktor
conduktor.io
56 out of 100 Total
- Cost a year
- 25 Console seats at $1,200 is $30,000 plus $2,880 operator time, so $32,880; Gateway Core adds $60,000 and Gateway Protect, which carries encryption and masking, a further $30,000 (modelled)
- On IBM Event Streams
- Any Kafka 2.5 or later; no Event Streams guide
- Deployment
- Console on PostgreSQL 13+; data-level controls through Gateway, a proxy
- Out of the data path ×3 weight, this criterion counts 3 times toward the total
- 3 out of 10
- Production access on request ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Audit trail per person ×2 weight, this criterion counts 2 times toward the total
- 8 out of 10
- Directory and Kafka sign-in
- 7 out of 10
- Many teams, shared clusters
- 7 out of 10
- Fit with IBM Event Streams
- 5 out of 10
Why these scores for Conduktor
- Out of the data path 3 out of 10
- Console needs PostgreSQL 13 or later, and its encryption, data-level masking and Virtual Clusters only work when client traffic goes through Gateway, a proxy in the data path.
- Production access on request 6 out of 10
- Masking can exempt users or groups, which beats every other tool here on who sees unmasked data, and cross-team access requests are approved by the owning team, but no expiring grant is described and topic creation that passes policy is a direct API call.
- Audit trail per person 8 out of 10
- Console logs produce, consume and admin requests across more than 70 event types with user, IP and timestamp, browsable in the UI and exported as CloudEvents.
- Directory and Kafka sign-in 7 out of 10
- Its SSO configuration covers LDAP and OIDC, with guides for Okta, Entra ID and Keycloak, and does not describe SAML.
- Many teams, shared clusters 7 out of 10
- Permissions are set per user or group across clusters, but a user in several groups inherits the most permissive grant, and Virtual Clusters for multi-tenancy need Gateway.
- Fit with IBM Event Streams 5 out of 10
- Conduktor states that Console works with any Kafka 2.5 or later and reads Confluent-compatible registries, and describes nothing specific to Event Streams; whether Gateway works in front of Event Streams is not documented.
On IBM Event Streams. Conduktor states that Console works with Confluent, MSK, Redpanda or any Kafka 2.5 and later. Conduktor’s Gateway documentation describes Gateway as a Kafka proxy between client applications and brokers, which is where its encryption, masking of the data itself and virtual clusters for multi-tenancy are enforced. The Conduktor review covers the rest.
Where it falls short. Console connects to Event Streams directly and needs PostgreSQL. Conduktor’s data-level controls, such as encryption, masking of the data itself and virtual clusters for multi-tenancy, run in Gateway, a Kafka proxy that client applications connect through, which puts Gateway in the data path in front of the Event Streams brokers. On AWS Marketplace, Conduktor Enterprise lists Console at $1,200 a seat for the first 100 seats, Gateway Core, which carries virtual clusters, at $60,000 a year, and Gateway Protect, the add-on for encryption and masking, at a further $30,000.
Compare Conduktor review
What teams on IBM Event Streams need
This page is about tools that sit beside an IBM Event Streams cluster: a UI for reading topics, managing consumer groups and schemas, and governing who does what. IBM Event Streams is built on open source Apache Kafka and comes in two forms: a fully managed service on IBM Cloud, and a deployment on OpenShift or other Kubernetes as part of Cloud Pak for Integration or Event Automation. The Cloud Pak form, in IBM’s Event Streams overview, incorporates the open source Strimzi project to deploy Kafka, so the tools on the Strimzi page face the same operator-managed clusters. IBM is also, since 17 March 2026, the owner of Confluent, as the IBM Newsroom announcement records, so one vendor now sells two Kafka platforms; what the IBM-Confluent deal means for Kafka users covers the questions that raises. A management tool that depends only on the Kafka protocol works the same on either, which keeps the choice of tool separate from the choice of platform. The practical rule is to use any provider’s protocol-level features freely and its proprietary ones knowingly, so the option to move stays open even if it is never used; Kai Waehner’s data streaming landscape for Q3 2026 maps who controls each part of the streaming stack today. The broader field of Kafka tools on any distribution is in the best Kafka management tools.
Out of the data path. IBM’s own answer to sharing topics with application teams is Event Endpoint Management, whose Event Gateways, in IBM’s words, are located between the Kafka clusters and the clients and apply the rules defined in the Event Manager. That is a deliberate design for publishing topics to consumers outside the platform team, and it means a team that uses it already runs one component in the data path. A management tool for the platform team should not add another, nor a database that must be backed up and patched beside each instance; Kai Waehner’s review of Kafka proxies weighs the use cases and trade-offs of putting a proxy between clients and brokers. Kpow is one container with no external database, installed in your own environment and out of the data path, and it does not replace Event Endpoint Management, which governs applications rather than the people operating the cluster. Conduktor Console also connects to Event Streams directly, with a PostgreSQL database of its own; Conduktor’s data-level controls, such as encryption, masking of the data itself and virtual clusters, run in Conduktor Gateway, a Kafka proxy that client applications connect through.
Each managed service publishes what it implements, and that table, read against a tool’s documented minimums, is the compatibility check rather than a vendor’s “works with” claim. IBM’s client configuration guide lists Kafka 3.8 on every IBM Cloud plan, Kafka Connect and Kafka Streams on the Enterprise and Standard plans but not on Lite, and ksqlDB on Enterprise only, and it requires every client to connect over TLS 1.2 with SASL PLAIN or SASL OAUTHBEARER. Managed services also restrict what clients may create, and that reaches any tool that keeps its own state in Kafka topics: on MSK Serverless, for example, only a short list of topic settings may be edited. On Event Streams the credential a tool connects with needs the IAM role or ACLs to create and write its own internal topics, which is worth settling before the first install.
Production access on request. A shared tool connects as one principal, so the cluster’s own authorisation cannot tell the engineers working through it apart. What a team needs from the tool is access to production for one task that then expires, and an approval step before a topic deletion or an offset reset runs. Temporary access narrows when and where a permission applies instead of widening who holds it, which keeps each person to the minimum authorisation needed, the principle of least privilege as NIST defines it. Those controls are compared across the field in Kafka RBAC tools.
Audit trail per person. IBM’s records name whoever presented the credential. On IBM Cloud, activity tracking for Event Streams records management events, and on the Enterprise plan message audit events can be enabled per topic, aggregated by initiator (user ID or service ID), operation and topic over a one-hour period. On Cloud Pak, the Kafka audit trail records the Kafka principal that initiated each request and has to be shipped to a separate log aggregator. A shared tool connects with one service ID or one KafkaUser, so in both records every action taken through it carries the tool’s name; which person read a topic or reset an offset has to come from the tool. Two logs then make one trail: the tool records who was allowed or denied what and what they did, and sign-in and session events stay in the identity provider’s own log, such as Microsoft Entra sign-in logs. The options are compared in Kafka audit logging tools.
Directory and Kafka sign-in. The tool has to connect to Event Streams the way IBM requires of every client, with an API key over SASL PLAIN or a bearer token over SASL OAUTHBEARER on IBM Cloud, and with mutual TLS, SCRAM-SHA-512 or OAuth on Cloud Pak, as IBM’s access documentation lists, while people sign in through the company directory. Large enterprises on Microsoft Entra ID can hit a limit in group-based roles: once a user belongs to more than 150 groups, Entra stops listing groups in the SAML token and sends a link to Microsoft Graph in their place, as the SAML token claims reference describes, so a role mapping that reads only the groups claim finds none. Checking that limit against the directory is part of choosing any tool that maps roles from groups.
Many teams, shared clusters. An Event Streams instance is usually shared by many application teams, and IBM scopes their access with IAM policies or Kafka ACLs on topic names. In the tool, each team needs its own view of its own topics, groups and connectors as well, and Apache Kafka’s multi-tenancy documentation describes what sharing takes on the broker side. When an action fails, the error should say which layer refused it: a denial from the tool’s own roles is fixed in the tool, while a Kafka TopicAuthorizationException means the tool’s own credential lacks a permission on the cluster, which on Event Streams is an IAM or ACL change.
Fit with IBM Event Streams. IBM Cloud’s registry, described in the Event Streams schema registry documentation, is included with the Enterprise plan and implements a subset of the API of version 7.2 of the Confluent Schema Registry at a /confluent path, intended in IBM’s words to provide limited compatibility with tooling designed for the Confluent registry; only the compatibility, config, schemas and subjects endpoints are implemented. A tool that reads schemas through the Confluent API can therefore browse subjects and decode records, but any feature that relies on other endpoints is for the team to test. On Cloud Pak, schemas live in Apicurio Registry. Registry tooling on any distribution is compared in Kafka schema registry tools.
No tool here leads on every point: IBM’s own Event Streams UI covers the service more completely than any third-party tool, Kpow has no Event Streams provider page or worked example, and Lenses has the stronger query model with SQL over topics. Kpow governs people working through Kpow, so applications keep their own credentials and IBM’s IAM policies and ACLs stay the control for them.
Who runs Kpow on IBM Event Streams
No Kpow customer has published an account of running Kpow on IBM Event Streams, and Factor House’s documentation does not list Event Streams among the platforms Kpow has been tested with. What the public record does show is how Kpow behaves on the platforms Event Streams resembles. Kpow’s tested-compatible list includes Red Hat AMQ Streams, another Strimzi-based distribution. For customer accounts of Kpow on those platforms, the Strimzi page carries Claritev and NORD/LB, the self-managed Apache Kafka page carries Gmarket and Claritev, and the Amazon MSK page carries Belong.
How a team runs IBM Event Streams with Kpow
Installing it beside the cluster. On Cloud Pak for Integration the natural place for Kpow is the same OpenShift cluster, installed with the Helm charts; beside the managed service on IBM Cloud it runs as one Docker container or Java JAR in the team’s own network. It needs no external database, because its snapshots, metrics and audit log live in topics on the cluster itself, so the credential it connects with needs rights to create and write those topics.
Connecting to the brokers and the registry. Kpow connects to Event Streams with the standard cluster settings: on IBM Cloud, SECURITY_PROTOCOL=SASL_SSL and SASL_MECHANISM=PLAIN, with the user value from the service credentials as the username and the API key as the password in SASL_JAAS_CONFIG, as IBM’s client configuration guide sets out for every client. A dedicated service ID with its own API key keeps the tool’s activity separate from any application in IBM’s activity records. The registry is added with SCHEMA_REGISTRY_URL set to the /confluent endpoint and the same credentials through SCHEMA_REGISTRY_AUTH, SCHEMA_REGISTRY_USER and SCHEMA_REGISTRY_PASSWORD (schema registry configuration). Data inspect then decodes Avro records with the registry’s SerDes, and engineers filter them across topics with kJQ. Because this is a configuration of general settings rather than a documented Event Streams integration, a team should confirm it on a non-production instance first.
Signing people in. Engineers sign in to Kpow through Okta, Microsoft Entra ID or another identity provider over SAML or OpenID Connect, or through LDAP, so access follows the company directory rather than a shared API key.
Giving teams their own view of a shared cluster. Tenants limit which topics, groups and connectors each role can see, and RBAC sets Allow, Deny or Stage per action and resource. IBM’s IAM policies or Kafka ACLs still decide what Kpow’s own credential can reach, so the tool can never grant more than the platform allows it.
Granting production access for one task. A temporary policy grants a role, such as the on-call engineers’ role, inspect access on a production topic for a set time and then expires, and staged mutations hold a topic deletion or an offset reset until an administrator approves it. Data policies mask sensitive fields in data inspect results on the server.
Watching lag. Kpow shows each consumer group down to partition level and resets, clears or skips offsets from the same view, and exports group lag with topic metrics to Prometheus, beside the metrics IBM provides for the service itself.
Keeping the record. The audit log records each action, data inspect queries included, with the user from the identity provider, and a webhook sends those records to Slack, Microsoft Teams or any HTTP endpoint, such as a SIEM collector, where they sit beside IBM’s own activity records for the service ID Kpow uses.
Running more than one platform. One Kpow instance manages up to 12 clusters, so an Event Streams instance, a self-managed Kafka cluster and a Confluent cluster sit in the same view, under the same roles and audit log, which IBM’s own UI, tied to one instance, does not offer.
Kpow live demo
See the Kpow UI before you connect Event Streams
The live Kpow demo runs on two Apache Kafka clusters on Amazon MSK, not on IBM Event Streams. It shows the views a team would use on any Kafka cluster: brokers, topics, consumer groups, schema registries and the __oprtr_audit_log topic where Kpow keeps its audit trail, with no signup. Connecting your own Event Streams instance is the step to try next.
For platform teams choosing a Kafka tool for IBM Event Streams.
Try the Kpow demoFAQ
What is the best Kafka UI for IBM Event Streams?
On this page’s rubric, Kpow, with 87 of 100 points: it connects to Event Streams as an ordinary Kafka client, adds time-boxed production access, approvals, masking, tenants and an audit trail that names each person, and runs as one container beside the cluster with no external database. IBM’s own Event Streams UI covers the service most completely and scores 66, and Kafbat UI is the highest-scoring free third-party option.
Does Kpow support IBM Event Streams?
Kpow’s documentation does not list IBM Event Streams among the platforms it has been tested with, and there is no Event Streams provider page. Event Streams runs Apache Kafka and asks clients to connect with standard SASL and TLS settings, which Kpow’s cluster configuration takes, and Kpow supports Confluent-compatible registries. A team should confirm the setup on a non-production instance.
Does Kpow work with the Event Streams schema registry?
Kpow’s schema registry documentation supports Confluent-compatible registries, including Apicurio Registry. IBM Cloud’s registry implements a subset of the Confluent Schema Registry 7.2 API at its /confluent path, so reading subjects and schemas is covered by that subset, and features that rely on other endpoints are for the team to test.
Why use a third-party tool when Event Streams has its own UI?
IBM’s UI is the most complete interface to one Event Streams instance. A third-party tool adds what IBM’s documentation does not describe: field masking, approval before a destructive change, access that expires, an audit trail that names the person rather than the credential, and one view across Event Streams and other Kafka clusters.
Does a Kafka UI need to sit in the data path to govern access on Event Streams?
No. Kpow runs as one container, connects to Event Streams like any Kafka client and applies roles, masking, approvals and the audit trail to the people working through it, so producers and consumers keep connecting straight to the brokers. IBM’s Event Endpoint Management uses gateways between clients and clusters to govern applications that consume shared topics, which is a separate job.
Is there a free Kafka UI for IBM Event Streams?
IBM’s Event Streams UI is included with the service. Kpow Community Edition is free on up to 3 clusters and 10 users, and Kafbat UI and AKHQ are open source. RBAC, masking, staged approvals and the audit log need Kpow Enterprise. More free options are compared in the best free Kafka UI tools.
How these tools were scored
Five of the six criteria are the ones Factor House scores on every page for teams that share a Kafka cluster; the sixth is fit with IBM Event Streams itself. They are listed here in order of weight. Each criterion is scored 0 to 10: 10 where a tool is the only one here doing it or clearly the best, 8 for a clean documented pass, 5 or 6 for partial support or support that needs work the reader must verify, 1 to 4 for a weak or indirect form, and 0 where it is absent.
1. Out of the data path (counts three times). The tool should run in your own environment, reach Event Streams over the same network your applications use as an ordinary Kafka client, and keep no data outside your own cluster. Scored lower: tools that need an external database of their own, and tools whose controls work only when application traffic passes through a vendor’s proxy. A self-hosted container with no external database and no proxy scores 9, a tool with a database of its own 6, one with several databases or an agent per cluster 4, and one that needs both a database and a proxy for its controls 3; 10 is kept for an option with nothing to deploy at all, which here is IBM’s own UI. This criterion is scored the same way on every Factor House page that uses it, and only its weight changes with the reader.
2. Production access on request (counts twice). Whether an engineer can be granted access to production for one task and have it expire, whether a destructive change can be held for a second person’s approval, and whether sensitive fields can be masked from people who do not need them.
3. Audit trail per person (counts twice). Whether the tool records each action, reads included, against the person from the identity provider, and whether that record can be read in the product and sent to the systems that keep it long term.
4. Directory and Kafka sign-in (counts once). Whether people sign in through SAML, OpenID Connect or LDAP, and whether the tool connects to Event Streams with the SASL and TLS settings IBM requires of every Kafka client.
5. Many teams, shared clusters (counts once). Whether each team can be given its own view of its own topics, consumer groups and connectors on a shared cluster, and whether one deployment reaches several clusters.
6. Fit with IBM Event Streams (counts once). Whether the tool’s own documentation, or IBM’s, covers Event Streams, and whether the tool reads schemas through the registry’s Confluent-compatible endpoint. A tool that can work through the standard API but is documented nowhere for Event Streams scores 5; Kpow scores 6 because its documentation names Apicurio Registry, which Event Streams uses on Cloud Pak, among the registries it supports; IBM’s own UI scores 10.
Costs are modelled for one production cluster and 25 engineers at $120 per engineer hour, using the same hours per tool class as Factor House’s other comparison pages. Tools with a licence carry the published price plus 2 hours a month to run. The open-source UIs carry 6 hours a month, $8,640 a year, to run, secure and keep current. Kpow’s $7,380 uses the published price of $4,500 per cluster with 100 users included. IBM’s Event Streams UI is included with the service at no extra cost. Lenses publishes a Team price of $4,000 a year for up to 15 users on one cluster, so 25 engineers is a custom quote. Conduktor’s Console is $1,200 a seat on AWS Marketplace, and its Gateway Core and Gateway Protect prices are added for the data-level controls; Conduktor prices Gateway per cluster with a 3-cluster minimum, and the listing does not say how many clusters that figure covers. Kpow Community Edition is free for 3 clusters and 10 users, so a 25-engineer team is on Enterprise. For free options compared at any team size, see the best free Kafka UI tools.
The criteria map onto Event Streams’ features in the figure below.
Every option is scored from 0 to 10 on each criterion, from the evidence and sources this page cites, and the reason for each score is on its card. The criteria are weighted: Out of the data path counts three times, Production access on request counts twice, Audit trail per person counts twice, Directory and Kafka sign-in counts once, Many teams, shared clusters counts once and Fit with IBM Event Streams counts once, for a total out of 100. Out of the data path counts three times. IBM's own governance layer for Event Streams, Event Endpoint Management, already places a gateway between clients and clusters for the topics it shares, so a management tool that adds a proxy or a database of its own adds one more component beside a platform that may already run one, and a tool that depends on nothing but the Kafka protocol carries over unchanged whichever of IBM's Kafka offerings, or anyone else's, the team runs next. Production access on request and the per-person audit trail count twice, because they decide whether a shared tool can be pointed at production at all: who could read or change it, and who actually did. Directory sign-in, shared clusters, and fit with Event Streams itself count once. This page is published by Factor House, which makes Kpow. Every option is scored on the same rubric and the same sources: Kpow's per-criterion scores are set the same way as every other option's and are not adjusted, and the weights apply to every option alike. Kpow ranks first on its total of 87 out of 100. The other options follow by total. Conduktor is listed last whatever its total; on its total of 56 it would place fifth.
Related reading
- Kafka: the complete guide
- What the IBM-Confluent deal means for Kafka users
- Best Kafka UI tools for Strimzi (Kafka on Kubernetes)
- Best Kafka management tools for Confluent Platform
- Best Kafka UI tools for Confluent Cloud
- Best Kafka UI tools for Amazon MSK
- Best Kafka tools for self-managed Apache Kafka
- Best Kafka management tools for banks