Best Kafka tools for NetApp Instaclustr managed Kafka

Tools compared

Rank	Tool	Total (out of 100)	Governance beyond Kafka ACLs	Out of the data path	Karapace and managed Connect	SCRAM and mTLS sign-in	Inspecting topic data	Clusters beyond Instaclustr	Cost a year, one cluster (modelled)
1	Kpow	88	RBAC, staged approvals, temporary access, masking, tenants, audit	One container, no external database, not a proxy	Both documented; connectors managed in the UI	SCRAM documented for Instaclustr	kJQ search, data inspect, Karapace decoding	Up to 12 clusters, any distribution	$7,380
2	AKHQ	72	Group roles, no masking	One container	Both, in Instaclustr's own guide	SCRAM, in Instaclustr's own guide	Message browsing	Named connections per cluster	$8,640
3	Kafbat UI	71	RBAC, global masking, opt-in audit	One container	Karapace; TLS truststore issues with Connect	SCRAM; TLS issues across components	Message browsing	Several clusters; Confluent Cloud breakage	$8,640
4	Lenses	64	SSO and RBAC from Team tier, audit	HQ on PostgreSQL plus an agent per cluster	In general; no Instaclustr guide	Standard client settings; no guide	SQL over topics	One agent per cluster	$20,882 before EC2 charges
5	Instaclustr console, API and Terraform	49	Kafka users and ACLs per application	Nothing to deploy	Provisions both; REST APIs to manage them	Creates the users and certificates	Metrics; records left to the CLI or another UI	Instaclustr clusters only	$11,520
6	Kafdrop	40	No sign-in, roles or audit	One process	Karapace only; no Kafka Connect	SCRAM through a properties file	Message browsing, no search	One cluster per deployment	$11,520
7	Conduktor	67	Strong; data-level controls through Gateway	Console on PostgreSQL; Gateway, a proxy, for data-level controls	In general; no Instaclustr guide	Standard client settings; no guide	Message browsing	Many providers from one Console	$32,880; $122,880 with Gateway Core and Protect

The tools, ranked for Instaclustr

What teams on NetApp Instaclustr managed Kafka need

NetApp Instaclustr runs open-source Apache Kafka for you, on AWS, Google Cloud, Azure or on-prem, and its console covers provisioning, Kafka users, firewall rules and cluster metrics. It does not give engineers a way to read the records in a topic, and it leaves the question of who may do what, once several teams share a cluster, to Kafka ACLs set per Kafka user. Everything on this page is about what a tool adds on top of the service, not about replacing it.

Three things come up once a team is running Instaclustr in production. The tool has to connect with the authentication the cluster already enforces, from an address the firewall rules allow. It has to understand the add-ons around the cluster, the Karapace Schema Registry and the managed Kafka Connect cluster, because otherwise engineers see undecoded bytes and manage connectors with curl. And it has to answer the governance questions Kafka ACLs leave open, because an ACL authorises the Kafka user that connects, and when twenty engineers share one tool that user is the tool’s. The paragraphs below take the six criteria in order of weight.

Governance beyond Kafka ACLs. Kafka ACLs on Instaclustr are managed through the Kafka CLI, the provisioning API or the Terraform provider, which suits applications. By default every Kafka user created in the Instaclustr console can read and write every topic in the cluster, according to Instaclustr’s user management documentation, unless it is created read-only or with no initial permissions. The example listing in Instaclustr’s ACL documentation shows a user with every operation allowed on every topic and every consumer group, and with Alter, AlterConfigs and ClusterAction denied on the cluster. In Apache Kafka’s table of operations and resources, deleting a topic is the Delete operation on that topic and committing offsets for a group is Read on that group. A tool connected as a Kafka user with the ACLs in that listing therefore passes on to everyone who signs in to it the ability to change any consumer group’s offsets and, where the cluster was created with topic deletion enabled, to delete any topic. What such a user cannot do is change ACLs or broker configuration, which need Alter and AlterConfigs on the cluster.

Narrowing those defaults at the broker works by subtraction. Instaclustr’s ACL documentation tells customers to think in terms of denying, because its users are allowed by default and a Deny rule takes precedence over an Allow. The Apache Kafka documentation treats Deny rules as something for the rare case where an Allow rule covers everyone but a few principals, so the case Apache calls rare is the ordinary one on Instaclustr. Each restriction is one Deny rule for one Kafka user on one resource, and the same Instaclustr page warns against using ACLs to grant more than its defaults. Roles in a tool work the other way round, since Kpow’s role-based access control implicitly denies every action that no policy allows. The narrowing for people is then written once against directory groups, and the cluster’s ACLs stay as Instaclustr set them.

Application access on Instaclustr can be declared as code, since Instaclustr’s Terraform provider has resources for Kafka users, ACLs, topics and client certificates, and the ACLs for services can then live in a repository and change through review. Engineers’ access has a different lifecycle, because people join and leave teams and need production for an hour at a time, and a Kafka ACL has no expiry, so it stays in force until someone removes it. ACLs also do not provide roles per person rather than per Kafka user, masking of sensitive fields, an approval step in front of offset resets and topic deletion, or an audit record of each engineer’s actions. Those are what a shared tool has to add once more than one team works on the same cluster, and the tools that manage ACLs themselves are compared in Kafka ACL management tools.

Teams in scope for PCI DSS get further controls from the platform. Instaclustr’s PCI Mode adds logging on the cluster, which its documentation describes as tracking every action taken by any user, and does not offer the PLAINTEXT listener, and its Karapace documentation requires that on such a cluster cardholder data and personal data never appear in a message schema. Those controls apply to the cluster, where whatever is recorded about a Kafka client identifies the Kafka user that connected. For work done through a shared tool that user is the tool’s, so which engineer opened a topic holding card numbers is still answered by the tool, through masking in data inspect and an audit log that names the person.

Out of the data path. Instaclustr’s case for managed open-source Kafka is that the provider runs the brokers to an availability SLA while the engine stays vanilla Apache Kafka. A tool that runs as a container next to the cluster and connects the way any Kafka client does adds nothing to the path producers and consumers take. A tool whose controls are enforced by a proxy that every client connects through becomes part of that path, with the trade-offs Kai Waehner’s review of Kafka proxies sets out, and it has to be sized, kept available and kept in step with every client upgrade, outside the provider’s SLA.

The joint Factor House and Instaclustr webinar, Migrating to open source Kafka, put a price on that SLA. At a business interruption cost of $25,000 an hour, an availability commitment of 99.9%, the level below which the Amazon MSK SLA starts to pay service credits, allows about 8.76 hours of downtime a year, or roughly $219,000 of accepted exposure, while 99.99% allows about $21,900 and 99.999% about $2,190. Managed-service commitments also carry exclusions, and the MSK SLA excludes unavailability that results from the customer’s own actions. A proxy that a team places in front of the brokers is the team’s own component, so its downtime is added to the figure the provider has committed to and is not covered by it.

Kpow is one container with no external database, installed in your own environment and out of the data path. Conduktor Console also connects to Instaclustr 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.

Where a tool runs also decides how many addresses the cluster’s firewall rules have to allow. Every address in a cluster’s rules is an address that can open connections to the brokers, so a command-line or desktop client on each engineer’s laptop is one rule per engineer, which is how the London workshop has each participant connect. A tool that runs beside the cluster is one rule, and engineers reach it over HTTPS with no route of their own to the brokers. Instaclustr runs clusters in its own cloud account or in the customer’s, and a cluster can be reached over a private network as well as over public addresses; Instaclustr’s Karapace guide, for example, connects to Kafka on port 9093 over the private network instead of 9092. A tool that connects as an ordinary Kafka client uses whichever addresses, port and security protocol the cluster’s Connection Info page gives, so it can run in the same cloud account or peered network as the cluster. On a cluster created with AWS PrivateLink, which Instaclustr builds on its Private Network Cluster feature, clients connect through a VPC endpoint, so the tool has to run inside the team’s own network. A self-hosted container does that, and a console hosted by its vendor needs a private connection of its own first.

Staying out of the path also covers where a tool keeps its state. Kpow holds its snapshots, metrics and audit log in internal topics that it creates on the first cluster it connects to, in the way a Kafka Streams application keeps its state in internal topics on the cluster. On Instaclustr that means the audit log is replicated by brokers Instaclustr operates, and it also means the topics use the cluster’s disk: Kpow’s system requirements put them at up to 10GB of replicated disk with the default retention of one week. A tool with a PostgreSQL database keeps that state in a second service the team provisions, backs up and upgrades.

Karapace and managed Connect. The add-ons are where Instaclustr tools diverge most. Instaclustr’s Karapace Schema Registry is chosen when the cluster is created and served over HTTPS with basic authentication, and the managed Connect cluster is driven through the Kafka Connect REST API, which Instaclustr’s own documentation calls with curl. Kpow and AKHQ cover both. Kafbat UI reads Karapace, with a truststore merge for TLS across several components, and Kafdrop reads Karapace but has no Kafka Connect support. Schema choices are compared more broadly in Kafka schema registry tools, and connector tooling in Kafka Connect monitoring tools.

Karapace is an open-source project that describes itself as a drop-in replacement for Confluent Schema Registry, compatible with Schema Registry 6.1.1 at API level, and its README lists caveats around schema normalisation and error messages. Instaclustr’s own Karapace example serialises with Confluent’s Avro serializer, so records carry the same wire format and a tool that speaks the Confluent registry API can decode them; the caveats are a reason to test schema registration and compatibility checks through the tool before relying on them. Karapace also cannot run beside Instaclustr’s older Kafka Schema Registry add-on on one cluster, and adding it to an existing cluster or migrating to it is a support request, so the choice is best made when the cluster is created.

Access to the registry is coarser than access to Kafka, because the registry is reached with one set of basic authentication credentials from the Connection Info page. Instaclustr’s user management documentation says its add-ons, the Karapace Schema Registry among them, do not support adding or deleting users, and that changing the password of a registry user restarts the service. Every application and tool therefore reads and writes schemas with the same credential, and the decision about which engineers may register, edit or delete a schema is made in the tool. Kpow has separate permissions for creating, editing and deleting schemas.

Instaclustr’s Kafka Connect documentation calls the Connect REST API with curl -k, the flag that curl’s manual describes as skipping verification of the server’s certificate, and notes that an HTTP client configured to verify the server needs the Connect cluster’s certificates from the Connection Info page. Tools inherit the same choice between an unverified connection and a truststore, which is the truststore merge Instaclustr’s guide to UI for Apache Kafka describes, and the settings Kpow uses for it are given further down this page.

Which connectors a managed Connect cluster can run is decided by the platform as well as by the team. Instaclustr bundles a set of connectors and loads custom ones from a storage bucket the customer owns, on Amazon S3, Azure Storage or Google Cloud Storage, and its documentation says that new accounts have to ask support to enable the custom connector feature. The Connect REST API lists the connector plugins a worker has installed, and the Apache documentation notes that the answer comes only from the worker that handles the request, so results can differ between nodes while new connector JARs are rolling out. A tool that lets an engineer pick a connector class and fills in that connector’s own configuration form shows what the cluster can run before anyone writes a configuration by hand.

SCRAM and mTLS sign-in. Instaclustr’s Kafka users sign in with SASL/SCRAM by default, SCRAM-SHA-256 in its connection examples, and a cluster with mutual TLS enabled can add certificate authentication, with each client certificate signed by the cluster’s own certificate authority. External traffic is blocked by default, so the address the tool runs from goes into the cluster’s firewall rules, and again into the rules for the Karapace and Kafka Connect add-ons if the tool uses them. Every tool on this page can connect that way, and the difference is in what is documented. Factor House publishes a Kpow guide for Instaclustr covering the brokers and both add-ons. Instaclustr itself has published guides to several tools: one to Operatr, from Operatr.IO (the company now called Factor House), in November 2019, and a three-part series in 2023 and 2024 on AKHQ, UI for Apache Kafka (the project Kafbat UI was forked from) and Kafdrop, each with its own limits on Instaclustr.

SCRAM authenticates the client and does not encrypt the connection. Instaclustr enforces SCRAM authentication on every Kafka cluster, while encryption between clients and brokers is an option chosen when the cluster is created, which is why a Connection Info page shows either SASL_PLAINTEXT or SASL_SSL. The Apache Kafka documentation’s security considerations for SCRAM say it should be used only with TLS encryption, to prevent interception of the SCRAM exchange. On a SASL_PLAINTEXT cluster every record an engineer opens in a tool crosses the network between the brokers and the tool unencrypted, so the tool belongs on the private network beside the cluster, or the cluster should be created with client to broker encryption.

An Instaclustr cluster with mutual TLS adds listeners on ports 9082 and 9083 beside the default 9092 and 9093, a client certificate has to be signed by the cluster’s own certificate authority, and the Kafka username has to match the certificate’s Common Name, because Apache Kafka takes the user name of a TLS client from the certificate’s distinguished name. Instaclustr’s mTLS documentation also says that a client certificate cannot be revoked, and that the equivalent is to change the Kafka ACLs of the user it belongs to. Removing a client from an mTLS cluster is therefore an ACL change, which is one more reason to give the tool a Kafka user of its own, since rotating or removing that user then touches no application.

Inspecting topic data. The Instaclustr console covers provisioning and metrics, and reading records is left to the Kafka CLI or a separate tool. In the joint webinar, Migrating to open source Kafka, Instaclustr’s solutions architect reported that teams which move from a proprietary platform to managed open-source Kafka miss the UI and the visibility of their data, because not every user of the platform is comfortable on the command line.

The console’s consumer group metrics have a defined scope as well. Instaclustr’s monitoring documentation describes them as collected for consumer groups that are live and consuming, summed per client ID for each topic, and available when Kafka is the offset store. Lag in Apache Kafka is a per-partition figure, the gap between a partition’s log end offset and the group’s committed offset, which is how the project’s own consumer group tooling reports it. The usual incident is one partition far behind while the rest have caught up, or a group whose consumers have all stopped, and a sum per client hides the first, while metrics collected for groups that are live and consuming are not the place to look for the second. A tool that computes lag from offsets for every partition and group, as Kpow does, shows that pattern, and its data inspect view then finds the record the group stopped on.

Clusters beyond Instaclustr. The joint webinar took a question on tooling for teams running several Kafka providers at once, as a team does for the length of a migration between them. A reader on Instaclustr may also have clusters on Amazon MSK or self-managed brokers, so one tool that reaches every cluster counts for something here, if less than governance and the data path.

Mixed topologies are a supported configuration on Instaclustr’s side too. Its managed Kafka Connect cluster can target a Kafka cluster that Instaclustr does not run, and its mirroring feature runs MirrorMaker 2 as connectors on that Connect cluster, in line with Apache Kafka, where MirrorMaker is built on the Kafka Connect framework. During a move onto Instaclustr or away from it, the replication that carries the migration therefore runs as connectors and tasks on the Connect cluster, and a tool that manages Connect lists them like any others, next to the topics and consumer groups of both clusters. MirrorMaker 2 translates consumer offsets between clusters, and KIP-1279 describes that translation as inherently lossy, which is why consumers can reprocess some records after a cutover. The same proposal adds cluster mirroring to Apache Kafka itself, which a provider that runs the open-source project can adopt once it ships. Because Instaclustr runs unmodified Apache Kafka, a tool that speaks only the Kafka protocol needs nothing specific to Instaclustr beyond the connection settings, and the same holds for whichever provider comes next.

Who runs Kpow on NetApp Instaclustr managed Kafka

No Kpow customer has yet described its Instaclustr setup in public, so this section names none. What is public is the record of the two companies working together. Instaclustr’s blog published a guide to running Operatr, from Operatr.IO (the company now called Factor House), on Instaclustr Managed Kafka in November 2019, noting that “all your data stays in Kafka internal topics, you never send your data out of the organization”. Instaclustr’s InstaBlinks video series devoted an episode to Apache Kafka and kPow in November 2021. The two companies presented Migrating to open source Kafka as a joint webinar in September 2026, with a Europe session of the same webinar, and Factor House’s hands-on workshops run Kpow against clusters on Instaclustr, with their material on GitHub.

How a team runs NetApp Instaclustr managed Kafka with Kpow

Installing it beside the cluster. A team runs Kpow from its Docker image, as a Java JAR on a virtual machine, or on Kubernetes with the Helm charts, in the same cloud region as the Instaclustr cluster. It needs no external database, because its state lives in topics on the Instaclustr cluster itself. The full walkthrough is Set Up Kpow with NetApp Instaclustr Platform.

Opening the firewall. Instaclustr blocks external traffic by default, so the address Kpow runs from is added under Firewall Rules in the Instaclustr console, for the Kafka cluster and separately for the Karapace Schema Registry and Kafka Connect if Kpow will reach them. The address to add is the one Kpow’s traffic leaves from. When Kpow runs in a private subnet or on Kubernetes on AWS and reaches the cluster over public addresses, that is the Elastic IP address of the NAT gateway and not the address of the container or pod. A missing or outdated rule shows up as a connection timeout, with no authentication error, so if Kpow times out on first start, check these rules first. On a cluster with Instaclustr’s Private Network add-on, Instaclustr’s documentation requires VPC peering to be set up before the Connect REST API can be reached, so the peering comes before Kpow’s first start.

Signing in to the cluster. The bootstrap addresses, Kafka user and password come from the cluster’s Connection Info page. Per Kpow’s Instaclustr documentation, Kpow connects with SASL_MECHANISM=SCRAM-SHA-256 and SECURITY_PROTOCOL set to SASL_PLAINTEXT or SASL_SSL, whichever Connection Info shows. A cluster with mTLS uses the standard SSL keystore settings in Kpow’s cluster configuration with the certificate Instaclustr signed, on the mTLS listener’s port, 9082 on public addresses and 9083 on private ones, and with a Kafka user whose name matches the certificate’s Common Name.

Giving Kpow its own Kafka user. The default ickafka user works for a first look, and a separate Kafka user for Kpow is the better arrangement afterwards, because rotating or removing it then affects no application. Instaclustr does not store new or changed Kafka passwords, and the ickafka credentials disappear from the Connection Info page once that user’s password is changed, so the password for Kpow’s user goes into the team’s secret store when the user is created. Kpow creates its internal topics on first start, so its Kafka user needs the Create operation on the cluster, or the topics created ahead of time. A team that wants the tool itself on least privilege can create the user with no initial permissions and add the minimum ACLs Kpow documents, and then one further ACL for each action it wants to allow, such as Read on a topic for data inspect.

Reading Karapace-encoded topics. With SCHEMA_REGISTRY_URL pointed at the Karapace endpoint secured with a CA-signed certificate and SCHEMA_REGISTRY_AUTH=USER_INFO, Kpow lists subjects and versions in its schema view, and data inspect shows Avro, JSON Schema and Protobuf records decoded, filtered across topics with kJQ. The public Kpow demo runs on Amazon MSK with AWS Glue, Karapace and Confluent schema registries, as the September 2026 product update describes, so the Karapace views can be seen before a trial.

Running the managed Connect cluster. With CONNECT_REST_URL, basic authentication and CONNECT_PERMISSIVE_SSL=true, Kpow manages connectors on the Instaclustr Connect cluster: it creates them, pauses, restarts and deletes them, edits their configuration with sensitive values redacted, restarts single tasks and shows the stack trace of a task in an error state, where Instaclustr’s own documentation starts connectors with a curl call to the REST API. With permissive SSL, Kpow’s counterpart to the -k flag in those curl calls, the connection to the Connect REST API is encrypted and Kpow does not check which server presented the certificate. Kpow’s Instaclustr guide notes that Instaclustr’s Connect REST endpoints often require it. The alternative in Kpow’s Kafka Connect configuration is a truststore holding the Connect cluster’s certificate from the Connection Info page, and the unverified connection matters less on a private network between Kpow and the Connect cluster than across public addresses.

Reading connector logs. Instaclustr’s troubleshooting page checks a connector’s status and restarts it with further curl calls, which Kpow does from the connector and task views above. Instaclustr can also ship the Connect cluster’s logs to a topic on the Kafka cluster, where its documentation reads them with a consumer, and with that option on, a connector’s log lines can be searched in data inspect by engineers who have no access to the Connect workers.

Managing ACLs without the CLI. Kpow’s ACL view lists, creates, clones and deletes Kafka ACLs, in Community and Enterprise, and records each change in its audit log, so a team that would otherwise run kafka-acls.sh against the cluster can manage the ACLs for its application users from the same place. Instaclustr gives its default ickafka user the right to change ACLs, so Kpow connected as that user can manage them, and Instaclustr asks for a support request before anyone grants more than its default privileges. Changing ACLs needs the Alter operation on the cluster, which the user in Instaclustr’s example listing is denied, so Kpow connected as a Kafka user with those ACLs lists ACLs and cannot change them, whatever role the engineer holds in Kpow.

Signing people in. Engineers sign in to Kpow through SAML, OIDC or LDAP, with Okta, Microsoft Entra ID or Keycloak, so access follows the company directory rather than a shared Kafka user.

Giving teams their own view of a shared cluster. Tenants limit which topics, groups and connectors each role can see, RBAC sets what each person may do, staged mutations hold an offset reset or topic deletion for approval, temporary policies grant production access that expires at a set time, and data policies mask sensitive fields in data inspect results.

Keeping the record and the metrics. The audit log records each action with the user from the identity provider, and a webhook sends those records to Slack, Microsoft Teams or any endpoint. Kpow’s consumer group lag and other computed metrics are exported to Prometheus, beside the broker metrics Instaclustr already serves from its own Prometheus endpoint, which Instaclustr’s documentation asks to be scraped no more often than every 20 seconds.

The London workshop repository runs most of these steps against Instaclustr clusters, from the firewall rules to webhooks, staged mutations, tenants, a custom connector and Prometheus, and is the quickest way to try them end to end.

No tool here leads on every criterion. Kpow governs people working through Kpow, so applications keep their own Kafka users and Kafka ACLs stay the control for them. Its Instaclustr documentation covers SCRAM, and an mTLS cluster takes the standard SSL settings with no Instaclustr-specific recipe. Lenses has the stronger query model with SQL over topics, AKHQ covers both add-ons for free in Instaclustr’s own guide, and the Instaclustr console needs nothing deployed at all.

Kpow live demo

See Kpow before pointing it at Instaclustr

The live Kpow demo needs no signup and runs on two Amazon MSK clusters rather than Instaclustr. Switch the cluster picker to MSK Primary to see its Kafka Connect cluster, browse topics, consumer groups and the Karapace schema registry, then open the audit log topic on MSK Secondary.

For platform teams choosing a Kafka tool for Instaclustr.

Try the Kpow demo→

FAQ

What is the best Kafka UI for NetApp Instaclustr?

On this page’s rubric, Kpow, with 88 of 100 points: it connects over SASL/SCRAM with documented settings, manages the Karapace Schema Registry and the managed Kafka Connect cluster, adds per-person roles, masking, approvals and an audit trail on top of Kafka ACLs, and runs as one container beside the cluster outside the data path. AKHQ is the highest-scoring free open-source option, at 72.

Which Kafka UIs has NetApp Instaclustr published guides for?

Instaclustr’s blog has published guides for Operatr, from Operatr.IO, the company now called Factor House (2019), AKHQ (2023), and UI for Apache Kafka, the project Kafbat UI was forked from, and Kafdrop (both 2024). Its guides describe the Instaclustr console as built for provisioning and monitoring and point to a separate UI for working with Kafka data. Factor House documents Kpow on Instaclustr in its own Instaclustr guide, and on this page’s rubric Kpow scores highest, with AKHQ the highest-scoring free option.

Does the Instaclustr console show messages in a topic?

No. Instaclustr’s own blog describes its console as designed for provisioning and monitoring, with limited Kafka-specific features, and topics, ACLs and users are managed through the console, the provisioning API, the Terraform provider or the Kafka CLI. Reading or searching records needs the Kafka CLI or a separate tool.

Which Kafka UI works with the Instaclustr Karapace Schema Registry?

Kpow, AKHQ, Kafbat UI and Kafdrop all have published settings for it: Kpow in Factor House’s Instaclustr guide, and the other three in Instaclustr’s own blog series. Each needs the address it runs from added to the Karapace Schema Registry’s allowed addresses in the cluster’s firewall rules, and the registry’s basic authentication credentials.

Can a Kafka UI manage Instaclustr’s managed Kafka Connect?

Yes. Kpow creates, edits, pauses, restarts and deletes connectors on the Instaclustr Connect cluster and shows task stack traces, and AKHQ shows connectors and tasks per Instaclustr’s guide. Instaclustr’s guide to Kafdrop states that Kafka Connect is not supported.

How do I manage Kafka ACLs on Instaclustr without the CLI?

Kpow’s ACL view lists, creates, clones and deletes Kafka ACLs in both Community and Enterprise and records each change in its audit log, so a team connected as a Kafka user that may change ACLs, such as Instaclustr’s default ickafka user, manages them without kafka-acls.sh. Instaclustr also manages ACLs through its provisioning API and Terraform provider, and its documentation warns that granting more than its default privileges could leave a cluster unrecoverable and outside its SLA.

Why can’t my Kafka UI connect to Instaclustr?

Usually the firewall. Instaclustr blocks external traffic by default, so the address the tool runs from has to be added to the cluster’s firewall rules, and separately to the rules for Karapace and Kafka Connect. After that, check that the security protocol matches the one on the Connection Info page, SASL_PLAINTEXT or SASL_SSL.

Can a Kafka UI connect to an Instaclustr cluster on a private network or in my own cloud account?

Yes, if it connects as an ordinary Kafka client. Kpow takes the bootstrap addresses, port and security protocol from the cluster’s Connection Info page, so it can run in the same cloud account or peered network as the cluster, whether Instaclustr runs the cluster in its own account or in yours. The address Kpow connects from still goes into the cluster’s firewall rules.

What can a default Instaclustr Kafka user do?

Instaclustr’s user management documentation says every Kafka user created in its console can read and write all topics unless it is created read-only or with no initial permissions, and the example listing in its ACL documentation shows a user allowed every operation on every topic and consumer group and denied Alter, AlterConfigs and ClusterAction on the cluster. A Kafka UI connected as a user with those ACLs can therefore browse every topic and change any consumer group’s offsets for whoever signs in to it, and it cannot change ACLs or broker configuration. Restricting it at the broker means adding Deny rules, and restricting what each person can do means roles in the tool.

Does SASL/SCRAM encrypt traffic to an Instaclustr cluster?

No. SCRAM authenticates the client, and encryption between clients and brokers is a separate option chosen when the cluster is created, which is why the Connection Info page shows SASL_PLAINTEXT or SASL_SSL. The Apache Kafka documentation says SCRAM should be used only with TLS encryption. On a SASL_PLAINTEXT cluster, run the tool on the private network beside the cluster, because the records engineers open travel between the brokers and the tool unencrypted.

Can a client certificate be revoked on an Instaclustr mTLS cluster?

Not according to Instaclustr’s mTLS documentation, which says there is no way to revoke client certificates and that the same result comes from changing the Kafka ACLs of the user the certificate belongs to. The certificate has to be signed by the cluster’s own certificate authority, and the Kafka username has to match the certificate’s Common Name.

Why do Instaclustr’s Kafka Connect examples use curl -k?

The -k flag makes curl skip verification of the server’s certificate, and Instaclustr’s documentation notes that a client configured to verify the server needs the Connect cluster’s certificates from the Connection Info page. Kpow’s equivalent is CONNECT_PERMISSIVE_SSL=true, and the alternative is a truststore set in its Kafka Connect configuration.

Is there a free Kafka UI for Instaclustr?

Kpow Community Edition is free on up to 3 clusters and 10 users, lists NetApp Instaclustr among its supported providers, and includes Kafka Connect and schema registry management. AKHQ, Kafbat UI and Kafdrop are open source, and Instaclustr has published a guide for each. RBAC, masking, staged approvals and the audit log need Kpow Enterprise. More free options are compared in the best free Kafka UI tools.

Does a Kafka UI need to sit in the data path to govern access on Instaclustr?

No. Kpow runs as one container, connects to Instaclustr 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 Instaclustr runs. Conduktor Console also connects directly, while Conduktor’s data-level controls run in Gateway, a Kafka proxy that client applications connect through.

Can one Kafka tool manage Instaclustr and Amazon MSK together?

Yes, if the tool is vendor-agnostic. Kpow manages Instaclustr beside MSK, Confluent and self-managed Kafka from one deployment, up to 12 clusters per instance. The MSK side is covered in the best Kafka UI tools for Amazon MSK.

How do I monitor consumer lag on Instaclustr?

Kpow computes consumer group lag and exports it, with its other computed metrics, to Prometheus, beside the broker metrics Instaclustr serves from its own Prometheus endpoint. Other options are compared in Kafka consumer lag monitoring tools.

How these tools were scored

Four of the six criteria start from Instaclustr’s own documentation; the other two are where the tool runs and whether it reaches clusters beyond Instaclustr. 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. Where an option is scored on the same criterion on another Factor House page, it carries the same score here.

1. Governance beyond Kafka ACLs (counts three times). A Kafka ACL decides what a Kafka user may do. It has no per-person view of data, no masking, no approval step before a topic is deleted and no audit trail of what an engineer looked at. This criterion scores per-person roles, production access granted on request and expiring, masking, directory sign-in, tenants for teams sharing a cluster, and an audit trail that names the person. The requirements for regulated teams are covered in Kafka governance tools for financial services, and the masking options are compared in Kafka data masking tools.

2. Out of the data path (counts twice). The tool should run in your own environment, reach the brokers as an ordinary Kafka client through the cluster’s firewall rules, 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 a component on the brokers 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, here the Instaclustr console. This criterion is scored the same way on every Factor House page that uses it, and only its weight changes with the reader.

3. Karapace and managed Connect (counts twice). Instaclustr’s Karapace Schema Registry add-on holds the schemas most Instaclustr teams serialise against, and its managed Kafka Connect cluster runs connectors started through the Kafka Connect REST API. A tool scores well here when its settings for both are documented on Instaclustr and it manages connectors and schemas in its own interface, rather than leaving them to curl.

4. SCRAM and mTLS sign-in (counts once). Instaclustr’s Kafka users sign in with SASL/SCRAM by default, and mutual TLS is an option per cluster. A tool scores well when its settings for Instaclustr are published, by its own vendor or by Instaclustr, and lower when it is possible but undocumented or recorded with connection issues.

5. Inspecting topic data (counts once). The Instaclustr console shows cluster metrics, not records. Reading a message, searching a topic for one key or tracing a stalled consumer to the record that caused it is the day-to-day job engineers need a tool for.

6. Clusters beyond Instaclustr (counts once). Teams on Instaclustr often run other Kafka beside it, or are moving between providers. One deployment of the tool should reach all of them. It is scored as the banking page scores “On-prem and cloud together”, and Kafdrop, which that page does not rank, carries the multi-cluster score of 1 it has on Factor House’s Kafka UI comparisons.

Costs are modelled for one production Instaclustr 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. AKHQ and Kafbat UI carry 6 hours a month, $8,640 a year, to run, secure and keep current, and Kafdrop 8 hours, $11,520, the class for tools with no access control of their own, which here means a proxy in front of it for sign-in. The Instaclustr console has no separate licence and nothing to run, and the Kafka CLI it leaves record reading to is modelled like the other tools with no access control of their own, at 8 hours a month, $11,520 a year. Kpow’s $7,380 uses the published price of $4,500 per cluster a year with 100 users included. Kpow Community Edition is free for 3 clusters and 10 users, so a 25-engineer team is on Enterprise. Lenses’ Team licence stops at 15 users on one cluster, so Lenses is priced at its smallest AWS Marketplace listing, $2.055 an hour on t2.large before the EC2 charge; a team running it outside AWS gets a quoted licence instead.

The criteria map onto Instaclustr’s features in the figure below.

F1 From Instaclustr feature to what a Kafka tool has to do

What Instaclustr does What the tool has to do

Firewall rules External traffic is blocked until an address is added to the cluster's firewall rules, separately for Kafka, Karapace and Kafka Connect Run from a known address and connect with ordinary client settings once that address is allowed

SASL/SCRAM and mTLS Kafka users sign in with SASL/SCRAM by default, and mTLS-enabled clusters can add client certificates signed by the cluster's own CA Take the credentials from the Connection Info page and connect like any Kafka client

Karapace Schema Registry An add-on chosen when the cluster is created, served over HTTPS with basic authentication Read, register and decode schemas from the Karapace endpoint

Managed Kafka Connect A separate Connect cluster whose connectors are started through the Kafka Connect REST API Show connectors and tasks and manage them without curl

Kafka ACLs Managed through the Kafka CLI, the provisioning API or the Terraform provider When people share one tool, add per-person roles, masking and an audit trail, because the Kafka user is the tool's

Where the tool runs Brokers run in Instaclustr's account or your own, and producers and consumers connect to them directly Run beside the cluster as an ordinary Kafka client, not as a proxy that applications route through

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: Governance beyond Kafka ACLs counts three times, Out of the data path counts twice, Karapace and managed Connect counts twice, SCRAM and mTLS sign-in counts once, Inspecting topic data counts once and Clusters beyond Instaclustr counts once, for a total out of 100. Governance beyond Kafka ACLs counts three times because on a shared Instaclustr cluster a tool connects as one Kafka user, so per-person roles, production access granted on request, masking, directory sign-in, tenants for shared clusters and a per-person audit trail are the only record of which engineer did what. Out of the data path and Karapace and managed Connect count twice: a tool that clients connect through becomes part of the path every producer and consumer depends on, a tool with a database of its own is one more component to run and secure, and a tool that cannot read Karapace schemas or manage the Connect cluster leaves two Instaclustr add-ons to curl. SCRAM and mTLS sign-in, inspecting topic data and reaching clusters beyond Instaclustr count once, because most tools here pass them. 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 88 out of 100. The other options follow by total. Conduktor is listed last whatever its total; on its total of 67 it would place fourth.

Related reading

• Kafka: the complete guide
• Kafka-compatible cloud brokers
• Set Up Kpow with NetApp Instaclustr Platform
• Migrating to open source Kafka: cutting TCO without the operational burden
• Best Kafka UI tools for Amazon MSK
• Best Kafka management tools for banks
• Best tools to manage multiple Kafka clusters from one place
• Best Kafka management tools