Best Flink management tool for platform teams serving many teams
ComparisonsA platform team running Apache Flink for many application teams needs each team to see and act on only its own jobs, every cluster in one view under one set of roles and tenants, routine work done without a ticket, and a tool that stays out of the data path. Of the six options scored here, Flex, Factor House’s management tool for Apache Flink, is the best fit: scored on the five weighted criteria explained below the rankings, it ranks first with 86 out of 100, ahead of Ververica Platform at 62, Apache StreamPark at 60, the Flink Kubernetes Operator at 58, Prometheus and Grafana at 40 and the Apache Flink Web UI at 29.
Tools compared
| Rank | Tool | Total (out of 100) | Many teams, shared clusters | Governance per person and job | One view across clusters | Out of the data path | Self-service for app teams | Cost a year (modelled) |
|---|---|---|---|---|---|---|---|---|
| 1 | Flex | 86 | Tenants by job, JAR and cluster | Deny by default; Allow, Deny or Stage per job | Each configured cluster in one UI | One container, no external database | Upload, submit, savepoint and stop own jobs | $14,730 for three clusters |
| 2 | Ververica Platform | 62 | Roles per Namespace | Roles per Namespace, not per job | One UI per installation | Platform with its own database | Editors run their own Deployments | $5,760 before the licence |
| 3 | Apache StreamPark | 60 | Teams as workspaces | Team admin and developer roles | Its own applications across clusters | Server with its own database | Teams build and deploy their applications | $5,760 |
| 4 | Flink Kubernetes Operator | 58 | Kubernetes namespaces and RBAC | Additive Kubernetes roles, no deny | One Kubernetes cluster, as resources | One deployment, no external database | Manifests per namespace, after platform setup | $2,880 |
| 5 | Prometheus and Grafana | 40 | Dashboards per team, not jobs | None over jobs | Metrics from every cluster | Time-series database of its own | Dashboards only | $14,400 |
| 6 | Apache Flink Web UI | 29 | One cluster per team | None | One UI per cluster | Nothing to deploy | Anyone can submit or cancel anything | $0 extra |
The tools, ranked for platform teams serving many teams
Rank 1 Flex
86 out of 100 Total
- Cost a year
- Enterprise from $3,950 per cluster a year with 100 users included, so $11,850 for Dev, UAT and Prod, plus about $2,880 in operator time, $14,730 in all (modelled)
- Tenancy
- Tenants by Flink job, JAR and cluster, assigned to directory roles (Enterprise)
- Deployment
- One container or JAR, no external database
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 9 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 8 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Self-service for app teams
- 7 out of 10
Why these scores for Flex
- Many teams, shared clusters 9 out of 10
- Tenants include or exclude Flink jobs and JARs by name, prefix or suffix, and whole clusters; a user working in a tenant sees only its resources, as a synthetic view of one cluster, and can only create resources valid to that tenant.
- Governance per person and job 8 out of 10
- Users are denied every action by default, and RBAC policies grant a role Allow, Deny or Stage on submitting, editing, terminating and deleting JARs for any cluster, one cluster or a named job, with Deny taking precedence where policies overlap.
- One view across clusters 9 out of 10
- Each cluster is added with its own
FLINK_REST_URL, repeated with_2,_3suffixes, Flex manages as many clusters as the licence permits, and tenants can span clusters, so one team’s jobs in Dev, UAT and Prod appear together in one UI. - Out of the data path 9 out of 10
- It runs as one container or JAR, has no dependency beyond the Flink clusters it reads, and calls their REST APIs, so it never sits between a job and its data; only the Flink Web UI, with nothing extra to deploy, scores higher.
- Self-service for app teams 7 out of 10
- A team allowed
FLINK_SUBMITuploads its own JARs and submits jobs from them, with a savepoint path to restore from, and a team allowedFLINK_JOB_EDITchanges its own jobs’ configuration and takes checkpoints and savepoints; Flex does not build jobs from source, keep jobs matching a manifest or create clusters, and tenants are set in the RBAC file by whoever runs Flex.
For a platform team. Flex’s multi-tenancy restricts what each role can see to the jobs, JARs and clusters its tenants include, and a user can hold several tenants and switch between them. Role-based access control then decides what each role may do to those jobs, from the authorization overview‘s deny-by-default starting point. Each Flink cluster is one entry in the Flink cluster configuration, so a platform team runs one Flex for its whole fleet.
Where it falls short. Flex’s multi-tenancy documentation marks multi-tenancy as an Enterprise feature and its RBAC documentation marks role-based access control as Team and Enterprise; the pricing page lists the free Community Edition at up to 3 clusters and up to 10 users, without SSO and role-based access control, and Enterprise from $3,950 per cluster a year with 100 users included, so tenants per team mean Enterprise. Tenants and policies live in one YAML file edited by whoever runs Flex, so application teams cannot create their own tenant, and the documentation shows no per-tenant quotas: a tenant decides what a team sees and does, not how much of a shared cluster its jobs may use. Flex does not build jobs from source, keep jobs matching a manifest automatically or create Flink clusters.
Rank 2 Ververica Platform
ververica.com
62 out of 100 Total
- Cost a year
- Licence priced on request and not published, plus about $5,760 in operator time for the platform and its database (modelled)
- Tenancy
- Namespaces with viewer, editor and owner roles, Stream Edition and above
- Deployment
- Helm chart into your Kubernetes cluster, with its metadata in SQLite or a remote database
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 7 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Self-service for app teams
- 9 out of 10
Why these scores for Ververica Platform
- Many teams, shared clusters 7 out of 10
- Namespaces are Ververica Platform’s stated means of isolating resources between groups of users, with roles scoped to each Namespace so that a role in one implies nothing in another, but roles stop at the Namespace rather than the Deployment.
- Governance per person and job 6 out of 10
- Viewer, editor and owner roles are bound per Namespace to users and groups, so who may act is decided per team rather than per job.
- One view across clusters 4 out of 10
- Each installation has its own web UI with its Namespaces inside it, so staging and production on separate installations, or a standalone Flink cluster beside them, mean separate UIs.
- Out of the data path 6 out of 10
- It is installed with a Helm chart into the team’s own Kubernetes cluster and stays out of the jobs’ data, but it persists its metadata through JDBC, in a remote database or locally in SQLite, the grade this criterion gives a tool with one database.
- Self-service for app teams 9 out of 10
- A Namespace editor has read and write access to every resource in the Namespace except Deployment Targets and API tokens, so an application team creates, upgrades and stops its own Deployments while the platform team keeps the targets they run on.
What it covers. Ververica’s Namespaces page calls Namespaces the primary means to isolate resources between groups of users and allow for multi-tenancy, and its authorization page scopes viewer, editor and owner roles to each Namespace. Its access control page says the feature is only available in Stream Edition and above. A team already on it is better served by the best Flink tools for Ververica Platform.
Where it falls short. Roles are set per Namespace rather than per job, each installation is its own UI, and it adds a database to run and back up. Ververica does not publish its prices, and adopting it means moving jobs onto its Deployment resource.
Rank 3 Apache StreamPark
60 out of 100 Total
- Cost a year
- $0 licence, about $5,760 in operator time for the server and its database (modelled)
- Tenancy
- Teams as workspaces, with team admin and developer roles
- Deployment
- A server with its own database (H2 by default, MySQL or PostgreSQL)
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 6 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 5 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Self-service for app teams
- 8 out of 10
Why these scores for Apache StreamPark
- Many teams, shared clusters 6 out of 10
- Teams act as workspaces, so with a team selected the platform shows only that team’s applications and projects, and a user can belong to several teams with a different role in each.
- Governance per person and job 5 out of 10
- A team admin holds every permission in the team and a developer fewer, such as not deleting applications or adding users, so rights are set per team and role rather than per job.
- One view across clusters 6 out of 10
- It registers Flink versions and Flink clusters, standalone, YARN or Kubernetes, and each team sees the applications it manages across them, as applications rather than a live view of every job on each cluster.
- Out of the data path 6 out of 10
- It is self-hosted and deploys jobs rather than carrying their data, but it runs as a server with a database of its own, H2 by default and MySQL or PostgreSQL in production, the grade this criterion gives a tool with one database.
- Self-service for app teams 8 out of 10
- Developers in a team build and deploy their own applications from the team’s projects, which is more of the job lifecycle than Flex covers, for the applications managed in StreamPark.
What it covers. Apache StreamPark manages Flink jobs from build to deployment. Its team management lets an administrator create a team for each department, describes a team as similar to a workspace, and gives each member a team admin or developer role.
Where it falls short. Its team view covers the applications StreamPark manages rather than every job running on a shared cluster, it keeps a database of its own, and roles stop at the team rather than the job.
Rank 4 Flink Kubernetes Operator
58 out of 100 Total
- Cost a year
- $0 licence, about $2,880 in operator time (modelled)
- What it is
- A deployment operator for Flink custom resources, not a management UI
- Tenancy
- Kubernetes namespaces and Kubernetes RBAC on Flink custom resources
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 5 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 5 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 4 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 9 out of 10
- Self-service for app teams
- 7 out of 10
Why these scores for Flink Kubernetes Operator
- Many teams, shared clusters 5 out of 10
- Kubernetes roles can be scoped per namespace and per resource and bound to users or groups, but anyone allowed to apply a Flink custom resource can submit arbitrary code with full execution trust.
- Governance per person and job 5 out of 10
- Who may change a job is whoever Kubernetes RBAC lets apply its FlinkDeployment, and Kubernetes permissions are purely additive with no deny rule, so one job cannot be carved out of a namespace a team may edit.
- One view across clusters 4 out of 10
- Cluster-scoped by default, one operator handles every FlinkDeployment in its Kubernetes cluster, and they can be listed together as Kubernetes resources with their status, but as resources in a terminal rather than jobs you can open, and the operator works within the one Kubernetes cluster it is installed in.
- Out of the data path 9 out of 10
- It runs as one deployment inside the Kubernetes cluster, keeps what it tracks in the resource status and in ConfigMaps rather than an external database, and reaches the Flink clusters through their REST endpoints, so it never sits between a job and its data; 10 is kept for an option with nothing to deploy.
- Self-service for app teams 7 out of 10
- A team allowed to apply FlinkDeployments in its namespace runs its own job lifecycle from a manifest, but its RBAC page says running jobs in any namespace beyond the operator’s own needs the flink service account, role and binding created there first, so each new team starts with platform work in Kubernetes.
What it covers. The operator’s RBAC page describes a cluster-scoped operator that is responsible for Flink deployments in every namespace, with a namespaced flink role created per watched namespace. The Kubernetes Operator section of Flink’s security page says the Kubernetes RBAC layer replaces direct cluster access as the authentication mechanism, so anyone allowed to apply Flink custom resources is the equivalent of an authenticated Flink user. The Kubernetes side is compared in the best Flink tools for Flink on Kubernetes.
Where it falls short. It has no users, roles or tenants of its own and no UI, so teams inspect running jobs in the Flink Web UI, which shows every job on its cluster to whoever reaches it.
Rank 5 Prometheus and Grafana
prometheus.io
40 out of 100 Total
- Cost a year
- $0 licence, about $14,400 in operator time (modelled)
- Tenancy
- Grafana teams and folder permissions over dashboards, not over Flink jobs
- Deployment
- Prometheus with its own time-series store, plus Grafana
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 3 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 2 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 7 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 6 out of 10
- Self-service for app teams
- 1 out of 10
Why these scores for Prometheus and Grafana
- Many teams, shared clusters 3 out of 10
- Grafana teams and folder permissions decide which team sees which dashboards, but data source permissions, which restrict who may query a data source at all, are available only in Grafana Enterprise and Grafana Cloud, and none of it reaches the Flink jobs themselves.
- Governance per person and job 2 out of 10
- Grafana’s roles and permissions govern who sees which dashboard, and neither tool can act on a Flink job, so there is nothing to approve and no record of job actions.
- One view across clusters 7 out of 10
- Prometheus scrapes every cluster that has the reporter switched on, so one set of dashboards spans them, as metrics rather than as jobs you can open.
- Out of the data path 6 out of 10
- Both are self-hosted, and Prometheus keeps a time-series database of its own, the grade this criterion gives a tool with one database.
- Self-service for app teams 1 out of 10
- Teams can build their own dashboards, but neither tool can submit, change or stop a job, so it is visibility only.
What it covers. Grafana’s team management groups users with common permissions, and folder access control applies a folder’s permissions to every dashboard and alert rule inside it, so each application team can have its own Flink dashboards.
Where it falls short. It is a monitoring stack rather than a Flink tool: it cannot open a job, take a savepoint or stop anything, and Grafana’s data source permissions, the control that would stop one team querying another’s metrics, are an Enterprise and Cloud feature. Its running cost is modelled at 10 engineer-hours a month, $14,400 a year at $120 an hour.
Rank 6 Apache Flink Web UI
29 out of 100 Total
- Cost a year
- $0, served by each JobManager (modelled at $0 extra)
- Tenancy
- None: cluster-wide view for whoever reaches it
- Deployment
- Built into every Flink cluster
- Many teams, shared clusters ×3 weight, this criterion counts 3 times toward the total
- 1 out of 10
- Governance per person and job ×2 weight, this criterion counts 2 times toward the total
- 1 out of 10
- One view across clusters ×2 weight, this criterion counts 2 times toward the total
- 1 out of 10
- Out of the data path ×2 weight, this criterion counts 2 times toward the total
- 10 out of 10
- Self-service for app teams
- 2 out of 10
Why these scores for Apache Flink Web UI
- Many teams, shared clusters 1 out of 10
- Everyone who reaches a cluster’s web UI sees every job on it, so teams are kept apart only by giving each its own cluster.
- Governance per person and job 1 out of 10
- It has no users, so there is no one to grant access to; uploading, starting and cancelling jobs are switched on by default for anyone who reaches it.
- One view across clusters 1 out of 10
- Each JobManager serves its own web UI for its own cluster, so a team with twenty application-mode jobs has twenty UIs.
- Out of the data path 10 out of 10
- It is served by the JobManager itself, with nothing to deploy.
- Self-service for app teams 2 out of 10
- Any team can upload and start a job through it, but on a shared cluster the same page lets that team cancel every other team’s jobs, so the self-service comes with no boundary.
What it covers. Flink’s web UI shows each running job’s graph, backpressure and checkpoint history, served from the same REST API that every other tool here reads, and it stays the reference for inspecting a single job.
Where it falls short. Flink’s configuration reference turns uploading and cancelling through the UI on by default, and says that switching them off leaves session clusters still accepting and cancelling jobs through REST requests. With no users or tenants, the only way to give a team a view of just its own jobs is a cluster of its own.
What platform teams need from a Flink management tool
This page ranks Flink management tools for the platform or infrastructure team that runs Flink on behalf of many application teams, on tenancy and fleet operations. Audit, directory sign-in and approvals are ranked on the best Flink management tool for regulated teams, and job lifecycle and metrics on the pages for self-managed Apache Flink and Flink on Kubernetes. Teams that run Kafka beside Flink can compare both on the best tool to manage Kafka and Flink together.
Many teams, shared clusters. Apache Flink has no notion of a team, and its REST endpoint has no notion of a user. Flink’s SSL documentation says the REST endpoint accepts connections from any client by default, and the configuration reference says that switching off cancellation in the web UI still leaves session clusters cancelling jobs through REST requests. On a session cluster shared by several teams, any team that can reach the endpoint can therefore cancel any other team’s job, and hiding the button does not change that. Tenant boundaries have to come from the tool that people use instead of the endpoint, with network rules keeping everyone else away from the endpoint itself. Pinterest, whose engineers’ published accounts are summarised in how Pinterest uses Apache Flink, runs its Flink jobs across multitenant YARN clusters, which is the shape this page is written for.
Tenant boundaries are not resource isolation. A tenant decides what a team sees and may do; it does not decide what a team’s jobs do to the cluster. Flink’s architecture documentation says that in a session cluster, if one TaskManager crashes, every job with tasks on it fails, and a fatal error on the JobManager affects every job on the cluster, while an application cluster scopes its ResourceManager and Dispatcher to a single application. A platform team picks between sharing session clusters, where tenancy in the tool keeps teams from touching each other’s jobs but not from sharing a failure, and one cluster per application, where failures stay apart and the number of clusters, and UIs, grows with the number of jobs.
Governance per person and job. On a shared cluster, the question a platform team answers most is who may stop which job. Kubernetes roles, which the Kubernetes RBAC documentation describes as purely additive, can grant a team its namespace but cannot carve one job out of it, and a proxy in front of the Flink web UI sees URLs rather than jobs. A tool that grants rights per job, denies by default and lets a Deny override an Allow is what turns “the payments team owns jobs starting with payments” into a rule.
One view across clusters. Flink’s REST API documentation says the monitoring API is backed by a web server that runs as part of the JobManager, so each cluster’s API answers for that cluster alone. A view across Dev, UAT and Prod, or across every application cluster, is something a tool assembles by calling each cluster in turn. That is also why tenants that span clusters matter: one team’s jobs in three environments should be one tenant, not three.
Out of the data path. A management tool that reads the same REST API installs nothing inside jobs or on the cluster, so it never handles the records a job reads or writes. For a platform team the other half of this criterion is running cost: every component it adds, such as a database the tool keeps, is one more system it runs and backs up for every tenant.
Self-service for application teams. Platform teams want routine work, such as uploading a new build, restarting a job from a savepoint or taking a savepoint before a change, done by the team that owns the job, without a ticket. Self-service is only safe inside a boundary, which is why it counts least here: a tool that lets any team submit anything, as the Flink web UI does by default, scores low on it.
Where Flex adds least. A single team with one cluster has no tenants to separate and gets most of what it needs from the Flink web UI behind network rules. A platform team that wants application teams to own the whole deployment lifecycle, from manifest or build to running job, gets more of that from Ververica Platform, the Flink Kubernetes Operator or Apache StreamPark than from Flex, which reads and acts on running clusters but does not build jobs or keep them matching a manifest. Flex adds most where several teams share Flink clusters and each should see and act on only its own jobs, across every cluster, in one place.
You can move seamlessly between Kafka and Flink and the vendors and the variants and … get about your job of doing your own business.
Derek Troy-West, Co-founder and CEO of Factor House
Evidence for Flex on shared Flink platforms
No Factor House customer has yet described running Flex as a multi-tenant Flink platform in public, so this page names none and ranks the tools against the requirements above and their documentation. Flex’s web application shares Kpow’s user experience and its security capabilities, including user authentication, RBAC, multi-tenancy and the audit log, as Introducing Factor House 2.0 describes, and Flex’s multi-tenancy documentation shows tenants applied to Flink jobs, JARs and clusters. Kafka’s own multi-tenancy documentation treats one cluster shared by many teams as a designed mode, isolating tenants with naming conventions that give each team a user space of topics, authorization and quotas; Flex’s tenants apply the same naming idea to Flink job and JAR names.
How a platform team runs Apache Flink for many teams with Flex
Installing one Flex for the fleet. A platform team runs Flex as one container from Docker or the Helm chart, beside its Flink clusters. Helm’s install command installs the latest stable version of a chart unless --devel or a version is given, so a team that wants upgrades of the one tool every tenant uses to land on a day it chooses names the chart version in its install.
Connecting every cluster. Each cluster is one FLINK_REST_URL, with further clusters repeating the settings with _2, _3, _4 suffixes and a FLINK_ENVIRONMENT_NAME shown in the UI, as in the Flink cluster configuration. The same page says Flex manages as many clusters as the licence permits, and that a larger fleet may need more memory and CPU so that each snapshot completes within thirty seconds.
Drawing tenant boundaries. Tenants are a top-level tenants key in the RBAC file. Each includes or excludes Flink jobs and JARs by name, prefix or suffix, or whole clusters, and is assigned to roles from the identity provider. Resources are excluded until a tenant includes them, and exclusions are applied last. A tenant on ReferralDelivery_* jobs and JARs across every cluster shows that team its own work and nothing else, as if those were the only resources in the system, so a job naming convention agreed before teams onboard keeps the file short. A role can hold several tenants, for an engineer who works across two teams.
Granting who may act on which job. The authorization overview says users are denied every action by default. RBAC policies grant a role FLINK_SUBMIT, FLINK_JOB_EDIT, FLINK_JOB_TERMINATE or FLINK_JAR_DELETE on any cluster, one cluster or jobs matching a pattern such as payments-*, and where policies overlap a Deny wins. By default only users holding at least one role in the RBAC file can reach the UI at all.
Letting teams do their own work. Inside its tenant, a team with the right policies uploads a JAR and submits a job from it, with a savepoint path and a claim mode, which says whether the restored job takes ownership of the savepoint, to restore from, and deletes JARs it no longer needs, as in Flex’s jobs documentation. A user can only create resources valid to their tenant, so a team cannot upload a JAR outside its own naming space. Changes to tenants and policies stay with the platform team, in the one RBAC file.
Watching every cluster at once. The cluster overview shows task slots, TaskManagers, running, finished, cancelled and failed jobs and bytes read and written for a cluster, and the multi-tenancy documentation says a user working within a tenant sees a fully consistent synthetic cluster view of that tenant’s aggregated resources. Teams that already run Prometheus can scrape Flex’s Prometheus endpoints, which are not secured by default and take basic authentication when configured.
FAQ
What is the best Flink management tool for a platform team serving many teams?
On this page’s rubric, Flex ranks first with 86 out of 100, ahead of Ververica Platform at 62, Apache StreamPark at 60 and the Flink Kubernetes Operator at 58. Flex leads on keeping each team to its own jobs, on rights per job and on one view across clusters, from one container outside the data path. Ververica Platform scores higher on self-service, because its Namespace editors run their own Deployments.
Does Apache Flink support multi-tenancy?
Not for people. Flink has no users or teams of its own, its REST endpoint does not authenticate clients by default according to the SSL documentation, and its web UI shows every job on a cluster to whoever reaches it. Teams are kept apart either by a cluster each or by a tool in front of the clusters.
Is a Flex tenant the same as resource isolation?
No. A tenant decides which Flink jobs, JARs and clusters a role sees and can create, according to Flex’s multi-tenancy documentation, and the documentation shows no per-tenant quotas. Jobs on a shared session cluster still share its TaskManagers and JobManager, so isolation of failures and resources comes from how the clusters are laid out.
Can application teams onboard themselves in Flex?
Not on their own. Tenants and policies are set in the RBAC file by whoever runs Flex. Once a team has a tenant and a policy, it uploads, submits, savepoints and stops its own jobs without the platform team.
How does Ververica Platform separate teams?
With Namespaces. Ververica’s Namespaces page calls them the primary means to isolate resources between groups of users, and roles bound in one Namespace imply nothing in another. Roles stop at the Namespace rather than the job, and each installation is its own UI.
Can Prometheus and Grafana give each team its own view of Flink?
Of dashboards, yes: Grafana teams and folder permissions decide which team sees which dashboards. Restricting who may query a data source needs Grafana Enterprise or Grafana Cloud, and neither tool can act on a Flink job.
How these tools were scored
The five criteria come from what a platform team running Flink for many application teams is asked for: keep teams apart, decide who may act on which job, see every cluster, add little to run, and let teams do routine work themselves. 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. Weights add up to 10, so totals are out of 100. Where a sibling page already scores an option on the same criterion, this page uses the same score: Many teams, shared clusters comes unchanged from the regulated teams page, Governance per person and job from the self-managed, Kubernetes and monitoring pages, and One view across clusters and Out of the data path from all of them. The new scores are the Self-service for application teams column and Prometheus and Grafana on Many teams, shared clusters, which no sibling page scores.
1. Many teams, shared clusters (counts three times). Scoping what each team can see and change to its own jobs, so that teams sharing a cluster cannot see or stop each other’s work. Shared-cluster safety is scored here, as separation in the tool; how jobs share a cluster’s resources is a matter of cluster layout and is not scored.
2. Governance per person and job (counts twice). On this page, who may act on which job: rights per person or role, scoped as narrowly as a single job, denied by default. The audit and approval side of the same criterion is weighed on the regulated teams page.
3. One view across clusters (counts twice). Showing every cluster’s jobs in one place, under one set of roles and tenants.
4. Out of the data path (counts twice). The tool should run inside your environment, reach the Flink clusters over their REST APIs, and keep no data outside your own infrastructure. 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 every node 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 Flink Web UI. This criterion is scored the same way on every Factor House page that uses it, and only its weight changes with the reader.
5. Self-service for application teams (counts once). An application team can upload, submit, savepoint and stop its own jobs without a ticket to the platform team, and only its own. Running the whole deployment lifecycle from a manifest or build scores highest where a new team can start without platform setup, 8 or 9, and 7 where each new team first needs that setup; acting on running jobs scores 7; dashboards alone score 1; and self-service with no boundary, where any team can act on any job, scores 2.
Costs are modelled for a platform team with three Flink clusters, Dev, UAT and Prod, at $120 per engineer hour, using the same hours per tool class as Factor House’s other comparison pages. Flex’s $14,730 uses the Enterprise price from $3,950 per cluster a year, with 100 users included, on the Factor House pricing page, for three clusters, $11,850, plus 2 hours a month, $2,880, to run it. Ververica Platform does not publish its price, so its figure is 4 hours a month, $5,760 a year, for running the platform and its database, before the licence. Apache StreamPark has no licence fee and carries the same 4 hours for its server and database. The Flink Kubernetes Operator carries 2 hours a month, $2,880 a year. Prometheus and Grafana carry 10 hours a month, $14,400, the figure Factor House’s other pages use for a metrics stack assembled from parts. The Flink Web UI comes with every cluster and is modelled at nothing extra.
The criteria map onto Apache Flink’s defaults 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: Many teams, shared clusters counts three times, Governance per person and job counts twice, One view across clusters counts twice, Out of the data path counts twice and Self-service for app teams counts once, for a total out of 100. Many teams, shared clusters counts three times, because keeping each application team to its own jobs is the job a platform team running Flink for others is hired to do, and Apache Flink has no notion of a team to start from. Governance per person and job, one view across clusters and out of the data path count twice each: who may act on which job decides whether one team can stop another's, a platform team runs several clusters at once, and every component the platform team adds is one more thing it runs on behalf of every tenant. Out of the data path counts three times on the regulated teams page and twice here, because this page ranks fleet operations rather than third-party review. Self-service for application teams counts once, because most options here offer some form of it and it only helps inside a boundary the other criteria set. This page is published by Factor House, which makes Flex. Every option is scored on the same rubric and the same sources: Flex'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. Flex ranks first on its total of 86 out of 100. The other options follow by total.
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