Mission Control installation requirements
Before installing Mission Control, ensure your environment meets all necessary requirements. This guide details the hardware specifications, storage needs, networking configurations, and other prerequisites for a successful deployment.
Mission Control deployment topologies
Mission Control serves as a platform and interface for deploying and managing DataStax Enterprise (DSE), Hyper-Converged Database (HCD), and Apache Cassandra® database clusters across logical and physical regions.
Here are some examples of deployment topologies:
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Deploy one instance of Mission Control for the entire organization.
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Dedicate multiple targeted installations to specific groups.
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Dedicate one instance per DEV, TEST, and PROD environments.
At the top-level, Mission Control consists of a centralized control plane and optional regionally deployed data planes.
- Control plane
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Provides the core interface for Mission Control, including the top-level API service, user interface, and observability endpoints. The control plane manages coordination across each data plane’s region boundaries.
- Data plane
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Each deployed data plane includes DSE, HCD, or Cassandra nodes and provides a self-contained environment for local resource management.
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The control plane can function as a data plane since it contains all the necessary components. As a result, you don’t need a separate data plane. For a single region deployment, DataStax recommends a single control plane. |
Resource capacity requirements
Installing Mission Control requires different instance types and varying resource capacities. Follow these guidelines as the minimum requirement. You might need to increase CPU capacity, memory, and disk space beyond the recommended minimums.
Platform instances
Mission Control observability includes metrics and logging from all components within the platform. These metrics and logs are centralized, aggregated, then shipped to an external object store. For more information, see Storage requirements. Managed database instances generate most Mission Control metrics and logs. The recommended values depend on the number of clusters deployed and their individual schemas because each table holds a number of tracked metrics. The following recommendations assume minimal deployment in 1 region with a single managed cluster and associated logical database datacenter.
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2 Instances
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32 CPU cores
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64 GB RAM
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1 TB storage
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To schedule platform services components, you must assign the Kubernetes label |
Database instances
Database instances host all scheduled HCD, DSE, and Cassandra nodes.
This sizing guidance assumes each node maps to a single Kubernetes worker. Alternatively, you can co-locate multiple instances on a single worker.
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Resource contention often occurs when you tune this deployment. |
Adjust the values according to your expected database node resource requirements.
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3 Instances
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16 physical CPU cores-32 hyper-threaded cores
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64 GB RAM minimal
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1.5 TB storage
DataStax benchmark testing shows that resource requirements and performance are similar between bare-metal VMs and Kubernetes install types. For production, DataStax recommends running Cassandra with the following specifications:
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8 to 16 cores
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32GB to 128GB RAM
CPU and RAM setting concepts
The precise amount of RAM required depends on the workload and is usually tuned based on observation of Garbage Collection (GC) metrics. For RAM, you should set the memory requirements to double the heap size. By default, the JVM allows processes to use as much off-heap memory as the configured on heap memory. With a heap size of 8GB, the JVM may use up to 16GB of RAM, depending on off-heap memory usage. Follow this rule to simplify memory allocation: Set the heap size to a reasonable value that matches the available memory on the worker nodes. For example, given 32GB RAM per worker node and extra processes such as metrics or log collectors and Kubernetes system components that need to run, you should set your heap size to 8GB, and memory requests to 16GB. If GC pressure is too high, you can raise those values to 12 and 24GB, respectively. During the installation process, allow the monitoring stack to run on the DSE, HCD, or Cassandra nodes to enable scheduling Mimir and all on the same worker nodes. This considers all infrastructure instances available for scheduling, which may lead to unexpected utilization of hardware resources. In production, you should separate these into different node pools. You can set the CPU requests to a minimum-for example, 1 core, to allow scheduling all components concurrently. Processes continue to use as many cores as possible. Note that in production, despite scheduling the monitoring stack and the DSE, HCD, or Cassandra pods on separate node pools, you still need to leave some RAM available for system pods that allow Kubernetes operations such as networking. For example, if you have 48GB RAM per worker, leave 1GB to 2GB for those extra pods by setting your resource requests to around 46GB.
Storage requirements
In addition to the local storage requirements for database and observability instances, Mission Control requires one of the following bucket types for object storage:
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Amazon Web Services Simple Storage Service (AWS S3) or S3 compatible-for example MinIO, OpenStack Swift
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Google Cloud Storage (GCS)
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Azure Blob Storage
Mission Control stores observability data and database backups in object storage for long-term retention.
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For EKS installations, define a default storage class before you install Mission Control. |
Load balancing requirements
The Mission Control UI is accessed through a specific port on any of the cluster worker nodes. DataStax recommends placing this service behind a load balancer that directs traffic from all worker nodes within the cluster to port 30880.
This ensures that the UI remains available should an instance go down.
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Mission Control does not support load balancing in front of database instances. |
Runtime installation requirements
Runtime installations come with an embedded Kubernetes environment that require additional prerequisites. The operating system is installed and the hosts comply with Replicated’s embedded cluster requirements. For more information, see Install the Mission Control server runtime using the embedded Kubernetes cluster.
Kubernetes management instances
Kubernetes Management nodes and load balancers are required for the runtime installation.
- Kubernetes Management nodes
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In addition to the number and types of instances determined during Resource capacity requirement planning, you must account for the overhead of Kubernetes Management nodes. These nodes contain metadata and services required to deploy workloads across all worker nodes. Mission Control requires three Management node instances, with each node set to:
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4 AMD64 (x86_64) CPUs or equivalent
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8 GB of RAM
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256 GB of disk space
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- Load balancers
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To provide high-availability of services, Mission Control runtime-based installations require an additional load balancer. Place it in front of the Management Kubernetes nodes for core Kubernetes API traffic running on port 6443.
Plan your networking
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Ensure that all database pods can route to each other. This is a critical requirement for proper operation and data consistency. The requirement applies to:
To achieve this:
Failure to establish proper pod-to-pod routing results in:
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Open TCP and UDP ports 1024-65535 between all hosts within a given region, a given control plane, or a given data plane.
This allows for the seamless shifting of workloads between instances due to changing environments.
| Instance types | Server-runtime installation | Kubernetes installation |
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Management |
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Platform |
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Database |
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CIDR planning for runtime installations
When you use the runtime installer for Mission Control, plan your Kubernetes cluster CIDR ranges carefully. The CIDR range determines the IP address space available for pods and services in your cluster.
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If you need to change the CIDR range after installation, you must stop the cluster, which causes downtime. Plan your CIDR ranges carefully before installation to avoid changes later. |
When planning CIDR ranges, consider the following:
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Plan for sufficient IP addresses to support your expected workload.
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Account for future growth in your CIDR range size.
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Verify that your chosen CIDR range doesn’t conflict with existing network ranges.
For single-region deployments:
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Choose a CIDR range that supports all your expected pods and services.
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Account for your planned number of database nodes and their potential growth.
For multi-region deployments, also consider:
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Choose non-overlapping CIDR ranges for each cluster.
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Plan separate CIDR ranges for:
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Your control plane cluster.
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Each data plane cluster.
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Any future clusters you plan to add.
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Next steps
Proceed to the instance configuration step based on your installation type.
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Kubernetes Installations: Online and Offline installation paths
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Runtime Installations: Online and Offline installation paths
