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Before installing Magic Collaboration Studio, ensure that the system requirements described in this chapter are met.

Note
titleCassandra installation

Magic Collaboration Studio requires Studio requires Cassandra installation. To learn more about the hardware requirements for Cassandra, see see https://cassandra.apache.org/doc/latest/cassandra/operating/hardware.html

Recommended

system requirements

system and storage requirements

Note
titleNote on system requirements

System requirements are dictated by the intended deployment, taking into account the overall load which the environment will experience, including:

  • Number of concurrent users
  • Level of activity (commits) per day
  • Overall number and size of the projects stored in Magic Collaboration Studio.

The database (Cassandra) can be located on the same server as Magic Collaboration Studio

or on

or on a separate server. Storage requirements apply only to the node where the database is located.

Magic Collaboration Studio hosting nodes

The product hosting nodes can be virtualized without any issues

if the

if the host is not oversubscribed on its resources.

Nodes containing both Magic Collaboration Studio and Cassandra:

  • 96 -128 GB ECC RAM
  • >=16 processor threads (such as E5-1660)
  • >1TB SSD DAS storage

Nodes containing only Cassandra:

  • 48 - 64 GB ECC RAM
  • >=8 processor threads (such as E5-1620)
  • >1TB SSD DAS storage

Nodes containing only Magic Collaboration Studio:

  • 48 - 64 GB ECC RAM
  • >=8 processor threads (such as E5-1620)
  • >250GB storage

    Info
    titleMulti-Node Clusters
    Recommended minimum sizing stated above applies to each node in a multi-node cluster.


    Note
    titleNote on storage requirements

    For on-premises deployment, Apache Cassandra is designed to run on multiple independent servers. Each Cassandra node should have Directly Attached Storage (DAS) composed of NVMe drives for optimum performance. Traditional network-attached storage solutions that rely on IP-based connections (iSCSI, NFS, or SAN) are not recommended for on-premises deployments, as they introduce additional latencies and anti-patterns. To learn more, see the following topics:

    For cloud deployment, use storage technologies that have been benchmarked for Cassandra. Modern solid-state/flash arrays with fast interconnects are preferred. Note that Magic Collaboration Studio is not compatible with managed Cassandra services, such as Amazon Keyspaces. To learn more, see the following topics:

    Warning
    titleSAN Storage

    SAN Storage should not be used on Cassandra nodes for data or commit log volumes on Cassandra nodes. This will result in severe performance degradation. There is no amount of SAN tuning and OS tuning which could mitigate this.

    Minimal hardware requirements

    For adequate Magic Collaboration Studio operation, your hardware should meet the following requirements:

    Resource requirements by deployment type
    Deployment typeRecommended system requirementsRecommended storage requirements

    Magic Collaboration Studio AND Cassandra

    • 96 -128 GB ECC RAM
    • >=16 processor threads (such as E5-1660)
    • >1TB SSD DAS storage
    • 8 Processor Cores - i.e. Quad-Core Hyper-threaded CPU (such as Intel E3-1230 or faster).
    • 32 GB RAM (Motherboard with an ECC RAM is recommended) and 8 GB RAM dedicated
    for TeamworkCloud
    • forMagic Collaboration Studio
    • At least 3 separate disks, preferably SSD (NVMe), (OS/Application, Data, and Commit logs). Depending on company backup procedures and infrastructure, an additional disk, equal to the data disk in size, may be required

    to store
    Only Cassandra
    • 48 - 64 GB ECC RAM
    • >=8 processor threads (such as E5-1620)
    • >1TB SSD DAS storage
    Only Magic Collaboration Studio
    • 48 - 64 GB ECC RAM
    • >=8 processor threads (such as E5-1620)
    • >250GB storage

    Software requirements

    Magic Collaboration Studio supports the following operating systems:

    • Linux 64-bit RedHat/CentOS 7, RedHat 8.

    • Windows 2016 or Windows 2019.
    Note

    The Linux operating system is highly recommended for Magic Collaboration Studio deployment. Cassandra 4.0.3 does not have native Windows support. For more information, please visit https://www.datastax.com/dev/blog/cassandra-and-windows-past-present-and-future.

    For a fully working environment, you will also need the following:

    • OpenJDK (Eclipse Temurin™ by ADOPTIUM) 11.0.14
    • FlexNet license server
    • Cassandra 4.0.3
    • A static IP address for each node.
    • Open ports 1101, 2181, 2552, 7000, 7001, 7199, 9042, and 9142 between servers in a cluster.

    • Open ports 3579, 8111, 8443, and 10002 (default) for clients. The port number 10002 can be changed according to the port assigned to secure connections between the client software and Magic Collaboration Studio.

    The following table lists the ports that Magic Collaboration Studio services use and their descriptions:

    ServicePortDescription
    FlexNet server (lmadmin)1101FLEXnet server port

    8090Default vendor daemon port (web browser management port)

    27000-27009Internal license server manager port



    Cassandra7000Internode cluster communication port (not used if TLS is enabled)

    7199JMX monitoring port of the Cassandra node

    9042Native client port used to connect to Cassandra and perform operations (used with 2021x version and later)

    9142Native client port when SSL encryption is enabled (used when Cassandra is on a separate server or Cassandra is deployed as a multinode cluster)



    Magic Collaboration Studio2552Magic Collaboration Studio default remote server port

    3579Default Magic Collaboration Studio port when SSL is not enabled

    8111Magic Collaboration Studio REST API port

    10002 Default port for encrypted TLS client-server communication.



    Web Application Platform8443Web Application Platform port (Teamwork Cloud Admin, Collaborator…)



    Zookeeper2181Zookeeper internal port


    For additional server capacity and performance recommendations, see https://cassandra.apache.org/doc/latest/cassandra/operating/hardware.html

    Info
    titleIf deploying on Amazon EC2
    When deploying on Amazon EC2, we recommend using the m5-2xlarge, r5-2xlarge, or i3-2xlarge instances. Depending on the workload, you may want to go to the -4xlarge instances, but for most users, the -2xlarge will suffice. The m5 instances meet the minimum system requirements and will be acceptable for small deployments. The r5 instances provide more memory for the same CPU density. The i3 instances should be used when workloads have a higher level of user concurrency due to the significantly improved performance of the ephemeral NVMe storage.