Software Alternatives, Accelerators & Startups

Atlassian Data Center VS Cisco Workload Optimization Manager

Compare Atlassian Data Center VS Cisco Workload Optimization Manager and see what are their differences

Atlassian Data Center logo Atlassian Data Center

Deploy Atlassian's software in your own data center with clustered failover and more to support large and mission critical deployments.

Cisco Workload Optimization Manager logo Cisco Workload Optimization Manager

Cisco Workload Optimization Manager effectively matches application demand with infrastructure supply so that you can keep pace with changes in your business.
  • Atlassian Data Center Landing page
    Landing page //
    2023-08-19
  • Cisco Workload Optimization Manager Landing page
    Landing page //
    2023-07-25

Atlassian Data Center features and specs

  • Scalability
    Atlassian Data Center can handle growing workloads with ease by distributing applications over multiple nodes, ensuring performance remains consistent even as user demands increase.
  • High Availability
    The architecture provides failover support to ensure applications remain available and operational even in the event of hardware failures or maintenance.
  • Performance
    Optimized to manage high user loads efficiently, improving overall application performance and user experience.
  • Flexible Deployment Options
    Organizations can deploy Atlassian Data Center on their infrastructure, in public clouds, or in hybrid environments, providing greater flexibility depending on their specific needs.
  • Compliance and Security
    Enhanced security and compliance features are available, which help organizations adhere to regulatory standards and protect their data.

Possible disadvantages of Atlassian Data Center

  • Complexity
    The setup and management of a Data Center environment can be complex, requiring significant expertise and time to manage efficiently.
  • Cost
    Generally, Data Center solutions are more expensive than their server counterparts, making them a significant investment for organizations.
  • Resource Intensive
    Running a Data Center instance demands more hardware and infrastructure resources, increasing operational overhead.
  • Maintenance
    Regular maintenance is more complicated, as updates and changes must account for the multi-node setup, potentially leading to increased downtime or more elaborate planning.
  • Learning Curve
    Teams may experience a learning curve as they get accustomed to the specific features, configurations, and capabilities of the Data Center version.

Cisco Workload Optimization Manager features and specs

  • Resource Optimization
    The Cisco Workload Optimization Manager provides dynamic resource allocation based on real-time demand and supply, ensuring optimal utilization of IT resources.
  • Cost Efficiency
    By efficiently managing workloads and resources, it can help reduce infrastructure costs by avoiding over-provisioning and under-utilization.
  • Integration Capabilities
    This tool integrates with multiple environments and platforms, such as public, private, and hybrid clouds, providing a unified view and control.
  • Performance Improvements
    Enhances application performance by ensuring that workloads have the necessary resources to meet service level objectives.
  • Automation Features
    Offers automation capabilities to handle routine workload management tasks, helping to reduce manual intervention and errors.

Possible disadvantages of Cisco Workload Optimization Manager

  • Complex Setup
    The initial setup and configuration can be complex and may require a significant time investment and expertise.
  • Cost
    While it helps with cost efficiency, the licensing and operational costs can be high for small to medium-sized enterprises.
  • Learning Curve
    Users may face a steep learning curve when first using the platform, particularly if they lack experience with similar tools.
  • Dependency on Vendor Support
    Organizations might heavily rely on Cisco’s support for problem resolution, which could be a concern for time-sensitive issues.
  • Integration Challenges
    Despite broad integration capabilities, there might be challenges or limitations when integrating with specific third-party software or custom in-house applications.

Atlassian Data Center videos

How to deploy Atlassian Data Center

More videos:

  • Review - Atlassian Data Center & Other Deployment Options

Cisco Workload Optimization Manager videos

03 How to Setup Cisco Workload optimization manager A Z (part 01)

Category Popularity

0-100% (relative to Atlassian Data Center and Cisco Workload Optimization Manager)
Monitoring Tools
100 100%
0% 0
Workflow Automation
0 0%
100% 100
DCIM Software
100 100%
0% 0
IT Automation
0 0%
100% 100

User comments

Share your experience with using Atlassian Data Center and Cisco Workload Optimization Manager. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing Atlassian Data Center and Cisco Workload Optimization Manager, you can also consider the following products

Cisco Data Center Network Manager - Cisco Data Center Network Manager offers network management system (NMS) support for traditional or multiple-tenant LAN and SAN fabrics.

Stonebranch - Stonebranch builds IT orchestration and automation solutions that transform business IT environments from simple IT task automation into sophisticated, real-time business service automation.

Cisco ACI - Application Centric Infrastructure (ACI) simplifies, optimizes, and accelerates the application deployment lifecycle in next-generation data centers and clouds.

JAMS Scheduler - Enterprise workload automation software supporting processes on Windows, Linux, UNIX, iSeries, SAP, Oracle, SQL, ERPs and more.

Device42 - Automatically maintain an up-to-date inventory of your physical, virtual, and cloud servers and containers, network components, software/services/applications, and their inter-relationships and inter-dependencies.

Control-M - Control‑M simplifies and automates diverse batch application workloads while reducing failure rates, improving SLAs, and accelerating application deployment.