Top 10 Data Center Automation Tools with Real-Life Examples

Picking a data center automation tool is critical for firms to have high-quality data, make data-driven decisions and assist the automation of data center processes. We picked 10 data center automation tools based on our research, features and the tools’ popularity. Follow the links below detailed information:

Software		Best For
1.	ActiveBatch	Hybrid cloud / API orchestration
2.	RunMyJobs by Redwood	Orchestrating SAP jobs while keeping a clean SAP core
3.	Stonebranch	Numerous community-driven pre-packaged integrations delivered as SaaS
4.	Tidal by Redwood	Cost-effective workload automation
5.	BMC Control-M	Data pipeline orchestration and managed file transfers
Show More (5)
6.	Fortra's JAMS	PowerShell integration & job scheduling management on the .NET framework
7.	SMA Opcon	Automating workflows in financial services
8.	Autosys Workload Automation	Broadcom-owned WLA solution
9.	AWS Batch	Running batch computing jobs at scale in the AWS cloud
10.	IBM Workload Automation	Job orchestration in the IBM ecosystem

1.

ActiveBatch

Hybrid cloud / API orchestration

2.

RunMyJobs by Redwood

Orchestrating SAP jobs while keeping a clean SAP core

3.

Stonebranch

Numerous community-driven pre-packaged integrations delivered as SaaS

4.

Tidal by Redwood

Cost-effective workload automation

5.

BMC Control-M

Data pipeline orchestration and managed file transfers

Show More (5)

6.

Fortra's JAMS

PowerShell integration & job scheduling management on the .NET framework

7.

SMA Opcon

Automating workflows in financial services

8.

Autosys Workload Automation

Broadcom-owned WLA solution

9.

AWS Batch

Running batch computing jobs at scale in the AWS cloud

10.

IBM Workload Automation

Job orchestration in the IBM ecosystem

We aim to inform IT professionals about the top data center automation tools, their features, and real case studies to support them in making decisions about data center automation tools.

Comparison of Top 10 Data Center Automation Tools

* Sorted with sponsors at the top and the rest sorted according to average rating. Ratings are based on Capterra, Gartner, G2, Peerspot and TrustRadius.

ActiveBatch

One of the most important aspects of a well-functioning data center is timely data delivery to the departments or clients. However, operations across cloud and virtual machine data centers can raise security concerns since integrating systems may provide access to a group of staff who are not entitled to access them.

ActiveBatch integrates data centers on-premises, cloud, and hybrid environments at a single interface to securely support workload management in data centers.
The tool supports event-based triggers, enabling tasks to initiate based on specific events such as file modifications, email receipts, or system alerts. This capability reduces manual intervention and ensures timely execution of processes.

Real-life example

For example, Vero Skatt, a Finnish tax agency, used ActiveBatch to connect six environments into a central interface.¹ They used ActiveBatch’s user permission feature to address security concerns to control user/group access to specific databases or applications. They expanded adherence to internal and external audit requirements while significantly reducing manual scripting and troubleshooting.

Vero Skatt’s operations benefitted additionally from ActiveBatch. Compared to traditional automation tools such as Windows Task Scheduler, ActiveBatch has a low-code interface with a drag-and-drop workflow designer and multiple workflow views. ActiveBatch’s easy-to-use interface enabled their IT to develop diverse and complex automation tasks that would have been difficult to accomplish with traditional tools.

RunMyJobs

RunMyJobs by Redwood can be used for business process automation, DevOps automation, data warehouse management, security management, and more. RunMyJobs is a SaaS solution that enables transparency and compliance across the enterprise by streamlining cross-departmental workflow processes. Delivered as SaaS, users also do not have to worry about updating or gaining access to the latest version of the software.

Real-life example

ALSO chose Redwood as a solution to enhance the speed of processing customer orders. By implementing the Redwood RunMyJobs solution within just one week, ALSO successfully integrates its warehouse application with its SAP operations, enabling them to swiftly handle incoming orders.

Through Redwood’s automation, ALSO was able to create automation processes once and utilize them repeatedly. This resulted in a significant reduction from their 46,000 SAP job definitions to only 570 Redwood scripts, including 140 job sets and 300 independent jobs. Previously, they required a team of six specialized SAP Basis administrators to manage these processes. However, with the implementation of Redwood, they now only need a single administrator, allowing the team to allocate their efforts toward other important tasks.

Redwood’s services used by organizations like Arthex, Avaya, Epson, and AMD. You can check their offerings in the video below:

Fortra’s JAMS

The data center administration is critical for your servers to communicate data across your business. However, disconnecting data centers with PowerShell and other software can be time-intensive and overwhelming for your IT team. 

Fortra’s JAMS scheduler is built on the NET framework and can assist your IT team with PowerShell scripts. In addition, JAMS enables IT teams to understand workflows between their servers, make quick edits, and increase their efficiency, unlike old-fashioned automation tools. JAMS’ Relational Job Diagram provides a graphical representation of the jobs running on servers, including their relationships, triggers, dependencies, and much more.

Real-life example

For example, Jupiter, a fund management firm, devoted significant time to monitoring its processes, security, and compliance.  JAMS run-time encryption, compliance trial, and various other features allowed their processes to generate approximately 36,000 from 1000 FTP and ETL processes across hundreds of servers.²

Stonebranch WLA

Managing mass workloads in different environments can be challenging for traditional data center automation tools. Older data center tools may have less operational capacity than modern ones, and they may cause database integration issues. Modern workload automation (WLA) tools can process many business operations across multiple platforms, maximize savings, and increase performance and scalability. Delivered as SaaS, Stonebranch gives the users the access to community driven pre-packed integrations.

Real-life example

For example, ITERGO, an IT service company for the ERGO insurance group, needed an alternative to their traditional WLA tools to manage their mass data center with about 15 million transactions per day and desired reliability in data transactions.³

The Stonebranch WLA tool offered them a single unified platform, Universal Automation Center, which connected their Tivoli Workload Automation Scheduler, other schedulers, and their cloud-based databases with 38,000 users. 

The platform provided the following features:

• A universal controller to manage all platforms in the data center.
• A universal agent remotely executes processes on various software.
• A universal data mover automating the data pipeline reliably and securely across your servers. 
• A universal data mover gateway for secure data transfer to third-party businesses from the data center.

BMC Control-M

A flowing business operation requires a good orchestration of your applications and data flow in your data center. With your company’s growth, keeping this organization can become difficult for your IT team to manage manually or with traditional tools.

Control-M, developed by BMC Software, is a workflow automation and job scheduling tool designed to streamline and manage complex batch processing across diverse environments. In the context of data center automation, Control-M provides a centralized platform to orchestrate workflows, ensuring tasks are completed in the correct sequence, at the right times, and with minimal manual intervention. This approach helps data centers maintain reliable operations while handling large volumes of interdependent tasks efficiently.

Real life example

As KoçSistem grew into one of Türkiye’s largest technology companies, its infrastructure team began to suffer due to a lack of employees and an overabundance of servers. They had difficulty initializing their servers to meet high-quality compliance standards and managing server patches causing server vulnerabilities.

Unlike traditional tools, the modern WLA tool Control-M provided patch and compliance management. Patch management aided them in their CI/CD pipeline by reducing the time spent in server DevOps operations such as downloading, analyzing, testing, and repairing patches from different vendors. Compliance management aided KoçSistem in better using its resources and achieved about a 100% patch compliance ratio.⁴

IBM WLA

In traditional automation tools, the software or AI can occasionally make inaccurate estimates about their server and processing capacity resulting in inaccurate estimates of task completion. This can result in poor scheduling decisions that can cause delays and inefficiencies in the workflow of the data center.

IBM’s WLA solutions contains a data advisor that lowers the possibility of the computer making inaccurate estimates. Data Advisor (AIDA) can detect anomalies in the overall workload or specific jobs. Thus, it can enable your IT team to accurately know the task completion time and report inaccuracies. 

Also, it can use data from big data and machine learning and data analytics methods to compare its estimates of task completion time across external and internal servers to guide your IT team about the efficiency of your data center. Additionally, its user interface (UI) can offer valuable insights into data center efficiency as it can record, track, and analyze historical data from jobs and workstations.

Real-life example

IBM’s data center automation efforts include its collaboration with the Montpellier Data Center in France. To reduce environmental impact while ensuring service quality, the center used IBM Turbonomic and IBM Instana. These tools analyzed application-driven energy use and provided optimization recommendations. This automation improved operational efficiency and advanced the center’s sustainability goals. ⁵

OpCon

OpCon WLA tool’s feature, OpCon deploy, enables IT teams to update their servers while the business processes are in progress. In traditional methods, this would entail that some servers must be shut down, and business operations must halt while the update is being processed. OpCon WLA tool can be important in your DevOps toolbox for efficient server management.

Real-life example

Open Technology Solutions (OTS), a credit union service organization, was experiencing errors in their core servers with their old automation tool. The use of OpCon WLA tools in their servers nearly eliminated system downtime.⁶

Tidal Workload Automation

Due to inefficiencies in scheduling and CPU management in data centers, servers can occasionally fail during data processing and distribution and cause delays. The innovative WLA tools can detect overloads in servers and CPU fails and they can direct the tasks to cloud-based and virtual machine environments to ensure that your service level agreement (SLA) is met.

Real-life example

For example, an insurance plan company having trouble processing the spikes in day-to-day (about 25,000 to 100,000 jobs per day) activities and more errors were occurring as the business and claim volume grew. Furthermore, the company had to submit the insurance plans on the next day at 9:00 to the government to avoid financial penalties.

Tidal WLA automation met the company’s requirements and allowed it to handle spikes ranging from 6,000 to 100,000 requests. Furthermore, since deploying Tidal in 2007, the company has not missed any SLAs.⁷

AWS Batch accelerates speed to market

AWS Batch is a fully managed service by Amazon Web Services that enables developers, scientists, and engineers to efficiently run batch computing workloads of any scale. It automates the provisioning and management of the necessary infrastructure, allowing users to focus on analyzing results and solving problems without the overhead of managing batch computing software or server clusters. AWS Batch integrates with other AWS services, providing a robust and scalable solution for batch processing needs across various industries.

Real-life example

Arm Limited, a world-renowned provider of licensable computing technology for semiconductor corporations, has seen more than 200 billion chips based on its design manufactured and shipped by partners over the past 30 years as of February 2022. However, Arm’s on-site data centers couldn’t keep up with escalating engineering needs, leading the company to instigate drastic changes in 2016 to meet its forecasted growth over the following 5 to 10 years.

Transitioning from traditional data centers to Amazon Web Services (AWS) allowed Arm to construct scalable cloud-based solutions for operating EDA tasks. Arm has optimized its computing expenses, boosted engineering efficiency, hastened product launch times, and improved product quality through this approach. Moreover, Arm has leveraged AWS CPUs based on its architecture to design and verify new chips, further propelling its business success. ⁸

AutoSys 

AutoSys streamlines data center automation by scheduling, managing, and monitoring tasks across multiple platforms like Linux, Windows, and UNIX. Its event-driven capabilities trigger tasks based on specific conditions, ensuring efficient workflow execution. With real-time tracking, alerts, and dependency management, AutoSys reduces manual intervention, enhances reliability, and optimizes complex data center operations.

Real-life example

Hanwha Life Insurance Co Ltd is a global life insurance provider with its main headquarters located in South Korea. Recognizing the need to enhance IT efficiency and reduce the burden of IT management tasks, Hanwha Life sought to streamline job scheduling through increased automation. Hanwha Life deployed AutoSys Workload Automation.

The solutions are currently utilized to schedule tasks across both mainframe and UNIX environments, specifically concerning the company’s accounting systems and data warehouse, managing approximately 8,000 jobs in total. Hanwha’s IT team uses intuitive online consoles, which allow them to categorize jobs by workload and server, as well as conveniently modify batch job configurations.

Data warehouse automation

While data center automation optimizes infrastructure and server operations, enterprises also need to ensure that their data pipelines, ETL processes, and data warehouses are automated for seamless analytics and reporting. Data warehouse automation tools help reduce development time, streamline database updates, and improve data accuracy. 

Many of the workload automation (WLA) tools mentioned earlier offer data warehouse automation capabilities. However, there are also dedicated DWA solutions specifically designed to optimize data warehousing processes.

• Seamless integrations: DWA tools should support pre-built connectors, APIs, and real-time integration to easily ingest data from databases (SQL, Oracle), operational systems (CRM, ERP), and third-party applications while ensuring smooth data flow to BI and analytics platforms.
• Low-code automation: A drag-and-drop workflow designer, pre-built automation templates, and metadata-driven automation reduce manual coding efforts, enabling faster and more efficient data pipeline management.
• ETL testing automation: Automates validation of data extraction, transformation, and schema changes by ensuring accuracy, business rule compliance, and consistency between source and transformed data, reducing errors in analytics and reporting.

Data warehouse automation (DWA) vs. data center automation (DCA)

Here is two technologies are different to one another:

• Focus:
  • DWA focuses on automating the design, deployment, operation, and maintenance of a data warehouse.
  • DCA covers the broader IT infrastructure within a data center, automating hardware, software, and networking configurations.
• Tasks to automate:
  • For DWA: Data ingestion and ETL (Extract, Transform, Load) processes, schema creation and updates, data modeling and optimization, performance tuning, metadata management, testing and validation of data pipelines
  • For DCA: Server provisioning and orchestration, storage and network management, security compliance and monitoring, disaster recovery and backup automation, energy management and resource optimization

To learn further about workload automation, you can download our whitepaper:

To discover other tools that you can replace or pair with data center automation tools, read our data-driven and comprehensive articles and benchmarks on:

• IT Automation: Top Tools, Examples, Rationale & Benefits
• Top 12 IT Automation Software: Vendor Benchmarking
• 5 Reasons for Data Warehouse Automation
• Top 10+ Data Warehouse Automation Software

External Links

• 1. ActiveBatch Case Studies - VeroSkatt .
• 2. Secure EDM and ETL for Trading Systems - JAMS. Fortra's JAMS Enterprise Job Scheduler
• 3. ITERGO Cuts Costs & Boosts Efficiency.
• 4. KoçSistem - BMC Software.
• 5. Top 10 Data Center Automation Tools with Real-Life Examples. AIMultiple
• 6. Opcon SMA “OTS Credit Union Services Organization“
• 7. Automating Mission-critical Claims Processing Fulfills Compliance SLAs.
• 8. Arm Limited Case Study.