When it comes to setting up new technology – especially one you rely on for monitoring and maintaining IT infrastructure service health and availability – the process is far more intricate than just tweaking a few settings. It demands thoughtful planning and specialized knowledge to ensure seamless integration and alignment with your operational goals. 

That’s why we’re excited to offer the ScienceLogic AI platform in both cloud-based and on-premises configurations. These options are designed to meet your needs for security, flexibility, and cost efficiency. 

Wondering which configuration best suits your requirements? Let’s explore both options and provide insights to help you decide about your organization’s ideal deployment strategy. 

ScienceLogic’s SaaS Offering

One of the most common ways our customers deploy the ScienceLogic AI platform is as a software-as-a-service (SaaS) model.  

ScienceLogic’s SaaS offering is a transformative solution for organizations that seek seamless platform deployment without the complexities of managing deployment architecture. This allows you to shift focus from the intricacies of infrastructure management to optimizing your operational efficiency and business outcomes.  

Consider the benefits:  

  • We manage the infrastructure: CIOs and IT teams no longer need to grapple with hardware procurement, software installations, or infrastructure maintenance. Instead, ScienceLogic assumes responsibility for the underlying technical framework, allowing you to quickly harness the platform’s full potential. 
  • Onboarding is simplified:  The ScienceLogic platform can be swiftly onboarded without the overhead of configuring hardware or setting up intricate software components. Whether your business operates on-premises or in a hybrid environment, ScienceLogic’s SaaS offering adapts to fit seamlessly, ensuring the platform aligns with your organization’s unique technological landscape. 
  • Scalability: Our SaaS offering liberates businesses from the intricacies of deployment and ensures scalability. As your organization expands and adapts, the platform effortlessly scales to accommodate evolving requirements without placing additional burden on IT teams to manage and oversee these changes.  

ScienceLogic’s On-Premises Offering 

If you prefer to run the ScienceLogic AI platform entirely on your own data center or cloud, we provide three configuration options to do so: all-in-one, distributed, and extended. While it’s ultimately your decision, we work closely with you to build and implement the right solution. 

  • All-in-one configuration  

In this configuration, a single node or appliance provides all the platform’s functions running on a single server.  

While the all-in-one configuration simplifies the initial setup and management, it does have some limitations compared to a distributed architecture. Consolidating all the ScienceLogic components into a single system may impact scalability and performance, particularly in large or complex IT environments with high data volumes.  

Ideal for: This configuration is best for smaller deployments.  

  • Distributed configuration  

This configuration divides the platform’s functions between multiple nodes or appliances. A distributed instance can be as small as two nodes or machines or include numerous instances of each node or appliance. This setup allows for efficient scalability, performance, and fault tolerance, as each component can be scaled independently based on the workload and requirements. 

Ideal for: This configuration is best for production environments that monitor many devices or a large volume of data for each device. 

  • Extended configuration  

This is an extension of a distributed instance. The extended configuration adds a compute cluster, a storage cluster, a management node, and a load balancer. This configuration provides scale and can take advantage of the platform agent to collect detailed data about devices and applications, ultimately enriching its ability to diagnose problems and suggest improvements.  

Ideal for: This configuration takes the distributed configuration a step further allowing you to scale out to optimize the various configuration sizes and locations that best suited for large organizations. 

Choosing the Right Configuration

To determine the right ScienceLogic platform deployment, it’s important to evaluate the following factors:  

  • Cost – SaaS offerings can reduce IT infrastructure costs and responsibilities. However, when choosing a deployment, it’s important to compare actual needs with pricing options and ensure you aren’t paying for features you don’t need.  
  • Security needs – Whether on-premises or in the cloud, the ScienceLogic platform is designed to be secure and to operate reliably in even the most secure IT environments in the world. This is affirmed by our Department of Defense Information Network (DoDIN) security certification and compliance with various other security requirements. Visit our Trust Center to learn more. 
  • Scalability – The ScienceLogic platform’s SaaS and distributed on-premises deployments ensure the flexibility and scalability needed to keep pace with innovation and technology integrations and accommodate changes in the number of users or resource needs. Understanding current and future needs is required to make the best choice. 
  • Customization – If you choose to go the SaaS route, you can take advantage of several customization options and get support for integrating with other SaaS tools or on-premises systems through APIs.  
  • Uptime/reliability – In an on-premises deployment, you assume responsibility for lifecycle management, including upgrades, maintenance, and other actions needed for continued use. When deployed as a SaaS offering, that burden is on our shoulders. We manage all servers, databases, and software maintenance, plus all updates are pushed automatically without manual intervention. 

Whatever your needs and goals, ScienceLogic provides the flexibility you need to establish the optimal deployment. Contact us today to learn more. 

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