FireScope Solutions for MSPs/CSPs

Drive customer loyalty and reduce overall costs by employing the unique differentiation of FireScope solutions.

Combine easy to implement Discovery and Dependency Mapping with best of breed enterprise service monitoring to give your customers unparalleled value. In the past, Managed Service Providers (MSPs) have had limited options with regards to planning resources and providing real-time monitoring and management of client infrastructures, typically requiring extensive customization, months of work and significant funds. This seriously impacts profitability and the potential to offer customers highly differentiated value. Fortunately, there’s an easier way.

FireScope Discovery and Dependency Mapping makes it easy for your customers to model their existing environment and plan a smooth and complete transition to the cloud.

FireScope Stratis expands on this capability to give your customers a single dashboard view of their critical services, regardless of whether dependencies reside in your cloud or in your customer's data center.

Automated Discovery and Dependency Mapping

A lack of detailed knowledge of IT Service dependencies has many organizations taking a conservative approach to cloud migrations, with possibly up to 25% of cloud-capable compute resources left in-house. If cloud providers could offer dependency discovery as a service as part of the on-boarding process with new customers, the additional revenue derived from more complete migrations would more than pay for itself.

  • Help your customers more effectively plan for cloud migrations by providing accurate maps of IT Service dependencies.
  • Provide unique capabilities for your customers that help you stand out in a crowded market.
  • Give your customers greater confidence that their cloud migration won't bring storms.

FireScope Stratis Delivers These Unique Capabilities for MSP/CSPs:

  • Big Data back end with native data segregation capabilities to support any multi-tenancy requirements. This is in stark contrast to all competitors who require new instances for each customer. Having multiple customers running on a single instance maximizes profitability and simplifies support.
  • Support for Very Large Instances (VLIs) running multiple customers to drive down costs and maximize profitability.
  • Granular, Service-based approach combined with business impact analysis provides deeper visibility for customers and a truly differentiated offering for your customers. While most cloud-based monitoring solutions only monitor applications and user experiences, FireScope provides coverage of the complete service stack, from physical to virtual, applications to user experiences.
  • SaaS delivery model and extensive use of automation to facilitate allocating and deploying new customers without manual effort or the need for extensive professional services and delivering dashboards on day one.
  • Three-layers of elastic scalability giving the solution unlimited scalability, and without the need for a re-install or re-engagement.
  • Support for white labeling to custom brand FireScope Stratis to make it truly part of your existing menu of offerings.



Complete Coverage of the Service Stack

Many emerging cloud-based monitoring solutions claim to provide end-to-end event management, yet when the marketing hype clears, in reality they only have visibility into the application or user experience layers. Effective Event Management cannot be accomplished with this incomplete picture, the virtual and physical infrastructure where the application lives must be included. That's why FireScope includes over 20+ native data collection capabilities as well as key integrations to deliver the complete picture of service health and performance.

Multi-Tenancy Support

FireScope Stratis was designed from the outset to support multiple approaches to secure multi-tenancy, enabling organizations to choose their level of segmentation and isolation. Our approach allows for either virtual or physical segmentation of customer data, without the need to deploy separate instances of FireScope Stratis.

  • Data can be segmented virtually or physically to support any multi-tenancy architecture and regulatory requirements.
  • Not necessary to install a new implementation for each new customer, reducing the effort to implement new customers.
  • Automation enables zero-touch implementation of new customers.
  • Smart data recovery for synchronization connection loss ensures accurate evaluation of data trending and SLA calculation.
  • Dynamically scalable without the need for manual effort, supports truly massive customer environments.
  • This approach also makes it quick and effortless to provision new customers and elastically scale FireScope Stratis. For Managed Service Providers, adding new customers can be as easy as starting a FireScope Edge device at a new customer's location, performing discovery and creating the new customer and their respective users - all of which can be completed in just a matter of minutes.

Automated Configuration

Project lifecycles have gone from 12+ months to just weeks thanks to emerging automation and cloud technologies. Unfortunately, organizations using legacy-monitoring tools require months to configure monitoring for new services, leaving considerable gaps in coverage and consuming hundreds of man hours. Organizations need a monitoring platform that is more agile and requires less manual effort.

FireScope's powerful discovery engine is far and away the most extensive of its kind, leveraging multiple vendor APIs such as those from VMware, NetApp, Cisco and others, as well as physical, virtual and logical topology mapping. When combined with our Blueprint technology, most of the configuration work to monitor your environment is done for you.

  • Powerful discovery enables auto-configuration of monitoring of your technology environment.
  • Discovery utilizes SNMP v1-v3, agents and APIs from VMware, NetApp, Cisco and others to identify all of your critical infrastructure.
  • Blueprints apply best-practice data collection, event analysis and visualization as each asset is identified with dynamic configuration based on asset configuration (number of CPUs, applications found, active ports, storage volumes, etc.).
  • Physical, Network, Service and Logical topology mapping of your environment are all performed automatically.

Big Data Advantage

While many solutions claim to be enterprise scale, the fact is that most monitoring solutions are designed around a relational database (e.g. Oracle, MySQL, MS SQL), severely limiting realistic scalability and performance due to:

  • Well known upper limits to data sets,
  • Data is segregated by tables in pre-defined fields, complicating the ability to query disparate data,
  • Limitations to the number of operations (read, write, searches, indexing, etc.) that can be conducted simultaneously, particularly in scenarios where tables can be locked during write operations, and
  • Redundancy and fail-over clustering capabilities are overly complex and unreliable.

FireScope Stratis is the only Enterprise management platform that leverages Big Data, enabling it to bypass all of these limitations to truly deliver the scalability, performance and depth necessary to replace the legacy monitoring suites from the Big-4 (BMC, IBM, HP, CA Technologies).

FireScope's Elastic Capabilities At-a-Glance

Take a peek inside the FireScope Stratis Cloud. Mouse over any component for a description of its function. Or use the links at the bottom to see how the solution scales.


The Elastic Application Component (EAC) handles securely receiving data collected by Edge devices, normalization and analysis for events, performance, capacity and SLA’s. As data arrives from an Edge device it gets processed by the first available EAC, enabling the solution to scale to support higher volumes of data simply by bringing additional EACs online.


The Elastic Storage Component (ESC) is based on Big Data technologies to maintain a data warehouse of service dependency performance and utilization, of which the EAC and EWC rely.

Out of the box, this architecture supports high availability and secure multi-tenancy. The ESC leverages MongoDB which is horizontally scalable. Rather than buying bigger servers, the solution scales by adding additional servers. Transactions are distributed across the larger cluster of nodes, which linearly increases database capacity.


The Elastic Web Component (EWC) leverages the latest web technologies such as HTML5, CSS3, Canvas and more to deliver 2-clicks to root-cause. Because the user interface is segmented from analysis and storage, it can be dynamically scaled to support an unlimited number of concurrent users while ensuring optimal user experiences.

Edge Devices


FireScope Edge Device(s) resides at each business location and performs discovery and data collection, and pushes the resulting data up to the central FireScope Stratis cloud. All configuration of Edge devices are performed through the central FireScope Stratis interface, enabling new business locations to be easily integrated into dashboards by starting up a new Edge device and pushing down configuration. Edge devices can be physical or virtual appliances, depending on the size of the environment they reside in and volume of data collected.

Use the Slides Below to Trigger Elastic Expansion of:

Event and Attribute Processing Power   

Event and Attribute Storage Capacity   

Concurrent Users   

Data Collection   

  • Elastic scalability across 4 layers - Collection, Processing, Storage and Interface - with loads distributed across multiple instances of each layer.
  • Big Data backend scales horizontally, with no upper limit to the size of the dataset.
  • Distributed nature and massive scale enables support for truly massive environments without sacrificing on depth or performance.
  • Historic data warehouse enables larger sample of data for use in utilization and capacity analysis, resulting in more accurate predictive modeling of resource requirements.
  • Multi-layered redundancy ensures high availability as well as the ability to take specific nodes off-line for maintenance without impacting user experiences.


Infinite Scalability

When it comes to scalability and redundancy, Big Data really proves its value. The solution has the ability to Shard (split) its data, which allows multiple servers to perform query operations simultaneously. Additionally, data is written on multiple instances simultaneously. It's core architecture includes the ability to absorb the failure of a master node and automatically elect the most up-to-date slave as the new master to keep the system functioning.

FireScope is horizontally scalable. Rather than buying bigger servers, we scale by adding additional servers. Built to handle large data sets, FireScope Stratis' use of multiple servers means you have all the resources you need to add compute, memory and storage capacity. As your data set gets bigger, there is no need to upgrade to expensive high-end hardware. This also means you can incrementally adopt newer and faster compute platforms without throwing out the models you had before. high transaction rate environments are easily supported because as more servers are added, transactions are distributed across the larger cluster of nodes, which linearly increases database capacity. With this model additional capacity can be added without reaching any limits.


New Possibilities for Insights

In FireScope Stratis, all data is written as rich objects stored in hierarchical documents. These documents use a flexible schema and can change dynamically as the data itself changes, and that flexibility enables FireScope to collect any type of data, regardless of format and size. This means that all data captured by FireScope can be analyzed against one another, regardless of the methodology of data collection or the format of the data, enabling more sophisticated event analysis. Furthermore, MongoDB offers the most advanced query capabilities of any document database in existance today. In other words, FireScope Stratis has the same complex analytical capabilities that Facebook uses to analyze the behavior patterns of its hundreds of millions of users.