FireScope Stratis - 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:

  1. Well known upper limits to data sets,
  2. Data is segregated by tables in pre-defined fields, complicating the ability to query disparate data,
  3. 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
  4. 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.

EAC

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.

ESC

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.

EWC

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.

 

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.

 

 

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.