“V5.0, targeted for GA in Q2, is the first part of the transformation of Centerity’s core platform,” say Eran Molot, VP of R&D. “In V5.0, we will introduce a new proprietary monitoring engine. The new engine, which based on cutting edge big data and container based technology, is much more scalable and redundant so we will see much higher performance per collector unit compared to the V4.X “node” methodology. The architecture of V5.0 will handle an amazing amounts of time-series data while the next version, V5.1, will revolutionize the UX/UI completely and increasing security at every level.”
As discussed in Centerity’s Academy 2019 sessions, with Sales teams from the US and EMEA offices participating, V5.0 and V5.1 are not just about an engine replacement, this is a dramatic change in Centerity core product and it’s functionalities.
With the new high performance platform, Centerity now offers many added values for businesses whose critical digital services need to function in highly dynamic IT environments. For example, companies who use Big Data platforms such as Kafka or Elasticsearch as their standard for management data flow will find Centerity’s native integration with both platforms compelling. “The new engine ensures greater scalability and faster deployments” adds Molot. “Advanced collectors send data to the Kafka streamer. The data is then enriched and correlated with other data in a powerful time-series database. These additional technical capabilities create real business value in terms of granular data capture, enhancement and analytics due to substantially greater scalability. Centerity can handle now X10 the data than previous versions via a single interface.”
The new technical attributes drive value and differentiation for Centerity. in V5.X customers will have visibility into the status of key Business Services with a very engaging U/I for critical processes at scale.
users will benefit from an AI-assisted digital business processes that influence business service quality and the user experience, allowing teams to identify IT faults quickly and receive real-time alerts of potential service degradation.
This way, Business Executives and Operations Leaders can minimize digital business service impact due to technology issues to optimize response time, throughput and error rate while decrease MTTR.
“At the end of the day, Business Executives and Operations Leaders are under pressure to do more with less,” says Roi Keren, CEO . “Business Executives and IT Operations Leaders need to ensure digital business success and improve performance, availability and the user experience. With Centerity’s AIOps and Dynamic Business Service Views, executives not only improve business process performance but also reduce operational complexity and costs. Centerity’s real-time, full- stack AIOps platform automatically discovers and organizes complex IT environments a into Dynamic Business Views that proactively ensures that critical service level objects are met.”
Why this is so Important
Digitization (Digital Transformation) is creating a Massive set of Business Critical Applications that have to work and have to perform
These applications are very complex, diverse, and dynamic so they are a massive challenge to monitor in production
Creating an Unprecedented Situation
- Digitization is an unprecedented business imperative for enterprises to compete and execute online as software vendors (Time to Market, Agility, Quality of Service, End User Experience)
- An unprecedented pace of innovation in processes and technology to support the business imperative of digitization
- Time to market pressures are leading to unprecedented levels of diversity in the software stack with continuous changes on a release by release basis
- Time to market and agility pressures are causing applications to be architected around microservices and released multiple times a day with CI/CD processes
- The need for continuous availability and performance is driving dynamic behavior in virtualized and cloud based compute, networking and storage services
Creating a new set of requirements that most monitoring products cannot meet
- The entire stack must now be monitored in real time (1 Min – 1 Sec) to be able to detect service quality issues in time
- Real-time monitoring across the stack creates a deluge of data which requires a big data architecture on the back end of the monitoring products
- AI (AIOps) must be deployed to cope with the deluge of incoming monitoring data and automatically understand normal vs. abnormal
- Relationships across the stack must be determined in real time
- AIOps and relationships must be leveraged for automated root cause
- The results of monitoring must be made relevant to business constituents