AIOps - Artificial Intelligence for IT Operations

Engage us to implement proactive, intelligent and automated IT Operations that gives cognitive insights across services, applications and infrastructure.

AIOps brings artificial intelligence, machine learning, and data science to go from reactive to predictive IT Operations. AIOps automate processes with significantly reduced human intervention and manual efforts. As per recent research by TechValidate found that 97% of surveyed IT organizations agreed that AIOps-enabled solutions that deliver actionable insights will help automate and enhance overall IT Operations functions.

Key Drivers for AIOps

Proactively managing and improving the experience of modern applications, cloud or traditional infrastructures and networks is a must requirement for enterprises to achieve competitive edge. And, it’s not easy with traditional ITOps tools and technologies. IT teams work under tremendous pressure to meet SLAs while managing increasingly dynamic, hybrid, and distributed nature of their computing environments. Additionally, the shift in recent years toward microservices and containers similarly increased the number of components that go into a single application, as well as the challenge of orchestrating all of them.

Today, 80% of the enterprises use automation tools to handle added complexity. However, these traditional automation tools require humans to configure, deploy and manage them. With the adoption of advanced AIOps tools and platforms such as Splunk, Moogsoft, Broadcom and few others offers a better solution to the meet ever increasing complexity in ITSM.

CREST AIOps Implementation Approach

A smarter approach to AIOps begins effectively by performing the essential steps to make AIOps possible. The key steps of AIOps include:

Data Collection and Normalization. We leverage AIOps platforms and big data technologies to collect, transform and aggregate the data as needed from disparate sources, backup and retain data effectively and maintain data quality sufficient for powering data analytics and machine learning for ITOps.

Data Analytics. Once data has been appropriately collected and aggregated, Our data scientists perform statistical analytics to derive insights from the data.

Machine Learning. As next step to data analytics, we deploy machine learning models to learn from the results of data analytics and make automated decisions.

Artificial Intelligence (AI). As a finishing step, we bring AI-based cognitive intelligence in automated IT operations to reduce manual interventions.

Our AIOps Technology and Platform Expertise

CREST AIOps will play a key role in enabling new efficiencies for IT teams. We make practical the adoption of complex next generation AIOps technologies and platforms and integrate them with traditional ITSM solutions. CREST AIOps experts not only helps IT teams to identify problems and areas of concern, it also enables quick resolution of issues once they have been identified using following technologies.

  • ITSM Data Collection and Intelligent Analytics: MoogSoft, Splunk, IBMQradar
  • Data Aggregation Tools and Technologies: Elasticsearch, Apache Kafka, Apache Hive, Apache HBase, CloverETL, KETL, Rsyslog, Logstash
AIOps Technology and Platform Expertise

Benefits We Deliver

Our AIOps professional and engineering services are designed to enhance all IT operations functions, including reliability, performance monitoring, security event analysis and response, and IT service management and automation. Using AIOps, CREST delivers key benefits such as:

  • Boost service levels. Using predictive insights and intelligent IT resource orchestration capabilities, we enable IT team to automatically identify and remediate issues.
  • Enhance operational efficiency. Eliminate manual efforts, streamline workflows, enhance collaboration, and establish autonomous operations by leveraging bet-in-class AIOps tools
  • Enhance agility. We improve agility as well as quality and speed of your ITSM services using intelligent incident detection and remediation.
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