In this blog post
Data is the single most accountable yet siloed component within any IT infrastructure. According to a Gartner report, an average enterprise IT infrastructure generates up to 3 times more IT operational data with each passing year. Large businesses find themselves challenged by frequent unplanned downtime of their services, high IT issue resolution times, and consequently poor user experience caused by inefficient management of this data overload, reactive IT operations, and other reasons such as:
- Traditional legacy systems that do not scale
- Siloed environments preventing unified visibility into IT landscape
- Unattended warning signs due to alert fatigue
- Lack of advanced tools to intelligently identify root causes of cross-tier events
- Multiple hand-offs that require manual intervention affecting problem remediation workflow
Managing data and automation with AIOps
The surge of AI in IT operations or AIOps is helping bridge the gap between the need for meaningful insights and human intervention, to ensure service reliability and business growth. AIOps is fast becoming a critical need since effective management of the humongous data volumes has surpassed human capabilities. AIOps is powered by AI/ML algorithms that enable automatic discovery of infra & applications, 360o observability into the entire IT environment, noise reduction, anomaly detection, predictive and prescriptive analytics, and automatic incident triage and remediation!
AIOps provides clear insights into application & infrastructure performance and user experience, and alerts IT on potential outages or performance degradation. AIOps delivers a single, intelligent, and automated layer of intelligence across all IT operations, enabling proactive & autonomous IT operations, improved operational efficiencies through reduction of manual effort/fatigue/errors, and improved user experience as predictive & prescriptive analytics drive consistent service levels.
The Need for AIOps for SRE
SRE mandates that the IT team always stays ahead of IT outages and proactively resolves incidents before they impact the user. However, even the most mature teams face challenges due to the rapidly increasing data volumes and expanding IT boundaries, created by modern technologies such as the cloud, and IoT. SRE faces challenges such as lack of visibility and technology fragmentation while executing these tasks in real-time.
SRE teams have started to leverage AI capabilities to detect & analyze patterns in the data, eliminate noise & gain meaningful insights from current & historical data. As AIOps enters the SRE realm, it has enabled accelerated and automated incident management and resolution. With AI at the core, SRE teams can now redirect their time towards strategic initiatives and focus on delivering high value to users.
Transform SRE with AIOps
SREs are moving towards AIOps to achieve these main goals:
- Improved visibility across the organization’s remote & distributed systems
- Reduced response time through automation
- Prevention of incidents through proactive operations
AIOps Platform ZIFTM from GAVS allows enterprises focused on digital transformation to become proactive with IT incidents, by delivering AI-led predictions and auto-remediation. ZIF is a unified platform with centralized NOC powered by AI-led capabilities for automatic environment discovery, going beyond monitoring to observability, predictive & prescriptive analytics, automation & self-remediation enabling outcomes such as:
- Elimination of digital dirt
- IT team empowered with end-to-end visibility
- Breaking away the silos in IT infrastructure systems and operations
- Intuitive visualization of application health and user experience from the digital delivery chain
- Increasing precision in intelligent root cause analyses helping drastic cut in resolution time (MTTR)
- ML algorithms for continuous learning from the environment driving huge improvements with time
- Zero-touch automation across the spectrum of services, including delivery of cloud-native applications, traditional mainframes, and process workflows
The future of AIOps
Gartner predicts a rapidly growing market size from USD 1.5 billion in 2020. Gartner also claims that the future of IT operations cannot operate without AIOps due to these four main drivers:
- Redundancy of traditional approaches to handling IT complexities
- The proliferation of IoT devices, mobile applications & devices, APIs
- Lack of infrastructure to support IT events that require immediate action
- Growth of third-party services and cloud infrastructure
AIOps has a strong role in five major areas — anomaly detection, event correlation and advanced data analysis, performance analysis, automation, and IT service management. However, to get the most out of AIOps, it is crucial to choose the right AIOps platform, as selecting the right partner is critical to the success of such an important org initiative. Gartner recommends prioritizing vendors based on their ability to address challenges, data ingestion & analysis, storage & access, and process automation capabilities. We believe ZIF is that AIOps solution for you! For more on ZIF, please visit www.zif.ai.