Zero Incident Framework
ZIF (Zero Incident FrameworkTM) www.zif.ai is an award winning Artificial Intelligence based Technology Operations (AIOps) tool developed by GAVS Technologies (www.gavstech.com) powered by advanced patent pending Machine Learning techniques to offer the Enterprise Computer Infrastructures a Business Service Level Assurance trending to Zero downtime. ZIF comprises of AI based Predictive Analytics, BOT based Remediation, Monitoring and Virtualized Desktop Infrastructure that could be deployed individually or as an integrated solution. ZIF is an on premise and a SAAS solution.
Agile For Customer And Employee Success - ZIF. Frequently Asked Questions of ZIF - Best AIOps Solutions in USA. 1) Is the ZIF platform implemented as an on-premise or cloud-based solution?
ZIF platform is implemented as a cloud-based solution and connects to the on-premise data centre components via VPN. Industries that prevents data to be sent outside the network, ZIF may be deployed on-premise. 2) Can our technicians access the platform on their mobile devices? Yes, the interface is responsive and intuitive on mobile devices. 3) What is the nature of the post-implementation support provided?
24×7 post-implementation support is provided via email, phone or even chats. 4) How long does it take to get the results once the ZIF platform is installed? Customer Focus Realignment. ZIF - Zero Incident Enterprise PowerPoint Presentation, free download - ID:10198394. Download Skip this Video Loading SlideShow in 5 Seconds..
ZIF - Zero Incident Enterprise PowerPoint Presentation Share Presentations Email Sent Successfully. Is AR is the Future of Digital World-converted - Télécharger - 4shared - zeroincidentframework. How does VDI’s help in Remote Work. The Basics of AI for IT Operations Management - AI for IT Operations AIOps best AIOps solutions AIOps solution in US. Points for CXOs to access AIOps tool: Rates of raw ingestion: The data collection speed is unravelled here from different nodes.Latency of transportRate of data flow to distributed databaseI/ O Mb/ SecRate of Data Processing: It is done for the purpose of measuring consumption.Query Latency: This needs to be monitored in the databaseRates of Pattern Learning:Time of Pattern RecognitionEffectiveness of Pattern RecognitionRate of anomaly detection:No of anomalies detected/ unit time: This measures the number of anomalies which are detected by AIOps.Anomaly co-relation with event data: For contextualizing and effectiveness, the anomaly information’s are correlated with event data and other sources of metrics.Data Utilization: Data from different IT systems and sources are incorporated here from ITOM data, application development tools etc.Support for wide variety of dataIntegration with automation tools: It is crucial to integrate the AIOps tools and the automation tools.
Modern IT Infrastructure. Infrastructure today has grown beyond the physical confines of the traditional data center, has spread its wings to the cloud, and is increasingly distributed, virtual, and abstract.
With the cloud gaining wide acceptance, most enterprises have their workloads spread across data centers, colocations, multi-cloud, and edge locations. On-premise infrastructure is also being replaced by Hyperconverged Infrastructure (HCI) where software-defined, virtualized compute, storage, and network are in one single system, greatly simplifying IT operations.
Infrastructure is also becoming increasingly elastic, scales & shrinks on demand and doesn’t have to be provisioned upfront. Let’s look at a few interesting technologies that are steering the modern IT landscape. Containers and Serverless Traditional application deployment on physical servers comes with the overhead of managing the infrastructure, middleware, development tools, and everything in between. Zero Incident Framework™: Machine Learning: Building Clustering Algorithms. Clustering is a widely-used Machine Learning (ML) technique.
Clustering is an Unsupervised ML algorithm that is built to learn patterns from input data without any training, besides being able of processing data with high dimensions. This makes clustering the method of choice to solve a wide range and variety of ML problems. Machine Learning and Clustering has been best explained by the best digital service desk AI software – Zero Incident Framework (ZIF). ZIF is an award-winning tool developed by GAVS Technologies for the management of AIOps, AI automated root cause analysis solution, AI data analytics monitoring tools and many more such applications. Lambda architecture in Big Data Computing. Inverse reinforcement learning. Zero Incident Framework™ (zeroincidentframework) on Bloglovin’ Inverse reinforcement learning is a recently developed Machine Learning framework that can solve the inverse problem of Reinforcement Learning (RL).
Basically, IRL is about learning from humans. Inverse reinforcement learning in the field of learning an agent’s objectives, values, or rewards by observing its behavior. This blog published by the best AI data analytics monitoring tools, Zero Incident Framework (ZIF), details about Inverse Reinforcement Learning (IRL), challenges with Reinforcement Learning (RL), the difference between IRL and what is its biggest motivation to work with. First, let us know RL. Automating IT ecosystems with ZIF Remediate. Alwinking N Rajamani Zero Incident FrameworkTM (ZIF) is an AIOps based TechOps platform that enables proactive detection and remediation of incidents helping organizations drive towards a Zero Incident Enterprise™.
ZIF comprises of 5 modules, as outlined below. This article’s focus is on the Remediate function of ZIF. Most ITSM teams envision a future of ticketless ITSM, driven by AI and Automation. Remediate being a key module ofZIF, has more than 500+ connectors to various ITSMtools, Monitoring, Security and Incident management tools, storage/backup tools and others.Few of the connectors are referenced below that enables quick automation building.
Key Features of Remediate Truly Agent-less software.300+ readily available templates – intuitive workflow/activity-based tool for process automation from a rich repository of pre-coded activities/templates.No coding or programming required to create/deploy automated workflows. Key features for futuristic Automation Solutions About the Author: Inverse Reinforcement Learning. What is Inverse Reinforcement Learning(IRL)?
Inverse reinforcement learning is a recently developed Machine Learning framework that can solve the inverse problem of Reinforcement Learning (RL). Basically, IRL is about learning from humans. Inverse reinforcement learning is the field of learning an agent’s objectives, values, or rewards by observing its behavior. Before getting into further details of IRL, let us recap RL. Discover, Monitor, Analyze & Predict COVID-19 PowerPoint Presentation - ID:9913032.
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Zero Incident Framework™: Assess Your Organization’s Maturity in Adopting AIOps. AIOps stands for using Artificial Intelligence in IT Operations. AIOps is adopted by organizations to deliver tangible business outcomes. Artificial Intelligence for IT operations implies the implementation of true Autonomous Artificial Intelligence in ITOps, which needs to be adopted as an organization-wide strategy. Thus, the implementation of AIOps requires evaluation and assessment of your organization’s current maturity state, existing landscape, processes, and more. This blog hereby focuses on 4 levels of maturity in AIOps adoption. Assessing an organization against each of these levels helps in achieving the goal of TRUE Artificial Intelligence in IT Operations. Level 1 – Knee Jerk - Events, logs are generated in silos and collected from various applications and devices in the infrastructure. Zero Incident Framework (ZIF) provides for the best AIOps product tools and products. Discover, Monitor, Analyze & Predict COVID-19 – Zero Incident Framework.
COVID-19, a common name now in every household has majorly impacted the world. With people being confined to their homes, and a minimal availability of essential resources, the entire world has come to a standstill. However, this blog published by ZIF (Zero Incident Framework), an AIOps tool for predictive analytics business forecasting, developed by GAVS Technologies, hereby describes how Artificial Intelligence techniques such as Big Data and Machine Learning are helping to discover, monitor, analyze and predict COVID-19. Some excerpts from the article are provided here – Discovering – Chinese technology giant Alibaba has developed an AI system for detecting the COVID-19 in CT scans of patients’ chests with 96% accuracy against viral pneumonia cases.
Per a report, at least 100 healthcare facilities are currently employing Alibaba’s AI to detect COVID-19.