How ZIF Delivers Service Reliability to Financial Institutions Using AIOps

Financial institutions use business applications to provide services to their users. They have to continuously monitor the performance of business applications to enhance service reliability. During peak business time, the number of impactful incident increase that downgrades the performance of business applications. IT experts have to spend more time addressing the incidents one by one. Financial institutions can use an AI-based platform for maintaining business continuity and service reliability. Let us know how ZIF enhances services reliability for financial institutions via AIOps.

What is service reliability?

Financial institutions are undergoing digital transformation quickly. For providing a digital user experience, financial institutions use software systems, applications, etc. The business applications need to perform continuously according to their specifications. If the performance gets deteriorated, business applications may experience downtime. It will have a direct effect on the ROI (Return on Investment).

Service reliability ensures that all the business applications or software systems are error-free. It ensures the continuous performance of IT systems within any financial institution. Business applications should live up to their expectations without any technical error. Financial institutions that have better service reliability also have larger uptime. Service reliability is usually expressed in percentage by IT experts.  

What is AIOps?

AIOps (Artificial Intelligence for IT Operations) is used for automating and enhancing IT processes. AIOps uses the mixture of AI and ML algorithms to induce automation in IT processes. In this competitive era, AIOps can help a business optimize its IT infrastructure. IT strategies can be deployed at a large scale using AIOps.

The use of AI in IT operations can reduce the toll on IT experts as they don’t have to work overtime. Any issues with the IT infrastructure can be addresses in real-time using AI. AIOps platforms have gained popularity in recent times due to the challenges posed by the COVID pandemic. Financial institutions can also use an AIOps platform for better DEM (Digital Experience Monitoring).

What is ZIF?

ZIF (Zero Incident Framework) is an AIOps platform launched by GAVS Technologies. The goal of ZIF is to lead organizations towards a zero-incidence scenario. Any incidents within the IT infrastructure can be solved in real-time via ZIF. ZIF is more than just an ordinary TechOps platform. It can help financial institutions to monitor the performance of business applications as well as automate incidence reporting.

Service reliability engineers have to spend hours solving an incidence within the IT infrastructure. The downtime experienced can cost a financial institution more than expected. ZIF is an AI-based platform and will help you in automating responses to incidents within the IT infrastructure. ZIF can help financial institutions gain an edge over their competitors and ensuring business continuity.

Why use ZIF for your financial institution?

ZIF has multiple use cases for a financial institution. If you are facing any of these below-mentioned challenges, you can use ZIF to solve them:

  • A financial institution may receive alerts at frequent intervals from the current IT monitoring system. An institution may not have enough workforce or time to address such a high volume of alerts.
  • Useful IT operations for a financial institution may face unexpected downtime. It not only impacts the ROI but also drives the customer away.
  • High-impact incidents within the IT infrastructure may reduce the service reliability of a financial institution.
  • A financial institution may have poor observability of the user experience. It will lead to the inability in providing a personalized digital experience to customers.
  • The IT staff of a financial institution may burn out due to the excessive number of incidents being reported. Manual efforts will stop after a certain number of incidents. 

How ZIF is the solution? 

The functionalities of ZIF that can solve the above-mentioned challenges are as follows: 

  • ZIF can monitor all components of the IT infrastructure like storage, software system, server, and others. ZIF will perform full-stack monitoring of the IT infrastructure with less human effort. 
  • ZIF performs APM (Application Performance Monitoring) to measure the performance and accuracy of business applications. 
  • It can perform real-time APM for improving the user experience.
  • It can take data from business applications and can identify relationships between the data. Event correlation alerts by ZIF will also inform you during system outages or failures. 
  • ZIF can make intelligent predictions for identifying future incidents. 
  • ZIF can help a financial institution in mitigating an IT issue before it leaves its impact on operations. 

What are the outcomes and benefits of ZIF?

The outcomes of using ZIF for your financial institution are as follows: 

  • Efficiency: With ZIF, you can enhance the efficiency of your IT tools and technologies. When your IT framework is more efficient, you can experience better service reliability
  • Accuracy: ZIF will provide you with predictive insights that can increase the accuracy of business applications. IT operations can be led proactively with the aid of ZIF. 
  • Reduction in incidents: ZIF will help you in identifying frequent incidents and solving them once and for all. The number of incidents per user can be decreased by the use of ZIF. 
  • MTTDZIF can help you identifying incidents in real-time. Reduced MTTD (Mean Time to Detect) will have a direct impact on the service reliability. 
  • MTTR: ZIF will reduce the MTTR (Mean Time to Resolve) for your financial institution. With reduced MTTR, you can offer better service reliability
  • Cost optimization: ZIF can replace costly IT operations with cost-effective solutions. If any IT operation is not adding any value to your institution, it can be identified with the aid of ZIF

ZIF can help you in automating various IT processes like monitoring, incident reporting, and others. Your employees can focus on providing diverse financial services to customers besides worrying about the user interface. ZIF is a cost-effective AIOps solution for your financial institution. 

In a nutshell 

The CAGR (Compound Annual Growth Rate) of the global AIOps industry is more than 25%. Financial institutions are also using AI for intelligent IT operations and better service reliability. Service reliability engineers in your organization will have to put fewer manual efforts with the help of ZIF. Use ZIF for enhancing service reliability! 

How Observability Bolsters Site Reliability Engineering

Are you familiar with the benefits of AIOps (Artificial Intelligence for IT Operation)? Well, artificial intelligence allows businesses to automate IT processes that require fewer human efforts. A key process for automating IT operations is SRE (Site Reliability Engineering). Read on to know about SRE and how it is affected by observability.

What is Site Reliability Engineering?

The IT operations in an organization are performed with the help of various software systems. These software systems are deployed on a large scale and need monitoring. There may be various types of large-scale software systems in an organization like supply-chain management, emergency response, etc. Businesses often hire expert system administrators to oversee the software systems.

To solve the underlying problem, site reliability engineering, a type of software engineering, was introduced. SRE can be termed as a better version of DevOps as it is not divided into multiple teams. SRE aids in building a reliable and scalable software system for an organization. It doesn’t just oversee the software development process but also reduces the friction between the development team and operations team.

Site reliability engineers induce required codes into the software to ensure that it does not need any human intervention The development team constantly wants to launch new updates or software(s). Contrary to that, the operation team only wants to launch an update/software after it is thoroughly tested. SRE removes this conflict between both teams and aids in developing reliable system software.

Understanding Observability in SRE?

How would you work with invisible software? It is difficult to measure the performance of any system software if you are not aware of its internal components that drive the performance. The outputs of system software are analyzed to know about the internal states of system software. High observability allows us to know about the internal states of system software. Observability is the measure of the degree that reflects how well the internal states of system software can be inferred.

Site reliability engineers willingly code their software to provide metrics and logs. These metrics are then used to know about the internal state of the software. Observability may seem similar to monitoring but, it is not. Besides telling about the functioning of the system software, it also provides required data to solve underlying problems in the system.

Due to enhanced observability, site reliability engineers do not have to eliminate a potential risk themselves. They can have access to data insights that contain the possible solution. AIOps with rich observability guide on eliminating a risk/problem in system software. The engineers will only know the external outputs of the system software and can still know about its internal state due to enhanced observability.

Pillars of Observability

The three pillars of observability are as follows:

  • Metrics: Metrics are used by reliability engineers to determine the health of the system. For example, there is a threshold for CPU consumption and, when the consumption goes beyond that number, it is being overused. A metric is defined for CPU consumption and alerts can be triggered when the consumption is more than usual. Site reliability engineers use metrics to find the threshold value and set trigger alerts.
  • Logs: Logs are mostly referred to at the time of any problem with the software system. It is a statement that describes the anomaly that occurred. A log can be generated as plain text or structured texts depending upon the requirements.
  • Traces: A trace helps us in determining the execution of a piece of code. Reliability engineers combine the traces and can find the code execution flow in a distributed software system. One can get to know about the part of code that is being executed in more time as compared to other code blocks.

Knowing about the pillars of observability also highlights its importance. Metrics, logs, and traces can help site reliability engineers to know more about the software system by asking questions from outside. While troubleshooting, reliability engineers do not analyze the pillars of observability separately. The pillars of observability should be analyzed together to gain a better understanding of the system and solve the underlying problems.

Benefits of Observability for Site Reliability Engineers

Some of the main benefits of observability for SRE are as follows:

  • Site reliability engineers study the observability pattern and can easily manage any incidents.
  • It will improve the uptime of software systems in an organization.
  • Observability provides a platform for inspection under SLO (Service -Level Objective).
  • When SLOs are not met and, the system software doesn’t live up to the expectation, observability is used to find the possible solution.
  • An employee has a limit to analyze and understand large chunks of data. With enhanced observability, the cognitive load of the data analysis team is reduced.
  • Observability brings together multiple autonomous teams to work together for a single goal.
  • Observability improves the productivity and innovation standards within an organization.
  • Site reliability engineers do not have to access the internal data of a software system to know about its performance. With enhanced observability, reliability engineers can easily find the performance of the software system by its outputs.

Observability Vs Monitoring

Observability definition may sound similar to monitoring but, it is not. As you delve deeper, you will understand that monitoring only informs us about the underlying problem and not the solution. Contrary to monitoring, observability allows us to find the possible solutions and measure the performance of a system.

The pillars of observability help us in making sure the system software is doing the job it was intended to do. Unlike monitoring, observability can identify and mitigate risks associated with system software(s).

In a Nutshell

For automating business processes and systems, first, you need to know about the underlying problems. Enhanced observability can determine the health of a system and can highlight underlying problems. AI-driven observability is also being preferred by businesses nowadays. Site reliability engineering is strengthened if the systems offer high observability. Go for high observability in your software system(s)!  

Exploring AIOps? Here’s Where to Begin

The IT operations, the lifeline of a company or a business, is where the active response system of the firm is centered. Constant innovation has led to significant changes in the operational infrastructure over the last few years and brought new-age challenges to the fore that continue to test the limitations of the existing structure. Especially with the digital revolution that is increasingly transforming the way businesses function and manifest themselves, the ITOps struggle to cope with the mounting data volume and in leveraging inputs from core systems.

This is prompting businesses to push their boundaries and resort to Artificial Intelligence (AI) solutions with greater bandwidth. AIOps or Artificial Intelligence for IT operations is the way traditional IT services and management can be reassessed by integrating machine-based learning and abilities into the existing database and launching it in a broader spectrum. This involves functions like automation, availability, event correlation alerts, and delivery at par with the rising complexities of the business.

AIOps as evolving platforms

The penetration of AIOps in modern job design has been slow but steady. Big business enterprises are now looking at AIOps as an advanced tool to single-handedly manage extensive data monitoring and analysis while processing burgeoning data and information load at a remarkably fast pace. AIOps are programmed for tackling a diversity of output for exact and efficient error spotting in real-time situations followed by critical problem-solving and addressing high-risk outages. Besides, the predictability of AIOps provides a clear sense of the shortcomings and be prepared for unforeseen disruptions in the workflow.

According to reports by the world’s leading research and advisory company and IT management specialist Gartner, the use of AIOps may rise exponentially in the next 3-5 years at a rate of up to 30% that can help catapult business statuses remarkably. However, harnessing this technology requires a solid investment which is why the businesses are interested in a model that is reliable and can prove to be beneficial to the clients and profitable to these ventures at large.

The roadmap for AIOps

Launching and incorporating a versatile technology like AIOps with the current business machinery can seem daunting initially. However, before proceeding with the AI setup, it is essential to consider both the immediate and long-term implications of such an arrangement. Most often, organizing pre-existing records is the key to implement AIOps to the best of capacity.

Here are a few pointers a business can follow to launch its own AIOps interface:

  • It’s always wise to understand the technology before applying it. AI is no rocket science but requires a focused approach to make sense of its terminology. Persistent engagement with the AI tools can result in a better grasp of the subject matter and an assured involvement with related projects and other stakeholders.
  • Start small and simple and demonstrate the power of AIOps to your team in the most convincing manner possible. Highlight the specific problems that you expect your AIOps to fix including the anomalies that escape human surveillance. This could imply automatic troubleshooting and recovery responses if the system reports any malfunction. In a larger picture, this will helps mobilize isolated IT entries and integrate the work ecosystem with a more robust yet feasible strategy.
  • Allow room for experiments to evaluate the true potential of an AIOps application. Even if the whole initiative is cost-intensive, there are resources available at a reasonable rate that can be used to expand knowledge and tap into its wide range of functionality.
  • Be well-versed with digital analytics and statistical figures to enable the management of big data and helps track and monitor performance updates. This gives a direct insight into the positioning of your business and measures that can be taken to upscale possibilities.
  • Equip your infrastructure with State-of-the-art facilities that can shoulder the AIOps network and fully support the system upgrades that may emerge in the process.
  • When it comes to monetization of the business, the AIOps capitalize on the Return on Investment factor and help the company earn big bucks and invest in furthering the threshold. This can give a fair sense of how to fund AI-driven businesses at every stage.


The partnership between IT and AIOps is the new currency for optimizing the digital operations of a company. AI could very well be the gamechanger but it requires the informed use of this feature to take any enterprise to the next level. AIOps are also ‘guardians of security’ of confidential data owing to their prompt detecting abilities that minimize the risk of breach, leaks, cloning, and other potential threats that may hamper its credibility.

Therefore, embrace this top-notch, persuasive technology without fear or hesitation as it not only beats the operational status quo in theory but also sets revolutionary but achievable standards for your business. As a result, your project becomes more ambitious and future-oriented and the tech more approachable and ubiquitous with each passing day.

AIOps Trends Reinforced by Covid-19

Are you able to manage your IT operations effectively? Well, managing IT operations can be more complex when you decide to scale up your IT infrastructure. The recent COVID pandemic has affected the IT ecosystem adversely. IT experts aren’t able to control the IT operations effectively as they can’t go to the workplace. All these issues led to the rise of AIOps (Artificial Intelligence for IT Operations). AIOps can help an organization to manage its IT operations and systems amidst the COVID pandemic. Read on to know about the AIOps trends reinforced by this global pandemic. 

What is AIOps?

Before we move on to the latest trends in the AIOps market, you should be well aware of the AIOps definition. AIOps use the blend of AI (Artificial Intelligence) and ML (Machine Learning) to solve issues in IT operations. AIOps can enhance or replace any IT process depending upon the requirements of any particular business.

It induces automation in IT operations and makes them less tedious. Various IT processes like data analysis, event correlation, service management, and others can be automated using AIOps. AIOps platforms can cope with the increasing volume and variety of business data. AIOps help businesses to boost productivity and maintain business continuity. Even if no one is there to manage your IT operations, you can still complete key processes using AIOps.

AIOps trends fuelled by the COVID pandemic

The recent COVID pandemic led to the suspension of business activities for a long time in various countries. It was hard for business owners to maintain business continuity in these times. Companies could not provide a reliable IT infrastructure to their employees outside the office premises. AIOps use cases were discovered during this time and, businesses started using them. The COVID pandemic led to the rise of many AIOps companies and use cases. Let us see some of the latest AIOps trends reinforced by the COVID pandemic.

Decrease downtime

This pandemic forced employees to move out of their organizational workplaces. The WFH (Work from Home) culture was quickly adopted by businesses for ensuring business continuity. However, the remote IT infrastructure was not up to the mark and significantly decreased productivity. System administrators and site reliability engineers could not visit each employee’s house for fixing operational issues.

To adapt to the remote work culture, firms started using AIOps tools. AIOps can address IT issues without the need for a system administrator. Responses to common IT operational issues can be automated using AIOps. It helped businesses to decrease the downtime significantly as their IT operations are running without any human intervention.


Every business produces large chunks of data that are used to extract meaningful insights. However, with remote work culture, it gets difficult to safeguard the business data. The growing complexity of the IT infrastructure makes it difficult for cybersecurity experts to identify the source of the problem. Also, they cannot rush to the workplace for addressing data breaches due to the COVID pandemic.

An AIOps platform for cybersecurity will help you in identifying the threats and automating responses to them. AIOps solutions for cybersecurity offer strong observability into your organization’s data. The source of a cyber-attack can be easily determined via AIOps. Even if no one is there at the workplace, data breaches can still be stopped using AIOps.


Better observability lets us know about the internal states of IT systems being used. AIOps connects the IT frameworks and provides end-to-end visibility. Due to the COVID pandemic, engineers cannot visit the home of each employee to know about the internal states of IT systems. With AIOps, you can monitor the performance of IT infrastructure in real-time.

Not only for the employees, but AIOps can also provide a better user experience to customers while interacting with digital interfaces. AIOps also helps CIOs (Chief Information Officers) with digital experience monitoring. With enhanced observability, you can improve the customer experience and productivity.

AIOps & DevOps

DevOps is focused on removing the gap between the development and the operations team. However, due to the COVID pandemic, both the teams are working remotely and, it is hard to collaborate. AIOps enhances the communication between the development and operations team and allows east collaboration. Continuous monitoring of DevOps processes via AIOps will provide better results.

AIOps can automate various DevOps processes like feedback collection, monitoring, deployment, and others. AIOps vendors offer products that are capable of performing testing during the development cycle without any human intervention. AIOps products focus on strengthening the integration between different IT teams so they work together to achieve business goals.

Digital transformation

Due to the COVID pandemic, businesses have to opt for online marketing strategies. The only way left to connect with the audience is via digital interfaces. Digital transformation not only requires adopting the latest technologies but also involves continuous monitoring. You will also have to perform data analysis to extract meaningful insights from the data produced via digital platforms.

AIOps can help you with digital transformation and can also help you make the best out of the business data. AIOps automation can help in analyzing data in real-time and extract meaningful insights. High-end data analytics via AIOps can help you in making better business decisions.

Cost optimization

The recent COVID pandemic has harmed businesses. The market disruptions caused by this pandemic have severely affected the ROI (Return on Investment) of businesses. Business owners are looking to slash costs by downsizing their staff thus, impacting the business adversely.

With AIOps, you can automate IT operations and do not need to affect your business reach. The cost of AIOps may seem high in the beginning but is less in the long run. You will also have to spend less on AIOps training as it is easy-to-use and an automated platform.

In a nutshell, The global AIOps market size will grow with a CAGR of 21.05% by 2026. It is the right time to use AIOps and steer through the challenges posed by the COVID pandemic. Use AIOps for business continuity and better uptime!  

Top 6 Things AIOps Can Do for Your IT Performance

With technological advancement and reliance on IT-centric infrastructure, it is essential to analyze lots of data daily. This process becomes challenging and often overwhelming for an enterprise. To ensure the IT performance of your business is on par with the industry, Artificial Intelligence for IT operations (AIOps) can help structure and monitor large scores of data at a faster pace.

What are AIOps?

It is the application of artificial intelligence, machine learning, and data science to monitor, automate and analyze data generated by IT in an organization. It replaces the traditional IT service management functions and improves the efficiency and performance of IT in your business.

AIOps eliminates the necessity of hiring more IT experts to monitor, manage and analyze the ever-evolving complexities in IT operations. AIOps are faster, efficient, error-free, and reliable in providing solutions to issues and challenges involved in IT.

Top 6 Things AIOps can do for your IT Performance

By moving to AIOps you save a lot of time and money involved in monitoring and analyzing using the traditional methods. You can also eliminate the risk of faulty data or outdated reports by opting for AIOps. Here are six reasons to choose AIOps and how they can enhance your IT performance.

1. Resource Allocation and Utilization

AIOps make it easy for an enterprise to plan its resources. Real-time analytics provides data on the infrastructure necessary for a seamless experience be it the bandwidth, servers, memory, and more details.

AI-based analytics also helps an enterprise plan out the capacity required for their IT teams and reduce operational costs. With AI-driven analytics, the enterprise knows the number of people required to address and resolve events and incidents. It can also plan the work shifts and allocate resources based on the number of incidents during any given time.

2. Real-time Notification and Quick Remediation

Real-time analytics has made it easy to make quick business decisions. With AIOps, businesses can create triggers for incidents and can also narrow down business-critical notifications.

According to a study, about 40% of businesses deal with over a million events daily. Assessing priority events becomes an issue in such cases. AIOps help businesses prioritize and effect quick remedies for anomalies. The priority incidents can then be assigned to the IT team to resolve on priority.

3. Automated Event and Incident Management

Using data collected by AIOps, both historical and real-time, businesses can plan for different events and incidents. Thus, offer automated remedies for such incidences.

Traditionally, detection and resolution of such events took a long time and required larger incident management teams. It also meant that the data collected would not be real-time.

Using AI-based automation reduces the workload and ensures that an enterprise is equipped to handle current incidents and planned events. It also requires less manpower to deal with such incidents saving a business from hiring costs.

4. Dependency Mapping

AIOps help understand the dependencies across various domains like systems, services, and applications. Operators can monitor and collect data to mark the dependencies which are even hidden due to the complexities involved.

AIOps even analyze interdependencies that might be missed unless there is thorough monitoring of data. It helps enterprises in the process of configuration management, cross-domain management, and change management.

Businesses can collect real-time data to map the dependencies and create a database to use in change management decisions like when, how, and where to affect system changes.

5. Root-cause Analysis

For improved IT efficiency and performance, understanding the root cause of anomalies and correlating them with incidents is important. Early detection will help affect quicker remedies.

AIOps let IT teams in a business have visibility on anomalies and their relation to abnormal incidents. Thus, they can respond quickly with efficient resolutions for a smooth experience.

The root-cause analysis also helps in improving the domain and ensuring that the business runs efficiently with less exposure to unknown anomalies. Businesses are equipped to investigate and remedy the issue with better diagnoses.

6. Manage IoT

With many Internet of Things devices used widely, the necessity to manage data and the device complexity is of utmost importance. AIOps sees a wide application in this field and help manage several devices at the same time. The sheer volume of devices can make it overwhelming to manage IT operations.

IoT devices have several variables in play and operators require AIOps to manage them with ease. Machine learning helps leverage IoT and monitor, manage and run this complex system.

AIOps ensure that the IT performance thrives with consistent efficiency. It not just helps monitor large data in real-time but also detects issues, analyzes correlation, and ensures quick resolutions. Automated resolutions and management can eliminate downtime and save time and money for any business.

In a nutshell, AIOps aid in the consolidation of data from various IT streams and ensures you receive the highest benefit out of it. Whether it results in automation, resolving incidents at a quick pace, or finding anomalies and making data-driven decisions, AIOps help an organization while ensuring the IT performance is efficient.

ZIF Offers a Resilient IT Cure to the Healthcare Sector

The healthcare sector is going through a paradigm shift as more and more facilities are undergoing digital transformation. The use of new-age technologies like AI and ML have boosted the productivity of healthcare facilities. Healthcare facilities are now focusing on implementing an organized IT infrastructure. Besides offering products and services, the healthcare industry is also involved in finance processes. To manage these components of the healthcare sector, a robust IT framework can be established. Read on to know how ZIF can offer a resilient IT cure to the healthcare sector.

What is ZIF?

ZIF (Zero Incidence Framework) is an AI-based framework distributed by GAVS Technologies. It is an AIOps (Artificial Intelligence for IT Operations) platform. AIOps platforms are used for inducing automation and resilience in the IT infrastructure. AIOps products use AI and ML to reduce the number of incidents in the IT infrastructure.

ZIF can help you in discovering business applications in your environment. It helps in monitoring the performance of digital interfaces in your environment. You can not only set a reliable IT infrastructure but can also make it resilient. Your IT tools and technologies will be able to recover quickly from any outage/failure with ZIF.

Artificial intelligence in the healthcare industry

Before choosing ZIF for your healthcare facility, you should be aware of the use cases of artificial intelligence. The uses of AI-based platforms in the healthcare industry are as follows:

  • AI is being used for medical imaging by healthcare facilities.
  • AI is used for drug discovery.
  • AI-based platforms are used by healthcare facilities for better IT infrastructure.  
  • AI helps in automating cybersecurity processes in the healthcare sector.
  • AI is used to create virtual health assistants.

ZIF for IT infrastructure in the healthcare sector

Healthcare facilities run critical enterprise applications that are responsible for patient care. If the performance of such critical applications downgrades, it will harm the reliability of the healthcare facility. The IT landscape has changed a lot over the years and, healthcare facilities are finding it hard to keep up. Most healthcare facilities do not hire IT experts and use premade IT frameworks for patient care. The premade frameworks often fail when they experience more load and traffic. All these challenges can be solved by using ZIF for a robust IT infrastructure in your healthcare facility.

ZIF is a reliable AIOps solution that can help you in eliminating risks and incidents from your IT infrastructure. ZIF works on an unsupervised learning model and does not needs more manual efforts. With the growing needs of a healthcare facility, ZIF can help the IT infrastructure to scale up. Your workers can focus on treating the patients while ZIF can handle the service reliability of your digital solutions.

System reliability with ZIF

The healthcare software systems are very sensitive and, a slight mishap can cause a big blunder. The Healthcare industry has to learn from past system failures to make sure it never happens. Healthcare systems should be safe and reliable to provide the best results. Healthcare organizations often face challenges while upgrading their software systems according to the requirements. System reliability in healthcare is measured in terms of failure-free operation of software systems.

ZIF will help you in ensuring that digital systems operate without any failures over time. It will continuously check for any issues with software systems. Once an incidence is reported, ZIF will help you in eliminating it as soon as possible. It will help you in enhancing system reliability and uptime for your healthcare facility.

Enhanced monitoring with ZIF

Due to the recent COVID pandemic, healthcare organizations have started monitoring the health of patients remotely. For online advisory and telemedicine, healthcare facilities have to deploy the required systems. They need to have reliable systems that connect them to the patients. For the continuous performance of these systems, they are connected to a central monitoring system. If the monitoring system is not able to detect the reason for the poor performance of other systems, it may harm the patient’s health.

With ZIF, you can monitor the health of all the consolidated systems under one dashboard. The OEM device monitoring feature of ZIF lets you analyze the health of digital systems anytime. ZIF is a reliable AIOps tool that can let you set thresholds for the maintenance of digital systems. ZIF also provides a consolidated view of your organizational data for high-end analytics. The monitoring of all digital systems via ZIF can significantly increase service efficiency.

Reliability prediction with ZIF

ZIF not only solves the current incidences but also predicts future incidences. ZIF will evaluate the performance of systems and will predict their future failure chances. ZIF will provide you with a failure rate that can define the vulnerability of a system. It will let you make proactive approaches to eliminating future failure chances. You can create resilient IT systems with ZIF for your healthcare facility. Resilient IT systems quickly recover after an incidence and provide effective performance over time.

Autonomous IT systems with ZIF

Do you want your staff members to focus more on patient service than system monitoring? Well, ZIF will help you in automating various day-to-day IT operations. You can set automated responses for a particular type of incidence via ZIF. It is an AIOps solution specifically designed for autonomous and predictive IT processes.

ZIF will monitor user experience and identify latencies and anomalies in real-time. This process will be done automatically by ZIF without any manual efforts. Even if the end-user is not able to identify any anomaly, ZIF will find it out. You can configure ZIF to send automated and real-time alerts for any incidence. It will also provide the SOP for incidence protection in real-time.

In a nutshell

The global AIOps market size will reach around USD 20 billion by 2025. AIOps platforms for healthcare can help them undergo digital transformation quickly. ZIF can help you with device monitoring and enhancing system resiliency. Choose ZIF for system reliability and resiliency!

Why You Should Outsource Your AIOps Needs

Are you scaling up the IT infrastructure for your business? Well, upscaling IT infrastructure comes with its challenges. You will need more employees to manage the IT operations effectively. This is where AIOps come into action. AIOps (Artificial Intelligence for IT Operations) is being adopted by firms to automate their key IT processes. Read on to know more about AIOps and why you should outsource your AIOps needs. 

What is AIOps?

AIOps is a new-age solution for IT operations that works on smart algorithms. The smart algorithms behind an AIOps platform are powered by artificial intelligence and machine learning. AIOps platforms for businesses are multi-layered platforms that reduce human intervention. It not only automates mundane IT tasks but also increases productivity. Repetitive IT tasks like performance monitoring, event correlation, and others can be automated via AIOps. 

AIOps is capable of managing the ever-growing IT infrastructure for a business. A business may not require the services of system administrators after using AIOps. AIOps is also capable of handling high volumes of business data that are always increasing. The data generated by IT processes can be easily analyzed via AIOps. This helps the management to access meaningful insights and make informed decisions.

Why does my business need AIOps?

AIOps tools are beneficial for a business and can boost productivity and administration. The main reasons that highlight the importance of AIOps tools for your business are as follows: 

  • Digitalization: Every business wants to dive into this new era of digitalization. With digital transformation, you can save time, effort, and money. AIOps can help in enhancing the visibility of the IT infrastructure and digital applications in your organization. 
  • Cloud enablement: IT services and applications can be deployed and operated via the cloud. AIOps can help you with enabling IT services via the cloud for your business. You can also automate cloud operations and can also monitor the health of the cloud system. 
  • Easy deployment: Organizations perform IT monitoring to identify the issues in the IT infrastructure. When an issue is detected, it takes hours to mitigate it and get the system online. With AIOps, you can automate the actions in response to IT issues thus saving time and effort. 
  • MTTD and MTTR: MTTD (Mean Time to Detect) and MTTR (Mean Time to Resolve) are important metrics for organizations to solve problems like system outages. With AIOps, you can reduce the MTTD and can identify issues quickly. Reduced MTTD via AIOps will help in increasing the uptime of your system software(s). 
  • Real-time analysis and automation: AIOps platforms record and IT data produced by the system software(s). It applies various algorithms to the data in real-time to produce meaningful insights. With AIOps, you can diagnose issues in real-time with the help of actionable insights. 
  • Security AutomationAIOps can help you automate the first-level incident response for your systems. It can also help with virus elimination and access management. You can pre-define a response to any particular system issue and it will be automatically applied next time via an AIOps platform. 

These were some of the main business processes that can be automated with the aid of AIOps. AIOps has diverse applications and can help in better administration and management of system software(s). According to studies, around 30% of businesses will be using AIOps for monitoring applications and business infrastructure by 2023. You can also outsource your AIOps needs and ensure better business resilience and continuity. 

Why outsource AIOps processes?

Developing and deploying an AIOps platform requires knowledge about the new-age technologies. It is hard to find AI/ML experts that can work full-time for your business. A reliable third-party that offers AIOps solutions will already have AI/ML experts. You don’t have to go through the recruitment process to hire in-house AI/ML experts.

If you go for recruiting AIOps experts, you will have to spend funds for recruitment and training. By outsourcing your AIOps needs, you can save money and also time. It will also be beneficial in the long run as you can automate key business processes via AIOps. IT operations are often affected by the high volume of data produced every day. AIOps can help team leaders to analyze this data and act upon it.

Different IT teams work on their respective operations and it makes it tough to address any immediate incident. Outsourcing your AIOps needs will help you in automating responses to such urgent incidents. Your full-time employees will have to put less effort into ensuring resilience and business continuity. 

How to start outsourcing my AIOps needs? 

The recent COVID pandemic has influenced various market disruptions. Organizational workplaces were also affected due to the COVID pandemic. System administrators are finding it hard to monitor the system software(s) remotely. It is better to adopt AIOps for the automation of system software(s). Some of the tips for outsourcing your AIOps needs are as follows: 

  • Adapt AIOps for smaller IT operations first that require fewer efforts. This way you will start small and can see the immediate benefits of AIOps. Once AIOps is successful for your initial test cases, you can apply the same to other IT operations. 
  • Look for areas that require more human effort and are costing you a lot. Such IT operations can be automated via AIOps. You can use your skilled workforce for other business processes. 
  • Free AIOps platforms are also available in the market but are not capable of handling complex IT operations. You should focus on building a customized AIOps platform for your business that can resolve complex operational issues. 
  • Partner with a reliable outsourcing firm that offers an effective AIOps platform
  • Influence your employees and stakeholders to use AI-based technologies for better business performance and uptime. 
  • Identify IT areas with greater downtime and apply AIOps for those operations first. 

In a nutshell 

The global AI market size will be more than $260 billion by 2027. More and more businesses are using AIOps for ensuring business continuity and sustainability. You can outsource your AIOps needs for cost optimization and reducing manual efforts. Choose an AIOps platform for your business! 

Lack of Visibility into User Experience: A CIO’s Nightmare

Have you hired a CIO (Chief Information Officer) for your organization? A CIO in an organization is responsible for managing the computer technologies used by the employees. However, sometimes CIOs find it hard to analyze the technological standard of an organization due to lower visibility. Read on to know more about the lack of visibility into the user experience.

What is a CIO?

A CIO monitors the technologies used by an organization and the usability of the information produced within the organization. Since more and more firms are working on a digital platform, the roles of CIOs have significantly increased over the years. CIOs find out the benefits of technologies used within the organization. A CIO makes sure that each technology is being used for any particular business process.

A CIO also analyses the technologies offered by a firm to its users. It makes sure that the information and technologies within an organization are used for the betterment of the organization. CIOs help a firm to adapt to the changes and use the latest technologies that can make the business processes less tedious.

Digital experience monitoring

DEM (Digital Experience Monitoring) is one of the main job responsibilities of a CIO. DEM is monitoring the way a customer or internal employee interacts with the digital interface of the firm. DEM analyses the user behavior within an enterprise application or digital interface. It focuses on checking the availability of enterprise applications. DEM helps us in knowing the user’s experience with any particular application and how to improve it.

DEM is done for both customers as well as internal employees. The DEM for internal employees is often referred to as EUEM (End User Experience Management). Digital interfaces can be any technology used by the firm to connect with customers. It can be the firm’s website used by customers to access the offered services or, it can be a management system accessed by the internal employees. You can provide a better customer experience with the help of DEM. Sometimes CIOs face hassles while improving the user experience as they have very little visibility into applications and system software(s).

What does poor visibility mean?

Good visibility signifies how well you can view and access the offered services. Every firm has its services that are visible to the users. If a user cannot find/interact with your offerings easily, it implies that your firm offers poor visibility. Visibility is talked about in the context of the user applications that work as a substrate between the firm and the user. For example, an e-commerce website contains a link to check the real-time availability of products in the warehouses. It is an example of enhanced visibility that can help the customers know about the availability of services in their geographical location.

Enhanced visibility implies a better user experience and also better marketing. When customers can know about the availability of your services easily, the conversion rate will also be high. CIOs aim at offering greater visibility to customers when they interact with enterprise applications or software(s). Poor visibility will not only hamper the user experience but will also drive away potential customers.

Challenges with poor visibility

Poor visibility leads to various issues that hamper the user experience. The challenges with poor visibility are as follows:

  • A wide range of applications and systems are being used by a firm. With poor visibility, your employees may not be able to complete the business processes effectively. Maybe your particular business process is lacking due to a bad user experience. You may not be able to visualize the shortcoming of your user experience due to poor visibility.
  • When you have poor visibility into user experience, you cannot determine the source of any problem. Your IT teams may blame each other as there is no dedicated communication pipeline.
  • As users do not get a better user experience, they might deviate to services offered by your competitors.

Possible reasons for poor visibility into user experience

There can be many possible reasons for poor visibility into the user experience that are as follows:

  • Your organization does not have a single view of performance metrics for different IT systems. Your administrators have to view the performance metrics of each IT system separately. It is not only time-taking but also lacks accuracy.
  • The existing business metrics for digital experience monitoring are not up to the standards. You need to choose the correct business metrics for gaining visibility into the user experience.
  • Your employees are not able to realize the cost impacts of poor user experience on your business. You may not even be aware of the problems arising due to poor visibility into the user experience.
  • Your employees may not have access to real-time performance metrics. You may not know about bad user experience until someone has reported it.

Pros of better visibility into user experience

The benefits of greater visibility into user experience are as follows:

  • You not only monitor the performance of digital interfaces for your customers but also for your employees.
  • With better visibility, you can decrease MTTD (Mean Time to Detect) and MTTR (Mean Time to Resolve) drastically.
  • You can solve issues with the digital experience immediately if your engineers have better visibility.
  • It is easy to track the root cause of an IT issue with enhanced visibility. You can significantly increase the uptime of your digital interfaces.
  • With better visibility, a CIO can understand the issues faced by customers/employees and can provide a personalized digital experience to them.

What’s the solution?

Many businesses are choosing AI-based platforms for better monitoring of IT infrastructure. AIOps platforms help in gaining more visibility into the user experience. With AIOps, you can automate the DEM process and can monitor user experience in real-time.

In a nutshell

The global AIOps market size will be more than USD 20 billion by 2026. You can use an AIOps platform for better visibility into the user experience. A CIO can automate steps for digital experience monitoring and can save time and effort. Enhance visibility into the user experience for better results!

Transform your Azure Ecosystem with AIOps to Increase Operational Efficiency

The cloud is now a primary place for SMEs and other large enterprises, and Microsoft’s Azure is considered one of the preferred IaaS and PaaS services for most business organizations.

As Artificial Intelligence and Machine Learning are changing the digital way of life, AIOps is set to uplift cloud services and make operations easy for the IT industry. It provides users with a broader range of benefits, including better customer experience, service quality assurance, and productivity boost.

Why Does Your Organization Need AIOps With Microsoft Azure Ecosystem

As cloud usage is in high demand, businesses are facing problems in managing their cloud infrastructure. AIOps for Azure provides better efficiency with the help of AI-driven software, ensuring smoother operations.

By executing AI operations and ML on Microsoft Azure, organizations can be benefited in many ways. Some of these are:

Efficient and Cost-Effective Infrastructure

Microsoft Azure helps lower the overall cost of a business when enabled with AIOPs and MLOps. AI and ML help make Azure cloud a better choice for Machine Learning Operations and Artificial Intelligence Operations.

Edge Computing

Edge processing aims to bring data resources closer to the users, thus improving the overall performance of the cloud infrastructure. It also helps reduce cost and increase processing capacity simultaneously.

Pre-Trained Machine Learning Models

The Microsoft Azure Platform offers pre-trained models. These can be used for a custom model for tailor-made processing of the company’s workloads. Many ML programs can be used as models through MicrosoftML for Python and MicrosoftML for R for various functions.

Manage Your Azure Infrastructure Easily With AIOps

Microsoft Azure is a reliable cloud service that manages data efficiently. As the cloud is always increasing and becomes complex as each day passes, it needs more developers and engineers to make it stable. It can become quite easy to remain at par with the constantly evolving cloud if there were a solution to make data-based decisions automatically.

Not only will this save a lot of time for the resources of your organization, but also make the process more efficient. AIOps and machine learning help streamline the process and assist engineers in taking actions based on the insights from the existing data.

AIOps is based on self-monitoring and requires no human intervention. Automation of services ensures improved service quality, reliability, availability, and performance.

Azure cloud professionals are no longer required to investigate the repeated process and manually operate the infrastructure. Instead, they use AI and ML engineering. AI operations can work independently, and human resources can utilize their time to focus on solving bigger problems and building new functions.

Design Your Own Growth Path by Systemizing Your Operations With AIOps

The AIOps framework can contribute in several ways. The major elements are explained below.

  • Extensive and Diversified IT Data: AIOps is predicted to bring together data from IT operations management and IT service management. Bringing data from different sources helps accelerate root cause identification of a problem and enables automation simultaneously.
  • Big Data Platform: The center of an AIOps platform is big data. As data is collected from different sources, it is required to be compiled together to support next-level analytics. AIOps aggregates big data and makes it accessible to be used in real-time.
  • Machine Learning: Analysing big data is not possible by humans alone. ML automates and analyzes new and diversified data with a speed that is unachievable without the AIOps framework.
  • Observation: It is the emerging of the traditional ITO domain and other non-ITOM data to enable new models and correlations. The combination of AIOps with real-time processing makes root cause identification easier.
  • Engagement: The traditional domain offers bi-directional communication to support data analysis and, thus, auto-creates documentation for audit while maintaining compliance. AIOps help in cognitive classification with routing and intelligence along with user touchpoints.
  • Act: This is the final stop for the AIOps strategy. It provides the codification of human knowledge into automation. It helps automate analysis, workflow, and documentation for further actions.

What Does the Future Have in Store for IT Operations?

Artificial Intelligence for IT operations is bringing a continuous change in the cloud business. In no time, adopting the AIOps way will become a necessity.

  • Accelerate Digital Transformation: Sooner than later, businesses will be able to offer data-driven experiences with the help of AIOps. It won’t be a hassle to migrate systems after systems, as most of the monotonous work will be handled by automated systems. This way, businesses can easily transform digitally to remain relevant
  • Solutions to Various Challenges: Often, when humans spend time performing basic calculations, a lot of time and energy is wasted. Moreover, there is always a chance of human error. Empowering developers with actionable insights, AIOps will make solving problems hassle-free, replacing many traditional monitoring tools
  • Finding Issues Automatically: A faster and more efficient way to improve customer satisfaction involves ensuring that there are no problems with your service or product. However, this can be challenging. With AIOps solutions, identifying issues and mitigating them will be a cakewalk. It will play an essential role in troubleshooting workloads and understanding and predicting customer needs in the current competitive environment, eliminating the need for having a dedicated team of resources to solve simple issues.

How Does AIOps Transform a Business?

1. Digitization of Routine Practices

The AIOps architecture helps digitize routine practices, like user requests, while processing and fulfilling them automatically. It can even evaluate whether an alert requires action and if all the supporting data is under normal parameters.

2. Recognizing Serious Issues Faster and More Accurately

There are chances of human error while looking out for threats. This may lead to an unusual download being ignored. AIOps tools tackle can solve this problem easily. It can run an antimalware function through the system, automatically and when required.

3. AIOps Streamline the Interactions Between Data Center Groups and Various Teams

AIOps shares all the relevant data with each IT group and provides the operations team with what they require. Manually meeting and sending data is no more required, as AIOps monitors data for each team to streamline the interactions between all groups.


With the help of Microsoft Azure, the value of companies associated with this ecosystem is scaling in an upward direction. To conclude, it can be rightly said that AIOps is the infusion of AI into cloud technology. When properly implemented, AIOps can help reduce time and attention on the IT staff of an organization.

AIOps open-source tools allow Azure cloud professionals to observe multiple systems and resources. With better ML capabilities, it can enable software to find the root cause of a problem and accelerate troubleshooting by providing the right remedies for all unusual issues of an IT organization running on Microsoft Azure.

Empowering VMware Landscapes with AIOps

VMware has been at the forefront of everything good in the modern IT infrastructure landscape for a very long time. After it came up with solutions like VMware Server and Workstation around the early 2000s, its reputation got tremendously enhanced amongst businesses looking to upgrade IT infrastructure. VMware has been able to expand its offering since then by moving to public and private cloud. It has also brought sophisticated automation and management tools to simplify IT processes within organizations.

The technology world is not static, it is consistently changing to provide better IT solutions that are in line with the growing and diverse demands of organizations across the world. The newest wave doing the rounds revolves around IT operations and providing support to business services that are dependent on those IT environments. AIOps platforms find their origin, primarily from the world that VMware has created – a world that is built on IT infrastructure that is capable of modifying itself according to needs and is defined by software. This world created by VMware consists of components that are changing and moving at a rapid pace. In order to keep up with these changes, newer approaches to operating environments are required. AIOps solutions are emerging as the ideal way to run IT operations with no reliance on static service models or fragile systems. AIOps framework promises optimal utilization of skills and effort targeted at delivering maximum value.

In order to make the most of AIOps tools, it is important that they be used in ways that can complement the existing VMware infrastructure strategy. Here are a few of those:

Software-defined is the way to go

Even though SDx is not properly distributed, it is still here and making its mark. However, the uneven distribution of SDx is a problem. There is still a need to manage physical network infrastructure along with some aspects of VMware SDN. In order to ensure that you get the most out of VMware NFV/SDN, it is important to conduct a thorough overview combining all these aspects. By investing in an AIOps solution, you will have a unified view of the different infrastructure types. This will help you in not only identifying problems faster but also aligning IT operation resources to deal with them so that they don’t interfere with the service that you provide to your users, which is the ultimate objective of choosing to invest in any IT solution.

Integrated service-related view across the infrastructure

Not too many IT organizations out there can afford to use only one technology across the board. Every organization has to deal with many things that they have done prior to switching to AIOps. IT-related decisions made in the past could have a strong bearing on how easy or difficult the transition is. There is not just the management of virtual network and compute amongst others, organizations have their work cut out with the management of the physical aspects of these things as well. If that’s not enough, there is a public cloud and applications to manage as well.

Having an overview of the performance and availability of services that are dependent on all these different types of infrastructure is very important. Having said that, this unified view should be independent of time-consuming manual work associated with entering service definitions at every point of change. Also, whenever it is updated, it should do so with respect to the speed of infrastructure. Whether or not your IT infrastructure can support software-defined frameworks depends a lot on its minimum or no reliance on static models.  AIOps can get isolated data sources into a unified overview of services allowing IT operations teams to make the most of their time and focus only on the important things.

Automation is the key

You have to detect issues early if you want to reduce incident duration – that’s a fact. But there is no point in detecting issues early if you are not able to resolve them faster. AIOps tools connect with third-party automation tools as well as those that come with VMware to provide operators a variety of authorized actions to diagnose and resolve issues. So there are no different automation tools and actions for different people, which enables everyone to make the most of only the best tools. What this leads to is helping the IT operations teams to deliver desired outcomes, such as faster service restoration.

No-risk virtual desktops

There is no denying the benefits of having virtual desktops. However, there are disadvantages of taking the virtual route as well. With virtual desktops, you can have a chain of failure points, out of which any can have a huge impact on the service delivered to end-users. The risk comes from the different VDI chain links that are owned by different teams. This could prove harmful and cause outages, especially if support teams don’t go beyond their area of specialization and don’t communicate with other support teams either. The outages will be there for a longer period of time in these cases. AIOps can detect developing issues early and provide a background of the entire problem throughout the VDI chain. This can help different support teams to collaborate with each other and provide a resolution faster, consequently saving end-users from any disruption.

Collaboration across service teams

VMware admins have little problem in getting a clear overview of the infrastructure that they are working on. However, it is a struggle when it comes to visibility and collaboration across different teams. The problem with this lack of collaboration is the non-resolution of issues. When issues are raised, they only move from one team to another while their status remains unresolved. AIOps can improve the issue resolution rate and bring down issue resolution time considerably. It does this by associating events with their respective data source, aligning the issue to the team that holds expertise in troubleshooting that particular type of issue. AIOps also facilitates collaboration between different teams to fast-track issue resolution.