“Cloud Native DevOps with Kubernetes: Building, Deploying, and Scaling Modern Applications in the Cloud” by John Arundel and Justin Domingus

This book covers the best practices for developing and deploying cloud-native applications using Kubernetes and DevOps principles.

Reason to read: Learn how to deploy, scale, and manage containerized applications in the cloud using Kubernetes.

Read: 5 Best Kubernetes Books for Beginners

“Site Reliability Engineering: How Google Runs Production Systems” by Betsy Beyer, Chris Jones, Jennifer Petoff, and Niall Richard Murphy

This book provides an insight into how Google manages its large-scale production systems and the techniques and practices they use to achieve high reliability.

Reason to read: Learn the best practices for managing large-scale systems and improving reliability.

“The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win” by Gene Kim, Kevin Behr, and George Spafford

This book is a must-read for anyone interested in understanding the principles of DevOps and how they can be applied in real-world scenarios.

Reason to read: Learn how DevOps principles can be used to improve IT operations and business outcomes.

“Infrastructure as Code: Managing Servers in the Cloud” by Kief Morris

This book covers the concept of Infrastructure as Code (IaC) and how it can be used to manage infrastructure in the cloud.

Reason to read: Learn how to manage infrastructure as code and automate the provisioning and deployment of cloud resources.

“The Docker Book: Containerization is the New Virtualization” by James Turnbull

This book provides a comprehensive guide to Docker and containerization and how they can be used to improve application deployment and management.

Reason to read: Learn how containerization can simplify application deployment and management and improve application portability.

“Effective DevOps: Building a Culture of Collaboration, Affinity, and Tooling at Scale” by Jennifer Davis and Katherine Daniels

This book covers the practices and techniques that organizations can use to build an effective DevOps culture.

Reason to read: Learn how to build a DevOps culture and improve collaboration, communication, and tooling.

“Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation” by Jez Humble and David Farley

This book provides an overview of the continuous delivery approach and how it can be used to achieve faster and more reliable software releases.

Reason to read: Learn how to improve software delivery and reliability through automation and continuous integration and deployment.

“Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations” by Nicole Forsgren, Jez Humble, and Gene Kim

This book provides insights into the practices and techniques used by high-performing organizations to achieve faster software delivery and better business outcomes.

Reason to read: Learn the best practices and techniques used by high-performing organizations to improve software delivery and business outcomes.

“The Art of Monitoring” by James Turnbull

This book covers the principles and best practices of monitoring applications and infrastructure in the cloud and how it can be used to improve reliability and performance.

Reason to read: Learn how to monitor applications and infrastructure in the cloud to improve reliability and performance.

“DevOps for the Modern Enterprise: Winning Practices to Transform Legacy IT Organizations” by Mirco Hering

This book provides practical advice and strategies for transforming legacy IT organizations to adopt DevOps principles and practices.

Reason to read: Learn how to transform legacy IT organizations and adopt DevOps practices to improve software delivery and business outcomes.

***

By reading these 10 must-read cloud technology books recommended by DevOps experts, you can gain a fresh perspective on essential and emerging technologies, learn the latest best practices, and stay ahead of the curve in the fast-paced world of IT. So, what are you waiting for? Start reading and enhance your cloud technology skills today. Don’t forget to subscribe to our newsletter to stay up-to-date with the latest tech trends and insights. Happy reading!

Сообщение 10 Must-Read Cloud Technology Books in 2023: A DevOps Perspective появились сначала на Acure AIOps Platform.

An event is recorded by a log, a time-stamped record produced by an application, operating system, server, or network apparatus. They may contain information about inputs from users, system functions, and hardware conditions.

A large portion of the information that provides a system’s observability can be found in log files, such as records of every event that occurs throughout the network devices, operating system, or software elements. Even user and application system communication is captured in logs.

The process of creating and keeping records for later examination is known as logging.

What Is Log Monitoring?

Designers and administrators regularly monitor logs as they are logged using the log monitoring technique. Using log monitoring software, units can gather data and raise alarms if system execution and fitness are affected. 

DevOps teams (or development and operations teams) frequently use a log monitoring solution to ingest applications, services, and overall system logs to identify problems through the software delivery lifecycle (SDLC). A log monitoring system ascertains circumstances instantly to assist teams in troubleshooting problems before they hamper development or impact customers, whether a situation occurs during development, testing, deployment, or production.

Teams must, however, be capable of evaluating logs to identify root causes.

How Does Log Monitoring Facilitate Log Analytics

The notions of log monitoring and analytics are interrelated yet distinct from one another. Concurrently, they guarantee that apps and critical services are in good shape and running at their best.

While log analytics analyzes logs in context to comprehend their meaning, monitoring only tracks records. This involves resolving problems with software, services, apps, and any underlying infrastructure. Container environments, multi-cloud platforms, and data repositories are examples of this infrastructure.

Analytics and log monitoring work in tandem to guarantee that applications are running as efficiently as possible and identify areas where systems can be improved.

It is possible to find solutions to improve infrastructure environments’ predictability, efficiency, and resilience using log analytics. Together, they offer organizations a look into problems and advice on how to manage systems most effectively.

Reap the Benefits of Log Monitoring

In cloud-native systems, log monitoring aids teams in maintaining situational awareness. Numerous advantages come from this practice, which includes the following:

• Quicker response to and settlement of incidents: Teams can respond more quickly and find problems before they impact end users, thanks to log monitoring.
• More automation in IT: Teams can better automate more procedures and reply more accurately when they have clear visibility into crucial system KPIs.
• Enhanced system efficiency: Through log monitoring, teams can optimize system performance by identifying possible blockages and ineffective setups.
• Heightened cooperation: Cloud operators and architects gain from a singular log monitoring solution to build more dependable multi-cloud setups.

Log Monitoring Use Cases

Log monitoring can be applied to any connected device that creates an activity log. The spectrum of applicability for artificial intelligence-based solutions has expanded beyond break-fix situations to handle various technological and commercial issues.

They consist of the following:

• Modern cloud infrastructure is automatically monitored through infrastructure monitoring:
  • Virtual machines and hosts;Platform-as-a-Service providers like Azure, AWS, and GCP;Platforms for containers like OpenShift, Kubernetes, and Cloud Foundry;Devices for networks, process detection, use of resources, and network performance;Integration of event data and from third parties; and
  • Open-source applications.

• Microservices workloads operating within containers are discovered through application performance monitoring, identifying and locating problems before they impact actual users.

• Every application is made available, responsive, quick, and effective across all channels thanks to digital experience monitoring, which includes real-user monitoring, synthetic monitoring, and mobile app monitoring.

• Vulnerabilities are automatically found in cloud and Kubernetes environments by application security.

• IT and business collaboration is facilitated by business analytics, which offers real-time visibility into the company’s key performance metrics.

• By integrating observability, automation, and intelligence into DevOps pipelines, cloud automation and orchestration for DevOps and site reliability engineering teams accelerate the development of higher-quality software.

Overcoming the Challenges of Log Monitoring 

In contemporary workplaces, it can rapidly become daunting to translate the deluge of incoming data and logs into compelling use cases. Although log monitoring remains crucial to IT procedures, doing it successfully in cloud-native settings presents specific difficulties.

The need for end-to-end observability, which allows users to gauge a system’s current condition on the basis of the data it produces, poses a significant barrier for companies. In addition, observability becomes more challenging as settings use hundreds of associated microservices spread across many clouds.

Organizations need more context as well. For example, logs are frequently aggregated nonsensically and assembled in data silos without any links. Without noteworthy connections, you often have to sift through billions of traces to determine whether two alerts are connected or the way in which they affect consumers.

Too frequently, logging technologies have engineers pouring over logs and browsing through data to determine fundamental causes using straightforward correlations. As a result, it is challenging to estimate consumer impact due to a deficiency of causation. It is also difficult to tell which optimization efforts are leading to performance gains.

Enterprises are frequently plagued by log monitoring’s elevated cost and blind spots. Many businesses remove sizable chunks of their logs to avoid the hefty data-ingest expenses associated with conventional log monitoring solutions. As a result, there is little sampling. Although rehydration and cold storage can reduce high costs, they are ineffective and lead to blind spots.

Traditional aggregation and correlation techniques must be improved, given the intricacy of contemporary multi-cloud settings. Teams must find bugs, abnormalities, and vulnerabilities as soon as possible. Organizations too frequently use various unrelated methods to handle multiple issues at different stages, which increases complexness.

Read our blog to learn more about log monitoring tools that are available for free.

Log Monitoring with Acure

Raw data coming into Acure from connected data streams are available in Events and Logs tab. Here you can filter it by period and pick the necessary interval which is very convenient for recurring events analytics and root cause analysis. Data are represented in two forms – table or JSON.

To collect raw logs, we recommend integrating with a logging and metric processor, such as Fluent Bit, which can either send raw logs or parse them. This type of integration is also configured with the AnyStream Default template.

Find more about data collection in Acure in our video manual.

Сreate a Userspace to start collecting and analyzing logs now!

Сообщение What Is Log Monitoring? Why Does It Matter in a Hyperscale World? появились сначала на Acure AIOps Platform.

IT service management involves creating, designing, managing, delivering, supporting, and improving all the IT services a firm provides to its end users. IT service management (ITSM) helps a business run and grow efficiently. In other words, ITSM aligns IT services with the organization’s or business’s objectives. 

For example, the laptops, software installed, and other tech devices in an office are all maintained and provided by the IT team or IT service management. 

It might seem like IT service management looks after a company’s technology needs and resolves day-to-day issues, but it goes way beyond it. IT service management holds the company together, which makes workflow effortless and efficient. 

ITSM effectively removes all the problems that come its way and coordinates all the tasks efficiently while ensuring they provide value to the customer. It helps and benefits the IT team, and service management policies help an organization to grow, aims to increase productivity, and through a structured approach, aligns business goals and IT on the same path. ITSM helps in getting the best out of the resources and budgets and reduces the risk factors while improving customer experience. 

In simpler words, ITSM helps support IT services throughout the lifecycle thoroughly, increases the employees’ productivity, and enhances the firm’s efficiency.

Breakdown of IT Service Management

ITSM can be broken down into five categories or areas to understand the role of IT service management in a firm.

1. Organization: ITSM helps a firm or a company function and performs its objectives to achieve the organization’s goals. It allows a company to perform its core functions without any hurdles.
2. Services: ITSM provides hardware, software, apps, infrastructure, and other IT-related assistance that the company needs. 
3. Problem-Solving: IT service management ensures no hindrance in the quality of work; hence ITSM solves all IT-related issues immediately, efficiently, and effectively. 
4. Cost: ITSM aims to get the most out of the IT budget without causing any additional burden to the firm’s budget. 
5. End-User: End-users are the ones who use IT services, such as customers and employees. 

These are the five essential areas of concern related to IT service management.

What Is ITIL?

Many IT professionals use ITIL and ITSM, sometimes interchanging the terms. Though they are used interchangeably, both terms have a crucial difference. 

ITIL is formerly known as the “Information Technology Infrastructure Library.” It was created by the Central Computer and Telecommunications Agency (CCTA) under the backing of the UK government. ITIL is a registered trademark of the British government’s OGC (Office of Government Commerce). 

ITIL was developed to define the organization’s structure and look into the skill requirements of the IT organization. In addition, it was created to introduce standard operational management practices and procedures for an organization to manage an IT operation. 

In simpler words, ITIL is a framework of all the best recommendations and practices for managing a firm’s IT services and operations for the firm’s improvement. It provides a set of guidelines for efficient and effective IT service management.

Difference between ITSM and ITIL

As mentioned above, there is a critical difference between ITSM and ITIL. ITSM is a model or a paradigm, whereas ITIL is a framework of best practices. 

IT Service Management

ITSM is a model for understanding the relationship between an IT organization and the firm it supports in a specific way. ITSM paradigm helps IT firms focus on managing all their services and delivering services to the business the firm supports.  

IT Service Management model can be summarized as follows:

• The function or goal of an IT organization is to provide services to the firm. 
• All the services provided must align and help accomplish all the goals and needs of the company.
• The services provided must be managed thoroughly and throughout their entire lifecycle.
• The IT sector or department is its organization, whereas the business is its customer. 

ITIL

While ITSM defines the relationship between the business and IT organization, ITIL is more than that. ITIL is a framework that helps manage IT services throughout the service lifecycle effectively and efficiently. 

ITIL is a collection of values, strategies, and processes that will assist in executing ITSM.  There are other ITSM frameworks, but ITIL is popular and most used.

The Benefits of IT Service Management

There are various benefits of implementing IT service management in the company. The company size does not matter while implementing and investing in an IT service management process.  

The benefits of investing in or implementing IT service management processes can be divided into two categories: Benefits for Business and Benefits for IT.

Benefits for Business

• It reduces the number of incidents in and around the business. It reduces the impact of the incident as well.
• ITSM provides the best services at a lesser cost. 
• The ITSM will have an advanced understanding of the goals and needs of the company. It will help the company reach its goals effectively.
• IT service management will handle and deliver the expectations of the company in a better manner. 
• The employees of a firm or an organization will be able to finish more work with good IT performance and availability. 
• The employees will be able to understand how to use the services and have more knowledge regarding all the services available. 
• If there is a change in the market, the IT service management can and will react to the change and innovation quickly. 

Benefits for IT 

• There will be an increase in IT productivity and efficiency. This is because there will be designated roles and responsibilities for everyone. 
• There will be a prevention of IT-related issues before the issue occurs.
• IT’s performance can be improved when ITSM is implemented.
• If there are repeated problems and challenges, it will be easier to identify and counter them. 
• The process of identifying and solving problems will take place in a shorter duration. 
• It is a scalable and repeatable process.

IT Service Management Processes

Here are a few core ITSM processes:

Service Request Management 

Service request management is the procedure of handling, managing, and following up on customer service requests. These requests include hardware updates, password resets, access to applications, updating personal information or data, or updating software. 

Service request management helps in looking after important requests and ensuring that the requests are solved. The request management workstream involves solving recurring requests. 

Incident Management

Incident management means tracking and responding to unplanned situations. Incident management also looks after service requests for new hardware, software, and other services. 

In addition, ITSM looks into solving the incident as soon as possible to restore the service to the customer. Incident management prioritizes incidents and requests according to their impact on the business. 

Problem Management

Problem management is the process where the incidents are identified and managed. The method also involves checking the cause of the incident. During this process, The root cause of the incident is understood and analyzed. 

Then, the underlying cause of the incident is looked into and eradicated with best practices. Problem management eliminates recurring incidents as well while removing defects.

Service-level Management

Service-level management is where service-level commitments from vendors and customers are tracked. This helps in understanding the weaknesses and taking action to correct them. 

Change Management

Change management is the process where all the changes in the IT infrastructure are handled efficiently. The changes can be introducing new services, resolving problems in the code, and taking care of existing services. 

Quick and effective change management helps decrease risk and creates space for transparency to avoid workflow stoppage. 

Workflow and Talent Management

Workflow and talent management means the process where the people with appropriate skills and knowledge are placed in the roles that suit them best. This process helps achieve business goals and objectives as employees with the right talent and skills are placed in the best position for them.

Continual Improvement Management

Continual improvement management implements tasks to track performance and measure success. This process helps in the improvement of the company and all its services. 

Configuration Management

Configuration management is tracking all configured items in the IT system. The important configured information for software, hardware, documentation, and personnel are identified, verified, and maintained during this process. 

This process gives IT teams a hold of all the IT-related information. In addition, it helps establish an evident bond between services and IT infrastructure components.

What Is an IT Service Management Tool?

An ITSM tool is software that is used to deliver IT-related services. The software can be standalone or a package of applications consisting of various apps to perform functions related to IT service management. 

The tool can perform various actions and functions, such as problem management, change management, and others. There is a popular term named service desk that is related to ITSM. A service desk is an ITSM tool. The tool functions as a single point of contact between the service provider and the customers. The customers can be internal or external. 

The service desk constantly helps customers when the services are down and monitors all the services. The service desk also handles software licensing, service requests, incident management, and many other activities. 

Points to Consider While Selecting an ITSM Tool

Many ITSM tools are available in the market. These tools help align the business goals and objectives with the IT team. It gives a strategic approach to the firm and helps in the growth of the business. 

While selecting an ITSM tool or software, there are a few pointers you must keep in mind. These pointers are essential as ITSM tools and software play a huge role in the firm’s functioning.

• Accessible to Use: The tools must be user-friendly. ITSM is created and designed to provide IT services throughout the organization. If it is hard to use, the employees can have trouble understanding how to use the tool or software efficiently. The tool should have a portal to help users find information and solutions. The tool should also help in tracking progress on issues. 
• Easy to Setup: Setting up the tool should be simple. If it has a complicated setup process, this can lead to a barrier while trying to adapt to the tool. The tool must come with instructions and support agents. 
• Flexibility and Adaptability: Needs keep changing in the business, and many changes also occur. The ITSM tool or software must be flexible and adaptable to all the changes. The tools must be able to grow with the business and accommodate space for new growth. It should provide value to an evolving IT team. 
• Collaborations: The tool or software must be able to handle and facilitate teamwork. This means that the tool must be able to provide a space for inter-departmental coordination. For example, the ITSM tool should provide a platform for developers and other teams across the organization to work together efficiently. 

Wrapping Up

IT service management changes the relationship between the business and IT. It enables employees to increase their productivity, reduces the number of IT incidents, eradicates all recurring problems increases the speed and effectiveness of IT services.

ITSM effectively removes all the problems that come its way and coordinates all the tasks efficiently while ensuring they provide value to the customer. It helps and benefits the IT team, and service management policies help an organization to grow, aims to increase productivity, and through a structured approach, aligns business goals and IT on the same path. ITSM helps in getting the best out of the resources and budgets and reduces the risk factors while improving customer experience. 

In simpler words, ITSM helps support IT services throughout the lifecycle thoroughly, increases the employees’ productivity, and enhances the firm’s efficiency.

Implementing IT service management in a company will be beneficial as it will be a long-term investment. The critical factor is choosing the right tool or software to align with the firm’s needs and goals. Furthermore, in the future, ITSM will integrate with AI technologies. This means that investing in ITSM will be even more beneficial. 

Сообщение A Complete Guide to IT Service Management  появились сначала на Acure AIOps Platform.

Big data refers to the enormous, complicated volumes of data that might be either structured or unstructured. However, what organizations do with the data impacts more than just the nature or volume of data. 

Big data, notably from new data sources, is simply a term for bigger, more intricate data collections. These data compilations are so large that already existing data processing software face difficulties handling it. However, these great data compilations can be taken advantage of to solve issues that were nearly impossible to solve earlier. 

Big data analysis will help generate information that will eventually help with the decision-making stages and provide support while making critical business implementations.

The emergence of big data depended on the creation of open-source frameworks, making massive data more manageable and less expensive to keep.

The Popular V’s of Big Data

Industry analyst Doug Laney introduced the three V’s in the early 2000s that defined big data in easy-to-understand statements. Let’s look at the V’s that together give meaning to big data. 

Initially, only volume, velocity, and variety were the V’s that were introduced but later on, veracity and value were also included in the list.

1. Volume 

The initial of the important V’s of big data, volume, refers to the quantity of data that is available to us. Volume, or the original size and quantity of information obtained, can be thought of as creating and giving basis to the foundation of big data. Big data can be used to describe a sufficiently massive set of data. 

2. Velocity 

Velocity refers to the high speed at which big data is accumulated. The speed at which data is created and managed to satisfy demands influences the data’s potential where a significant and constant flow of data is present. 

Data comes from various sources, including social media platforms, databases, computers, smartphones, etc. Dealing with problems like “velocity” might be easier compared to other difficult sampling problems.

3. Variety 

The range and diversity of data kinds are referred to as variety. An organization may collect data from various sources, the value of which may differ. Data might originate both inside and outside of an organization. Unstructured, semi-structured, or structured data can be collected. The standardization and dissemination of all the data being gathered pose a problem in terms of variety.

4. Veracity 

Veracity relates to sampling errors and uncertainty that is, readily available data can occasionally become disorganized, and both quality and precision are challenging to manage. 

The gathered information can be incomplete, erroneous, or unable to offer any useful, insightful information. Veracity, in general, refers to the degree of confidence in the data that has been gathered. Because there are so many different data dimensions arising from several dissimilar data types and sources, big data is also unpredictable.  

5. Value 

This is a reference to the benefits using big data can offer, and it has a direct bearing on what businesses can do with the information they gather. Data by itself is useless and unimportant; information must be extracted from it by transforming it into something worthwhile. Therefore, value can be identified as the most significant of the five virtues.

It is necessary to be able to extract value from big data because the importance of big data greatly depends on the conclusions that can be obtained from them.

Interesting Trends Emerging in the Big Data Industry

Data Quality Testing

Data quality checking protects your company from inaccurate data. It’s time to think about a remedy if the quality of the company’s information assets is affecting sales.

For businesses across all industries, accurate data is crucial for statistics and data-driven solutions. Without this information, businesses struggle to remain effective, profitable, and competitive in their market.

Preserving data quality is essential to creating a successful company, especially given how many aspects of daily operations it now supports. Better company decisions are made as a result of high-quality data, which also benefits customers.

Writing test strategies for certain products and initiatives that concentrate on the project’s objectives will be necessary. Before creating and running tests, data sources need to be reviewed after such criteria have been determined.

To provide IT and data owners with an audit record of all access instances, live monitoring, mapping, and alerting of exactly who is receiving and accessing which type of data when and from where helps keep them aware as to how sensitive data is being utilized. The procedure guards against data breaches and misuse.

Anomaly Detection

Data mining’s anomaly detection process, also known as outlier analysis, seeks out data points, occasions, and/or observations that differ from a dataset’s typical pattern of activity. 

Unusual data can point to serious occurrences, like a technological malfunction, or promising opportunities, like a shift in consumer behavior. Automated anomaly detection is increasingly being done using machine learning.

You may use your resources more wisely because monitoring systems will keep hold of your infrastructure, including many other things. You will become more productive as a result, which is undoubtedly essential in your decision to utilize a monitoring system. 

With the knowledge that you will be notified as soon as an issue occurs, your employees will have more time to focus on other activities.

However, with data monitoring, the data is automatically verified to make sure it is accurate at every stage. If a discrepancy is discovered, the data is flagged so that it may be reviewed and any necessary modifications can be made. Your analytics and reporting become more reliable as a result.

The analytics reports may become biased if any data is altered. These reports are designed to assess the company’s performance and identify areas for improvement. But you can’t choose the best course of action for your company and customers if you don’t have the appropriate information.

Shift from Data Monitoring to Data Observability

Teams from DevOps and ITOps must advance from monitoring to observability. Software and systems that can be seen and used to provide answers to inquiries about their behavior are said to be observable.

By releasing data from compartmentalized log analytics programs, observable systems encourage research as opposed to monitoring, which depends on fixed views of static resources. 

You can engage with customers better the more precise the data is. Monitoring data along with observability enhances connections in a variety of ways. Furthermore, accurate information reveals any potential areas for improvement. You can concentrate on customer retention rather than gaining new customers if your analytics suggest that you frequently acquire new customers but rarely see those same customers return.

Correct data monitoring and observability reveals the demographics of your clients. This data can be utilized to target your consumer base more accurately, saving you money on marketing to uninterested parties.

You can read more about the differences between Data Monitoring and Data Observability in our blog.

Low-Code and No-Code

More and more companies have recently been trying to make their solutions more flexible, allowing data engineers to independently adjust systems for themselves and customize functionality without having deep knowledge in programming. Low-code and no-code come to the rescue in this case, when you can create entire scripts without writing long lines of code.

We talked about this approach in more detail in the article.

This is a very promising direction in light of the data decentralization trends and skill shortage.

New Trends – New Stars

Obviously, new trends also impact big data solutions and bring new players to the market that match these trends. In the following research, new “stars” are collected, which currently show promising growth in data monitoring, data observability and data quality testing

Download research on new data observability and monitoring solutions:

A Cure for Big Data

Acure.io is one of the fresh and promising solutions for working with big data. It is not just another monitoring system, it is an AIOps platform that integrates all other log and alert monitoring systems, takes data from there, puts it on a single dynamic link map, and automates the processes of monitoring it.

The dependency map is built automatically based on data from existing monitoring systems and other tools. This is vital for dynamic environments, such as modern cloud ecosystems and microservices on Kubernetes. It not only improves data observability but also provides rapid identification of the root cause of an incident and the impact of various technical resources on business services.

In order to avoid information noise, a solution called Signals is used. It aggregates, normalizes and enriches events collected from various monitoring tools and automatically correlates alerts into actionable insights.

As for automation, here Acure also follows trends and uses a Low-code scripting engine (including auto-building and auto-correlation). Running built-in scripted automation tools with low-code and external runbooks allows workflows to be automated for faster incident response.

Can’t wait to try all these features in action? Create Userspace in Acure.io!

Wrapping Up

The final analysis and the implemented choices can only be foolproof if the data has been handled well and can be trusted. Being dynamic has several advantages. Organizations that are data-driven perform better, have more predictable operations and are significantly profitable.  

Businesses must fully take advantage of the benefits provided by big data to remain at the top of the pop league. They must also go for a more data-driven path so that they can base their choices more on the facts provided by big data rather than just relying on intuition.

Businesses use big data analytics to reap benefits and understanding from large quantities of data. Big data is being used to fuel modern advanced analytics projects like AI and machine learning.

Сообщение The New Trends and New Stars in the Big Data появились сначала на Acure AIOps Platform.

A root cause is an element that contributes to nonconformance and ought to be permanently removed via process improvement. The root cause of the problem is the underlying issue that started the chain of events.  

The concept of root cause analysis (RCA) refers to various methods, instruments, and procedures used to identify the root causes of issues. Some root cause analysis (RCA) methodologies are more focused on determining the actual reasons for an issue. Other RCA methodologies are more generic problem-solving approaches.

What Does a Root Cause Analysis Do?

Root cause and impact analysis is the process of searching for the underlying causes of issues, identifying the best strategy to fix flaws and finding a solution that can be used to stop the recurrence of the problematic event. 

The strategy encourages all efforts to identify the actual reasons behind process flaws or obstructions and address them to make improvements over time.

A prevention strategy can be successfully developed using the RCA approach to determine a problem’s underlying causes and contributing variables. Root cause and impact analysis is useful for incident management, maintenance problems, productivity problems, risk analysis, barrier analysis, etc.

What Advantages Does Root Cause Analysis Offer?

The root cause analysis method aids in identifying and describing a problem’s root cause(s). RCA may provide a productive, organized approach to problem-solving by getting to the root of a problem and looking at all of its components. 

The problem-solving technique helps companies and processes by forcing them to dig deep into a problem and develop long-term solutions because of this preventive feature. 

Additionally, it develops a prevention strategy and pinpoints areas for organizational development. Of course, RCA has benefits and drawbacks. So let’s take a look at them.

Fundamental Ideas of Root Cause Analysis

Effective root cause analysis is guided by a few fundamental ideas, some of which should be obvious. These will improve the analysis’s quality and assist the analyst in gaining the confidence and support of patients, clients, and stakeholders.

• Instead of just treating the symptoms, concentrate on addressing the underlying causes.
• Don’t discount the significance of addressing symptoms if you only need temporary relief.
• Recognize that there may be – and frequently are – many basic causes.
• Instead of focusing on WHO was at fault, consider HOW and WHY something occurred.
• Be meticulous when locating specific cause-and-effect data to support your claims about the core cause.
• Give enough details to determine a course of action for correction.
• Consider how a root cause might be avoided (or repeated) in the future.

As the aforementioned guidelines demonstrate, it’s critical to adopt a thorough and holistic approach when analyzing complex problems and their root causes. It should work to provide context and facts that will lead to an action or a choice in addition to identifying the core cause. Always keep in mind that sound analysis is actionable.

Guidelines for Conducting a Successful Root Cause Analysis

Root cause analysis is crucial in continuous improvement and a more general problem-solving procedure. Root cause analysis is, therefore, one of the fundamental pillars of an organization’s continuous improvement efforts. 

It’s crucial to remember that root cause analysis alone will not result in quality improvement; it must be integrated into a bigger effort to solve problems. The following three guidelines will help you conduct a root cause analysis effectively.

1. Get a Team Together and Some Fresh Eyes 

Any additional eyes, whether it be a single partner or an entire team of coworkers, will speed up the process of finding solutions and prevent bias.

2. Make Plans for Upcoming Root Cause Analysis

Understanding the method is crucial as you conduct a root cause analysis. Make a note. Inquire about the analytical procedure in general. Find out if a particular strategy or method suits the demands and conditions of your particular organization. 

3. Keep in Mind to Do Success-related Root Cause Analysis as Well

Root cause analysis is a fantastic method for identifying the source of a problem. The root cause of success can also be determined via RCA, which is normally used to diagnose issues. 

Finding the reason why something is working out well is rarely a terrible idea if we can identify the cause of success, overachievement or an early deadline. 

This kind of study can aid in prioritizing and proactively protecting important aspects, and we might be able to apply the lessons learned from one sector of the company to another.

4. Procedures of a Root Cause Analysis 

It’s crucial to keep the following in mind while using root cause analysis methods and procedures: 

• While a single person can utilize various root cause analysis methods, the results are typically better when several individuals collaborate to identify the reasons for the issue.
• The analysis team that sets out to find the root cause(s) should have significant members who will eventually be responsible for eliminating them.

The following are some steps that a typical root cause analysis in an organization might take:

1. It is decided to put together a small team to investigate the root cause.
2. Team members are chosen from the organizational department or business process that is having problems. The following could be added to the group: 

• A line manager has the power to make decisions and implement solutions
• A problematic internal consumer from the process
• If the other team members have limited expertise with this type of job, a quality improvement expert should be brought in.

3. About two months pass throughout the analysis process. Equal weight is given during the analysis to identifying and comprehending the issue, coming up with potential reasons, dissecting causes and effects, and coming up with a solution. 
4. The team meets at least once weekly, perhaps twice or three times during the analysis period. Since the sessions are intended to be creative in nature, they are always kept brief, lasting no more than two hours.
5. A team member is responsible for ensuring that the analysis moves forward or that assignments are distributed among the team members.
6. Depending on what is involved in the implementation process, it may take anything from a day to several months until the change is complete once the solution has been established and the choice to adopt has been made.

Root Cause Analysis: How to Perform It

For conducting root cause analysis, there are numerous methodologies, approaches, and techniques available, such as:

1. Events and causative factor analysis: This methodology, which is frequently used for significant, single-event issues like a refinery explosion, employs evidence collected swiftly and meticulously to create a timeline for the events leading up to the catastrophe. The causative and contributory elements can be found once the timeframe has been defined. 

2. Change analysis: This method might be used when a system’s performance dramatically changes. It looks into adjustments made to people, tools, information, and other things that may have caused a change in performance.

3. Barrier analysis: This method focuses on the controls present in the process that is intended to either prevent or detect a problem and which may have been ineffective.

4. Risk tree analysis and management oversight: One part of this strategy is using a tree diagram to examine what happened and its potential causes. 

5. Kepner-Tregoe Decision-Making and Problem Solving: This paradigm offers four unique stages for problem-solving:

• Analyzing the situation 
• Analysis of the issue
• Solution evaluation
• Examination of potential issues

What Equipment Does Root Cause Analysis Use? 

The five whys approach, Pareto charts, scatter diagrams, fishbone diagrams, and failure mode and effects analyses are some of the most well-known and often used root cause analysis tools.

1. Pareto Charts 

The frequency and distribution of flaws and their cumulative effect are first shown on Pareto charts. The well-known 80/20 Pareto rule aids in examining potential fundamental causes of failures. As a result, it is highly effective at locating problems with the equipment or process obstructions. 

The Pareto chart ranks the identified flaws according to their seriousness and gives a more thorough description of the flaws that must be fixed first.

2. Five Whys

Second, one of the most effective problem-solving tools in the Lean toolbox is the 5 Whys analysis. It enables you to dissect an issue or an incident’s components in order to identify the underlying reasons. 

The method suggests asking as many “Why” questions as necessary to determine the true cause. The 5 Whys method was developed in the manufacturing industry and is currently used in many industries when problems with people, technology, or processes arise.

3. Scatter Diagrams

Scatter diagrams are another technique for root cause analysis. The scatter diagram is a statistical method for displaying the association between two variables in a two-dimensional figure. The scatter diagram is used to pinpoint potential variation reasons by showing cause and effect in it.

4. Fishbone Diagrams

Fishbone diagrams are another tool used in root cause analysis. The fishbone diagram, sometimes referred to as the Ishikawa technique, is a diagram that resembles a fishbone and shows the various elements that can contribute to a problem, failure, or occurrence. 

Where the fish’s head would be, the issue or incident would be displayed, and the fish’s backbone would serve as the cause. 

Along the fish bones are illustrations of additional important variables. By visualizing the process in a diagram, the fishbone diagram method aids in idea generation, identifies process bottlenecks, and identifies areas for improvement.

5. Failure Mode and Effects Analysis

The root cause analysis method used by FMEA is preventive in nature. The approach uses data on past performance to forecast system problems in the future. For the analysis to determine a system’s risk priority number (RPN), input from safety and quality control teams is required. 

The team must consider prospective disruptions, previous failure modes, and analysis of potential failure modes to arrive at this number. The FMEA method makes it easier to find a weak spot in a process or a system.

What Difficulties Does Root Cause Analysis Face?

The root cause analysis method extensively uses data to develop a methodical approach to problem-solving. Inadequate and ineffective analysis of a process barrier can result from the absence of critical information. 

On the other side, collecting data over a lengthy period of time might make it very difficult and time-consuming to pinpoint a harmful incident. 

To assist you in differentiating between common and unique causes of problems, gathering information and creating a timeline of occurrences is crucial. Finding that a condition has multiple primary causes rather than just one is not unusual. 

The root cause analysis approach can encounter difficulties when establishing a causal graph that displays several root causes.

How and in What Areas is RCA Used?

Root cause analysis may be used in a variety of settings and sectors thanks to its extensive toolkit, which gives businesses ways to solve problems and aid in decision-making. Healthcare, telecommunications, information technology, and manufacturing are a few industries that frequently use root cause analysis approaches.

Safety and Health 

When examining events to identify the underlying causes of issues that resulted in undesirable results, such as patient injury or drug side effects, root cause analysis is used in the healthcare industry. The analysis is used to increase patient safety and take corrective action to stop similar situations from happening in the future.

IT and Telecommunications  

Using root cause analysis methodologies in IT and telecommunications enables the identification of the underlying reasons for recently developed problematic services or resolving recurrent issues. 

In procedures like incident management and security management, analysis is frequently applied.

Industrial and Manufacturing Process Control

In manufacturing, RCA is used to pinpoint the major reasons for maintenance or technical failure. The industrial process control discipline uses root cause analysis techniques to control chemical production quality.

Analysis of Systems

Because of its ability to solve problems, RCA has been successfully used to change management and risk management fields. RCA is perfect for system analysis since it can also be used to analyze firms, identify their objectives, and develop processes to achieve them.

Root Cause Analysis in Acure

Root cause analysis in Acure is based on a topology tree that displays the IT infrastructure’s data from disparate sources. The topology includes configuration items and the relationships between them. Each configuration item contains information about the health and relationships with other elements of the system. The health of each item is calculated based on the health of the affected objects, as well as the monitoring events associated with it. The following are used as metrics:

1. the weight of the connection — used in assessing the “equivalent” effect;
2. a critical factor — the direct inheritance of health, suitable for critical nodes.

After any changes in the topology, the health of the system is instantly recalculated, coloring the entire tree appropriately.

If the health of the root configuration item turns red, you will see in detail which factors most negatively affect the object and go through the branches to eventually come to the element that affected the health of the entire system.

Try the root cause approach by yourself in Acure Userspace.

Сообщение A Complete Guide to Root Cause Analysis  появились сначала на Acure AIOps Platform.

CMDB is a database that serves as a data warehouse that stores details on your IT environment, including the hardware and software needed to provide IT services. Lists of assets (also known as configuration items) and the connections between them are among the information kept in a Configuration Management Database.   

Modern IT operations are centered around configuration management databases (CMDBs), which allow businesses to manage information about various IT components in one location.

The CMDB assists the organization in carrying out service management procedures like incident management, change management, and problem management. It also serves as a vital informational tool for decision-makers who require data to enhance the cost, quality, and performance of the organization’s IT services.

CMDB Characteristics 

1. Integrated Dashboards 

It is simple to track the health of data, the impact of changes, trends that indicate incidents or difficulties and the health of the CIs, thanks to the integration of dashboards with CI metrics and analytics. It dramatically shortens the time it takes to resolve a problem by providing the operations team with real-time insights about the preceding incident, problem, and change associated with a CI.

2. Access Limitations 

Access controls allow the flexibility to assign multiple access levels to people or teams as needed and track any changes back to their original location in case of an incident or query.

3. Compliance 

You will receive thorough records for the purpose of visibility and auditing. The condition of CIs, historical changes, checks and balances, and occurrences are among the insights into records.

4. Data Population and CI Creation 

This is backed by three distinct approaches that all search IP addresses within a company’s network to identify software and hardware information: integrations, discovery tools, and manual input. A company’s entire inventory of resources, including cloud resources, is created through this procedure.

5. Combined Data Sets 

Assistance with federated data sets includes CI normalization and reconciliation of the necessary data.

6. Service Mapping for IT 

A tangible illustration of the connections and interdependencies relating to an IT service.

How Does a CMDB Function?

A Configuration Management Database is a repository (a database) that houses relationships and lists of data. The data that a CMDB includes is what distinguishes and adds value to it. 

The physical IT environment’s connective tissue is described by lists of configuration elements, their corresponding attributes, and the relationships between them. The CMDB is frequently included in a larger IT Service Management (ITSM) platform or suite of capabilities, which will probably also include tools for discovering and importing data into the CMDB and tools for consuming data from the CMDB. The CMDB functions by offering a central location where employees can access data on IT assets and other configuration elements. Without the CMDB, it would be exceedingly challenging to put together a complete and accurate picture of the IT environment because this data is frequently gathered from various sources. 

Most of the time, configuration elements in the IT environment are found and added to the CMDB using discovery and data import technologies. Some businesses may manually update their CMDB data through audits and inventories. 

The information can then be accessible by tools and processes that need to consume it in a uniform, and consistent manner after data from the various sources has been loaded in the CMDB.

Due to the volume of data present and the format in which it is kept, accessing configuration data straight from the CMDB is uncommon. Rows and columns of data are challenging to interpret. Other ITSM tools and reporting capabilities play a part in this. 

These tools gain access to the data stored in the CMDB then sort, filter, and display it to users in a more appropriate way for the operational or business issue they are attempting to address.

Development of CMDBs  

A collection of procedures for service asset and configuration management are described in the IT Infrastructure Library (ITIL), to store data on configuration items (Cis), which are the parts needed to deliver an IT service. 

In addition to the lists of objects, relationships between them are also tracked as part of ITIL service asset and configuration management. The configuration management system (CMS) used by ITIL to enable asset and configuration management is represented as a logical data model that may span numerous physical CMDBs.

The CMDB plays a bigger part in helping IT staff members comprehend the production environment and make real-time choices about problems and modifications when businesses adopt new methodologies like Agile and DevOps. 

Companies will need to incorporate additional external data sources into the CMDB in order to retain the overall perspective of a modern hybrid IT environment as cloud infrastructure and SaaS usage proliferate. Many firms are looking into novel approaches to managing data assets within the context of the CMDB to support digital transformation initiatives and business processes.

The CMDB will have a bigger role in future business operations and IT operations (in a digitally transformed corporation). It will be crucial to start with the correct CMDB solution, one that not only meets your demands today but also allows you to expand with your organization as the market changes.

What Advantages Does the CMDB Offer?

One of the main advantages of CMDB is that it consolidates all the siloed data needed to run IT across the enterprise into one location, allowing IT operations visibility into all the IT resources in the company. It stops data from being dispersed among numerous sites. 

Here are just a few ways a CMDB benefits IT teams: it helps prevent outages, drastically shortens the time it takes to fix an outage, maintains compliance, prevents security and audit fines, helps decision-makers understand key service contexts, which improves risk assessment and reporting and tracks software license and cloud costs.

Planning

CMDB aids technology managers in making plans for both high-level enterprise architecture and detailed asset management.

Accounting

Applications and service codes are crucial for IT finance since they facilitate the distribution of billing statements and the management of other finances.

Operating

CMDB enhances fundamental ITSM techniques, including incident, change, and problem management. By anticipating which systems and users may be most negatively affected, CMDB helps enhance risk assessment in change management. Assisting teams in managing audit trails and controls, also promotes compliance.

By locating the modifications and underlying reasons for an issue and working toward a quicker resolution, CMDB impacts incident management. Teams can follow incidents over time together with the assets affected by the occurrence because incident records are linked to their CIs.

CMDB enhances problem management by assisting with root-cause analysis, which enables teams to locate a problem’s origin more rapidly. Additionally, it helps teams discover assets that require an upgrade to cut down on service costs and downtime. This enables proactive management.

Why Is It Essential to Have a Configuration Management Database? 

An organization needs the configuration management database because IT infrastructure is becoming more sophisticated and is a key part of the ITIL framework. Additionally, as your IT infrastructure becomes more complicated, monitoring and comprehending the information in your IT environment also becomes more crucial.

For IT leaders who need to identify and validate each element of their infrastructure in order to manage and enhance it, using a CMDB effectively is regarded as the best practice. Other advantages of using one of these for CMDB include:

• Increased awareness of users and connected CIs.
• Efficiency gains from a single source of information on the IT system.
• Improved decision-making with precise, current facts.
• Reduced downtime due to the problem, incident, and event mitigation.
• Automation lowers the expenses of operations, equipment, and labor.
• Faster MTTR because it can perform root-cause analysis and comprehend CI connections.
• Reduced risk through enhanced change management.

Problems with CMDB

Despite the clear benefits of CMDB, many organizations struggle to reap the benefits of their CMDB solutions. 

Here are just a few reasons why: manual processes were used to build the CMDB, there were no established procedures or methods for identifying the crucial data that needed to be transferred into the CMDB, and there were no automated tools to make sure the data was placed in the correct location in the CMDB. 

However, this does not imply that the technology is inherently defective; problems that can impair CMDB effectiveness can be anticipated and avoided by figuring out the variables involved.

Accuracy

Maintaining the accuracy of a CMDB can be challenging; some of these challenges include discovery tools not being used frequently enough, a lack of automated protocols, or an excessive reliance on data input. Accuracy will increase due to concentrating on and optimizing discovery within your CMDB.

Centralization

Although a CMDB is a centralized location to examine data, not all asset data must necessarily reside there. A great practice is using information from different tools such that the one most pertinent to each instance is used to support it.

Several Sources of Data 

A CMDB serves as a central store for data about IT assets. However, there may occasionally be too much data coming from sources that are feeding the CMDB. This could make it harder to categorize the data and cause confusion.

Process

Some businesses operate under the misconception that CMDBs are used to map outdated systems rather than the new cloud and software infrastructure stack. It’s crucial to avoid letting the debate over semantics stop you from tracking the value of your CIs in a platform that offers a comprehensive perspective of your technological ecosystems.

Relevancy

Some businesses view their CMDBs as the only reliable source of information, which might cause them to want to consolidate all of their data there without taking use cases or their specific needs into account. Only pertinent and valuable data that supports processes should be included in a CMDB; make sure to identify the value, objective, owner and methods for updating each piece of data.

Team Dedication   

One of the key determinants of the effective adoption and integration of new technology and processes is the level of team commitment. Your CMDB solution is unlikely to be successful if your company and the individuals involved are not totally dedicated to its success.

Tools

If you want to succeed, it’s essential to select the appropriate tool. Some CMDB technologies are little more than fixed asset repositories that rely on antiquated infrastructure discovery methods and have a sluggish response to change. The finest CMDB tools are ones that can swiftly adapt and that take new asset kinds into consideration. 

CMDBs vs. Asset Management

For change management, there is some functional overlap between CMDBs and ITAM platforms, and these platforms’ capabilities are being more thoroughly incorporated into larger service management frameworks. They serve various functions but they are distinct tools.

Unlike what a CMDB tracks, which includes acquisition/procurement, operation, maintenance, and disposal, an ITAM tool tracks hardware and software details throughout the whole asset lifecycle. This includes details about its configuration as well as the costs associated with each stage, such as those associated with purchasing, licensing, service/support and depreciation. 

Better asset utilization and proactive asset compliance and security auditing are two advantages of asset management. Additionally, better asset visibility facilitates quicker and more precise corporate decision-making.

ITAM tools are often used to accomplish business-oriented objectives, like reviewing and making choices throughout the lifecycle of an infrastructure asset. Configuration management solutions can assist IT employees in comprehending dependencies and planning and maintaining IT services when used for service-oriented objectives.

It should be noted that CMDB and ITAM are not exclusive. An example of an IT asset is an application server. It has a cost that depreciates over time, needs upkeep, and might incorporate operational data like service agreements that are not contained in a CMDB. That server is also a configuration item, and details about it, including the installed OS and applications, the server configuration, and firmware versions, may be monitored and managed through a CMDB.

Impact analysis uses the CMDB to show the potential effects of configuration changes on performance, stability issues and security.

CMDB in Acure

In Acure, a unified CMDB is used to record CI attributes and relationships between CIs throughout their lifecycle. Using the low-code engine scenarios you can automatically build CMDB with all connections, discover the integration items and place them on automatic monitoring.

All data collected from CMDB are presented in a form of a logical service model that describes the composition and relationships of a set of configuration items that together provide the service at an agreed level. In Acure, it is a network graph containing information about model entities and their relationships.

Find more about a CMDB and Service Model in our documentation and try it by yourself in Userspace.

So in summation

The foundation of ITIL processes is a Configuration Management Database (CMDB). A database of data about all the parts of an information system and the configuration items (CI) in the IT infrastructure are included in the CMDB. 

Hardware, software, people and documentation can all be CIs. In terms of IT asset management, a CMDB is a thorough “map” of your complete IT infrastructure that enables you to keep track of the condition of endpoint hardware, software, and data to detect and respond to security incidents.

Сообщение A Complete Guide to CMDB   появились сначала на Acure AIOps Platform.