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Tag: business operations

  • Measuring the Business Benefits of AIOps

    Measuring the Business Benefits of AIOps

    Staffing levels within IT operations (ITOps) departments are flat or declining, enterprise IT environments get more complex by the day and the transition to the cloud is accelerating. Meanwhile, the volume of data generated by monitoring and alerting systems is skyrocketing, and Ops teams are under pressure to respond to incidents more quickly.

    Faced with these challenges, companies are increasingly turning to AIOps – the use of machine learning and artificial intelligence to analyze large volumes of IT operations data – to help automate and optimize IT operations. But before investing in a new technology, leaders want assurances that it will bring value to end users, customers and the business at large.

    Leaders looking to measure the benefits of AIOps and build KPIs for both IT and business audiences should focus on key factors such as uptime, incident response and remediation time and predictive maintenance to prevent outages that could affect employees and customers.

    AIOps KPIs include employee productivity, customer satisfaction and web site metrics such as conversion rate or lead generation. AIOps can help companies cut IT operations costs through automation and rapid analysis; it can support revenue growth by enabling business processes to run smoothly and deliver excellent user experiences.

    Specific IT and Business Benefits

    AIOps can digest operational data and spit out actionable recommendations for keeping important systems running at peak efficiency. These are the most-cited benefits of the technology:

    • Alert management: In most cases, the first problem AIOps systems will address is reducing the volume of noise: the torrent of alerts that inundate IT operations. AIOps uses clustering and pattern matching algorithms to eliminate as much as 90% of false alarms and other redundant or irrelevant alerts, making it far easier for staffers to focus on what really matters.
    • Incident prioritization and routing: AIOps systems can learn, over time, which types of alerts should be sent to which teams, reducing redundancy and confusion when, say, networking and database teams both get the same alert related to an incident.
    • Event correlation: AIOps can correlate alerts and event data to identify the root cause of an outage or application slowdown so that IT teams can respond faster.
    • Advanced anomaly detection: AIOps systems can identify anomalies to proactively detect abnormal conditions and relate them to business impact. For example, AIOps can predict if a system will run out of disk space based on projected growth or seasonal patterns, even if the growth is non-linear. Or, if there’s a sudden increase in the number of failed server requests, the technology can determine whether the server in question is handling a mission critical task or simply performing routine backups.
    • Automation: AIOps can be used to handle routine tasks such as backups, server restarts and other low-risk maintenance activities which otherwise involve heavy manual effort.
    • Predictive analytics: A more advanced use case could involve predicting events before they happen – such as detecting when network bandwidth is reaching its limit or storage capacity is nearing threshold.

    Seven KPIs for AIOps

    These common KPIs can measure the impact of AIOps on business processes:

    1. Mean time to detect (MTTD): This KPI refers to how quickly it takes for an issue to be identified. AIOps can help companies drive down MTTD through the use of machine learning to detect patterns, block out noise and identify outages. Amid an avalanche of alerts, ITOps can better understand the importance and scope of an issue, which leads to faster identification of an incident, reduced downtime and better performance of business processes.
    2. Mean time to acknowledge (MTTA): Once an issue has been detected, IT teams need to acknowledge the issue and determine who will address it. AIOps can use machine learning to automate that decision-making process and quickly make sure that the right teams are working on the problem.
    3. Mean time to restore/resolve (MTTR): When a key business process or application goes down, speedy restoration of service is key. ITOps plays an important role in using machine learning to understand if the issue has been seen previously and, based on past experiences, to recommend the most effective way to get the service back up and running.
    4. Service Availability: Often expressed in terms of percentage of uptime over a period of time or outage minutes per period of time, AIOps can help boost service availability through the application of predictive maintenance.
    5. Percentage of automated versus manual resolution: Increasingly, organizations are leveraging intelligent automation to resolve issues without manual intervention. Machine learning systems can be trained to identify patterns, apply solutions, such as previous scripts that were executed to remedy a problem, and take the place of a human operator.
    6. User Reported versus Monitoring Detected: IT operations should be able to detect and remediate a problem before the end user is even aware of it. For example, if application performance or web site performance is slowing down, ITOps should get an alert when the issue can be measured in milliseconds; they can then fix the issue before the slowdown worsens and affects users. AIOps enables the use of dynamic thresholds to ensure that alerts are generated automatically and routed to the correct team for investigation, or automatically remediated when policies dictate.
    7. Time savings and associated cost savings: The use of AIOps, whether it’s to perform automation or more quickly identify and resolve issues, will result in both operator time savings and business time-to-value improvements. These have a direct impact on the bottom line.

    These seven AIOps KPIs can be correlated to business KPIs around user experience, application performance, customer satisfaction, improved e-commerce sales, employee productivity and increased revenue. ITOps teams need the ability to quickly connect the dots between infrastructure and business metrics so that IT is prioritizing spend and effort on real business needs. In the future, as machine learning matures, AIOps tools may even recommend ways to improve business outcomes or provide insights as to why digital programs did or did not succeed.

  • DataOps: The Key for Real-Time Data Application Development

    DataOps: The Key for Real-Time Data Application Development

    Data engineers and developers face challenges every day to help their organizations digitally transform. To do this, they must deliver real-time data applications faster, better and cheaper. With businesses in every industry now data-driven, data professionals must work more efficiently and accelerate time to market for their products. That’s where DataOps comes in.

    Development of real-time data applications slows down when strategic business project teams are dependent on small, centralized engineering or IT teams for basic data operations such as exploring data or even building most data processing applications. Needlessly, engineering teams are notorious for being a bottleneck for strategic digital transformation initiatives. Rather, they can become known as strategic project enablers that provide the best tooling to their customers—instead of building it and being known as gatekeepers.

    Business users, outside of IT and engineering, need access to data but lack the necessary deep technical knowledge to work with the latest data technologies. DataOps brings people closer to data, helping organizations accelerate the delivery of their strategic projects, reduce costs and minimize the need for hard-to-source engineering skills.

    To accelerate digital transformation initiatives, teams and organizations should onboard new users directly onto a data platform quickly with the right tooling and resources required to get to work on their projects. DataOps empowers these business-focused users to work with data tools on their own to self-serve. A DataOps approach makes it easier for more people across an organization to work with its data, resulting in better alignment for data engineers and developers with their business and technical partners and improved data access.

    Serious new security, compliance and governance risks are introduced when less-technical users increase their interaction with technology, such as onboarding to a data platform. More people now understand that personal data has tremendous value. Initiatives such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have brought the need to respect data privacy to the forefront. The stakes for safeguarding data are increasingly high and regulators are unforgiving—costing some organizations several billion dollars in fines, lawsuits and loss of market cap for some data breaches.

    When providing access to data, stringent management, control and real-time monitoring must be applied from a governance perspective. A surprise compliance auditor visit can result in questions such as which applications are reading credit card data, how an organization is keeping customer data safe, who has access to data and what are they doing with it. While locking down for compliance, you must help your business stay agile and avoid any slow down in data initiatives.

    Build vs. Buy to Streamline Operations

    In addition to adopting a DataOps approach, a key step is to onboard users to a data platform. This will optimize your data strategy and will help take the worry out of managing data projects, putting you on a path to faster execution and accelerated time to market.

    When onboarding users to a data platform, you need to choose between building your own or buying. It takes time and resources to develop your own system to onboard users and clients and can take years to build your own technology in-house. If your engineers are spending all their time working with open source technology to build tooling for onboarding, they’re not focusing on better ways to use data and get solutions to market fast—which is an inefficient approach.

    When your users are onboarded, the cycle begins again, as users request access to more data sets. More time at the command-line console means less time for your engineering teams to focus on higher-value work and strategic initiatives.

    Get a Leg Up on Competition With a DataOps Approach

    Buying a solution requires an upfront investment to support onboarding and, when combined with DataOps principles, is formidable to remain competitive. Together they enable support and manage the onboarding of clients to a data platform at scale and to maintain security and compliance. A DataOps approach fosters improved communication between data and business professionals to share data more effectively and to build a data mesh architecture.

    A Swedish digital bank, Avanza, needed to ensure the continuous improvement of the customer experience of its digital services to remain the leader in the Swedish market. Doing so required giving developers direct and constant access to real-time business data in Apache Kafka.

    The organization applied a DataOps approach and intelligent data masking rules to meet GDPR and protect customer confidentiality, featuring a large single data platform to address how it delivered data access and applied data governance to support more than 20 strategic projects. Using the platform, tenants who build streaming applications gained visibility into the health of their Kafka clusters and improved insight into data flows. This self-service approach means fewer support calls to data engineers, minimizing bottlenecks and freeing them up to work on more strategic initiatives.

    Data is the fuel that propels insights by tying back to analytics, decision-making and business systems. The better the shared data, the more it can be applied to supporting better business decisions, better customer experiences and execution of strategic business objectives and goals.

    DataOps also builds compliance and governance into your processes. It provides the visibility needed to understand who is accessing data and how to maintain governance and ensure people are acting ethically with the data they are enabled to access.

    The daily challenges faced in data-driven organizations only continue to grow. A DataOps approach helps data engineers and developers meet these challenges to digitally transform and build real-time data applications that help organizations gain a competitive business edge in their respective marketplaces.

  • 5 Reasons Why Companies Should Analyze Their Logs

    5 Reasons Why Companies Should Analyze Their Logs

    At first thought it might seem as though analyzing logs is something that only affects the IT portion of your business. However, nothing could be further from the truth. In reality, log analysis affects every aspect of your business. This includes finance, legal, human resources, sales and marketing, security and operations. In fact, with log analysis, you’ll discover issues either before or as they happen and avoid both lost time and unnecessary delays.

    There are many benefits to properly analyzing your logs. Your organization can increase revenue, reduce expenses, better manage employees, respond to incidents and even keep yourself out of legal hot water. Read on to learn about the five major business areas impacted by log analysis and why every business needs to analyze its log—and the sooner the better.

    Business Operations

    Probably the most obvious use of log analysis is in supporting business operations. These functions include the following:

    • Detecting critical system errors
    • Identifying key trends
    • Improving operational efficiency
    • Supporting service level agreements (SLA)
    • System troubleshooting

    Early indication of problems can pinpoint money-wasting processes. It also can mitigate risk in support of business continuity. This will help avoid service disruptions that can lead to unhappy customers and lost sales.

    Compliance and Legal

    Every organization has internal policies: security policies, employee policies, legal policies, etc. In fact, most organizations have regulations (such as HIPAA and Sarbanes-Oxley) they must adhere to. Often these regulations are imposed by the government. The only feasible way to ensure policies are followed and regulations are met is through log analysis.

    Log analysis simplifies compliance. It also supports audit requirements, litigation needs, subpoena requests and forensic investigations. In short, log analysis is the only way to ensure an organization stays out of legal trouble.

    Proper Resource Sizing

    One of the worst things any company can do is have the wrong amount of resources to support its business operations. From network bandwidth to storage capacity to CPU cycles, businesses have to get these quantities just right. Not enough resources in any area can lead to poor performance, frustrated customers and, eventually, lost sales.

    Of course, the easy thing to do is just overspec these resources. However, doing that leads to increased expenses, which adversely impact the bottom line. Using logs to determine proper resource sizing is the only way to ensure you have maximized your profits.

    The use of logs can also be used to verify third-party billing. For instance, your company can use your logs to make sure the amount of bandwidth you were charged for by your service provider is actually the amount you used. This, too, can benefit the bottom line.

    Sales and Marketing

    It may not seem as though log analysis can be used to directly impact sales and marketing, but it certainly can. For starters, log analysis can be used to quantify the effectiveness of a sales campaign. Information such as referring sites, pages accessed and conversion rates all can be used to tweak different aspects of the sales effort.

    Log analysis also can be used to optimize website performance in the support of a sales funnel. Information such as customer navigation, traffic loads and conversion errors can be used to improve the sales process. In fact, analyzing logs can be used as a revenue driver in any organization.

    Security

    One of the most important areas in any business today is security. Logs can be used to both proactively protect an organization, as well as forensically investigate security breaches.

    Proactively, logs can be used to accomplish the following:

    • Optimize blocking and filtering of incoming traffic
    • Maximize email virus protection
    • Monitor failed authentication attempts
    • Verify configurations in firewalls

    After the fact, logs can be used to do the following:

    • Assess security policy compliance
    • Initiate incident response
    • Investigate security breaches

    You cannot understand security risks or respond to security incidents without the ability to analyze your logs.

    In short, whether you were aware to it or not, log analysis impacts every department in your organization. It directly and indirectly impacts every company’s bottom line by increasing revenue, decreasing expenses and delighting customers.

    You now know that log analysis is not just a “back office” IT function. Every department in your company needs to use the intelligence contained in your logs to do their jobs better. It is why every business needs to analyze their logs, and now is the time to start.

    About the Author / Ariel Assaraf

    arielassarafAriel Assaraf is a co-founder and CPO at Coralogix. Previously Ariel was a GL at Verint and a Product manager at an elite Israeli intelligence unit.  He is into Software design, UX, growth hacking and basketball. Ariel holds a BEc in Economics and Math from the Open university of Israel. Connect with him on LinkedIn and Twitter

  • Communication Skills Matter in DevOps

    Communication Skills Matter in DevOps

    While the precise definition of DevOps is an evolving matter, a simple way to describe it is this: DevOps is a change of mindset toward an agile and inclusive approach to IT. DevOps enables IT professionals to think and work beyond technology silos, thereby deriving meaningful results at a faster rate than with more traditional methodologies.

    This involves going outside of our comfort zones and collaborating outside the confines of our own cliques. By working across operational boundaries, DevOps will require an understanding of technical, operational and service aspects of the business. This means the heart of DevOps lies not in technology, methodology nor administration: The heart of DevOps lies in communication, which brings all these together.

    DevOps professionals seem to agree. In Incapsula’s DevOps Salary Survey conducted in 2015, the California-based cybersecurity firm identified communication skills as one of the highest priorities for DevOps professionals, almost as much as operational skills.

    In other words, effective communication across the organization is considered as important as actually building the product, and it is integral to building the product itself. This means when you’re in the field of DevOps, a smart investment in communication skills will pay off for both individuals and the team.

    Communication Fosters Teamwork

    There usually exists a disjoint between technical and non-technical departments, particularly in technology companies. Engineers, for example, might be fascinated by an elegant piece of code, an algorithm that automatically governs a process or an infrastructure that does exactly what it’s supposed to do. But to the rest of the organization, those things take place purely in the background and work best when they aren’t noticed at all.

    Tech people take pride in the technology, while operations people take pride in business results. The two often find themselves at odds due to a lack of communication about what is really needed, and how to get there. Successful communication in DevOps focuses on finding common ground and working toward achieving this.

    For communication to be effective, the emphasis should be on the user of your message. You’ll need to have a deeper understanding of where they’re coming from. No amount of expertise matters if you can’t convey it properly. You can’t gain any growth or value for your career or organization if there is always a unidirectional disconnect.

    Bottom line is, you need to correctly identify your intended recipients and find a common ground to better engage.

    You Can Increase Your Value as a DevOps Pro

    Trust is an essential component of teamwork, which is also important in the development life cycle and in decision-making processes. Being a communicator enables you to better establish trust among your colleagues—something that, unfortunately, is lacking in many IT project life cycles.

    This is why pure technologists don’t necessarily make good DevOps professionals—an observation highlighted by the Incapsula survey, which shows that a mix of general and technical skills are essential for a successful DevOps career. In fact, general skills are usually more important in securing higher-paying jobs in this field. These include understanding business operations, developing communication skills and remaining flexible and open to change. In addition, the rising trend in outsourcing DevOps pros across a global talent pool means your communication skills have to transcend languages and contexts.

    A good DevOps professional knows that value is not just about the technology, but rather about the product. Even the best technologies in the world are just abstract concepts until you translate them into a product people can actually use and enjoy. Thus, going beyond technical capabilities, you will need to know how to collaborate to transform technologies into useful and marketable products.

    You Can Advance Your Career Faster

    Chatting up the project managers, glad-handing the operational staff and picking the brains of departmental leaders may not come naturally to pure technologists. However, for DevOps professionals increasingly engaged in conversations across the enterprise, knowing the language unique to the organizational culture—verbal and nonverbal—can make all the difference in terms of career advancement.

    Such organizational language can be considered as its own kind of coding. This facilitates everything from a working knowledge of financial reporting, to the listening skills needed to understand the technology goals meaningful to each business unit. It’s also how unwritten rules about business priorities or hierarchies are communicated.

    After all, the career survey cites at least 26 job descriptions among DevOps professionals, including project manager and operations manager, among others. This means you don’t necessarily have to get stuck in one position or job description. In an organization that fosters the DevOps culture, your value goes well beyond your technical capabilities, but rather the focus is more on organizational skills.

    The Takeaway

    Since DevOps involves cross-functional teams instead of compartmentalized departments, everyone will need to be more involved in business operations, product development and support. Being an effective communicator is at the heart of all this, and it can spell the difference between success and failure in a DevOps environment.

    It’s easy to think that there is little more to learn in terms of communication, especially if your DevOps integration is already mature and your team is functioning optimally. However, your investment in becoming a better DevOps communicator begins with learning the language and culture of the organization. This also includes a continuous reassessment of skills and the ability to build connections from each and every encounter with colleagues, partners and other stakeholders.

    About the Author / Laureen Fagan

    LaureenFaganA senior PR counsel and thought leader, Laureen Fagan has 15 years experience as a media and PR professional, which includes her stint at CBS and Fox broadcast affiliates in the United States, and in print and wire-service newsrooms in Chicago, Washington D.C., and Jerusalem. Laureen received her MSJ from Northwestern University’s Medill School of Journalism, and completed additional graduate study at University of Notre Dame in Theology / Hebrew Bible that includes French, Arabic and Hebrew study. In addition to tech and business, Laureen creates informed content and deep analysis on international affairs, health care, culture and religion.