devopsy.kinsta.cloud

Author: Erik Rudin

  • Five IT Ops-tackles that Stifle Business Growth

    Five IT Ops-tackles that Stifle Business Growth

    I was recently asked about the top five IT obstacles that stifle business growth, and I want to help clear a path too often lined with fear, uncertainty and doubt. In the not-so-distant past, IT was all about the tools. Solutions were more straightforward, teams were less globally connected, and the ever-present data deluge was not changing our business landscape by the millisecond.

    With this in mind, I have created a list of the five most common IT obstacles and will pinpoint the single tool you can implement to help alleviate these pain points.

    IT Staff Lack Time to Learn New Technologies

    This is not to slam our tech teams or leaders; this is just the byproduct of condensed customer schedules, tight purse strings and managing the MOOSE (maintenance and operations of the organization, systems and equipment). The demand on IT teams is high, and we don’t always have the opportunity or the resources to restructure operations for a new tool, as upgrading requires learning new APIs, UI/UX and deployment architectures.

    Difficulty Supporting New Technologies Quickly

    It is hard to keep pace with IT complexity and manage it properly. New services, applications and infrastructures are constantly being added and there are plenty of vendors out there that will get you locked into solving a single issue versus addressing your macro problems. While the benefits of upgrading are there, the difficulty lies in understanding the complexity of these systems and how to leverage them most effectively.

    Lack of Support for Hybrid IT

    Hybrid by definition adds complexity, and multi-cloud, on-prem and private/public clouds are only a few ways to make your hybrid dream a nightmare. No matter the combination, understanding different architectures and their components is a must. Additionally, we need to understand how we manage our own data as well as how our vendors are managing it.

    IT Complexity

    We need to know our machines and architectures well enough to focus limited resources on what impacts the business most. IT will always be complex—there’s always something new, and the amount of information to process is insurmountable and exhausting. Adding context to IT data can help you identify the root cause of overly complex systems. The most difficult task will be to understand the technology well enough to know what to do next. 

    Inability to Understand Business Impact in Order to Prioritize Tasks

    Prioritization is by far the most important aspect of IT. There is a lot of noise, lack of visibility, lack of context, and—the squeakiest wheels of them all—legacy tools. Prioritizing means routing the right people to the right problem to get it solved quickly and elevating IT service visibility, health and risk into the business function.

    Let’s Get Digital

    IT pros can start to tackle these challenges through prioritization and then automation, or AIOps—the principal of AIOps being to add context to data, using machine processes to enrich the data and bring it to a business level. Understand what is important to the organization and think about the outcomes important to IT. To do this, you can create a realization plan to tackle the low-hanging fruit and create achievable milestones and outcomes. For example, look for opportunities and create a crawl-walk-run phased approach driven by business priorities. Each organization has different needs and different timelines—and this process can be applied to customers, too.

    Next, take into account how your team does work and focus on automation as a principle within how you do work. One of the biggest impediments to digital transformation is culture. Remove manual processes, capture tribal knowledge and figure out how to repeat this approach in a consistent way. Additionally, absorb feedback and learn from it. This will drive acceleration when done right, and we all know that better digital experiences boost enterprise value.

    Finally, automation is useless if your data is flawed, and accuracy is a key fault for legacy configuration management database systems. Data must be accurate for effective machine-enabled automation. Leverage the tech you have to build an interconnected ecosystem that is fully integrated and automated—and that avoids tool sprawl. Have an open mind to consider new approaches and be brave enough to shed the legacy mindset. Additionally, take into consideration your partners and vendors, and how that team collaborates, to determine your strategy.

    The Light at the End of the Tunnel

    The path for today’s CIO can be unclear. But you can take bite- (or “byte-”) sized steps to put machines to work and leverage processes that deliver on AIOps. By understanding business outcomes, prioritizing automation as a principle and leveraging trustworthy internal and external relationships, you will have more time in the day for more important tasks. I measure outcomes based on customer experiences, and I ensure great customer experiences by running a great system. While your mileage may vary, moving forward is the most important part.

    — Erik Rudin

  • Rethinking the APM Paradigm: A New Vision for Enterprise Application Monitoring

    Rethinking the APM Paradigm: A New Vision for Enterprise Application Monitoring

    Traditional APM systems today can’t measure up to tomorrow’s processes

    IT today is inordinately complex; continually pushing the boundaries and comprehension for even the most sophisticated minds. And while modern IT is unlocking new, innovative experiences and capabilities, the advent of cloud computing and its distributed, ephemeral nature has also made it extremely difficult for IT managers to keep apprised of their infrastructure stacks.

    This reality has taken shape so swiftly and with such a vengeance that Gartner estimates by 2021, enterprises will be able to monitor only 20 percent of their applications accurately. In a digital world, that is like a department head saying he or she knows what happens in only 20 percent of your factories or storefronts. Twenty percent, regardless of the industry or circumstance, is both unacceptable and a grave risk to business continuity and success.

    APM Helps, But Not Much

    Enterprises need to know what the other 80 percent is doing. Unfortunately, the traditional application performance management (APM) tools on which enterprises typically rely are no longer up to this task for three reasons.

    First, the modern application suite looks very different today than it did just a short time ago. The monolithic and custom ERPs, CRMs and other enterprise systems that were the hallmark of big businesses a decade ago are giving way to cloud-based, off-the-shelf, as-a-service solutions constantly updated with iterative DevOps and agile development techniques.

    Second, most traditional APM tools rely on embedded monitoring agents installed on the monitored system, or they need code-level insertions tactics to monitor. Either way, that type of burden is unsustainable at today’s enterprise scale and doesn’t work when applications are launched in containerized cloud environments. It also fails to account for the shift to more off-the-shelf or as-a-service solutions created without APM data outputs.

    Finally, the very infrastructure enterprise operates on looks nothing like it did even five years ago. Most enterprises have moved (or are in the process of moving) to cloud, multi-cloud, or at least hybrid infrastructure. The advent of cloud and the ephemeral nature of microservices and containers means that application topology looks very different at 8 a.m. when only early-bird employees are in the office, then it does at 10 a.m. when the remaining employees arrive. That unpredictability is a nightmare for APM tools, which, at best, now offer only a keyhole view of the entire IT enterprise; performance management now relies as much on the infrastructure as it does the application.

    So, What Needs to Change?

    Traditional APM tools are battleships in an asymmetric warfare age: highly specialized and designed for a single mission, but at the cost of the flexibility to adapt to modern environments as needed. We need carrier groups, not battleship armadas.

    The ideal APM solution for modern enterprises is an “agent-less” or “agent everywhere” approach. A modern solution must holistically consider how one application interacts with other applications. For instance, how does online ordering generate data and feed into warehouse processing tickets? And it must understand how those applications interact with the underlying infrastructure. For example, where are databases or applications stored and how reliable is that infrastructure?

    Current APM solutions miss the mark entirely, scratching only the most superficial layer of today’s technology stack when instead, they need to understand the relations from the deepest layers of infrastructure out to the end users’ experiences. Such an approach will allow enterprises to see into the other 80 percent of applications and deliver the insight and automation needed to drive robust and innovative digital experiences.

    However, knowing you need visibility and having it are two very different things. Fortunately, innovation within AIOps through agent and agentless technologies promises to deliver what conventional APM can no longer.

    By making visibility into application layers easier and deploying machine learning-enabled topological mapping between infrastructure and applications, AIOps is allowing for more detailed insights into the health of mission-critical business services than ever before. It allows enterprises to regain the visibility they’ve lost to an ephemeral world and be able to understand, organize and innovate with the agility they need to compete in today’s business environments.

    It is time to leave traditional APM behind and move forward into an AIOps enabled world. Neglecting to do so puts the business at ever-greater risk.

    — Erik Rudin