devopsy.kinsta.cloud

Author: Thomas LaRock

  • Before ChatGPT, AIOps Powered Enterprises for Years

    Before ChatGPT, AIOps Powered Enterprises for Years

    Led by OpenAI and its ChatGPT software, a new era of consumer use cases for artificial intelligence is here. These exciting new tools have made AI more accessible to more users than ever before. No longer is this technology the exclusive domain of wealthy corporations.

    However, while the world is now focused on the potential use cases for AI in consumer applications, it’s important to remember that this technology has been part of the business world for years. Behind the scenes, AI has quietly been powering solutions that companies of all sizes have harnessed to improve business outcomes. These technologies have specifically been used by IT teams in the form of artificial intelligence for IT operations (AIOps) to help modernize their companies and operate more efficiently.

    By leveraging AIOps-powered solutions in use cases like observability, overworked and understaffed technology teams are improving their ability to manage complicated, hybrid and multi-cloud IT environments, automate processes and optimize their businesses. As companies prepare for a potential economic downturn and a reduction in resources, these solutions and AIOps are more important than ever.

    Here are four ways that AIOps is helping businesses overcome today’s IT challenges.

    Providing Unified Visibility Into Complicated Networks

    Companies have accelerated their digital transformation efforts in recent years. This has included migrating workflows to public and private clouds, implementing new productivity tools and adopting next-generation technologies. The average business now relies on geographically dispersed workforces and IT environments that use 2.6 clouds and leverage more than 200 apps!

    The result is that organizations lack visibility into these environments. A recent SolarWinds survey found that 54% of technology professional respondents stated they only have visibility into about half or less of their apps and infrastructure. This lack of visibility can lead to problems that negatively impact the return on investment for projects.

    AIOps helps overcome this challenge by providing comprehensive visibility into an organization’s systems, regardless of whether those environments are hosted in on-premises, hybrid or multi-cloud environments. AIOps automatically collects and integrates insights and information across geographies, apps and infrastructures into one dashboard. This provides technology teams with single-pane-of-glass visibility into the state of IT environments.

    Automating Processes & Remediating Issues

    While the visibility provided by AIOps and observability is integral to managing today’s complex IT environments, the technology goes a step further.

    With AIOps, teams can automate processes including the identification and remediation of issues. Given the stakes, this is critical. Companies must ensure their environments are always available and that their performance meets and exceeds customer demands. Even short service outages can lead to frustrated users and a damaged customer experience.

    This is challenging, as an IT anomaly often results in many alerts and a flood of log messages, making the problem difficult for a human to understand and address. AIOps quickly ingests massive amounts of information, provides rapid root cause analysis, data/event correlation and incident management which allows for fast and automated remediation of issues as they arise.

    Additionally, since this technology is always observing and gathering information on potential incidents, it can predict and prevent future issues proactively. By implementing AIOps, companies are taking a step toward autonomous operations or environments that can manage themselves without human involvement.

    Protecting Revenue

    In the face of an uncertain economy, every organization is taking steps to protect its revenue. With AIOps, enterprise technology companies have a powerful tool in this fight.

    By implementing AIOps and observability, companies can quickly resolve and prevent IT issues before they arise. This ensures that IT environments are operating at maximum efficiency.

    With AIOps, organizations can reduce downtime and prevent outages. This ensures that business-critical applications and infrastructure are available and functioning. These capabilities are more important as even short service outages have reportedly been capable of causing millions of dollars in damages.

    Freeing Up Employee Time for Innovation and Efficiency

    Over the last few years, companies have experienced severe staffing challenges, with many organizations finding it difficult to fill critical technology roles. This has led to smaller teams with more responsibilities and less free time. The result has been overworked technology professionals who spend far too much time on manual and menial tasks that do little to support the business’s bottom line.

    By implementing AIOps, organizations can streamline workflows by automating repetitive and routine tasks. Doing so can cut down on the amount of overwhelming metrics technology professionals are required to analyze and, instead, empower those individuals and teams to again focus on innovating and completing projects that support key business objectives.

  • Database Observability: How to Circumvent your Weakest Link

    Database Observability: How to Circumvent your Weakest Link

    Today, IT pros field an increasing number of assets they need to monitor to secure systems and understand what’s happening in their database and applications. This is further complicated as organizations adopt hybrid IT strategies and IT pros are tasked with managing tech stacks that span across on-premises and public clouds. 

    To cut through complexity and create end-to-end visibility into their IT systems, organizations must enact an observability approach.

    Monitoring Vs. Observability

    When it comes to observability, many think it means the same as monitoring. Whereas monitoring is a verb; observability is a measure of how well the internal states and conditions of a system can be inferred from its external outputs. 

    When monitoring systems are set up, dashboards are built around certain assumptions that an IT pro may expect will happen. When monitoring databases, teams are building multi-level component IP systems. The algorithms must process that data, and the user interface must interact with it. 

    However, to make that system highly observable, performance information and other kinds of metrics across all kinds of different endpoints must be incorporated. Especially since IT pros must deal with microservices, mesh, IoT or containers orchestrated through Kubernetes.

    How to Monitor Effectively 

    In the past, IT pros would typically monitor a SQL Server or even other database platforms like PostgreSQL or MySQL. In this new era of observability, on the other hand, IT pros need to do something different with the front-end code with regard to the different kinds of algorithms processed against that data set. Typically, developer teams would write the code, but there wasn’t anything written in that code to send out debug signals.

    Today that has changed. To make sure our systems are fully observable (because we can’t anticipate all possible problems!), we must log different steps to keep track of the many moving pieces. Organizations must collect as much of everything as possible. The more data, the more information organizations have about what’s happening in their application, from the database through the virtualization or containerization layer to the virtualization host or the orchestration to the bare metal. If organizations can get visibility into those elements, we can enable our systems to be fully observable and more easily diagnose any problem or anomaly that happens.

    An Observability Approach

    When using the observability approach, high-level dashboards are handy. They can help IT pros roll up everything that’s happening and get to a root cause analysis if there is a problem. However, sometimes there’s not a specific problem; there’s just a general performance issue. With observability platforms, teams can quickly discover, map and understand dependencies in ways that make it easier to achieve and maintain service level objectives (SLOs). 

    As IT teams increasingly distinguish between merely monitoring IT environments and achieving observability, they can proactively surface anomalies using machine learning algorithms and other forms of data science. And the depth and insight that can be applied to managing IT is increasing dramatically. Observability is quickly becoming table stakes for any modern IT organization. 

  • Overcoming IT Complexity With Full-Stack Observability

    Overcoming IT Complexity With Full-Stack Observability

    Organizations embarking on digital transformation journeys tend to develop complex infrastructures. They update their legacy applications while adding multi-cloud, virtual and cloud-native capabilities. Eventually, IT pros find themselves managing diverse, complex and distributed networks including cloud, system, application and database infrastructures.

    To rein in the resulting complexity, organizations tend to amass monitoring and managing tools. The goal is to simplify systems oversight—but instead, silos tend to develop because teams use a wide variety of tools to manage their networks or infrastructures. 

    This piecemeal approach worsens operational blind spots and delays problem resolution. It also increases security exposures. Soon, overwhelmed IT pros can’t keep pace with app modernization or infrastructure dynamics because they’re awash in complexity.

    Though this scenario is common, it’s not inevitable. IT teams can ease their digital transformation journey by implementing an integrated and cost-effective full-stack, end-to-end monitoring service capable of overcoming complexity and silos. 

    Organizations require full-stack observability.

    How Observability Differs From Traditional Monitoring

    Observability goes beyond traditional monitoring. Traditional monitoring helps IT organizations understand the actual state of their infrastructure and applications. It captures and processes volumes of infrastructure and application telemetry data and notifications and displays which components are up, which ones are down and which ones have changed. 

    Usually, traditional monitoring focuses on a specific network, cloud or infrastructure. It tracks application and infrastructure elements so IT pros can identify anomalies and investigate problems as they arise.

    Monitoring relies on metrics-oriented dashboards built to assess telemetry data against manual or basic statistically relevant thresholds. Monitoring tools are invaluable, but they don’t offer cross-domain correlation, service delivery insight, operational dependencies, or predictability. Modern systems have complex multi-cloud environments and a deluge of telemetry data: This counts as a shortfall.

    Observability does more. It measures the internal states of systems by examining the outputs and looks at applications and systems in their entirety—from the end-user experience to server-side metrics and logs.

    But observability also includes monitoring as a critical element. To gain observability, you must first collect information through monitoring. Observability uses the insights and metrics generated through monitoring to understand what’s causing the issue at hand. 

    Monitoring aggregates and displays the data to determine whether the systems are operating as expected. The analysis of this information is compared with expected outcomes and objectives. This allows IT pros to understand the state of their infrastructure and applications. 

    Silos are thus avoided because complex environments are viewed in their entirety.

    Observability in Action

    Once in place, observability allows IT organizations to continuously improve performance, availability and digital experience across complex, diverse and distributed hybrid and cloud environments.

    With observability, organizations can quickly find and resolve anomalies. However, full-stack observability goes beyond monitoring and expedited problem resolution: It supplies insights, automated analytics and actionable intelligence through cross-domain data correlation, machine learning (ML) and artificial intelligence for IT operations (AIOps). It works across massive real-time and historical metrics, logs and trace data.

    Observability goes beyond the silos and the piecemeal approach associated with traditional monitoring. And when observability isn’t limited—when it includes ML and AIOps—it uses the large volume of gathered data and supplies insights, automated analytics and actionable intelligence to help IT staff expedite problem resolution. It also enables ITOps, DevOps and security organizations to achieve consistent, optimized and predictable business service delivery with continuously improved digital experience and IT productivity. 

    The result is customers and employees benefit from better-run systems. The technology provides organizations of all sizes and industries with comprehensive, integrated, and cost-effective functionality through cloud-connected on-premises or software as a service (SaaS) deployment flexibility.

    When embarking on digital transformation journeys, organizations don’t need further complexity—certainly not while they update legacy applications and add a plethora of modern services and capabilities to their stack. The key to reducing complexity is observability.

    Observability simplifies the transformation process. It reduces operational noise to benefit ITOps, DevOps and security teams. They can become more proactive in issue and anomaly detection to achieve optimum IT performance, compliance, and resilience. With full-stack observability, any organization—no matter its size or industry—can reduce IT complexity while readying itself for digital transformation.

  • Tackling CostOps When You’re a Developer

    Tackling CostOps When You’re a Developer

    The implementation and successful execution of IT initiatives often comes down to developers. From those working with commercial vendors to those working with open source projects, cloud-based software-as-a-service (SaaS) solutions, managed service providers (MSPs) and internal teams, they all play an important role in the successful running of IT and operations teams.

    One challenge developer and operations teams face is the huge time barrier between development and follow-on operations. What a developer builds today for an organization may continue to be used decades from now, and will likely be maintained, patched, updated and modified by other developers. Though it’s a point of pride for the developer—who will have likely moved on in their career—it can be challenging for the operations team who has to continue to deploy it year after year.

    With more applications than ever before, the traditional role of the developer is changing. Today, developers need to start factoring operations cost containment into their responsibilities.

    Opportunity for the Developer

    Developers are rarely responsible for long-term business decisions. Once code is out of their hands, they often have little to no stewardship of their work. The business will make critical IT cost optimization and containment decisions about its code, language and toolchain epochs later. Developers focus on the now and the near future. Spending hours envisioning the one winning outcome out of 10,000 possibilities years later won’t get code out the door or achieve the delivery goals of their managers.

    However, developers have an often-overlooked opportunity to include the gears to activate cost containment support during initial development. From there, if their work is good, it’ll endure; extended support will eventually be necessary. The first step is to ensure new and modernized applications include solid cloud-native monitoring from the outset. This not only helps DevOps and SRE teams but benefits the entire business, who’ll own those applications for the long term.

    Integrating operations-focused monitoring is a top priority for developers. In some cases, an application using platform-managed serverless or orchestrated containerization has no shortage of opportunities to provide developers and operations with detailed performance data.

    A developer’s expertise with dependency analysis, code maturity and ease of integration is a great measurement tool to evaluate tool durability. A solution capable of easily combining cloud-native application performance details with infrastructure performance, user experience and operational expense data is even more likely to help developers and businesses manage costs in the long run.

    A New Dimension

    As cloud-native becomes a mainstream enterprise strategy, cost containment is a key opportunity. To meet the future challenges of application management, leadership is rapidly expanding their definition of application suitability and quality to incorporate all aspects of application ownership. For some teams, cost containment is a new dimension of senior developer maturity.

  • Avoid Security Apathy with DevSecOps

    Avoid Security Apathy with DevSecOps

    Against the backdrop of rapid digital transformation accelerated by the pandemic, every industry has seen an increase in high-level cybersecurity breaches. As organizations continue to support distributed and remote work, organizations must address the risk of incomplete security policies and procedures resulting in exposure to IT risk of all kinds. SolarWinds recently revealed findings of its SolarWinds IT Trends Report 2021: Building a Secure Future, which analyzes the degree to which organizations are prepared to manage, mitigate and prevent risk in the future.

    Measuring Risk

    The survey found 46% of tech pro respondents admitted to having medium exposure to enterprise IT risk over the past 12 months. The level of perceived risk differs by size of the organization, where a sense of high or extremely high-risk exposure is perceived at enterprise organizations (19%) compared to their small business (11%) and mid-sized business (7%) counterparts. With the rise of high-level cybersecurity breaches this past year, this is a concerning reality for security within enterprises.

    However, the findings highlight a possible disconnect—although enterprise IT risk exists within their organizations, tech pro respondents are confident in their risk management and mitigation preparedness strategies. In fact, 73% of tech pro respondents “agree” or “strongly agree” their IT organization is prepared to manage, mitigate and resolve risk factor-related issues due to the policies and/or procedures they already have in place.

    How to Avoid Security Apathy

    As a tech pro, it’s easy to think of security as an afterthought or to expect ownership to fall solely on the shoulders of a dedicated security team. This is especially true for tech pros who have been with a company for a long time and are resistant to change.

    As we emerge from the pandemic, those continued perceptions reflect apathy and complacency when it comes to security and will only increase their business’ level of risk. They’ll be more apt to limit exposure to new technologies, ignore better ways of working, or worse continue to be oblivious to other areas of less obvious risk within an organization. Something needs to change.

    Tech pros must shift their mindset and accept security as one of their responsibilities. To start this process, IT teams must examine current processes from the outside in and apply rigor when evaluating solutions. Since it’s common to be bombarded with marketing messages, this means spending time verifying a tool or solution’s functions and capabilities to help separate fact from fiction.

    Next, tech pros must focus on providing complete visibility into all systems to identify areas of risk and opportunity. Even small adjustments, like speedier upgrades and patches, the adoption of password managers and multi-factor authentication (MFA) solutions can help improve an organization’s overall security posture.

    Most important of all, tech pros should be continuously assessing their risk management, mitigation, and protocols to avoid complacency and becoming “blind” to risk.

    After a year of “crisis mode” induced by the pandemic, it’s easy to be complacent and sidestep the responsibility of risk assessment and aversion. As the security landscape continues to evolve, tech pros must remain vigilant and deploy solutions that provide better visibility into systems to identify risk and opportunity. This year’s study reveals the opportunity ahead for tech pros and IT leadership to align on priorities and policies that can best position not only individual organizations but the industry at large to succeed in managing, mitigating and preventing risk in the future.

  • The SolarWinds Query Report 2021: Database Priorities and Pitfalls

    The SolarWinds Query Report 2021: Database Priorities and Pitfalls

    The rise of hybrid IT and the accelerated adoption of cloud-native apps have evolved traditional database design, management and monitoring. Workloads are rapidly shifting to the cloud and application performance is heavily dependent on the performance of the underlying database. Meanwhile, the global COVID-19 pandemic has forced companies to make significant changes in the last year. Although it was and is a necessity, the transition to remote work and many organizations’ rapid pivots in strategy posed significant challenges for the technology professionals tasked with supporting new employee demands and shifting business priorities.

    As a result, organizations are increasingly acknowledging the importance of database performance management and strategy to ensure their most valuable asset: Data. SolarWinds recently revealed the findings of The SolarWinds Query Report 2021: Database Priorities and Pitfalls, which examines the current state of database management, evaluates the primary challenges database professionals face today and outlines how database professionals can best overcome these challenges.

    The North American results are based on responses to an online survey fielded in February 2021, which included participation from 331 technology professionals responsible for database performance management in the U.S. and Canada from public and private sector small, mid-size and enterprise organizations.

    Among many other key findings, this year’s report revealed the following:

    Increasing Complexity

    Database design and management are evolving in tandem with increased complexity, and IT professionals are on the verge of a significant shift in strategy that embraces cloud database-as-a-service (DBaaS) platforms as critical database performance success factors.

    • Though nearly 80% of the respondents said Microsoft SQL Server is the most critical platform in use today, there’s a relatively even split between the second, third, and fourth most-used platforms: cloud DBaaS (54%), Oracle (47%) and MySQL (43%).
    • As tech pros keep pace with advances in database platforms and indicate an intended shift toward cloud DBaaS adoption (33% of the respondents ranked cloud DBaaS as the number-one priority database platform to adopt over the next three years), the new mix of traditional/cloud DBaaS platforms will also require new skills.
    • Complexity increased in response to COVID-19 and the transition to remote work over the past year, according to 31% of respondents, who cited increased data demands from users, increased volume of data and security/compliance issues (such as GDPR) as the top three drivers of added complexity.

    The industry’s acknowledgment of cloud DBaaS platforms as critical success factors for database performance is now underway. When it comes to cloud migration (especially amidst a pandemic dramatically accelerating planning and execution of cloud computing and digital transformation), database professionals should start with a basic data and code cleanse and ensure only what’s truly needed is being migrated to reduce complexity and overall cost (we know cloud computing costs can add up). A comprehensive, successful migration strategy should also include a detailed assessment of the data estate—what dependencies or complex coding features exist? Remember, everything interconnected with a database has to go with it to the cloud, so taking these preliminary steps will help organizations avoid surprises down the road.

    Database Security/Compliance Influence Priorities

    The cloud and security/compliance are key factors influencing priorities and resource allocation in 2021 and beyond.

    • Nearly 60% of tech pros surveyed stated that of the data/systems currently managed within their organization, less than 25% are in the cloud. But this is expected to change, as 36% of respondents reported integrating cloud DBaaS is one of their organization’s top priorities in 2021.
    • Two-fifths of the respondents anticipated bigger budget allocations in 2021 (compared to 2020) for cloud services and security/compliance (42% and 39%, respectively).

    Managing database platforms is a big undertaking—a balancing act between proactive and reactive responses. But tech pros must make sure they’re covering all their bases, especially when it comes to security and compliance (and, on occasion, cost and licensing). Time and time again, we see these four big-ticket items pushed to the bottom of the priority list, and falling at one of these hurdles can do a great deal of damage. The new generation of legal compliance has real teeth if you fail to comply with the law. A simple cost-benefit analysis can be the proof point you need to highlight the potential impact of not upskilling in one of these areas and can give you a reason to move it back to the top of the priority list.

    Maintenance Constraints

    Database professionals devote more than a third of their day to database maintenance. This constrains both time and opportunity for activities such as innovation and upskilling in response to increased complexity and data-driven initiatives.

    • Maintenance work accounts for a greater portion of database professionals’ time when compared to other tasks. One-third of the tech pros surveyed stated one of the top areas where they spend the most time as a database/data/tech pro is maintenance (33%) and database development (22%).

    Daily database maintenance consumes time tech pros could otherwise be spending on things like upskilling or innovating new ways of working. For example, nearly half of those polled stated performance/query tuning was one of the top three skills/tools they believed they could develop/improve to better manage increasing database complexities, followed by security management and data engineering (45% and 41%, respectively). One of the best ways to work smarter, not harder: Mitigate downtime spent on maintenance and enable efficiency is to implement appropriate automation and monitoring tools. When implemented properly, automation and monitoring solutions can improve overall performance and eventually lead to reduced costs. Additionally, they can free up tech pros’ time, allowing them to focus on more proactive database performance management.

    The report reveals just how quickly the database architecture and operations tech pros are managing in today’s organizations are changing—and the web of management complexity accompanying this change. With application availability and performance as critical business drivers, the database has long been the linchpin of today’s IT environments. However, against the headwinds of increasingly diversified platforms and reduced resources, tech pros must be equipped to do more than reactive maintenance in environments that keep adding more databases with each passing day.

    Tech pros must capitalize on the opportunity ahead to maximize the performance potential of cloud-hosted databases and ensure the successful optimization of their organizations’ data.