Category: IT as Code

  • Forget Automation: Why IT Should Take UX Cues From Fine Dining

    Forget Automation: Why IT Should Take UX Cues From Fine Dining

    As a college student, I worked at a five-star Italian restaurant where I learned the discipline and practice of customer service. The general manager knew exactly which corner to stand in to get a view of every single table during service. They would gauge diners’ experience according to how they were interacting, their microsignals, how much food was left on their plate and the way they glanced around the restaurant. What does this intense attention to detail and individual customer experience have to do with running a service-oriented technology business? Everything.

    The tech industry is notorious for automating processes at the expense of personalization, and that aversion can extend to building the relationships necessary to produce a successful end product. Understandably, some companies and their developers prefer to keep relationships with their clients strictly functional because these connections are messy, people are unpredictable and nothing ever goes completely according to plan. It’s a dance we have to do over and again with every new client and project. 

    For those of us who wish to function as service-oriented tech companies, keeping on top of client and customer experiences requires us to stay attentive and listen with active care. Just like the veteran restaurant manager, we have to constantly scan our environment for cues of satisfaction and dissatisfaction.

    Service is More Than an End Product

    Before opening every night, the general manager would make staff hold long pieces of string to measure the angles and distance between tables to ensure they were straight and the edges perfectly aligned. Then, after telling staff the evening specials, he would randomly quiz them about the menu. What color is a fava bean? 

    Seeing the value of such old-school standards left a deep impression and helped me embed attention to detail as a foundational practice across the board, from designing good UX to cultivating relationships. Creating a desirable environment is about successfully orchestrating a million tiny details and always looking for tweaks to make the customer experience better. 

    That seemingly omniscient Italian from my earliest experience in the restaurant industry also taught me that being empathic goes hand-in-hand with the hard-nosed realities of running a service-oriented business. They showed me how to take care of people, how to make them feel good and how to read body language. 

    It might be easy to stereotype tech companies as impersonal dispensers of products (and their developers as cogs in the machinery), but we don’t want to just take orders. Our job is to become strategic partners from the ground up for long-term success, and that requires constant care and continual adaptation. 

    Mapping the Client Experience

    We must be willing to redesign how we work with customers and end users over and over again—it’s always changing because expectations are always changing, and market norms are always changing. The moment that we stop trying to get better through small incremental improvements is the moment we stop being service-oriented.

    In the same way that a restaurant has a sequence of service that maps a diner’s journey from the moment they enter the door, we can architect a customer experience from every touchpoint. 

    In the sales process, it’s valuable to layer in different people to create more relationship touchpoints throughout an organization, so, in our case, a new client meets a member of our operations team and then somebody from our engineering team in order to ensure that they feel fully supported. Then, we set expectations in terms of communication as part of a scripted onboarding experience. In our review meetings, we seek feedback to determine whether we have under-delivered and course correct if necessary. 

    The other thing I learned from that Italian restaurant is that no mistake is irredeemable. It doesn’t really matter if you get it right or wrong the first time, it is how you respond when the unexpected happens that matters. Turning a situation around after making a horrible mistake—even sending out a cold steak—can breed even more loyal customers because it demonstrates that you really care.

    The Creative Heart of Service

    Despite the image of tech as cold and distant, it’s important to recognize that coding and development itself is creative and we should seek to nurture a healthy environment so that people can perform at their best. To that end, it makes sense to think of your responsibility as running the entire length of the chain, from employees to clients and, finally, to end users. Finding humanity in the work along each link is key to building successful partnerships. 

    In the context of building products, we must be creative to design seamless, curated experiences for end users. There are plenty of apps that sit on someone’s phone unused before ultimately being deleted. The only way to grab the attention of people that share the same interests and problems is by understanding their needs. 

    To that end, we must always be asking our clients: What is the easiest point of entry for the user? Creating a low barrier is a quick win that in and of itself is an onboarding experience and an opportunity to build trust. 

    Equally, what may make one customer happy may not actually have any resonance in the wider market. If customers were only hiring us to write code, we would only be interested in meeting their expectations. The goal is not just to build products, but successful products that establish or reinforce a client’s reputable presence in the marketplace. 

    Adding Value Through Relationships

    When we stand in our metaphorical corner of the room to observe the customer experience, we are consolidating data from products that have millions of users and harvesting insight. We are not interested in quick fixes. Customer service and a focus on the end-user experience means being oriented to what the market wants, not designing in a vacuum. We can then continue to build value over time.

    In the restaurant business, the little surprise at the end of dinner adds value because it is unexpected. A complimentary after-dinner liqueur with a pithy origin story is a point of detail at its finest. Creating a richer, fuller customer experience can set a tech business apart in an exploding marketplace. For my old mentors, paying attention to every nuance from the beginning to the end is what defines five-star service.

  • Protecting CI/CD Pipelines to Secure the Software Supply Chain

    Protecting CI/CD Pipelines to Secure the Software Supply Chain

    Cloud-native applications have become increasingly complex. Composed of an infrastructure stack of mash-up code, hundreds of open source and commercial components, services and APIs, today’s software supply chain is fraught with security risks. At the same time, the ability to manage existing application requirements while building innovation and taking on new areas of responsibility like security is stretching DevOps teams beyond their capacity. The concern for the number of connected and exploitable weaknesses across the software supply chain are now requiring organizations to take a proactive approach to protect their continuous integration and continuous delivery (CI/CD) systems, as they have become a target through which attackers infiltrate multiple production systems. But meeting this requirement is no easy feat as it often requires organizations to choose between how much security to enforce in the build cycle while quantifying their risk to build and deploy quickly. 

    A recent survey revealed that nearly all (97%) of an organization’s assets—and security issues—are now in the cloud. And yet, only 29% of an organization’s assets are associated with cloud-specific policies. Addressing this gap requires organizations to have a proactive approach to protect their technology infrastructure, especially securing the artery of their software supply chain: The CI/CD pipeline. By embracing new security and compliance strategies within their governance approach, organizations can better protect their CI/CD pipeline and cloud applications. 

    There is a growing shift toward programmable infrastructure and infrastructure-as-code (IaC) practices to build out infrastructure and manage configuration files. But with this practice comes the increased risk of exposing application credentials, API keys, encryption keys and digital certificates. Tools supporting the CI/CD pipeline have now become the artery of cloud applications, and it’s becoming more challenging to store, transmit and audit data securely. In addition, when CI/CD tools interact with other systems in the DevOps environment, it increases the risk of exposure for configuration files. A compromise in the build system, for example, can be used to get access to production systems that can result in the exposure of sensitive information or the injection of malicious code, corrupting the entire CI/CD pipeline and thus the software supply chain. 

    A recent Unit 42 Cloud Threat report revealed that overly permissive credentials created added risk opportunities in the CI/CD pipeline. The study found that 63% of IaC templates contained misconfigurations and 91% of container images contained high or critical security vulnerabilities. To address this, organizations need to catch security problems in the build process before cloud workloads are provisioned. During the SolarWinds compromise, for instance, attackers used custom malware designed for the company’s build cycle to observe each step. The sophistication of the intrusion in this attack during the software build process is a key lesson for DevOps and DevSecOps professionals and revealed how security needs to be approached. 

    One way to address this is by being able to identify CI pipeline misconfigurations, which can improve security in the software supply chain. Because CI pipelines are configured in the code, the same policy-as-code approach can be used to identify IaC misconfigurations or open source vulnerabilities to surface CI/CD weaknesses. DevOps and developer teams can keep configurations accessible to just a small group who are building for production release. By establishing enforceable permissions to the pipeline, there is better control over who can commit code changes to the repositories, create containers and deploy code to different environments. 

    Strong chains of trust throughout the build cycle are not commonplace today. But as organizations look at ways to strengthen their risk posture by shifting left, security and DevOps teams can work toward proactively hardening pipelines with the right CI/CD tools and frameworks and push the industry toward a more secure software supply chain. 

  • What’s Next for Cloud Computing? Distributed Cloud

    What’s Next for Cloud Computing? Distributed Cloud

    The public cloud has greatly advanced IT by allowing teams to interact with their data and write new applications in a cloud-native way. The cloud simplifies the application development process, provides services on demand and allows you to pay as you go. There has been phenomenal growth in public cloud use and all estimates show that it is likely to keep growing in the near future. 

    Nevertheless, most IT computing still takes place outside of the public cloud, simply because there has been no effective way to consume cloud-native services outside of data centers (or “regions”) operated by the hyperscale cloud providers. This location constraint negatively affects cloud computing in three main ways: Performance (latency, throughput), data sovereignty (residency, regulations) and commercial considerations (legacy architecture, pricing). 

    As a result, to realize the cloud’s fullest potential, many enterprises are turning to a recent innovation in cloud computing: Distributed clouds that are untethered to specific locations or regions.  

    How does this work? Through APIs, the distributed cloud connects to any IT stack in any location and provides cloud functionality as if running on a hyperscale cloud. However, instead of running in a dedicated location, it runs on existing infrastructure on top of any IaaS, virtualized environment or bare-metal machines. It is agnostic to the stack’s underlying physics and doesn’t require any installation or capex. It runs workloads in any environment: Commercial data center, on-premises facility, edge microcenter or even in a multi-facility hybrid environment. 

    How the Cloud is Transforming Enterprise and SMBs

    Modern application development lives and breathes cloud computing. It’s been the enabler for much of the recent progress with modern applications—such as those dedicated to IoT, smart cities and personal health, for example—and will continue to be the infrastructure on which enterprises and small businesses develop new innovations. But as more and more businesses employ a cloud-first approach using cloud-native architectures and technologies, “IT budget” has become synonymous with “cloud budget.” And this is often a very expensive proposition.

    Therefore, the next step for many businesses is to manage cloud computing costs while supporting legacy and cloud-native applications as well as cloud migration. Their computing strategy may be simultaneously on-premises, bare metal and hybrid across multiple continents. And so they need a cloud with architectural latitude to match their needs as well as their budget. 

    This flexibility is provided by the customizable distributed cloud. By facilitating interoperability with existing infrastructure, it enables enterprises to deploy and infinitely scale applications anywhere they need. The more openness they have in terms of where they run applications, the more freedom they have to optimize their budget. 

    Who is Driving Cloud Computing Innovation?

    Amazon, Microsoft and Google have gone from being the innovators in cloud computing to being the incumbents. Innovation in the cloud is coming from startups as well as legacy IT companies. Here are a few examples:

    • Kyndryl has emerged as one of the system integrators of choice when the Fortune 500 look to innovate and modernize their IT and application infrastructures. Kyndryl has been engaged by large companies to solve many of the challenges that cloud computing has created. One of the innovations they have championed is the distributed cloud.
    • NetApp has spent over $2 billion on more than a dozen acquisitions to build their cloud portfolio. Their focus has been on creating a portfolio that gives enterprises the ability to bridge their various compute and storage infrastructures to the cloud. As opposed to assuming that their customers will have greenfield implementations on cloud infrastructure, NetApp has built a portfolio that allows them to meet their clients where they currently are in terms of architecture and to shift from there into more cloud-native capabilities. 
    • Zenlayer has built cloud infrastructure in diverse geographies, giving them global reach that even the hyperscalers can’t rival. Zenlayer claims to provide cloud infrastructure that is so globally distributed that they are within 25 milliseconds of latency from 85% of the world’s internet population. This focus on physical infrastructure locations that enable global performance is an important innovation for many modern applications. 

    Emerging Cloud Computing Innovations

    The distributed cloud, which integrates programmatically into any existing local infrastructure, is an innovation that drives businesses forward by providing them with a cloud that can be customized for specific locality requirements. Without requiring any installation, its cloud-native building blocks leverage existing servers to run application workloads in any environment—private, public, on-premises and hybrid. 

    As a result, application owners are able to build an optimized cloud computing strategy, taking advantage of existing and available infrastructure in the location—or multiple locations—of their choosing.  

  • EvolveWare Further Automates App Modernization Tasks

    EvolveWare Further Automates App Modernization Tasks

    EvolveWare today announced it has added an Agile Business Rules Extraction capability to its Intellisys application modernization platform.

    EvolveWare CEO Miten Marfatia said the Agile Business Rules Extraction capability eliminates the need to freeze code development while applications are either being shifted to the cloud or refactored. Instead, the Intellisys platform will now keep track of updates to code and apply them once the application has been modernized, he said.

    Code updates can now be transferred automatically into the extracted business rules repository without affecting the rules that are not impacted by the updates. For rules impacted by the updates, a report is generated that highlights the changes. IT teams can now also update business policies and modernize applications concurrently via the repository that also keeps track of documentation such as diagrams, logic, database details and critical dependencies, said Marfatia.

    In addition to presenting logic in multiple formats, including pseudo-code, flowcharts, decision tables and business analyst language, it enables consolidation and optimization actions to be reverted to their original state if required.

    In general, IT teams have been struggling with application modernization efforts that require them to either lift and shift a monolithic application running in an on-premises IT environment into the cloud or refactor it into a set of microservices that run natively in the cloud. Eventually, most organizations will refactor monolithic applications, so the debate becomes to what degree to undertake those efforts before lifting and shifting an application into the cloud. Most monolithic applications were not designed to run in the cloud, so when the app is shifted it’s not uncommon for any number of performance issues to be encountered.

    EvolveWare claims that its Intellisys platform reduces the cost of application modernization by as much as 60% by eliminating much of the manual effort that would otherwise be required. Modernization efforts, in general, are hindered by manual processes that should be automated, said Marfatia.

    The issue that most DevOps teams encounter when modernizing an application is that it is not a task they regularly perform. As such, many of the processes required have not been automated with the same level of zeal they’ve applied to more routine manual tasks. The Intellisys platform is designed to enable IT teams to automate the most common tasks associated with migrating an application to another platform.

    The biggest driver of those migrations these days has been digital business transformation efforts that have accelerated since the start of the COVID-19 pandemic. Organizations of all sizes are moving applications to the cloud to ensure greater availability and resiliency to limit the amount of disruption that might be encountered should the pandemic worsen, or in case some other unexpected event makes accessing IT services difficult.

    The challenge, of course, is moving applications—and the database they depend on—from one platform to another is not easy. It can take some organizations months, sometimes even years, to make the transition. Given the backlog of applications that many organizations are looking to migrate to another platform, it’s clear there is a need for much higher levels of automation to accelerate a transition that, on its present trajectory, might take years to complete.

  • Dynatrace Adds Grail Data Lakehouse to Observability Platform

    Dynatrace Adds Grail Data Lakehouse to Observability Platform

    Dynatrace today announced it has added a data lakehouse, dubbed Grail, to the Dynatrace Software Intelligence Platform to make it simpler to aggregate all the observability data an IT team collects.

    Bob Wambach, vice president of product marketing for Dynatrace, said Grail will initially drive analytics of log data but in time will also be applied to additional types of application development, security and business intelligence data.

    The goal is to streamline processes such as data indexing and rehydration across a unified observability platform that eliminates the need to maintain multiple disparate repositories, he added.

    Grail, at its core, is a causational data lakehouse based on a massively parallel processing (MPP) analytics engine that will initially be made available on the Amazon Web Services (AWS) cloud. IT teams can use the Dynatrace Query Language (DQL) to query data stored in the data lakehouse. Additionally, the Davis artificial intelligence (AI) engine that is already embedded within the Dynatrace Software Intelligence Platform will be able to apply machine learning algorithms to the data stored in Grail.

    Data lakehouses have recently emerged as an approach to enable organizations to apply the structure of a data warehouse platform to massive amounts of data that previously would have been stored in a data lake. In effect, a data lakehouse combines the attributes of both types of platforms for centralizing the management of data. One of the biggest issues with any approach to observability is the massive amount of data that winds up being stored to allow DevOps teams to track issues over time.

    Of course, it’s up to each individual IT team to determine how much data they want to save to drive analytics, but the more data they save the more cloud storage costs will naturally increase. Grail provides a purpose-built means of consolidating data silos in a way that reduces the total cost of observability, noted Wambach.

    In general, because of the need to embed a data lakehouse capability, most observability platforms will be consumed as a software-as-a-service (SaaS) application. That means the number of IT teams that will likely build and maintain their own observability platform will be limited. IT teams are also now struggling to manage increasingly complex IT environments made up of both cloud-native applications built using microservices and legacy monolithic applications. In fact, a global survey of 1,303 CIOs and senior IT practitioners commissioned by Dynatrace found 71% of respondents believed the explosion of data produced by cloud-native technology stacks is beyond the ability of IT staffs to manage without help from an AI platform.

    It’s not clear how quickly IT teams will be migrating from legacy monitoring tools that are designed to track specific metrics to observability platforms that promise to make it easier to identify the root cause of an issue by simplifying the launch of queries against a massive pool of data. However, as organizations continue to become more dependent on software, it’s apparent that the level of tolerance for any kind of disruption is steadily declining; it’s now more a question of when rather than if a different approach to managing IT will be required.

  • Cosmonic Previews Deployment Platform for Distributed Wasm Apps

    Cosmonic Previews Deployment Platform for Distributed Wasm Apps

    Cosmonic has made available a preview of a platform for deploying applications built using the portable WebAssembly (Wasm) binary format that enables applications to be deployed on any platform.

    Cosmonic CEO Liam Randall said the company is providing early access to the Cosmonic Platform Developer Preview platform to enable developers to experiment with a new type of software artifact that will be used to build a new class of cloud-native applications.

    The Cosmonic Platform Developer Preview platform is based on wasmCloud, an open source application runtime that hosts components written as Wasm modules that can then be loosely connected to build applications. Originally developed under the auspices of the World Wide Web Consortium for building browser applications, Wasm is a portable binary instruction format for building software that describes a memory-safe, sandboxed execution environment.

    That approach replaces the current predominant method for building software that relies on the aggregation of software components that tend to lack distinct boundaries. It’s that lack of distinct boundaries that enables malware to flow so easily from one software module to another. The wasmCloud runtime, originally developed by Cosmonic, provides a platform for deploying distributed Wasm applications and is now being advanced under the auspices of the Cloud Native Computing Foundation (CNCF).

    Prior to Wasm, Randall noted, every format for building applications led to the creation of ‘walled gardens’ that resulted in developers being locked into a platform. Wasm is the first software artifact that enables applications to run on an platform, including Linux and Windows, without any modification required, said Randall.

    It may be some time before Wasm becomes the preferred artifact for building applications, but it’s clear the walls that have separated one IT platform from another are about to crumble. Once applications become much more portable, the longstanding goal of writing an application once and then deploying it anywhere may finally be achieved. Just as importantly, those applications will run in a memory-safe sandbox that is more secure than what can be enabled in legacy IT platforms. In fact, as more organizations review the security of their software supply chains, they may decide to accelerate their embrace of Wasm to build more secure applications.

    Naturally, the transition to Wasm will have major implications for DevOps teams, as it represents an opportunity to streamline deployment processes across multiple platforms. In effect, the total cost of application development and deployment would decline as processes spanning multiple platforms become more automated using platforms such as wasmCloud. Ultimately, much of the infrastructure complexity that developers need to navigate today would be eliminated, noted Randall.

    It’s not clear just yet to what degree Wasm will drive a transition to another era of computing, but the potential to change almost every aspect of IT is on the horizon. Ultimately, the issue will be decided by how quickly developers are willing to embrace yet another software artifact for building and deploying applications. What is clear is that the number of platforms that will make it possible to experiment with Wasm are starting to multiply.

  • Business Leaders Will Trade Speed for Security

    Business Leaders Will Trade Speed for Security

    A global survey of 600 C-level executives conducted by CloudBees found that when it comes to building software, more than three-quarters of respondents said it is more important to be secure and compliant than fast and compliant.

    As a result, more than three-quarters (77%) also noted their organization is implementing a shift left strategy for implementing security and compliance even though 58% recognized that those efforts created additional burdens for developers.

    Three-quarters of respondents also conceded that compliance (76%) and security (75%) challenges limited their company’s ability to innovate. Nevertheless, 83% said shift left is important for them as an organization despite the fact that 88% of executives said their software supply chain is secure or very secure. However, only 33% of respondents said their software supply chain is completely compliant.

    Not surprisingly, 86% are focusing on compliance more now than they were two years ago and, in the wake of a series of high-profile breaches of software supply chains, 82% are more concerned about attacks.

    CloudBees CEO Anuj Kapur said it’s clear there is a greater need to reduce security and compliance burdens for developers by putting guardrails in place that automate DevSecOps processes. The survey noted that only 22% of executives believed their software delivery supply chain is completely automated, while another 37% said it is close to being automated. Only 22% said their compliance process is completely automated, with 35% believing it is almost completely automated.

    Three in five (59%) executives said they have all, or mostly all, external tools for security and compliance issues and 29% said they have a mix of internal and external tools. Only 11% use mostly internal tools. A full 90% said their risk management team has the tools, knowledge and expertise to build and/or maintain a secure software supply chain.

    The real challenge, of course, is that while compliance issues are relatively static, new security issues arise all the time. Developers make mistakes or a new zero-day vulnerability is discovered after an application has been deployed in a production environment. It’s critical for organizations to embrace automation to enable developers to address those issues as part of a continuously automated update cycle, noted Kapur.

    As more responsibility for compliance and security is shifted left, the degree to which DevOps workflows will need to be adjusted will naturally vary by organization. However, the days when developers could ignore security issues during the application development process are all but over. The leadership of organizations of all sizes are making it clear they want to see a reduction in the number of security and compliance issues that arise in production environments.

    Ideally, efforts to build more secure and compliant applications would not slow down the rate at which applications are being built and deployed. However, the CloudBees survey made it clear that more executives are willing to prioritize security and compliance over speed of application development. The issue is how to strike a balance between what are clearly two competing priorities.

  • Alleviating Developer Workflow Headaches by Moving to the Cloud

    Alleviating Developer Workflow Headaches by Moving to the Cloud

    Leaders in tech make one common mistake when it comes to serverless and cloud computing: They want to migrate their current environment exactly as it is to the cloud. That’s about as limiting as planning a flight path along the road network and deciding the route based on street-level traffic. You can do it, but everyone’s going to look at you like you’re crazy.

    Keeping that ‘lift and shift’ mindset prevents developers from seeing the real ROI of cloud computing and serverless technology. Instead, we have to challenge our traditional ways of thinking.

    Redefining How we Think About Software Development

    The traditional definition of software is anything that makes the hardware do what we want it to. We use operating systems to control internal functions as well as peripherals. We use application software to direct our computers to execute commands. So we tend to think of software as programmatic, needing specialized programming languages to develop. But the most popular functional programming language isn’t Erlang or Haskell or Lisp. It’s Microsoft Excel, if you can believe it, with over 750 million users.

    Every Excel spreadsheet represents someone’s software; it makes their hardware process data in a way that’s valuable to them. In a similar way, the “systems” we build on the information technology side are just more software. And cloud computing gives us a new range of powerful tools so we can build bigger systems faster than before.

    What are Cloud Computing and Serverless Computing?

    Cloud computing largely references data centers and data storage. Serverless computing is one piece of cloud computing. It lets developers create software without managing infrastructure. In the end, it increases productivity, speeds up product delivery, optimizes resources and keeps developers focused on the end product rather than infrastructure maintenance.

    Once deployed, serverless apps respond to demand, scaling up or down as needed. So when a serverless function sits idle, it costs nothing.

    Key Benefits of Cloud Computing and Serverless Computing

    There are many benefits of cloud computing and serverless frameworks. By far, the one leaders are most excited about is cost control and increased ROI. It’s also one that leaders most often miss.

    Increase ROI With Cloud Computing and Serverless

    The number-one way to increase ROI with serverless frameworks and cloud computing is to avoid building anything from scratch. Invest in open-minded research. Sometimes you need to build something yourself, but often there’s a way to shift some of the burden away from your team. 

    An easy example is functions. The first thing most developers think of when they hear “serverless” is functions. But the functions running code are just a tiny piece of the puzzle. Serverless technology allows development teams to hand off as much work as they can to cloud platforms like Azure, Amazon Web Services (AWS) and Google Cloud Platform (GCP). 

    Just like someone wouldn’t buy a field, till it, plant wheat, water it, thresh the wheat into flour, bake bread and toast it to make a piece of toast, developers shouldn’t write their own code when the building blocks already exist in their cloud platform. Take, for example, Azure’s Durable Functions feature. This feature manages stateful workflows so teams don’t need to explicitly create, store and retrieve the progress through your data’s workflow in some other place. This process is so common to the systems that teams build that the cloud providers made it available without needing us to write lines of code. It’s like instant toast delivered to your door!

    The more a team can leverage already-made code, the more time they get back on their schedules and the more money goes back into the team’s budget, something we can all appreciate!

  • Scaling Predictive Analytics With AIOps to Drive Next-Gen SRE

    Scaling Predictive Analytics With AIOps to Drive Next-Gen SRE

    Enterprise systems are only as valuable as they are reliable, in the sense that they don’t suffer excessive breakdowns. Otherwise, companies experience costly downtime and added stress for engineers due to the additional burden of managing issues. This critical function of ensuring systems run reliably and optimally, at production scale and with minimum human intervention, is the purview of site reliability engineering (SRE) teams.  

    The SRE professional’s job is to reduce human toil by developing and implementing reliable and highly scalable systems that optimize software and applications. Their goal is to proactively identify and, where possible, anticipate potential disruptions to minimize risk and ensure optimal system performance. However, to be successful, SRE teams require a level of enterprise-wide visibility that can be difficult to provide without the right tools to capture and analyze data at the appropriate level of detail. 

    Let’s examine how artificial intelligence for IT operations (AIOps) can support the SRE mission by connecting data enterprise-wide for unprecedented visibility and control of systems and processes, enabling auto resolution of most issues and more efficient triaging for the few remaining cases where SRE teams must collaborate around a fix.

    Challenges of Complexity and Scale in Pursuing SRE Excellence

    As more enterprises digitize their operations and move to greater automation, their IT operations must leverage all data assets skillfully in order to improve reliability and reduce human toil. The SRE profession arose to satisfy this need, with a focus on monitoring systems, accessorizing automated releases, understanding change impacts and automating some of the most common system processes. 

    To do their job effectively, SRE teams need a wide variety of data and analytics capabilities at their disposal. This includes the ability to deep dive into descriptive and diagnostic analytics to look backward and at present conditions to discover what happened in the past and why and to baseline current operations. But this is just the beginning. The true value  of SRE comes with the scaling of predictive and prescriptive analytics to draw on that historic data and apply detailed analysis to generate predictive insights into what is most likely to happen in the future; these insights are the basis for identifying proactive measures that can serve to address any potential problems and optimize those future outcomes, minimizing adverse impacts on operations 

    These analytic capabilities must be fed by robust data that comes from across the entire IT estate. Developers assigned to the SRE role face an especially strong mandate to have this holistic visibility as they plan, build, test, release, monitor and secure systems; their job is hampered to the extent that organizational silos or problems of scale get in the way of achieving that visibility. It is here that AIOps can help evolve IT operations to become more proactive and autonomous by scaling the power and reach of predictive and prescriptive analytics. 

    AIOps Empowers the SRE Mission Enterprise-Wide

    AIOps is an essential tool for the SRE community in the battle to reduce operator stress, configure IT systems to be more stable and run efficiently with less human intervention. AIOps employs artificial intelligence (AI) and machine learning (ML) for observability, context, normal behavior analysis and automated health diagnostics. This, in turn, enables anomaly detection in real-time and closed-loop automatic resolution of most issues. 

    For example, AIOps can uncover patterns showing that, 90% of the time, a particular alert in the organization’s payment system triggers a seemingly unrelated alert within 15 minutes. Moving forward, this gives SRE teams a 15-minute head start on addressing that secondary alert; the discovery forms the basis of an auto-resolution or triaging scenario that uncovers the underlying cause of both alerts and provides a permanent fix. 

    That’s just one illustration of how AIOps uses advanced analytics to discern subtle patterns in data to predict when and where problems may occur, so proactive fixes can automatically be prescribed to head off those problems. In this way, AIOps is the technology backbone that scales and automates the SRE team’s insight and control across all system assets and dependencies, a critical tool for continuous optimization of performance with minimal human intervention. 

    Conclusion: The Game-Changing Role for AIOps in SRE

    AIOps is a game-changer for the critical function of site reliability engineering. Powered by a potent blend of advanced analytics on robust data coming from systems across the enterprise, AIOps delivers unprecedented visibility and control for SRE teams in their mission to reduce toil and ensure the reliability and resiliency of enterprise systems. The result is less human intervention and enhanced value from IT systems that are made more robust, more stable and more efficient.

  • Aligning Cloud Spend Management With Cloud Transformation

    Aligning Cloud Spend Management With Cloud Transformation

    The cloud transformation movement is well underway, with more than half of enterprise organizations moving to a cloud-native approach this year, according to Forrester Research. Spending on cloud infrastructure is rising accordingly – more than $21 billion in Q4 2021, up 13.5% from Q4 2020, according to IDC. The cloud offers economies of scale and connectivity that companies can leverage to optimize operations, make better use of their data and identify opportunities. However, if a company’s cloud infrastructure investment isn’t well planned, they can end up spending more than expected due to unplanned access costs, applications consuming more resources than expected and underperformance caused by inefficient architecture or lack of maintenance.

    Spending governance–creating and managing a budget that supports the company’s cloud goals–also helps to maintain cloud security by ensuring that there are adequate solutions in place to prevent phishing, ransomware and other attacks that can disrupt or disable an organization’s cloud operations. Financial monitoring allows organizations to accurately evaluate the cost-efficiency of the apps in their cloud ecosystem. This can help control costs and avoid situations where different groups add their own apps without first leveraging what’s already available or correctly gauging associated cloud spend. Unchecked app proliferation in the cloud can create a cycle that includes overconsumption of resources and security issues. 

    Cloud governance can address sustainability concerns, too, as executives increasingly focus on reducing their organizations’ carbon footprint. It’s important to benchmark the organization’s on-premises servers’ carbon impact, so you can quantify how moving workloads from on-premises to the cloud impacts sustainability progress. As with spending, cloud sustainability measurement requires adequate planning, execution, organization-wide visibility, effective monitoring, and efficient use of cloud resources. 

    Planning for Effective Cloud Spend Governance

    Spending management processes have always been crucial for business, but governance of cloud initiatives is playing catch-up to technology advances and an accelerated digital transformation. We see many organizations that are relying more heavily on cloud infrastructure because of the speed it offers to deliver new products and experiences through innovation. But without financial controls, there can be an element of inefficiency that affects cloud spending decisions—something that we’ve seen as an increasing issue for companies over the past decade. 

    Whether an organization is preparing for the transition to the cloud or seeking to make existing cloud spending more visible and accountable, the financial governance aspect requires readiness. Assessing this readiness starts with cataloging the tools and expertise available in the organization to build a cloud budget, put monitoring tools in place, setting threshold levels that trigger notifications when spending exceeds certain levels and providing organizational controls to remedy any spending excesses. 

    It’s also helpful to define the goals and potential benefits of implementing better spending controls. First, no one wants to deal with unplanned costs that create budgetary problems and have a negative impact on the business. Second, spending accountability allows you to identify the internal groups that are knowledgeable enough about both cloud operations and spending management to take ownership of their role in the move to the cloud. At the same time, you can also identify the groups that need more training, guidance, and resources to get the most value and beset employee experience from their cloud transformation. Third, proper cloud governance can help companies avoid scenarios where cloud-related issues such as security, budget or over-proliferation of apps in the cloud ecosystem lead to customer experience problems. 

    All these planning requirements are more complex for organizations with an existing or planned multi-cloud environment. Because each cloud provider has its own processes and features, the organization will need to understand–and financially manage–a diverse set of tools and resources to analyze what happens across their cloud network. For example, it’s relatively simple to pull two similar reports from a single-cloud environment and synthesize them to create a summary report. When the reports are coming from two different cloud platforms, there can be format differences that make synthesis more challenging, time-consuming and costly to aggregate that data and present it in a dashboard for leaders. 

    Platform differences also mean that simply comparing previous on-premises spending to proposed cloud spending may not be a good model for accurate cost planning for multi-cloud environments. For all of these reasons as well as technical ones, multi-cloud governance often requires creating a team or task force to collaborate and share knowledge for effective technology and budgetary decision-making. 

    Cloud Spend Governance in Practice

    Like cloud technology and applications, cloud spend governance is a continually evolving practice, not a one-and-done task. That’s because proper financial visibility and management require monitoring to identify any emerging issues in terms of capacity, cost and security. For example, a manufacturer might analyze their cloud usage data and find they’re underutilizing some resources, which enables them to turn those resources off to save costs. 

    Financial governance also allows companies to find opportunities for optimization–something that can be as simple as identifying potential configuration changes that make cloud operations more efficient and secure. In the end, the promise and potential of the cloud for companies depend on smart, properly planned use of cloud resources and spending governance is a critical part of that smart planning.