Author: Mike Vizard

  • Cloud Management Issues Are Coming to a Head

    Cloud Management Issues Are Coming to a Head

    A survey of 1,300 technology and data executives found that more than a decade after the initial rise of cloud computing, organizations are still struggling to manage these environments.

    Conducted by Wakefield Research on behalf of NetApp, the survey found 98% of respondents reported their business has been impacted by everything from the increasing complexity of data and heightened cybersecurity risk to lack of visibility into business operations and staff burnout.

    Top challenges include cybersecurity risk (45%), staff not taking full advantage of business applications (44%), increased skepticism about the cloud from leadership (44%), lack of visibility into business operations (42%), going over budget (37%) and burning out staff (31%).

    A full 88% continue to encounter technical challenges, including data mobility between clouds (33%), security risks (33%) and interoperability between cloud services (30%).

    The top drivers of cloud investments are scaling artificial intelligence (AI) and automation (39%), followed by driving business innovation (35%) and creating digital experiences (34%).

    Organizational challenges encountered include having a clear vision for cloud strategy (32%), establishing the right level of governance (31%) and managing costs (30%). A full 84% are under pressure to show short-term return on investments (ROI) in cloud computing platforms, with 76% noting CFOs and other business leaders are skeptical of savings. Nearly half of the tech executive respondents (49%) reported that when cloud strategy discussions occur, cost concerns come up often or all the time. As a result, nearly three-fourths of executives (74%) said tiered workloads are either very or extremely important, the survey found.

    Other factors impacting multi-cloud strategy include environmental, social and governance (ESG) concerns (79%) and data sovereignty (74%), the survey found.

    Ronen Schwartz, senior vice president and general manager for cloud volumes at NetApp, said as more organizations employ multiple clouds, total costs tend to rise. Each cloud platform requires mastering another control plane, which means someone in the IT organization must have the right skills to manage, he noted. IT leaders are attempting to exercise more control over cloud deployments, but developers, for a variety of reasons, have already deployed workloads across multiple cloud computing environments, added Schwartz. One approach to achieving that goal is to make sure data is stored on the least expensive tiered service possible for any given specific use case, he noted.

    Less clear is whether an uncertain economy might push organizations to consolidate workloads on fewer cloud computing platforms. Even then, the cost of moving a workload is not trivial given the proprietary application programming interfaces (APIs) that many developers have likely invoked as DevOps built and deployed cloud applications.

    Of course, there is no going back; the issue now becomes how to define a set of best practices for managing cloud computing environments in a way that minimizes costs. It turns out that cloud computing can be more costly than an on-premises IT environment simply because the infrastructure resources made available to developers are almost infinite. In the final analysis, however, that can turn out to be too much of a good thing—especially if organizations wind up spending more on IT to support these environments. Many of those environments are not rigorously managed because, for example, developers may not be inclined to spin down a development environment on a Friday because it takes too long to spin it back up the following Monday.

    One way or another, however, a level of long overdue scrutiny of cloud computing costs may be on the horizon.

  • Enfabrica Makes Cloud Networking Performance Advances

    Enfabrica Makes Cloud Networking Performance Advances

    Enfabrica Corp. today emerged from stealth at the MemCon conference to launch a class of processors for networking in cloud computing environments that are optimized for moving data between CPUs, graphical processor units (GPUs), accelerators and memory.

    Enfabrica CEO Rochan Sankar said the Accelerated Compute Fabric (ACF) enables scalable, streaming, multi-terabit-per-second movement of data in a way that also reduces the total cost of cloud networking. That’s critical as the amount of data being generated by applications infused with artificial intelligence (AI) capabilities that require access to larger amounts of data continues to increase, he added.

    At the same time, DevOps workflows will need to evolve as it becomes possible to compose AI fabrics of compute, memory and network resources capable of scaling to tens of thousands of nodes versus relying on top-of-rack network switches, network interface cards (NICs), PCIe switches and CPU-controlled DRAM that creates too many bottlenecks when moving large amounts of data.

    Enfabrica’s first chip, the Accelerated Compute Fabric Switch (ACF-S), supports standards-based interfaces, including multi-port 800 Gigabit Ethernet networking and high-radix PCIe Gen5 and CXL 2.0+ interfaces. The company claims that Enfabrica’s ACF-S is the first data center silicon product in the industry to deliver headless memory scaling to any accelerator by incorporating CXK memory bridging to enable a single GPU rack to have direct, low-latency, uncontended access to local DDR5 DRAM at more than 50 times greater capacity than GPU-native High-Bandwidth Memory (HBM). That approach should enable customers to cut their cost of GPU compute by an estimated 50% for large language model (LLM) inferencing and 75% for deep learning recommendation model (DLRM) inferencing, the company claimed.

    Simulation tests suggested ACF-enabled systems could achieve the same target inference performance using only half the number of GPUs and CPU hosts compared to the latest GPU servers.

    The cost of building AI applications today is prohibitive for many organizations, but as processor advances are made, there may come a time when the cost of building and training AI models substantially decreases. Advances in networking processor technologies will, as a result, accelerate the pace at which network operations are integrated into programmable DevOps workflows versus relying on dedicated networking teams to manage top-of-rack switches.

    It’s not clear yet whether cloud service providers will embrace ACF, but the chip makes it clear there is a significant opportunity to reduce the amount of networking infrastructure needed to build and deploy AI applications.

    Less clear, of course, is to what degree machine learning operations (MLOps) might ultimately be folded into DevOps workflows. While developers of AI models create a unique type of software artifact, they still need to be integrated with application code running in a production environment via application programming interfaces (APIs). One way or another, the total cost of building and deploying applications infused with AI models will need to decline.

    In the meantime, the networking bottlenecks that conspire to make deploying distributed computing applications difficult today may soon become overcome as latency issues are increasingly overcome.

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    LinkedIn

    M-Logic
    Dallas, Texas/Chicago, Illinois
    Security Engineering – DevOps
    $150,000 to $160,000

    SimplyHired

    Cisco Systems
    Waltham, Massachusetts
    DevOps Engineer
    $134,200 to $197,700

    Indeed.com

    AT&T
    McLean, Virginia
    DevOps/Python Specialist
    $111,000 to $140,000

    Monster.com

    Capgemini FS
    Charlotte, North Carolina
    AEM Full Stack Developer
    $110,000 to $130,000

    Dice.com

    Booz Allen Hamilton
    McLean, Virginia
    Lead DevOps Engineer
    $99,300 to $212,000

  • Tabnine Extends Generative AI Alliance With Google

    Tabnine Extends Generative AI Alliance With Google

    Tabnine has extended its alliance with Google Cloud to advance the adoption of generative artificial intelligence (AI) to automate the writing and testing of code.

    The generative AI platform provider has already developed its own large language model that is hosted on Google Cloud. Tabnine is now also committing to leveraging the large language model that Google is developing to automate software development life cycle processes.

    Brandon Jung, vice president of ecosystems for Tabnine, said it’s apparent that application development and deployment teams will be making use of multiple large language models across SDLC workflows. Not all those large language models will be developed by one single platform provider, he noted.

    Rather than being dogmatic about large language models, Tabnine plans to make it possible to invoke multiple models via application programming interfaces (APIs) that are integrated with development environments, he added.

    The Tabnine platform supports multiple programming languages, including Python, Java and JavaScript and is designed to be integrated with integrated development environments (IDEs) such as Visual Studio Code and Jetbrains. The company also previously integrated its code completion tool with the GitLab continuous integration/continuous delivery (CI/CD) platform. The overall goal is to make it easier for developers to automatically write code based on custom models using approved source code hosted in a secure private repository.

    Generative AI creates a large language model that assesses the probability of what the next line of code will be based on what has preceded it. It’s not likely DevOps teams will be replaced as generative AI is extended across workflows, but the overall size of those teams might shrink as it becomes possible to do more with fewer people. At the same time, the barrier to DevOps adoption will also fall as AI platforms make it simpler for more organizations to embrace DevOps best practices.

    The challenge will be making sure the data collected to train AI models is of a high enough quality to ensure the desired outcome. Organizations will need to find a way to apply generative AI to data models that have been validated by DevOps teams.

    One way or another, it’s only a matter of time before generative AI capabilities are applied more broadly. Platforms such as OpenAI’s ChatGPT are only the tip of an iceberg that impacts almost every manual process, including software development and deployment. The issue will be determining how quickly those innovations will become practical enough to employ.

    In the meantime, it is already apparent generative AI platforms are having a significant impact on the rate at which code can be developed. Inevitably, that means the amount of code moving through DevOps pipelines at any one time should increase significantly. DevOps teams should expect generative AI technologies to be applied both before and after application code is built and deployed, noted Jung.

    In the meantime, the biggest issue is, arguably, keeping up with a rate of generative AI innovation that is occurring faster than many organizations can absorb.

  • Survey Surfaces Application Modernization Challenges

    Survey Surfaces Application Modernization Challenges

    A survey of senior IT leaders suggested the level of confidence in application modernization projects that many organizations initially had is now starting to wane.

    The survey polled 200 senior IT leaders at organizations with more 1,000 employees and was conducted by Global Surveyz Research on behalf of EvolveWare, a provider of platform for automating application modernization processes. The survey found 70% of respondents reported they were confident or very confident in their understanding of their applications when they prepared for modernization. However, that level of confidence dropped to 41% at the planning stage and even lower (28%) at the point the project began, the survey found.

    More than half of respondents (51%) are already experiencing or anticipating critical issues that need to be addressed immediately, the survey found. The top areas of importance are understanding the parts of the code that contain business policies (47%), database access details (43%) and understanding the complexity (40%).

    EvolveWare CEO Miten Marfatia said the survey makes it clear organizations are encountering issues associated with capturing tribal knowledge that has been lost mainly because the teams that initially built an application are no longer with an organization. In fact, the survey found a full 81% of respondents reported they currently have or anticipate challenges hiring or retaining talent to support legacy applications. Nearly half (46%) currently don’t have enough talent available to manage legacy applications.

    The survey found the primary reason these initiatives are launched is to boost employee productivity (40%), followed by retiring mainframe infrastructure (37%), reducing the dependency on legacy code (36%), reducing maintenance costs (30%), improving customer experience (29%) and cloud migration (22%). Most of these projects are generally focused on critical applications (55%) as well as applications that have few or no dependencies (55%), the survey finds.

    The primary success metrics for assessing these projects, however, are improving customer experience (46%), the readiness to migrate to the cloud (46%) and meeting the performance requirements of the modernized application (45%).

    Less than a third of respondents (31%), however, reported having access to modern tooling. More than half would like to automate code transformation and business rules extraction (BRE) while 40% would like to automate documentation.

    Nearly two-thirds (64%) said freezing code during the modernization process would have significant business and financial consequences, with 59% noting that finding a way to modernize applications without freezing code is at the top of their technology wish list.

    Application modernization efforts usually have multiple goals. IT teams are usually motivated by a desire to reduce the amount of time and effort required to support legacy applications that are generally less efficient than modern applications. In addition, many IT teams are also looking for ways to reduce the total cost of running those applications, especially during uncertain economic times. Business leaders, meanwhile, are funding digital business transformation initiatives that typically require some level of modernization of legacy applications.

    Regardless of motivation, it’s apparent many IT teams initially underestimate the amount of effort required to achieve those goals.

  • Dylibso Releases Tool for Tracking and Validating Wasm Modules

    Dylibso Releases Tool for Tracking and Validating Wasm Modules

    Dylibso today made generally available a system of record for tracking, investigating, searching and validating modules built using the WebAssembly (Wasm) binary instruction format.

    Fresh from raising $6.6 million in additional funding, Dylibso CEO Steve Manuel said Modsurfer exposes the internal contents to enable developers to debug Wasm modules and ensure compatibility with runtime environments.

    Modsurfer provides development teams with a console for accessing a fully auditable database of modules indexed for search and debugging. In addition, development teams have the ability to extract critical information from binary formats in a way that can be integrated with DevOps pipelines. In effect, Modsurfer provides application development teams with X-ray vision into previously opaque Wasm modules, said Manuel.

    Dylibso previously developed Extism, an open source universal plug-in system that supports multiple programming languages used to build Wasm modules. That reduces the level of effort required to integrate Wasm modules and provided the foundation upon which Modsurfer was created, noted Manuel.

    Wasm, at its core, is a portable binary instruction format for building software that describes a memory-safe, sandboxed execution environment. The World Wide Web Consortium (W3C) drove the development of Wasm as part of an effort to create a common format for browsers executing JavaScript code. Wasm is now being extended beyond browsers and JavaScript to enable developers to create a set of universal binaries that could work on any platform without modification.

    That approach replaces the current predominant method for building software that relies on the aggregation of software components that tend to lack distinct boundaries between them. One of the issues of that approach is that it becomes relatively simple for malware to infect all the components of an application.

    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 finally starting 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. That’s not only critical in terms of overall application developer productivity; it also has major implications in terms of streamlining the management of DevOps workflows as it becomes easier to both initially deploy applications and continuously update them.

    As organizations continue to review their application development practices to better secure software supply chains, it’s also become apparent that legacy approaches to building applications are fundamentally flawed. Rather than attempting to reengineer processes to encourage developers to better secure applications, it may be more effective to change the way applications are built. After all, considering all the processes required to secure legacy development approaches, it may be cheaper and easier to adopt a new method for building applications that lowers overall risk, said Manuel.

    Of course, the amount of Wasm expertise that exists in the developer community is still limited. However, DevOps teams should expect to see more Wasm modules moving through DevOps pipelines as Wasm tooling continues to improve.

  • Postman Releases Tool for Building Apps Using APIs

    Postman Releases Tool for Building Apps Using APIs

    Postman today made generally available a visual tool infused with artificial intelligence (AI) that makes it simpler to build software by invoking application programming interfaces (APIs) found on its network.

    Shamasis Bhattacharya, chief software architect for Postman API, said Postman Flows makes it possible to use a low-code tool to build software using tens of thousands of APIs that can be found on the Postman API network.

    The goal is to reduce the amount of toil required to build applications of moderate to medium complexity in a way that doesn’t require developers to have deep programming expertise, he added.

    Instead, developers are presented with “blocks” that they can drag and drop to create an application and deploy the associated workflows. Postman Flows leverages AI to manipulate data returned by APIs using a natural language interface that reduces the level of technical acumen required to create those workflows.

    That approach provides developers with a reactive experience that is embedded within a visual tool, noted Bhattacharya.

    Many developers still have a natural bias toward writing code, but as demand for applications continues to increase, Postman Flows provides a means to significantly increase developer productivity, said Bhattacharya. There may still be instances where writing code is required, but as developers save more time using Postman Flows, many of them will switch over to a visual tool to build software faster by essentially gluing blocks together, he added.

    There’s naturally a lot of focus these days on developer productivity during uncertain economic times. More organizations than ever are dependent on software, but their ability to hire armies of developers is limited. Low-code tools have emerged to provide a means for accelerating application development, but Postman is now looking to apply that concept directly to the network of curated APIs that it provides to application developers.

    The one thing that is certain is that as the pace at which applications are being built increases, the number of them running in production environments will steadily increase. DevOps teams will find themselves maintaining a wide range of applications that were constructed using both procedural code and low-code platforms.

    In the meantime, IT organizations may want to start evaluating which types of applications lend themselves to being built by development teams that may not require as much experience writing actual code. Much of the application development backlog organizations are struggling with today could be reduced using tools that automate a wide range of development tasks. That should free up developers with more advanced skills to work on more complex applications. That approach might also reduce developer turnover as much of the fatigue associated with building more routine applications is reduced.

    Regardless of how applications are built, there will be a need to manage them in production environments. DevOps teams may soon be able to focus more of their time and expertise on optimizing application performance in production environments versus continuing to shepherd massive amounts of code through continuous integration/continuous delivery (CI/CD) pipelines.

  • HPE to Acquire OpsRamp to Gain AIOps Platform

    HPE to Acquire OpsRamp to Gain AIOps Platform

    Hewlett-Packard Enterprise (HPE) this week revealed it is acquiring OpsRamp to gain access to a platform for embedding artificial intelligence in IT operations (AIOps).

    Latha Vishnubhotla, chief platform officer in the office of the CTO for HPE, said the company would embed the machine learning technology developed by OpsRamp across its entire portfolio in addition to leveraging it to automate IT processes the company manages via its GreenLake service for HPE customers.

    Ultimately, HPE will be applying machine learning across the entire IT stack, including applications, to reduce the total cost of IT, she said.

    The acquisition of OpsRamp is expected to close in the third quarter of this year. Terms of the deal were not announced, but it comes at a time when more organizations are getting comfortable with AIOps.

    A recent OpsRamp survey polled 138 IT leaders working for enterprise IT organizations and 127 representing managed service providers (MSPs) that generate at least $25 million in revenue and have more than 500 employees. The survey found the primary reason organizations are embracing AIOps is to improve service and application availability and performance (60%), followed closely by automation of operations (58%) and processes (54%).

    The survey found that the greatest IT operations challenge for enterprises in 2023 was automating as many operations as possible (66%), followed by driving greater efficiency and productivity of IT operations teams and processes (61%). Application-to-infrastructure dependency mapping is the top incident management challenge (64%), the survey found.

    The primary operational benefit cited was reducing open incident tickets (65%), followed by reducing mean-time-to-discovery (MTTD) and mean-time-to-remediation (MTTR), tied at 56%, and automation of tedious tasks (52%).

    In general, organizations are choosing one of two AIOps paths, said Vishnubhotla. Some are waiting to evaluate the recommendations made by the AIOps platform before implementing, while others are looking to completely automate processes so they can focus more of their time and effort on application development and deployment, she said. In much the same way a driver of an autonomous vehicle learns to trust the AI over time, there is a similar transition occurring with AIOps, noted Vishnubhotla.

    The challenge is that it takes an AIOps platform a few months to learn an IT environment. The more dynamic that IT environment is, the longer that process can take. At the very least, however, AIOps platforms have the ability to automate many low-level IT tasks today that conspire to increase the amount of toil DevOps teams would otherwise encounter.

    It’s difficult to determine how pervasive AIOps may be within IT environments, but there is no doubt as organizations look for ways to manage IT at scale, there will be increased reliance on automation. Most organizations can’t afford to continue to hire armies of IT personnel, especially as the global economic outlook remains uncertain.

    In fact, one of the benefits of an AIOps platform is that, unlike an employee, it does not take any days off or suddenly decide to take another job. It also, for better or worse, doesn’t forget anything once it’s been learned. As such, it’s now only a question the degree to which AIOps platforms will be trusted over time to manage increasingly more complicated IT tasks.

  • Oracle Makes Java 20 Platform Generally Available

    Oracle Makes Java 20 Platform Generally Available

    At an Oracle DevLive Level Up event, Oracle today announced the availability of a Java 20 update that makes a range of innovations more accessible to application development teams.

    Georges Saab, senior vice president of development for the Java Platform and chair of the OpenJDK Governing Board for Oracle, said the latest version of the venerable programming language builds on previous extensions made to the Java development kit (JDK) that exemplify how the pace of Java innovation is now increasing.

    Specifically, seven JDK Enhancement Proposals (JEPs) are now supported in Java 20, including OpenJDK project Amber for record patterns and pattern matching for switch expressions and statements; enhancements from OpenJDK Project Panama to interconnect Java Virtual Machines (JVMs), features related to Project Loom that streamline the process of writing, maintaining and observing high-throughput, concurrent applications and a Function & Memory application programming interface (API) and Vector API.

    Oracle also revealed Java 20 is supported by Java Management Service, an Oracle Cloud Infrastructure (OCI) native service that provides a single pane of glass to help organizations manage Java runtimes and applications on-premises or on any cloud.

    Finally, Oracle is making available an Oracle Java Universal SE Subscription that provides access to a pay-as-you-go offering that includes entitlement to GraalVM Enterprise, the Java SE Subscription Enterprise Performance Pack, access to the advanced features of the Java Management Service and the flexibility to upgrade at any pace an organization prefers.

    Oracle Java Standard Edition (SE), GraalVM Enterprise and the Java SE Subscription Enterprise Performance Pack are also now available free of charge on OCI.

    Despite the number of programming language alternatives that exist, many enterprise IT organizations remain committed to Java. Rather than opting to retrain developers, it’s simply been more cost-effective to enable developers to continue to build applications using a programming language they already know.

    Java itself, meanwhile, has been experiencing a renaissance after more organizations began contributing to projects once the core platform became available under an open source OpenJDK license. In fact, the Java community is now adopting many concepts pioneered in other programming languages to enable organizations to, for example, drive digital business transformation initiatives that are dependent on legacy applications that are being modernized. As part of those efforts, the rate at which Java applications are being deployed in the cloud has substantially increased.

    As part of those efforts, many organizations are currently in the process of shifting to Java 17. It’s not clear how many organizations will skip Java 17 and jump to Java 20 from previous versions of Java, but DevOps teams should expect to be supporting a wide range of versions of Java for years to come.

    In fact, most organizations will deploy Java applications everywhere from the network edge to the cloud. The one thing all these applications will have in common is they will be written in a programming language that has persevered through two decades and appears to have enough staying power to stick around well into the next.

  • Awareness of Software Supply Chain Security Issues Improves

    Awareness of Software Supply Chain Security Issues Improves

    A global survey of 167 software professionals suggested that, while there is a lot more awareness of application security issues, the adoption of DevSecOps best practices is still not pervasive.

    The survey, conducted by Chainguard, the Eclipse Foundation, the Rust Foundation and the Open Source Security Foundation (OpenSSF), found that just over half (51%) of respondents are either concerned or are extremely concerned about software supply chain security.

    In addition, only a third of respondents (33%) reported they are familiar with the Supply-chain Levels for Software Artifacts (SLSA) framework for building more secure applications. Well over a third (36%), however, said they had never heard of it.

    Only a quarter of respondents (25%) reported that their team always signed built artifacts, the survey found.

    The survey identified the most challenging issues developers are encountering and found they are reproducing builds (64%) followed by creating hermetic builds that are isolated from other software libraries (62%).

    Mikaël Barbero, head of cybersecurity for the Eclipse Foundation, said while awareness of software supply chain issues is higher, it’s apparent that other priorities are still getting in the way of adoption of DevSecOps best practices. For example, software bills of materials (SBOMs) may generate a lot of headlines, but their adoption remains mixed, he added.

    John Speed Meyers, a security data scientist for Chainguard, noted that incentives still need to change; too many managers that hire developers still emphasize performance and delivery times over application security. Many developers, as a result, still tend to view cybersecurity as an obstacle to be overcome or worked around rather than a core capability that they will be graded on, he added.

    In theory, as responsibility for application security shifts left toward developers, overall cybersecurity will improve. Most developers, however, have little to no cybersecurity training, so the odds they will be able to resolve these issues are low. Instead, many organizations are either trying to embed cybersecurity professionals within DevOps workflows or, at the very least, deputize at least one developer to advocate for cybersecurity within those teams.

    Regardless of commitment level, it’s apparent that organizations need to address everything from locking down developer environments to thwart phishing attacks to ensuring application builds are not inadvertently infected with malware. The challenge organizations face is both technical and cultural, so the amount of effort required should not be underestimated.

    In the meantime, organizations should expect to see cybercriminals increase their attempts to compromise software supply chains. Infecting malware into software components that will be used by multiple downstream applications is, from their perspective, one of the most efficient means of wreaking havoc. Right now, organizations make it too easy for cybercriminals to compromise application environments.

    Organizations should also recognize that tolerance for insecure applications is also declining, as evidenced by the National Cybersecurity Strategy put forward by the Biden administration. It’s not so much a question of whether organizations that create software will be held liable for application security issues as much as it is to what degree.