Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.
This week: Translating legacy COBOL code to a slightly more modern language, and Arm will go public (again) next month. (more…)
At its VMware Explore 2023 conference today, VMware previewed what will become a suite of intelligent assistants that use generative artificial intelligence (AI) to automate the management of a wide range of IT tasks.
Krish Prasad, senior vice president and general manager for cloud infrastructure at VMware, said VMware will eventually build out assistants for managing individual platforms such as VMware vSphere and the integrated VMware Cloud Foundation (VCF) platform through which the company aggregates those offerings into a single platform.
VMware is creating those assistants, also known as co-pilots, using multiple large language models (LLMs) that the company uses to train AI models using code written by site reliability engineers (SREs), said Prasad. That approach ensures that the recommendations being made along with the code generated are of the highest quality, he added.
That approach will enable IT teams to identify configuration drift that might be adversely impacting performance or that could create a cybersecurity risk, for example, noted Prasad. The first of those assistants is being made available in beta for VMware Tanzu, a platform based on Kubernetes. VMware is also building an assistant for its NSX virtual networking software that analyzes security events to generate policies and rules that can be applied to firewalls in real-time as threats are identified.
It will then be up to each IT team to decide whether to implement those recommendations. Over time, it’s clear that the management of IT infrastructure is going to become increasingly automated as confidence in those recommendations increases, he added. In fact, the ultimate goal is to fulfill the promise of ‘lights-out’ IT management, said Prasad.
In effect, advances such as these will lead to the democratization of DevOps workflows as it becomes simpler to manage IT infrastructure at scale. IT organizations will be able to invest more resources in building and deploying applications rather than hiring specialists to manage IT infrastructure, noted Prasad.
In fact, the pace at which applications are built and deployed should dramatically increase in the months ahead, Prasad predicted.
The rise of generative AI creates a unique opportunity for IT teams to become more relevant than ever to their organizations. It will soon be possible to build and deploy a wide range of distributed applications capable of processing and analyzing data at the point where it is created and consumed.
While generative artificial intelligence (AI) has captured the popular imagination, it’s becoming apparent that multiple forms of AI will soon be used together to automate DevOps workflows at levels of unprecedented scale.
Machine learning algorithms, of course, are already used by many organizations to automate everything from analyzing log data to identifying security issues to surfacing patterns in tests made using multiple regression, function and unit testing tools. With the rise of generative AI, it is now possible to automatically generate code and create summaries of reports that multiple stakeholders can more easily understand. Generative AI doesn’t replace the need for previous use cases involving machine learning algorithms. Instead, generative AI makes use of a form of deep learning algorithms to create different types of AI models.
As a result, DevOps workflows will soon be invoking multiple classes of AI models to automate workflows in ways that should enable IT teams to automate processes at unprecedented levels of scale.
SmartBear announced today it plans to acquire Stoplight, a provider of tools for editing and governing application programming interfaces (APIs).
Sean Butler, vice president of product management for SmartBear, said the deal, once finalized, will add a set of complementary tools and open source software that extends the core API catalog platform that SmartBear provides to manage APIs. The open source software provided by Stoplight includes Prism, an HTTP mock server that emulates API behavior; Spectral, an API style guide enforcer and linter; and Elements, an API Documentation tool.
The governance capabilities are especially critical as organizations begin to deploy hundreds, even thousands, of APIs that are used to integrate the microservices that are at the core of modern cloud-native applications, noted Butler.
As those applications are deployed, the management of APIs is naturally becoming more challenging. Organizations, for example, might have a different set of rules for APIs that are externally facing than they do for internal APIs. However, it’s not uncommon for internal APIs to be made externally facing without updating them when a new use case is discovered.
SmartBear is advocating a “design first” approach to the building of APIs that ultimately serves to make them simpler to manage, said Butler. In fact, good governance provides the foundation upon which API security can be achieved and maintained at a time when the number of cyberattacks seeking to exfiltrate data via API endpoints is starting to increase, noted Butler.
Unfortunately, too many developers are still prone to building and deploying rogue APIs, many of which turn into zombie APIs that developers forget to remove long after the function they were designed to enable is no longer required.
It’s not clear how many organizations are adopting a design-first approach to building APIs before they write application code, but as more APIs are deployed, the way IT is managed is rapidly changing. Application services are essentially becoming more disposable, so long as the APIs used to expose them to other applications remain stable. In fact, it’s now only a matter of time before most organizations fully appreciate the degree to which their entire IT strategy now revolves around their APIs.
The challenge is that it’s not always clear who within an IT organization is responsible for API management. Although an API is created by a developer, that developer eventually moves on to other projects. Therefore, responsibility for managing and updating APIs often winds up shifting to DevOps teams that were not part of the API development process.
One way or another, the management of APIs will need to improve once legislation that holds organizations more accountable for how data is managed becomes law. The issue that many organizations will soon discover as they move to address those requirements is: A general lack of visibility into both the number of APIs they have and, just as importantly, how they are being employed.
Hopefully, advances in artificial intelligence (AI) will one day soon make it simpler to manage APIs. In the meantime, however, a modicum of governance applied today should go a long way to preventing a problem that otherwise is all but inevitable.
At its VMware Explore 2023 event, VMware today unveiled an orchestration tool, dubbed VMware Edge, that promises to simplify the management of edge computing services at scale.
At the same time, VMware has launched a Project Keswick initiative through which it will work with customers to define additional use cases for VMware Edge based on zero-trust principles and GitOps workflows for deploying applications. The company also unveiled a VMware Retail Edge platform based on VMware Edge and is planning to add additional offerings aimed at specific vertical industry segments.
Finally, VMware is making available a managed connectivity service through which it will provide private 4G/5G wireless services.
VMware Edge Cloud Orchestrator is based on a tool that VMware created to orchestrate the management of its secure access service edge (SASE) platform. That has now been extended to support a wider range of software running on edge computing platforms.
Sanjay Uppal, senior vice president and general manager of service provider and edge for VMware, said the goal is to streamline the management of software-defined edge computing platforms via a single console. Achieving that goal requires the ability to identify and programmatically manage workloads distributed across a mix of networks, he added.
VMware is betting that as more workloads are distributed to edge computing platforms, there will be a greater need to centralize the management of workloads running on platforms that are not always easy to physically access. Less clear, however, is to what degree those edge computing platforms will be managed by IT teams versus operational technology (OT) teams that are usually embedded within a department that manages a specific business process.
However, regardless of who manages those platforms, they will be relying more on GitOps workflows to programmatically provision infrastructure and deploy applications that will need to be regularly updated. In fact, because these platforms are often dispersed across hundreds of physical locations, the need for a pull-based orchestration tool that works asynchronously is critical, said Uppal.
In the longer term, IT teams should also expect artificial intelligence (AI) capabilities to be applied in a way that makes edge computing self-healing, he added.
No one can say exactly how many organizations have adopted GitOps to manage the provisioning of both infrastructure and the delivery of applications, but it’s conceivable that edge computing will force the issue. The tricky part will be finding a way to manage those GitOps workflows at the necessary level of scale. Most DevOps teams already struggle with implementing DevOps workflows at scale, so if more workloads are to be distributed across hundreds of edge computing platforms, there will be a much more acute need for automation to consistently deploy, secure and update applications.
Regardless of approach, however, there may come a day when the number of workloads deployed at the edge far outnumbers the number of workloads deployed in the cloud or in a data center. The challenge and the opportunity now is to get ahead of edge computing issues before they inevitably create a set of management issues that will be more difficult to address after applications have already been deployed.
VMware today integrated its console for managing cloud instances with its VMware Cloud Foundation to streamline the deployment of its software in on-premises IT environments.
Announced at the VMware Explore 2023 conference, the latest edition of VMware Cloud will make it simpler to manage multi-cloud computing environments by combining VMware Cloud Foundation Software and VMware Cloud Services into a single platform.
VMware also announced early access to an ESXi life cycle management cloud service for VMware vSphere+ that enables IT teams to centrally manage upgrades across a distributed vCenter environment. Additional updates to vSphere in the upcoming release include doubling GPU capacity per virtual machine.
Krish Prasad, senior vice president and general manager for cloud infrastructure at VMware, said the goal is to improve the overall pace of innovation; in addition to deploying workloads in on-premises IT environments, organizations are also deploying workloads on multiple cloud computing services.
VMware Cloud is being made available in five editions that can either be managed by an internal IT team, an external services provider or by VMware. In addition, a VMware Ransomware Recovery service based on VMware Cloud is also generally available. Following a breach of an on-premises IT environment, VMware Ransomware Recovery will enable organizations to run production workloads in the cloud until forensics are completed. The company also unveiled a technology preview of cybersecure storage that will integrate recovery workflows with native vSAN snapshots and add support for Google Cloud VMware Engine.
In addition, VMware is adding a managed NSX service delivered via the cloud, dubbed NSX+, that manages instances of the virtual networking software that runs on top of its virtual machine software. There is also now an NSX+ virtual private clouds (VPCs) option that isolates instances of the virtual networking platform.
Finally, VMware is adding a VMware Cloud with VMware vSAN Max, which will make 8.6 petabytes of disaggregated capacity and 3.6 million IOPS per cluster available on demand later this year.
VMware appears to be streamlining the number of platforms IT teams need to acquire to support and manage IT infrastructure at a time when more organizations are trying to navigate increasing economic headwinds.
One way or another, IT teams will need to reduce the cost of IT at a time when IT environments are becoming more complex. VMware is betting that, given its dominance in on-premises IT environments, there will be a natural inclination to deploy more of its software in the cloud to create a more homogenous IT environment that is less complex.
However, it’s not clear whether organizations are willing to pay extra for the privilege. Many organizations are now supporting multiple classes of virtual machines and associated software despite the fact that each additional platform raises the total cost of IT.
In the meantime, many IT organizations are also awaiting the outcome of Broadcom’s effort to acquire VMware before deciding how to centralize the management of multi-cloud computing environments.
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:
Dice.com
FICO
New York, New York
Senior Director of DevOps Enablement
$140,000 to $220,000
Indeed.com
Cisco Systems
Research Triangle Park, North Carolina
DevOps Engineer
$139,000 to $176,000
SimplyHired.com
Candid Health
San Francisco, California
DevOps/Infrastructure Engineer
$121,000 to $154,000
CareerBuilder.com
CACI
Springfield, Virginia
DevOps/Cloud Engineer
$110,000 to $180,000
Cox Communications
Atlanta, Georgia
Lead DevOps Engineer
$105,700 to $176,100
A segment of the community that has embraced open source Terraform software, originally developed by HashiCorp to provision infrastructure as code (IaC), has published a manifesto calling on the company to reverse recent changes made to licenses that determine how the software can be used.
If that demand is not met, the group plans to launch its own fork dubbed OpenTF under the terms of the previous license that governed the usage of Terraform.
Pawel Hytry, CEO of Spacelift, a provider of a platform for orchestrating the management of multiple IaC tools, said the issue comes down to restrictions that Hashicorp has put in place restricting use within platforms that have embedded it, in addition to limitations on how Terraform can be used in production environments.
HashiCorp is shifting from a Mozilla Public License v2.0 (MPL 2.0) to a Business Source License (BSL) v1.1 in all future releases of its software including Terraform, Vault, Consul, Boundary, Nomad, Waypoint, Packer and Vagrant, as part of an effort to maintain maximum control over its intellectual property.
This shift will have a chilling effect on Terraform innovation because fewer individuals and organizations will want to contribute to advancing the tool, said Hytry.
However, Hytry added, historically HashiCorp has not been perceived as not being overly receptive to contributions from external developers, so the bulk of the code used to create Terraform has come from developers working for HashiCorp.
It’s not clear to what degree this firestorm impacts DevOps teams, but the fragmentation of open source projects stemming from issues that come down to revenue streams is increasing as it becomes more difficult for vendors that create open source software to continue to increase the number of subscription services for the support they provide. Red Hat, for example, recently decided to no longer make the source code for the Red Hat Enterprise Linux (RHEL) edition of its operating system available. The decision led to Oracle, SUSE and CIQ pooling their resources to create a fork of RHEL that they promise will be compatible with future updates to RHEL.
It remains to be seen how many vendors might throw their weight behind OpenTF. HashiCorp, in addition to having partners that built the business on the open source edition of Terraform, also has plenty of rivals that offer IaC tools.
It may be a while before this conflict is resolved, but for now, the situation remains fluid, said Hytry. DevOps teams that make extensive use of Terraform will need to monitor events to make sure any future usage of Terraform complies with BSL terms that supporters of the manifesto claim are at this point too vague.
In the meantime, organizations that rely on open source software should brace themselves for any abrupt changes to licensing terms that may be forthcoming in more challenging economic times. In fact, one of the hidden costs of using open source software is the different terms and conditions under which it is licensed. Resources to monitor each additional instance of open source software for compliance, with terms and conditions that are not always as simple or clear cut, need to be dedicated to a task that doesn’t make any meaningful contribution to return on investment.
The Sysdig Threat Research Team (TRT) has uncovered this week that cyberattacks using binaries written in Go and .NET compromise instances of the on-premises editions of the GitLab continuous integration/continuous delivery (CI/CD) platform.
Michael Clark, director of threat research for Sysdig, said most attacks against software supply chains employ scripts. Cybercriminals that appear to be based in Russia are using binaries to launch proxyjacking and cryptomining campaigns utilizing infrastructure resources used to host instances of GitLab.
Cryptomining is the process used to validate cryptocurrency transactions. Proxyjacking involves reselling bandwidth to providers of proxyware services to allow someone to hide their physical location.
The Sysdig research effort, dubbed LABRAT, also noted that the tactics and techniques used to launch attacks are reasonably sophisticated. In addition to using binaries, the cybercriminals also employ tools with undetected signatures, cross-platform malware designed to evade cybersecurity platforms, a command and control (C2) platform that bypasses firewalls and kernel-based rootkits to hide their presence. Furthermore, the attackers abused a legitimate service, TryCloudFlare, to obfuscate their C2 network.
The attacker, still active, is also continuously updating their tools, which requires organizations running GitLab to track the tactics, techniques and procedures (TTP) being employed by the cyberattacker to keep their indicators of compromise (IoCs) list updated.
Relative to the illicit revenue that might be gained from cryptojacking and proxyjacking, this cyberattack is noteworthy in its sophistication. What is less clear is the degree to which this attack might also be used to inject vulnerabilities into the software supply chains based on the GitLab platform.
The one certain thing is that cybercriminals have developed more advanced capabilities for compromising software supply chains that are likely to be used to compromise multiple DevOps platforms.
Fortunately, there’s a lot more focus on securing software supply chains in the wake of a series of high-profile breaches. The challenge is most efforts are still relatively nascent. As such, there isn’t a high enough appreciation for the lengths cybercriminals might go to compromise a software supply chain. The ability to inject malware that might one day find its way into any number of downstream applications makes a software supply chain a tempting target.
Multiple legislative initiatives have been launched that eventually will require organizations to better secure software supply chains. As such, most DevOps teams would be well-advised to begin those efforts now. Some aspects of the proposals being debated today eventually will become law. Rather than trying to comply with a requirement, a more methodical approach to ensuring the security of software supply chains would create less stress for all concerned later.
In the meantime, thanks to the adoption of DevSecOps best practices application security continues to steadily improve. The issue stands that those advances are not being made as quickly as cybercriminals are evolving new tactics and techniques.
Zenhub this week made available an edition of its project management platform for software engineering teams that makes use of generative artificial intelligence (AI) to summarize reports and identify bottlenecks to help streamline DevOps workflows.
Aaron Upright, the co-founder of Zenhub, said the company plans to work with each Zenhub AI customer to enable them to securely use their personal data to train an AI model using the ChatGPT platform to make DevOps teams more productive.
For example, DevOps teams will be able to use historical sprint data to identify bottlenecks more easily. Natural language processing (NLP) will also enable teams to reduce the impact of project label sprawl by making it easier to associate related projects regardless of naming conventions.
Overall, the quality of data being collected will also improve story point estimations, noted Upright.
It’s still early days as far as the usage of generative AI within the context of project management applications is concerned, but the potential AI has to transform the role of project managers is already apparent as more data is collected and analyzed by AI models. Rather than reacting to changes to project schedules as they occur, it should become easier for project managers to proactively surface issues that might have previously delayed or derailed a software development effort.
Project managers should also be able to better track the return on investment (ROI) metrics for any given project as changes occur, added Upright.
In theory, project managers augmented by AI models should be able to simultaneously manage more complex development efforts at levels of scale that previously would have been unachievable. The challenge is making sure project managers have visibility into the suggestions being made by AI platforms. Often when presented with conflicting data they will make up an inaccurate response, also known as a hallucination.
However, the narrower the range of data used to train an AI model the more accurate it tends to become. The critical issue many organizations will initially face is vetting the quality of the data being used to train the AI model. In addition, organizations will also need to make sure that no biases have been inadvertently injected into an AI model because the data used to train it was either flawed or inaccurate.
Ultimately, the amount of toil that project managers regularly experience should decline considerably as AI continues to advance. The expectation should be that AI will soon be pervasively applied across multiple project management applications. The race is now on to deliver on that promise.
In the meantime, project managers might want to start assessing which tasks they perform daily that are likely to be automated. This will enable them to add higher levels of value by having the time needed to focus more on strategic imperatives. After all, every minute spent checking to see whether data is accurate is one less minute spent understanding what needs to be done to affect a better project management outcome.
Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.
This week: Rethinking return-to-office mandates and a ridiculous, ancient Windows bug. (more…)