In a world where cloud computing is becoming increasingly popular, iExec RLC offers a unique solution for businesses looking to make the most out of their resources. By providing access to distributed applications and services, iExec RLC unlocks new possibilities in the cloud computing space.

The platform allows users to securely access and deploy any application or service from anywhere in the world without having to worry about data security or reliability. It also eliminates the need for complex infrastructure setup and maintenance, as all applications and services are hosted on an Ethereum-based blockchain network. As such, businesses can benefit from reduced costs associated with theiExec RLC Priceand hosting fees while also having the advantage of increased flexibility when scaling their solutions according to their needs.

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Furthermore, iExec RLC gives users complete control over their data privacy settings, allowing them to decide who can access what information they store on the platform. All of these features make iExec RLC an attractive option for businesses looking for a reliable and secure way to unlock new possibilities in the cloud computing space.

iExec RLC (RLC stands for Run on Lots of Computers) is a decentralized cloud computing platform that enables users to rent out their computing resources in exchange for cryptocurrency. It was created by the French startupiExec, which has been developing blockchain-based solutions since 2016. The platform allows users to access distributed applications and services without owning or managing any hardware. Instead, they can rent out the necessary computing power from other users on the network. This makes it easier and more cost-effective for developers to create and deploy distributed applications and for businesses to access powerful computing resources without investing in expensive hardware, allowing them to tap into new digital markets like theMetaverse, accessing a new market of digital consumers. Additionally, iExec provides a marketplace where developers can list their applications and services, allowing them to monetize their work while giving users easy access to high-quality products.

To buy and sell iExec RLC tokens, you will need to use a cryptocurrency exchange. First, you will need to create an account on the exchange platform of your choice. Once your account is created, you can deposit funds using various payment methods such as bank transfer or credit card. After your funds have been deposited, you can then search for the iExec RLC token and place an order to buy or sell it at the current market price. Once your order has been filled, you will be able to withdraw your tokens from the exchange into a secure wallet that supports them.

iExec RLC uses distributed ledger technology (DLT) to ensure the integrity of its network by providing an immutable record of all transactions on the platform. This makes it an ideal solution for companies looking for a secure way to store sensitive information such as customer data or financial records. iExec also offers a range of advanced analytic capabilities which allow businesses to gain valuable insights into their operations and make better decisions based on real-time data analysis. All user data is encrypted using industry-standard encryption algorithms, and all communication between servers and the customers device is done over a secure HTTPS connection. Two-factor authentication has also been implemented for added security, so you can be sure that only you have access to your account. Additionally, the company regularly monitors its systems for any suspicious activity or potential threats. By combining these various security measures, iExec RLC ensures that its users data remains safe and secure at all times.

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Key Takeaways

Kubernetes and cloud native have been around for nearly a decade. In that time, weve seen a Cambrian explosion of projects and innovation around infrastructure software. Through trial and late nights, we have also learned what works and what doesnt when running these systems at scale in production. With these fundamental projects and crucial experience, platform teams are now pushing innovation up the stack, but can the stack keep up with them?

With the change of application design to API-driven microservices and the rise of Kubernetes-based platform engineering, networking, and security, teams have struggled to keep up because Kubernetes breaks traditional networking and security models. With the transition to cloud, we saw a similar technology sea change at least once. The rules of data center infrastructure and developer workflow were completely rewritten as Linux boxes in the cloud began running the worlds most popular services. We are in a similar spot today with a lot of churn around cloud native infrastructure pieces and not everyone knowing where it is headed; just look at the CNCF landscape. We have services communicating with each other over distributed networks atop a Linux kernel where many of its features and subsystems were never designed for cloud native in the first place.

The next decade of infrastructure software will be defined by platform engineers who can take these infrastructure building blocks and use them to create the right abstractions for higher-level platforms. Like a construction engineer uses water, electricity, and construction materials to build buildings that people can use, platform engineers take hardware and infrastructure software to build platforms that developers can safely and reliably deploy software on to make high-impact changes frequently and predictably with minimal toil at scale. For the next act in the cloud native era, platform engineering teams must be able to provision, connect, observe, and secure scalable, dynamic, available, and high-performance environments so developers can focus on coding business logic. Many of the Linux kernel building blocks supporting these workloads are decades old. They need a new abstraction to keep up with the demands of the cloud native world. Luckily, it is already here and has been production-proven at the largest scale for years.

eBPF is creating the cloud native abstractions and new building blocks required for the cloud native world by allowing us to dynamically program the kernel in a safe, performant, and scalable way. It is used to safely and efficiently extend the cloud native and other capabilities of the kernel without requiring changes to kernel source code or loading kernel modules unlocking innovation by moving the kernel itself from a monolith to more modular architecture enriched with cloud native context. These capabilities enable us to safely abstract the Linux kernel, iterate and innovate at this layer in a tight feedback loop, and become ready for the cloud native world. With these new superpowers for the Linux kernel, platform teams are ready for Day 2 of cloud nativeand they might already be leveraging projects using eBPF without even knowing. There is a silent eBPF revolution reshaping platforms and the cloud native world in its image, and this is its story.

eBPF is a decades-old technology beginning its life as the BSD Packet Filter (BPF) in 1992. At the time, Van Jacobson wanted to troubleshoot network issues, but existing network filters were too slow. His lab designed and created libpcap, tcpdump, and BPF as a backend to provide the required functionality. BPF was designed to be fast, efficient, and easily verifiable so that it could be run inside the kernel, but its functionality was limited to read-only filtering based on simple packet header fields such as IP addresses and port numbers. Over time, as networking technology evolved, the limitations of this classic BPF (cBPF) became more apparent. In particular, it was stateless, which made it too limiting for complex packet operations and difficult to extend for developers.

Despite these constraints, the high-level concepts around cBPF of having a minimal, verifiable instruction set where it is feasible for the kernel to prove the safety of user-provided programs to then be able to run them inside the kernel have provided an inspiration and platform for future innovation. In 2014, a new technology was merged into the Linux kernel that significantly extended the BPF (hence, eBPF) instruction set to create a more flexible and powerful version. Initially, replacing the cBPF engine in the kernel was not the goal since eBPF is a generic concept and can be applied in many places outside of networking. However, at that time, it was a feasible path to merge this new technology into the mainline kernel. Here is an interesting quote from Linus Torvalds:

So I can work with crazy people, thats not the problem. They just need to sell their crazy stuff to me using non-crazy arguments and in small and well-defined pieces. When I ask for killer features, I want them to lull me into a safe and cozy world where the stuff they are pushing is actually useful to mainline people first. In other words, every new crazy feature should be hidden in a nice solid Trojan Horse gift: something that looks obviously good at first sight.

This, in short, describes the organic nature of the Linux kernel development model and matches perfectly to how eBPF got merged into the kernel. To perform incremental improvements, the natural fit was first to replace the cBPF infrastructure in the kernel, which improved its performance, then, step by step, expose and improve the new eBPF technology on top of this foundation. From there, the early days of eBPF evolved in two directions in parallel, networking and tracing. Every new feature around eBPF merged into the kernel solved a concrete production need around these use cases; this requirement still holds true today. Projects like bcc, bpftrace, and Cilium helped to shape the core building blocks of eBPF infrastructure long before its ecosystem took off and became mainstream. Today, eBPF is a generic technology that can run sandboxed programs in a privileged context such as the kernel and has little in common with BSD, Packets, or Filters anymoreeBPF is simply a pseudo-acronym referring to a technological revolution in the operating system kernel to safely extend and tailor it to the users needs.

With the ability to run complex yet safe programs, eBPF became a much more powerful platform for enriching the Linux kernel with cloud native context from higher up the stack to execute better policy decisions, process data more efficiently, move operations closer to their source, and iterate and innovate more quickly. In short, instead of patching, rebuilding, and rolling out a new kernel change, the feedback loop with infrastructure engineers has been reduced to the extent that an eBPF program can be updated on the fly without having to restart services and without interrupting data processing. eBPFs versatility also led to its adoption in other areas outside of networking, such as security, observability, and tracing, where it can be used to detect and analyze system events in real time.

Moving from cBPF to eBPF has drastically changed what is possibleand what we will build next. By moving beyond just a packet filter to a general-purpose sandboxed runtime, eBPF opened many new use cases around networking, observability, security, tracing, and profiling. eBPF is now a general-purpose compute engine within the Linux kernel that allows you to hook into, observe, and act upon anything happening in the kernel, like a plug-in for your web browser. A few key design features have enabled eBPF to accelerate innovation and create more performant and customizable systems for the cloud native world.

First, eBPF hooks anywhere in the kernel to modify functionality and customize its behavior without changing the kernels source. By not modifying the source code, eBPF reduces the time from a user needing a new feature to implementing it from years to days. Because of the broad adoption of the Linux kernel across billions of devices, making changes upstream is not taken lightly. For example, suppose you want a new way to observe your application and need to be able to pull that metric from the kernel. In that case, you have to first convince the entire kernel community that it is a good ideaand a good idea for everyone running Linuxthen it can be implemented and finally make it to users in a few years. With eBPF, you can go from coding to observation without even having to reboot your machine and tailor the kernel to your specific workload needs without affecting others. eBPF has been very useful, and the real power of it is how it allows people to do specialized code that isnt enabled until asked for, said Linus Torvalds.

Second, because the verify checks that programs are safe to execute, eBPF developers can continue to innovate without worrying about the kernel crashing or other instabilities. This allows them and their end users to be confident that they are shipping stable code that can be leveraged in production. For platform teams and SREs, this is also crucial for using eBPF to safely troubleshoot issues they encounter in production.

When applications are ready to go to production, eBPF programs can be added at runtime without workload disruption or node reboot. This is a huge benefit when working at a large scale because it massively decreases the toil required to keep the platform up to date and reduces the risk of workload disruption from a rollout gone wrong. eBPF programs are JIT compiled for near native execution speed, and by shifting the context from user space to kernel space, they allow users to bypass or skip parts of the kernel that arent needed or used, thus enhancing performance. However, unlike complete kernel bypasses in user space, eBPF can still leverage all the kernel infrastructure and building blocks it wants without reinventing the wheel. eBPF can pick and choose the best pieces of the kernel and mix them with custom business logic to solve a specific problem. Finally, being able to modify kernel behavior at run time and bypass parts of the stack creates an extremely short feedback loop for developers. It has finally allowed experimentation in areas like network congestion control and process scheduling in the kernel.

Growing out of the classic packet filter and taking a major leap beyond the traditional use case unlocked many new possibilities in the kernel, from optimizing resource usage to adding customized business logic. eBPF allows us to speed up kernel innovation, create new abstractions, and dramatically increase performance. eBPF not only reduces the time, risk, and overhead it takes to add new features to production workloads, but in some cases, it even makes it possible in the first place.

So many benefits begs the question if eBPF can deliver in the real worldand the answer has been a resounding yes. Meta and Google have some of the worlds largest data center footprints; Netflix accounts for about 15% of the Internets traffic. Each of these companies has been using eBPF under the hood for years in production and the results speak for themselves.

Meta was the first company to put eBPF into production at scale with its load balancer project Katran. Since 2017, every packet going into a Meta data center has been processed with eBPFthats a lot of cat pictures. Meta has also used eBPF for many more advanced use cases, most recently improving scheduler efficiency, which increased throughput by 15%, a massive boost and resource saving at their scale. Google also processes most of its data center traffic through eBPF, using it for runtime security and observability, and defaults its Google Cloud customers to using an eBPF-based dataplane for networking. In the Android operating system, which powers over 70% of mobile devices and has more than 2.5 billion active users spanning over 190 countries, almost every networking packet hits eBPF. Finally, Netflix relies extensively on eBPF for performance monitoring and analysis of their fleet, and Netflix engineers pioneered eBPF tooling, such as bpftrace, to make major leaps in visibility for troubleshooting production servers and built eBPF-based collectors for On-CPU and Off-CPU flame graphs.

eBPF clearly works and provides extensive benefits for Internet-scale companies and has been for the better part of a decade, but those benefits also need to be translated to the rest of us.

At the beginning of the cloud native era, GIFEE (Google Infrastructure for Everyone Else) was a popular phrase, but largely fell out of favor because not everyone is Google or needs Google infrastructure. Instead, people want simple solutions that solve their problems, which begs the question of why eBPF is different. Cloud native environments are meant to run scalable applications in modern, dynamic environments. Scalable and dynamic are key to understanding why eBPF is the evolution of the kernel that the cloud native revolution needs.

The Linux kernel, as usual, is the foundation for building cloud native platforms. Applications are now just using sockets as data sources and sinks, and the network as a communication bus. But cloud native needs newer abstractions than currently available in the Linux kernel because many of these building blocks, like cgroups (CPU, memory handling), namespaces (net, mount, pid), SELinux, seccomp, netfiler, netlink, AppArmor, auditd, perfare decades old before cloud even had a name. They dont always talk together, and some are inflexible, allowing only for global policies and not per-container or per-service ones. Instead of leveraging new cloud native primitives, they lack awareness of Pods or any higher-level service abstractions and rely on iptables for networking.

As a platform team, if you want to provide developer tools for a cloud native environment, you can still be stuck in this box where cloud native environments cant be expressed efficiently. Platform teams can find themselves in a future they are not ready to handle without the right tools. eBPF now allows tools to rebuild the abstractions in the Linux kernel from the ground up. These new abstractions are unlocking the next wave of cloud native innovation and will set the course for the cloud native revolution.

For example, in traditional networking, packets are processed by the kernel, and several layers of network stack inspect each packet before reaching its destination. This can result in a high overhead and slow processing times, especially in large-scale cloud environments with many network packets to be processed. eBPF instead allows inserting custom code into the kernel that can be executed for each packet as it passes through the network stack. This allows for more efficient and targeted network traffic processing, reducing the overhead and improving performance. Benchmarks from Cilium showed that switching from iptables to eBPF increased throughput 6x, and moving from IPVS-based load balancing to eBPF based allowed Seznam.cz to double throughput while also reducing CPU usage by 72x. Instead of providing marginal improvements on an old abstraction, eBPF enables magnitudes of enhancement.

eBPF doesnt just stop at networking like its predecessor; it also extends to areas like observability and security and many more because it is a general-purpose computing environment and can hook anywhere in the kernel. I think the future of cloud native security will be based on eBPF technology because its a new and powerful way to get visibility into the kernel, which was very difficult before, said Chris Aniszczyk, CTO of Cloud Native Computing Foundation. At the intersection of application and infrastructure monitoring, and security monitoring, this can provide a holistic approach for teams to detect, mitigate, and resolve issues faster.

eBPF provides ways to connect, observe, and secure applications at cloud native speed and scale. As applications shift toward being a collection of API-driven services driven by cloud native paradigms, the security, reliability, observability, and performance of all applications become fundamentally dependent on a new connectivity layer driven by eBPF, said Dan Wendlandt, CEO and co-founder of Isovalent. Its going to be a critical layer in the new cloud native infrastructure stack.

The eBPF revolution is changing cloud native; the best part is that it is already here.

While the benefits of eBPF are clear, it is so low level that platform teams, without the luxury of Linux kernel development experience, need a friendlier interface. This is the magic of eBPFit is already inside many of the tools running the cloud native platforms of today, and you may already be leveraging it without even knowing. If you spin up a Kubernetes cluster on any major cloud provider, you are leveraging eBPF through Cilium. Using Pixie for observability or Parca for continuous profiling, also eBPF.

eBPF is a powerful force that is transforming the software industry. Marc Andreessens famous quote on software is eating the world has been semi-jokingly recoined by Cloudflare as eBPF is eating the world. However, success for eBPF is not when all developers know about it but when developers start demanding faster networking, effortless monitoring and observability, and easier-to-use security solutions. Less than 1% of developers may ever program something in eBPF, but the other 99% will benefit from it. eBPF will have completely taken over when theres a variety of projects and products providing massive developer experience improvement over upstreaming code to the Linux kernel or writing Linux kernel modules. We are already well on our way to that reality.

eBPF has revolutionized the way infrastructure platforms are and will be built and has enabled many new cloud native use cases that were previously difficult or impossible to implement. With eBPF, platform engineers can safely and efficiently extend the capabilities of the Linux kernel, allowing them to innovate quickly. This allows for creating new abstractions and building blocks tailored to the demands of the cloud native world, making it easier for developers to deploy software at scale.

eBPF has been in production for over half a decade at the largest scale and has proven to be a safe, performant, and scalable way to dynamically program the kernel. The silent eBPF revolution has taken hold and is already used in projects and products around the cloud native ecosystem and beyond. With eBPF, platform teams are now ready for the next act in the cloud native era, where they can provision, connect, observe, and secure scalable, dynamic, available, and high-performance environments so developers can focus on just coding business logic.

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The Silent Platform Revolution: How eBPF Is Fundamentally ... - InfoQ.com

Western Digital (WD), a renowned manufacturer of Scandisk drives, has announced a data breach on its network, resulting in unauthorized access to data on multiple systems by attackers.

WD is a company based in the United States that specializes in manufacturing computer drives and data storage devices, providing data center systems, and offering customers cloud storage services.

The incident is ongoing, so the Company has promptly deployed incident responders and collaborated with digital forensic experts to investigate the attack.

Western Digital identified a network security incident involving Western Digitals systems. In connection with the ongoing incident, an unauthorized third party gained access to a number of the Companys systems. WD said in a Press release.

The Company is implementing proactive measures to secure its business operations, including taking systems and services offline, and will continue taking additional steps as appropriate.

Additionally, the Company has stated that they are actively working on restoring the affected systems. They suspect that the unauthorized party obtained detailed data from their systems and are striving to comprehend the nature and extent of that data.

As a result of this incident, several users reported that My Cloud, another cloud operating service, experienced over 12 hours of downtime.

Our team is working urgently to resolve the issue and restore access as soon as possible. We apologize for any inconvenience this may cause and appreciate your patience.

According to their incident report, We are experiencing a service interruption preventing customers from accessing the My Cloud, My Cloud Home, My Cloud Home Duo, My Cloud OS 5, SanDisk ibi, SanDisk Ixpand Wireless Charger service.

Following the attack, the storage manufacturer has taken further security measures to protect its systems and operations, which may affect some of Western Digitals services.

Here the following products are impacted by this security incident:

My CloudMy Cloud HomeMy Cloud Home DuoMy Cloud OS5SanDisk ibiSanDisk IxpWireless Charger

We attempted to contact Western Digital for further information on the incident but did not receive a response. We will provide updates to the article as soon as they become available.

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Western Digital Network Breach Hackers Gained Access to Company Servers - GBHackers

Vaadin recently released new research on the state of Java in the enterprise.Combined with other sources, this survey offers a good look into Javas evolution.The overall view is one of vitality, and even a resurgence of interest in Java, as it continues to provide a solid foundation for building applications of a wide range of sizes and uses.

I dug into Vaadin's 2023 State of Java in the Enterprise Report, along with a few others. This article summarizes what I think are the most significant developments in enterprise Java today.

Java has seen a long succession of incremental improvements over the last decade.We're currently on the cusp of more significant changes through the Java language refactor in Project Valhalla and Java concurrency updates in Project Loom.Those forthcoming changes, combined with security considerations, make staying up to date with Java versions especially important.

Vaadin's research indicates that developers using Java have kept up with version updates so far. Twenty-six percent of respondents report they are on version 17 or newer; 21% are in the process of upgrading; and 37% are planning to upgrade.

These results jive with research from New Relic showing that Java 11 is becoming the current LTS (long-term support) standard, gradually supplanting Java 8.Java 17 is the newest LTS release, replacing Java 11 under the two-year release cadence, and will soon become the baseline upgrade for Java. The next LTS release will be Java 21, currently targeted for September 2023.

Survey results indicate that security is a major concern for Java developers, and for good reason.Discovering the Log4j vulnerability shined a glaring spotlight on code vulnerabilities in Java applications and elsewhere. Cybersecurity is a slow-moving hurricane that seems to only gather strength as time goes on.

The Vaadin report indicates that 78% of Java developers see ensuring app security as a core concern; 24% describe it as a significant challenge; and 54% say it is somewhat of a challenge.

Java by itself is a very secure platform. But like any other language, it is open to third-party vulnerabilities. Writing and deploying secure Java applications requires maintaining good security practices across the entire application life cycle and technology stack.Even the federal government, through CISA, is taking securing open source software and tracking vulnerabilities seriously, and urging the adoption of zero-trust architectures.

Because Java is a solid, evolving platform, Java developers are well-positioned to take on the very real and changing universe of threats facing web applications. We just need to be aware of security concerns and integrate cybersecurity into our daily development activities.

According to the Vaadin research, 76% of respondents see hiring and retaining developers as either a significant challenge or somewhat of a challenge.This is, of course, an industry-wide problem, with developer burnout and dissatisfaction causing major difficulty in both attracting and retaining good software developers.

Perhaps the best way to think about developer retention is in light of the developer experience (or DX). Like other coders, Java programmers want to work in an environment that supports our efforts and allows us to use our skills and creativity.A supportive environment encompasses the development tools and processes and the overall culture of the organization.

One way to improve developer experience is through a robust devops infrastructure, which streamlines and brings consistency to otherwise stressful development phases like deployment.There is an interplay between devops and developer experience. Improving the tools and processes developers use makes it easier for us to maintain them and ensure adaptive correctness.

Deployment figures large in the Vaadin research.Cloud infrastructure and serverless platformscloud-native environmentsare seen as an essential evolution for Java applications.Right now, 55% of Java applications are deployed to public clouds.On-prem and private hosting still account for 70% of application deployments.Kubernetes and serverless account for 56% of deployments, spread between public cloud, on-prem and PaaS.

Of serverless providers, Amazon Web Services (AWS) leads the space, with 17% of respondents saying they deploy their Java applications using AWS Lambda.Microsoft Azure and Google Cloud Platform serverless both account for 4% of all deployments, according to survey responses.

After on-prem servers and virtual machines, on-prem Kubernetes is the most prevalent style of deployment, used by 29% of respondents.

These numbers point to a Java ecosystem that has continued to move toward cloud-native technology but still has a big chunk of functionality running on self-hosted servers.Many Java shops feel a sense of urgency to adopt cloud platforms. But some developers continue to prefer self-hosted platforms and frameworks to being locked into a cloud provider's compute-for-rent business model.

Not surprisingly, the lions share of Java applications are web applications, with desktop applications accounting for only 18% of all products in development at the time of the survey.As for the composition of new and existing applications that use Java, its a diverse group.The Vaadin research further distinguishes between current technology stacks and planned changes to the stack.

The continued strong focus on full-stack Java applications is particularly interesting.Fully 70% of respondents indicated that new full-stack Java applications were planned for upcoming projects.

Just behind full-stack applications is back-end development.Back-end APIs accounted for 69% of new investment plans, according to respondents.

After full-stack and back-end development, respondents' development efforts were spread between modernizing existing applications (57%); developing heterogenous (Java with JavaScript or TypeScript) full-stack applications (48%); migrating existing applications to the cloud (36%); and building new front ends for existing Java back ends (29%).

The survey also gives a sense for what front-end frameworks Java developers currently favor. Angular (37%) and React (32%) are in the lead, followed by Vue (16%).This is in contrast to the general industry where React is the most popular framework.Other frameworks like Svelte didnt make a strong enough showing to appear in the survey.

Given its popularity and utility, it is unsurprising that Spring is heavily used by Java developers.Of respondents, 79% reported using Spring Boot and 76% were using the general Spring framework.The forecast among developers is for them both to continue being used.

Fifty-seven percent of respondents to the Vaadin survey indicated that modernization was a chief concern for planned investment.The highest ranked reason given for modernization was maintainability.

Maintainability is a universal and perennial concern for developers of all stripes and stacks.With the huge volume of what we might term legacy codethat is, anything thats already been builtin Java, there is a strong sense that we need to upgrade our existing systems so that they can be worked on and brought into the future. It's a healthy impulse.To find the will and money to refactor and strengthen what is already there is key in any long-term project.

After maintainability comes security, which weve already discussed. In this case, though, security is seen as another reason for modernization, with20% of respondents ranking security as their number one cause, 16% in second place, and 21% in third.Security is once again a reasonable and healthy focus among developers.

Among all the challenges identified by Java developers, building an intuitive and simple UX appears to be the greatest.It is a significant challenge for 30% and somewhat of a challenge for 51% of developers.

The UI is a tricky part of any application.I get the sense that Java developers are strong with building back-end APIs and middleware and longing for a way to use their familiar technology to build across the stackjust notice the heavy emphasis on full-stack Java applications.One respondent commented in the survey, We want to use Java both for backend and frontend.Maybe with WASM that will be possible someday.

For the time being, Java developers are confronted with either building in a JavaScript framework like React, using a technology that allows for coding in Java and outputting in JavaScript (like JavaServer Faces or Google Web Toolkit), or using a framework that tries to encompass both Java and JavaScript under a single umbrella like Hilla or jHipster. (I've written about both here on InfoWorld.)

With the industry as a whole, Java developers have moved toward better devops practices like CI/CD as well as adopting third-party integrations.The Vaadin report identifies logging, observability, and single sign-on (SSO) solutions as the most popular tools in use.Kubernetes, business tools like enterprise resource planning (ERP) and customer relationship management (CRM), devops, and multi-factor authentication (MFA) solutions round out the rest of the most-used third-party tools in the Java ecosystem.

Like the State of JavaScript survey for JavaScript, Vaadin's State of Java in the Enterprise Report offers an expansive portrait of Java, both as it is and in where it is moving.Overall, Java appears to be riding a wave of stability coupled with an evolving dynamism. The two together indicate a vital technology that is ready for the future.

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The changing world of Java - InfoWorld