The Power of GenAI in Data Exploration and Querying

One of the most immediate benefits of GenAI in observability tools is its ability to simplify data exploration and querying. Traditionally, enterprise IT teams have had to rely on complex query languages such as SQL or PromQL to navigate massive data sets—tasks that often require specialized knowledge and can slow down problem-solving.

Austin Parker, Director of Open Source at Honeycomb, highlights the challenge: “Even for experienced engineers, mastering these languages takes time, and the complexity often hinders data exploration. With generative AI, we’re making that process much easier. At Honeycomb, our Query Assistant uses GenAI to allow users to ask questions in natural language, such as ‘show me all my errors grouped by region,’ and the AI converts that into a query that’s ready to run.”

For enterprise IT leaders, this has profound implications. With AI handling the complexities of query syntax, IT teams can more quickly extract actionable insights from their observability platforms. This enables real-time troubleshooting and more effective monitoring, without needing to dive deep into query language intricacies. “By making data more accessible, we are democratizing observability across teams,” says Parker. “The result is faster response times and a significant reduction in time-to-resolution.”

From Data Access to Actionable Insights

The value of GenAI goes beyond mere query simplification—it’s about turning data into actionable insights at scale. Enterprises run on massive amounts of telemetry data, and manual methods of sifting through this information are not only inefficient but often lead to critical insights being missed.

Generative AI’s capability to analyze this data in real-time and provide contextual answers is a game-changer for software developers and IT executives alike. “The sheer volume of data generated by modern cloud-native architectures is staggering,” says Parker. “Observability tools powered by GenAI help distill this ocean of data into manageable, actionable insights that teams can leverage to maintain uptime and optimize system performance.”

For software developers managing distributed systems, this enhanced accessibility can directly impact continuous integration and delivery (CI/CD) pipelines. With AI-powered tools providing insights into performance issues, dev teams can identify bottlenecks and inefficiencies earlier in the process, ensuring smoother releases and fewer production incidents.

“Instead of waiting for incidents to reach a critical threshold, observability tools with AI integration allow us to be proactive in identifying system anomalies,” says a Senior Software Engineer at a leading cloud services provider. “We can focus on optimizing performance instead of spending hours decoding logs and telemetry data.”

Limitations and the Future of Root Cause Analysis

While Generative AI is revolutionizing querying and data interpretation, Parker acknowledges that AI’s potential in automated root cause analysis is still developing. “There’s a lot of excitement around AI-driven root cause analysis, but the reality is that most systems are too unique for generalized solutions to work across the board,” says Parker. “For companies like Microsoft with vast, structured data sets and predefined operational processes, AI can provide meaningful root cause insights. But for smaller or less structured environments, the results might be less reliable.”

For enterprises operating complex systems, AI can offer suggestions and hypotheses based on past incident data. However, full automation in incident remediation remains a challenging task. “What we’ve found is that AI can assist, but it’s not yet at a stage where it can consistently identify root causes across diverse architectures,” Parker explains. This is particularly true in the fragmented world of Kubernetes clusters, where even slight variations in configuration can lead to drastically different outcomes.

Despite these limitations, Parker believes that AI-powered observability tools will continue to improve. As enterprises move toward more structured environments, with richer and more consistent data, the potential for AI-driven automation in root cause analysis will grow. “We’re already seeing advances in AI’s ability to analyze highly structured environments like managed Kubernetes or cloud platforms,” Parker adds. “With the right data context, AI can offer increasingly accurate diagnoses and even suggest potential fixes.”

Observability 2.0: The Future of Context-Driven AI

To unlock the full potential of Generative AI, enterprises need to evolve their observability strategies toward what Parker refers to as Observability 2.0. This next-generation observability relies on high-quality, structured data that allows AI tools to perform at their best. Without this foundation, even the most advanced AI models struggle to produce meaningful insights.

“Observability 2.0 is about creating a context-rich environment where AI can thrive,” says Parker. “This means gathering structured, high-context data from across your systems and ensuring that every piece of telemetry is semantically accurate and meaningful.”

For enterprise IT executives, this shift requires investment in modern observability platforms that go beyond simple log management or metrics collection. Companies must also adopt open standards like OpenTelemetry, which provide the structured data frameworks that AI tools need to function optimally.

“The more context and structure you give the AI, the better the results will be,” explains Parker. “When enterprises commit to this approach, the possibilities are endless—from automated remediation to proactive incident management.”

Generative AI and the Future of Observability: A Strategic Imperative

For enterprise-level IT executives, the implications of GenAI in observability tools cannot be understated. In an era where systems are becoming more distributed and complex, manual methods of monitoring and troubleshooting are increasingly inadequate. Generative AI offers the promise of not only simplifying data access but also transforming how organizations manage incidents, optimize performance, and maintain business continuity.

“Generative AI is going to be a key player in the future of observability,” says Parker. “But for it to be truly effective, enterprises need to align their infrastructure with Observability 2.0 principles—structured data, high context, and a commitment to AI-driven automation.”

As the technology continues to evolve, so too will the role of IT executives and software developers. The focus will shift from reactive problem-solving to proactive system optimization, with AI providing the insights and automation needed to stay ahead of the curve. Generative AI may not yet offer a magic bullet for all observability challenges, but for forward-thinking enterprises, it represents a strategic opportunity that cannot be ignored.

For enterprises looking to maintain a competitive edge in a world where IT infrastructure is becoming ever more critical, the adoption of AI-powered observability tools will be a key differentiator. As Parker puts it: “Those who embrace AI will find themselves better equipped to navigate the complexities of modern systems, while those who hesitate may find themselves left behind.”

The future of observability is here, and Generative AI is poised to play a defining role in shaping it

Rifi’s platform, housed in the cloud, empowers data teams to stay ahead of the curve by offering unparalleled visibility into their operations. Sanjay highlights two key features that define Rifi’s offering. Firstly, the platform helps teams manage their budgets effectively, ensuring they don’t exceed allocations for cloud services like Snowflake or BigQuery. This proactive approach to cost management saves money and fosters trust within organizations, as data flows smoothly and reliably.

Secondly, Rifi prioritizes the time of data teams, recognizing that efficiency is crucial for building trust and making informed decisions. Sanjay notes that Rifi has enabled some customers to drastically reduce escalations from data teams to their businesses, a testament to the platform’s ability to streamline operations and increase productivity.

One of Rifi’s standout success stories involves a public company with a $10 billion market cap. Within just three weeks of implementing Rifi’s solution on BigQuery, the company noticed a significant increase in failed jobs, indicating issues with data accessibility. Instead of resorting to the traditional approach of requesting more resources, Rifi’s platform enabled the company to identify the root cause of the problem quickly: certain user and query patterns consuming excessive capacity. By addressing these issues promptly, the company was able to free up nearly a quarter-million dollars worth of capacity, demonstrating the tangible impact of Rifi’s technology on the bottom line.

When asked about Rifi’s approach to innovation, Sanjay emphasizes the company’s commitment to listening to its customers. With clients spanning various industries, including public, healthcare, finance, and startups, Rifi understands the diverse needs and challenges facing data teams today. By staying attuned to customer feedback and continuously iterating on its platform, Rifi ensures that it remains at the forefront of innovation, delivering solutions that meet the dynamic demands of the modern tech landscape.

In conclusion, Rifi’s groundbreaking approach to data observability and rapid issue detection is revolutionizing the way organizations harness and leverage their data. By combining cutting-edge technology with a customer-centric approach, Rifi empowers data teams to navigate the complexities of today’s digital world with confidence and agility.

At the forefront of this movement is Megan Grant, IBM’s Worldwide Data Observability Leader. With years of experience in the data management space, Grant is passionate about helping organizations harness the full potential of data observability to optimize their data pipelines and unlock new opportunities for growth.

In a recent discussion, Grant shared her insights on the transformative power of data observability and its role in driving organizational success. “Data observability is about more than just monitoring data pipelines; it’s about gaining deeper insights into data behavior and proactively addressing issues before they impact operations,” she explains.

Grant emphasizes that data observability is a journey rather than a destination, requiring organizations to adopt a proactive approach to data management. “By implementing robust observability solutions, organizations can gain greater visibility into their data workflows and identify potential issues early on,” she says.

According to Grant, one of the key benefits of data observability is its ability to streamline data operations and improve overall efficiency. “With observability tools in place, data engineers can quickly identify and resolve issues, minimizing downtime and ensuring smooth data flow,” she notes.

Moreover, Grant highlights the impact of data observability on data consumers, such as data analysts and data scientists, who rely on high-quality data to perform their tasks effectively. “By providing data consumers with access to reliable data, observability solutions empower them to make informed decisions and drive business value,” she adds.

Grant also underscores the importance of data governance and compliance in the context of observability. She notes that organizations must adhere to regulatory requirements while maintaining visibility and control over their data assets. “Data observability enables organizations to implement robust governance policies and ensure compliance with industry regulations,” she explains.

Looking ahead, Grant sees immense potential for data observability to drive innovation and fuel business growth. “As organizations continue to harness the power of data, observability will play a crucial role in enabling them to adapt to evolving challenges and seize new opportunities,” she predicts.

Grant urges organizations to embrace data observability as a strategic imperative and invest in robust solutions that empower them to unlock the full potential of their data assets. “By embracing data observability, organizations can gain a competitive edge in today’s data-driven world and pave the way for future success,” she concludes.

As businesses continue to grapple with the complexities of data management, the insights shared by Megan Grant offer a valuable roadmap for leveraging the power of data observability to drive organizational excellence and innovation.

“Data observability is not merely a buzzword; it’s a foundational pillar upon which data-driven organizations build their success,” Yackel asserted, emphasizing the profound impact of effective data monitoring and management.

Drawing parallels to the robust monitoring frameworks prevalent in software engineering, Yackel articulated the essence of data observability as a proactive mechanism for detecting and resolving issues within data pipelines. “Much like application performance monitoring (APM) revolutionized software development, data observability empowers organizations to maintain the integrity and reliability of their data infrastructure,” he remarked.

Yackel’s analogy of a train representing a data pipeline vividly illustrated the complexities inherent in data management. “Just as a train’s journey requires meticulous planning and oversight to ensure smooth operation, data pipelines demand constant vigilance to prevent disruptions and bottlenecks,” he explained.

Furthermore, Yackel underscored the transformative potential of data observability in driving organizational growth and innovation. “By harnessing the insights gleaned from robust data observability practices, organizations can unlock new avenues for innovation while mitigating risks and ensuring regulatory compliance,” he affirmed.

The discussion illuminated the pressing need for organizations to prioritize data observability in their strategic agendas. “In an era where data serves as the lifeblood of business, the ability to monitor and manage data effectively is paramount,” Yackel remarked. “Data observability equips organizations with the tools they need to navigate the complexities of modern data ecosystems with confidence.”

In conclusion, Yackel’s insights underscored the pivotal role of data observability in shaping the future of data management. “As organizations continue to harness the power of data to drive success, the adoption of robust data observability practices will be instrumental in unlocking new opportunities and ensuring sustained growth,” he concluded.

In Part 1 of this review, we looked at openSUSE’s background, its openQA-provided stability, outstanding installer, choice of desktop environments, and its security. All of these are significant advantages of the distro. Unfortunately, security is also where openSUSE’s disadvantages begin to shine through.

Disclaimer: Some will say the following points are too critical of openSUSE since it’s a more technical distro and not necessarily aimed at desktop users. Nonetheless, openSUSE’s own website says it is: “The makers’ choice for sysadmins, developers and desktop users.” Therefore, my final rating will reflect the distro’s ability to meet the needs of all three of those categories.

Too Much Security?

Security is only a good thing if it’s not so restrictive that people begin disabling features for the sake of convenience, and this is where openSUSE’s disadvantages begin to shine through.

Of all the distros that I have tried to date (Fedora, Manjaro, openSUSE, KDE Neon, Pop!_OS, Kubuntu, and Zorin OS), openSUSE’s security policies are by far the most restrictive. Want to adjust your network settings? You’ll need to enter your password. Want to install a Flatpak app? You’ll need to enter your password. Change your timezone? Enter your password.

What’s more, the default firewall settings are so strict that printer discovery doesn’t work out of the box. To be clear, every single other distro I’ve tried automatically discovers my HP printer on my network and lets me print without installing any additional drivers.

In contrast, openSUSE cannot even discover the printer without changing the firewall profile from the default ‘Public’ to ‘Home,’ or adding the mDNS service to the ‘Public’ profile. Even when making sure mDNS is enabled, openSUSE still requires “hplip” software/driver package installed.

Is it possible to overcome these issues? Yes. But many people, especially less technical users, give up before figuring out how to jump through all these hoops. In fact, a quick look at openSUSE’s Reddit will reveal that two common solutions to printing on openSUSE are a) disable the firewall altogether or b) “don’t print on openSUSE.” Seriously…I have seen that advice multiple times…”don’t print on openSUSE.”

The issues with printing on openSUSE are irritating enough that Linux creator Linus Torvalds famously dumped openSUSE and switched to Fedora because printing was just too hard to bother with. Fans of the distro will point out that it has gotten better since that day…but it’s still not good enough for the average desktop user.

Yast

Yast stands for Yet Another Setup Tool and is one of the defining characteristics of openSUSE. The tool is a throwback to the earlier days of Linux when such setup and configuration tools were more common.

There’s no denying that Yast is a powerful tool, one that is available as both a graphical and command-line package. For system admins, Yast provides a powerful way to administer openSUSE instances. There is almost nothing you can configure via the terminal that can’t be configured via Yast’s GUI, and it’s a tool I miss on other distros.

At the same time, however, like openSUSE’s other hallmark features, Yast is something of a two-edged sword. While it’s undeniably useful — and this is purely subjective — I’m not a fan of how it takes over functions normally handled by a distro’s built-in tools. For example, I run the KDE Plasma desktop, which has excellent built-in tools for printing and firewall management. Yast takes these tasks over, however. Gnome has similarly useful tools as part of the system settings.

As I said, I realize this is very subjective. Some users prefer to have one tool to manage such tasks, regardless of the desktop environment they use. Many users prefer to have one desktop-agnostic tool that never changes. I am not one of those users. I would prefer to use Plasma’s tools when they’re available and fall back to Yast when they’re not.

Btrfs and Snapper

One of openSUSE’s greatest features is its use of the btrfs filesystem and built-in Snapper support. Btrfs is a relatively new filesystem that provides automated system snapshots. This gives users the option to rollback to a previous snapshot from the boot menu in the event something goes wrong.

Tinkering with your system and mess something up? Not a problem, just rollback and it never happened. The same goes for an update that borks something. Just rollback and wait for the issue to be addressed. This is truly a must-have setup for a rolling release distro.

There are two downsides to keep in mind with btrfs (there’s that two-edged sword again):

Btrfs is one of the slower filesystems in use by Linux distros. The excellent DJ Ware, on YouTube, has done extensive benchmarks showing how much slower the filesystem is. While I’ve not done such extensive benchmarks myself, I do have an everyday data point.

When setting up the digiKam photo organizing software for the first time, the app scans your Pictures folder. On any distro using the older ext4 filesystem, it takes digikam anywhere from 4:57 to 5:17 to scan my 49GB of photos. In contrast, digiKam on openSUSE takes more than 7:50 to complete. This result, which I have been able to consistently reproduce, jives with DJ Ware’s benchmarks.

The other potential downside is in regard to data integrity. Given that it’s still a young filesystem, there are still an uncomfortable number of reports about btrfs filesystems becoming hopelessly corrupted. Without a doubt, openSUSE has the most mature implementation of btrfs, but your mileage may vary.

Patterns and Recommendations

One of the things that makes openSUSE so successful at providing stability with a rolling release is its use of Patterns and recommendations.

Patterns are collections of software that are related and share dependencies. For example, there’s a KDE Plasma Pattern, KDE Apps Pattern, Office Suite Pattern, Mobile Pattern, and more.

The power of patterns is that it allows openSUSE developers to update an entire collection of software rather than try to determine what is or is not installed on a machine. Similarly, openSUSE defaults to installing any and all recommended dependencies when installing an application, unlike almost every other distro, in the interest of making sure no app is installed with any missing features.

On paper, both of these seem like good ideas, and, to be clear, they are…to a point. Both of these features contribute greatly to openSUSE Tumbleweed being one of the most stable rolling-release distros.

Unfortunately, Patterns and recommendations also result in some unfortunate side effects. For example, if you delete an application that is included in one of the default Patterns, it will be reinstalled on the next update. You will need to manually block the package, or the entire Pattern, in order to prevent its reinstallation.

Random Papercuts

Slack Issues

In addition to the major things highlighted above, openSUSE running KDE has a bug that makes it almost impossible to add the workspaces I’m subscribed to. I can easily add three of them with no problem, but the fourth one always fails.

The only way I can get it added to the Slack client is to try importing that workspace along with three or four defunct workspaces. After trying this one or three dozen times, the troublesome workspace will finally get imported. From what I’ve been able to tell via research, the workspace string that gets passed from browser to Slack clients gets mangled.

At one point, I thought this was a KDE Plasma bug since it doesn’t happen on Gnome or Xfce. However, this only happens on openSUSE. It doesn’t happen on Manjaro KDE, Kubuntu, or KDE Neon. I have no idea what the problem is but, at least in my experience, it is a uniquely openSUSE issue.

Network Login

On multiple installs of openSUSE, I’ve had issues where I was constantly prompted to enter my root password and network password in order to stay connected. Wake the computer from sleep…enter my passwords. Needless to say, this got old quick.

Conclusion

openSUSE Tumbleweed is one of the most well-engineered distros on the market and offers a tremendous amount of features and abilities. Unfortunately, some of those features are a two-edged sword that cause as many problems as they solve.

openSUSE Tumbleweed is a distro I love to play with and would love to use as my daily driver. Unfortunately, the inconveniences quickly wears on my nerves in daily use, and I end up moving on.

That being said, for the right person, openSUSE is hands-down the best distro available.

Rating

For System Admins: 5 out of 5 stars

The combination of Yast and its enterprise connections makes openSUSE quite possibly the best distro for system admins.

For Developers: 4 out of 5 stars

On the one hand, having the latest and greatest packages can be a big help to developers. On the other hand, the papercuts and irritations may take unnecessary time away from development.

For Desktop Users: 3 out of 5 stars

Before writing about tech, I was a software developer for over a decade. I’ve created software for major universities, companies, and the commercial market. In spite of that high-tech background, openSUSE was just too irritating and difficult for me to use on a daily basis, and I would never recommend it to most everyday users. It would have to be a special breed of desktop user, one that wants to spend as much time managing their computer as using it before I could recommend it to them.

The X Window System has been the default display solution for Linux for three decades. Unfortunately, Xorg and X11 have become a patchwork of code that make it difficult to update and add new features. As a result, Wayland has been in development for the last 15 years as a replacement, with developers eager to avoid the issues that have led to the Xorg dead-end. The road to Wayland has not been without its own challenges, however, which is why it still isn’t the default on my many Linux distros.

Red Hat has been one of the largest maintainers of the old Xorg code. According to Carlos Soriano Sanchez, Software Engineering Manager, that is about to change:

Earlier this year (2023), as part of our RHEL 10 planning, we made a study to understand Wayland’s status, not only from an infrastructure perspective, but also from an ecosystem perspective. The result of this evaluation is that, while there are still some gaps and applications that need some level of adaptation, we believe the Wayland infrastructure and ecosystem are in good shape, and that we’re on a good path for the identified blockers to be resolved by the time RHEL 10 is out, planned to be released on the first half of 2025.

With this, we’ve decided to remove Xorg server and other X servers (except Xwayland) from RHEL 10 and the following releases. Xwayland should be able to handle most X11 clients that won’t immediately be ported to Wayland, and if needed, our customers will be able to stay on RHEL 9 for its full life cycle while resolving the specifics needed for transitioning to a Wayland ecosystem. It’s important to note that “Xorg Server” and “X11” are not synonymous, X11 is a protocol that will continue to be supported through Xwayland, while the Xorg Server is one of the implementations of the X11 protocol.

As Sanchez points out, there are still gaps in Wayland’s functionality, although these are rapidly closely. Those gaps have, however, caused some developers to hold off from adopting Wayland. Red Hat’s announcement should serve as a clear message that Xorg’s days are numbered and Wayland is the future.

Microsoft’s security reputation has taken a beating in recent years, with a hack that compromised US government email address bring the straw that broke the camel’s back. To make matters worse, Amit Yoran, CEO of security firm Tenable, blasted the company’s Azure security as “grossly irresponsible.”

It appears Microsoft is finally working to address both the problem — and its reputation — with its new initiative, which was revealed in an internal company memo from company President Brad Smith:

Satya Nadella, Microsoft Chief Executive Officer; Rajesh Jha, Microsoft Executive Vice President, Experiences and Devices; Scott Guthrie, Microsoft Executive Vice President, Cloud and AI; and I have put significant thought into how we should anticipate and adapt to the increasingly more sophisticated cyberthreats. We have carefully considered what we see across Microsoft and what we have heard from customers, governments, and partners to identify our greatest opportunities to impact the future of security. As a result, we have committed to three specific areas of engineering advancement we will add to our journey of continually improving the built-in security of our products and platforms. We will focus on 1. transforming software development, 2. implementing new identity protections, and 3. driving faster vulnerability response.

Smith goes on to outline the company’s plan which will rely heavily on artificial intelligence and automation to improve the software development process, as well as increase the use of memory safe languages:

This means we’re going to apply the concept of continuous integration and continuous delivery (CI/CD) to continuously integrate protections against emerging patterns as we code, test, deploy, and operate. Think of it as continuous integration and continuous security.

We will accelerate and automate threat modeling, deploy CodeQL for code analysis to 100 percent of commercial products, and continue to expand Microsoft’s use of memory safe languages (such as C#, Python, Java, and Rust), building security in at the language level and eliminating whole classes of traditional software vulnerability.

Smith also says the company will enable more secure defaults:

We all realize no enterprise has the luxury of jettisoning legacy infrastructure. At the same time, the security controls we embed in our products, such as multifactor authentication, must scale where our customers need them most to provide protection. We will implement our Azure tenant baseline controls (99 controls across nine security domains) by default across our internal tenants automatically. This will reduce engineering time spent on configuration management, ensure the highest security bar, and provide an adaptive model where we add capability based on new operational learning and emerging adversary threats. In addition to these defaults, we will ensure adherence and auto-remediation of settings in deployment. Our goal is to move to 100 percent auto-remediation without impacting service availability.

Microsoft will work to continue improving identity management in an effort to combat identity-focused espionage:

We will enforce the use of standard identity libraries (such as Microsoft Authentication Library) across all of Microsoft, which implement advanced identity defenses like token binding, continuous access evaluation, advanced application attack detections, and additional identity logging support. Because these capabilities are critical for all applications our customers use, we are also making these advanced capabilities freely available to non-Microsoft application developers through these same libraries.

To stay ahead of bad actors, we are moving identity signing keys to an integrated, hardened Azure HSM and confidential computing infrastructure. In this architecture, signing keys are not only encrypted at rest and in transit, but also during computational processes as well. Key rotation will also be automated allowing high-frequency key replacement with no potential for human access, whatsoever.

Finally, Smith says Microsoft will rely on AI to improve vulnerability response time:

Lastly, we are continuing to push the envelope in vulnerability response and security updates for our cloud platforms. As a result of these efforts, we plan to cut the time it takes to mitigate cloud vulnerabilities by 50 percent. We are in a position to achieve this because of our long investment and learnings in automation, monitoring, safe deployment, and AI-driven tools and processes. We will also take a more public stance against third-party researchers being put under non-disclosure agreements by technology providers. Without full transparency on vulnerabilities, the security community cannot learn collectively—defending at scale requires a growth mindset. Microsoft is committed to transparency and will encourage every major cloud provider to adopt the same approach.

It remains to be seen if Microsoft can deliver on its promise, but it’s a promising sign that the company’s executives see the need to do something different.

Software supply chain attacks are designed to hide their presence from the user. As a result, users may unwittingly run a phone with a compromised OS, giving bad actors unfettered access to their information. Google is making it easier for users to be sure their devices have not been hacked, and their OS is intact with Pixel Binary Transparency.

Software Engineer Jay Hou described the feature in a company blog post:

Pixel Binary Transparency responds to a new wave of attacks targeting the software supply chain—that is, attacks on software while in transit to users. These attacks are on the rise in recent years, likely in part because of the enormous impact they can have. In recent years, tens of thousands of software users from Fortune 500 companies to branches of the US government have been affected by supply chain attacks that targeted the systems that create software to install a backdoor into the code, allowing attackers to access and steal customer data.

One way Google protects against these types of attacks is by auditing Pixel phone firmware (also called “factory images”) before release, during which the software is thoroughly checked for backdoors. Upon boot, Android Verified Boot runs a check on your device to be sure that it’s still running the audited code that was officially released by Google. Pixel Binary Transparency now expands on that function, allowing you to personally confirm that the image running on your device is the official factory image—meaning that attackers haven’t inserted themselves somewhere in the source code, build process, or release aspects of the software supply chain. Additionally, this means that even if a signing key were compromised, binary transparency would flag the unofficially signed images, deterring attackers by making their compromises more detectable.

Google says many users won’t need to use all the features involved in Pixel Binary Transparency, but the ability is there for those that need/want it:

Most Pixel owners won’t ever need to perform the consistency and inclusion proofs to check their Pixel’s image—Android Verified Boot already has multiple safeguards in place, including verifying the hash of the code and data contents and checking the validity of the cryptographic signature. However, we’ve made the process available to anyone who wants to check themselves—the Pixel Binary Transparency Log Technical Detail Page will walk you through extracting the metadata from your phone and then running the inclusion and consistency proofs to compare against the log.

LabView got its start in the 1980s and “is a graphical programming environment engineers use to develop automated research, validation, and production test systems.” Despite decades supporting macOS, NI says the current version will be the last to support Apple’s OS.

A customer took to the company’s support forums to post a copy of the email they received from NI announcing the decision:

In addition, we are informing you that this will be the final release of LabVIEW on macOS. Starting with releases in 2024, LabVIEW will continue to be available on Windows and Linux OSes. We understand that this change of availability likely impacts your active and future plans. We have the following alternatives available for you to consider.

The VIs from the macOS LabVIEW version will port easily to LabVIEW on Windows and Linux, often without changes. In addition, the LabVIEW for macOS that you purchased includes the right to download and use LabVIEW on Windows and LabVIEW on Linux as well, so you don’t need to buy any additional software to do these migrations.

According to a follow-up post by Eric Reffett, Director of Product Management, the decision to drop macOS support was intentionally made after the migration to Apple’s custom silicon chips, as the company felt this would give Mac users the longest window to migrate or adopt an alternate solution.

NI’s decision to update LabVIEW to run on the M-series processors and latest MacOS was an intentional choice. We believed this would provide the longest transition window available for people using the MacOS version of LabVIEW.

Reffett also emphasized the company’s Linux support as a major factor in the decision:

NI moved all of its Real-Time development to Linux several years ago and many of NI’s largest partners and customers use Linux as their primary OS for test systems. NI’s decision to discontinue support on the MacOS is in-part a reflection of our need to be focused on the primary development OSes in the test systems space, which are Windows and Linux. Due to these conditions, Linux OS is an integrated part of NI’s long-term OS plans, which wasn’t true for the MacOS.

While we are sure that this decision is disappointing for MacOS users, we hope that the combination of supporting the M-series devices and the availability of LabVIEW on Linux will provide a long-enough transition window for most users to make necessary plans for how to move forward.

Nod.ai creates compiler-based automation solutions that are used by startups, enterprises, and hyperscalers. The company’s software makes it possible to deploy AI models across a broad range of applications and scenarios.

“The acquisition of Nod.ai is expected to significantly enhance our ability to provide AI customers with open software that allows them to easily deploy highly performant AI models tuned for AMD hardware,” said Vamsi Boppana, senior vice president, Artificial Intelligence Group at AMD. “The addition of the talented Nod.ai team accelerates our ability to advance open-source compiler technology and enable portable, high-performance AI solutions across the AMD product portfolio. Nod.ai’s technologies are already widely deployed in the cloud, at the edge and across a broad range of end point devices today.”

“At Nod.ai, we are a team of engineers focused on problem solving — quickly – and moving at pace in an industry of constant change to develop solutions for the next set of problems,” said Anush Elangovan, co-founder and CEO, Nod.ai. “Our journey as a company has cemented our role as the primary maintainer and major contributor to some of the world’s most important AI repositories, including SHARK, Torch-MLIR and OpenXLA/IREE code generation technology. By joining forces with AMD, we will bring this expertise to a broader range of customers on a global scale.”

The terms of the deal were not disclosed.

However, developers are often highly paid, which can create some budget
challenges, especially for small businesses. Fortunately, there’s a tried-and-true
solution many organizations turn to when seeking new talent: nearshore outsourcing:
https://otakoyi.software/blog/nearshore-software-development-a-guide-to-choosing-
an-outsourcing-partner.

Are you looking to move your company towards its goals faster while enhancing day-
to-day operations? In this article, we’ll explore the basics of nearshore software
development and how it can work and do some magic for your business.

Understanding nearshore software development

Nearshore outsourcing is about turning to software companies that are located in
neighboring countries. Example of such cooperation includes American businesses
outsourcing companies from Colombia, Canada, or Mexico. It really is a great
decision in terms of optimizing your budget.

When compared to offshore and onshore outsourcing, nearshore outsourcing is
simpler and more beneficial. Beyond the advantage of cultural similarities with the
team you’re working with, the geographic closeness translates to reduced travel
costs, minimal time zone differences, and improved communication. Moreover,
workers are likely to speak the same language, making project discussions with the
outsourced team much smoother.

Nearshoring, offshoring, and onshoring explained

When it comes to outsourcing, we have three options: nearshoring, offshoring, and
onshoring.

Nearshoring is between offshoring and onshoring. It involves outsourcing your needs
to a third-party agency in a country geographically near your location, hence the
name. Offshoring, on the other hand, means getting services from any foreign
country, regardless of its proximity. Lastly, onshoring is about keeping processes
within your own country, where your business is based. It is only up to you to decide
which approach to choose. The factors that may define your choice include budget,
time constraints, goals, and technologies needed. Why have we mentioned the
technologies? The reason is that some countries offer very specific services that are
not so developed in others.

7 ways a nearshore software development team boosts your company: a
simple breakdown

Let’s explore the top 7 reasons why companies prefer nearshoring when seeking a
software development team.

1 Shared time zone for smooth collaboration

Dealing with software development firms in far-off countries often leads to time zone
challenges. This can severely impact collaboration and effectiveness. Nearshore
software developers work in a time zone similar to your company’s, making
collaboration seamless and face-to-face meetings easy to arrange.

2 Breaking down cultural and language barriers for effective communication

Effective communication is vital for timely, high-quality project completion. Nearshore
outsourcing helps bridge the gap in language and culture, leading to better project
outcomes. Moreover, many nearshore countries share the same culture, making
communication and understanding more efficient.

3 Cost-efficiency without compromising quality

One of the primary reasons companies explore offshore outsourcing is the allure of
lower programming rates. However, nearshore outsourcing often provides cost
savings comparable to offshore outsourcing while maintaining a high standard of
work.

4 Unlocking new levels of value with fresh talent

Nearshore outsourcing brings a fresh approach to the talent pool. For companies
that may have faced challenges with outsourcing before, nearshoring offers a new
perspective, avoiding common offshore obstacles.

5 Potential savings on taxes

Major IT outsourcing firms often operate in countries with favorable taxation laws,
contributing to potential tax savings for businesses. This aspect further boosts the
attractiveness of nearshore software development.

6 Guaranteed protection of your intellectual property

Regardless of where your developer is based, your application legally belongs to you
once it’s fully developed. Nearshore software development provides the assurance
that your intellectual property is safeguarded under your country’s law. Moreover,
nearshore companies comply with your country’s rules.

7 Transparency in costs with no hidden surprises

Working in a close time zone significantly reduces the chances of developers
overcharging due to the transparency required. This keeps your project cost-
transparent, helping you avoid unexpected financial hurdles down the road.

The attractiveness and popularity of nearshore development are growing. Many big
corporations like Apple and Amazon reap the benefits of this type of cooperation. It’s
no wonder, given the advantages of hiring nearshore developers to function as a
temporary in-house team when needed. Apart from saving time and money,
nearshore developers enable your in-house team to focus on client communications
and effective project management. Moreover, there are companies that do not need
constant software services. That is one more reason why nearshore outsourcing can
be a great option for you. You will save a lot on an in-house team while achieving all
the goals you have set for your business.

Hiring a nearshore software development team is undoubtedly one of the most
trending recruitment methods. What does the future hold? There is a high chance

that nearshore outsourcing will get even more recognition among all tech giants. The
business industry has changed significantly. And it is not the final destination.

Wrapping up

Considering the modern digital environment, nearshore software development offers
a compelling solution to tackle all the issues that occur on the way. Its advantages in
shared time zones, optimized communication, cost-efficiency, talent acquisition, tax
savings, intellectual property protection, and cost transparency make it a strategic
choice for businesses. It is especially beneficial to stand out among competitors as
you will get a fresh perspective on software development. Are you ready to embrace
nearshore development and unlock new potentials for growth and success in the
competitive digital world? Don’t hold back!

Muse is a popular app for the Mac, iPad, and iPhone that offers “flexible boards for notetaking, whiteboarding, and connecting the dots.” The app is quite popular, averaging 4.7 stars in App Store reviews.

Despite its popularity, the team says it has not succeeded in turning Muse into a sustainable business, as detailed by the company’s Adam Wiggins:

Today we’re sharing some difficult news: despite all of the above, we did not manage to make Muse into a sustainable business. Therefore I and most of the team are departing. My longtime colleague Adam Wulf will continue to develop Muse as a solo entrepreneur.

Wulf, one of the engineers working on Muse, went on to emphasize his commitment to the project:

While today brings big changes, I want to reassure you that this is a new chapter in the same book. Muse is here to stay and is focused on you.

…

A bit more about me: I’ve been a software engineer with Muse for 3 years, and have worked on every aspect of the product. I’m also an entrepreneur, starting and selling my first company shortly after college. I’m most at home building well-crafted, purposeful, productivity software. In every place that I’ve worked, it’s the customers and community that make the work rewarding. Muse holds a very special place in my heart, and I’m committed to making Muse the best place for unstructured thinking.

The announcement is certainly concerning for Muse users, but hopefully Wulf is able to keep the project going, delivering what the Muse community loves about the app.

The US Bureau of Labor Statistics predicts that employment of software developers is projected to grow 22 percent from 2019 to 2029, significantly faster than the average for all occupations. This shows how popular the field is going to continue to be.

Whether you want to learn to code on your own, or to study a computer science degree at university, there are plenty of paths to becoming a software developer. This article aims to explore them as well as the skills you will need and the salary you may earn.

What Can I Study At Uni To Become A Software Developer?

Many people who want to become software developers choose to study computer science at university. This degree typically lasts for 3 years and covers a wide range of topics including but not limited to:

• Programming
• Algorithms
• Data structures
• Computer systems
• Virtual private networks 

It also allows students to specialise in areas such as artificial intelligence, cybersecurity, or software engineering.

One of the huge advantages of studying at university is the opportunity to access a wide range of resources and opportunities. You will work on projects with other students, get access to the latest research, and bounce your ideas off industry experts. 

Your degree will also give you the chance to get internships or work placements, which can help you to gain the real-world experience you need to thrive in your career. It will also help you to make contacts in your industry and potentially also help you to land your first job.

Do I Need To Go To Uni To Become A Software Developer?

No! If you would rather not study at university, or if you are already working in a different field, you can still become a software developer. You can take advantage of the wealth of information available on the internet for free, including:

• Coding bootcamps 
• Online courses 
• Ebooks
• Video tutorials

These resources can help you to gain all the skills you need to get started. Some of these resources even offer job placement services upon completion. Software tutorials can be quite helpful.

One huge advantage of this approach is that it is far cheaper than studying at university, and avoids you falling into debt. You are able to learn at your own pace and focus on gaining the skills you need for your career.

The downside is that it can be significantly harder to get your foot in the door without a degree. Although you will be able to gain all the relevant skills without a degree, you may be in a position where you have to work harder to prove your skills and experience to your potential employers. 

What Skills Do I Need To Become A Software Developer?

The skills you need to become a software developer include:

• Programming languages: You must have a certain level of competency in at least one programming language, such as Python, Java, or C++. You may need to learn multiple languages depending on the projects you work on.
• Algorithms and data structures: You will need to understand how they work in order to write efficient and effective code.
• Software development methodologies: You will need to be familiar with agile and other software development methodologies.
• Problem-solving skills: In your day-to-day life as a software developer, you must solve complex problems that require you to think creatively and analytically.
• Communication skills: You will need good communication skills to collaborate effectively with other developers, designers, and stakeholders.

How Much Do Software Developers Make?

The salary of a software developer will depend on factors such as experience, location, and industry. However, the average annual salary for a software developer in the UK is around £40,000 to £50,000. 

Entry-level positions tend to be around £25,000, whereas experienced developers can make over £80,000. 

Software developers working in industries such as finance, healthcare, and government will likely have access to higher salaries than those in other industries, and developers working in cities such as London may earn higher salaries than their countryside counterparts.

What Are The Downsides Of Becoming A Software Developer?

The downsides of working as a software developer include the following:

Long Hours

Software development can require long hours, particularly when working on a big project or when facing tight deadlines. Many software developers state that their hours can sometimes lead to burnout or work-life imbalance.

Sitting for Extended Periods

As with all computer-based jobs,  software developers spend a lot of time sitting at their desks. This can lead to health problems like back pain or carpal tunnel syndrome. To avoid these issues, it is  important to take regular breaks to stretch, walk, or engage in some light exercise.

Constant Learning

This may not be a ‘downside’ depending on your perspective. Because technology is always evolving, software developers need to keep on top of the latest developments, including learning new programming languages. This can require a lot of continuous learning, sometimes even in your free time.

Pressure to Deliver

Many software developers work on high-stakes projects. This is especially true for those working in industries such as finance and healthcare. One small mistake might lead to serious consequences, creating a sometimes overwhelming amount of pressure to deliver top-quality work under tight deadlines.

Collaboration 

Software developers often need to collaborate with designers and stakeholders, as well as other developers. These people may be remote, and even in different timezones. 

Whilst working independently may be an advantage, you may be at the helm of any clients that you have, which could mean working long hours whilst not getting the same bonuses, rewards or financial assistance from working in a large firm.

What Are The Advantages Of Becoming A Software Developer?

The advantages of working as a software developer include the following:

High Demand

The demand for skilled software developers is high, and will continue to be as long as technology continues to play such a huge role in our lives. This means that the field boasts generally strong job prospects, especially compared to other fields. 

Remote Working

Being a software developer means you could work in a fast-paced tech environment or work remotely or anywhere in the world if you wanted to. It allows for a good quality of life and work life balance if you have children or enjoy travelling.

High Salaries

Entry-level positions in software development are higher than many other fields, and the salaries only continue to grow. As developers gain experience or find a specialisation, they gain access to even higher salaries. 

Creative Problem-Solving

Software development is a creative field that gives developers a chance to use their problem-solving skills. Quick thinking is needed to create clever solutions to complex problems, which can be very satisfying for most developers. 

COBOL is one of the oldest programming languages and is used in a wide array of mission-critical applications. Unfortunately, because of its age and lack of popularity among up and coming programmers, organizations often struggle to fix or update aging COBOL code.

IBM has unveiled its solution, watsonx Code Assistant for Z, to help companies translate COBOL to Java on IBM Z.

The COBOL data processing language supports many vital business and operational processes at organizations globally. At scale, using watsonx Code Assistant for Z in comparison to other approaches could make it easier for developers to selectively and incrementally transform COBOL business services into well architected high-quality Java code – with estimated billions of lines of COBOL code as potential candidates for targeted modernization over time. Generative AI can help developers to more quickly assess, update, validate and test the right code, allowing them to more efficiently modernize large applications and focus on higher impact tasks.

“By bringing generative AI capabilities through watsonx to new use cases, we plan to drive real progress for our clients,” said Kareem Yusuf, PhD, Senior Vice President, Product Management and Growth, IBM Software. “IBM is engineering watsonx Code Assistant for Z to take a targeted and optimized approach. It’s built to rapidly and accurately convert code optimized for IBM Z, accelerate time to market and broaden the skills pool. This can help enhance applications and add new capabilities while preserving the performance, resiliency, and security inherent in IBM Z.”

“Our collaboration with IBM is an important element in our drive to leverage generative AI interfaces to challenge legacy approaches with material productivity gains, and reinvent our Capital Markets solutions,” said Roger Burkhardt, CTO, Capital Markets and AI, Broadridge Financial. “We have had excellent client response to our generative AI investments and we are intrigued by the opportunity to further our efforts by leveraging IBM watsonx Code Assistant for Z to address a broader range of platforms.”

Intel is amid an an attempted turnaround under CEO Pat Gelsinger that has seen the company re-focus on its core semiconductor manufacturing business. As part of the company’s turnaround, there are key segments Intel has been focusing on, with cloud and GPU being two such segments.

Despite their importance to the company’s plans, according to CRN, that hasn’t stopped Intel from including staff in those two departments in its latest round of layoffs.

CRN says the layoffs affect a total of 315 people in California:

The affected roles in those areas consisted of 11 GPU software development engineers and two graphics hardware engineers, an engineering manager and four engineers working on AI software as well as 28 engineers and architects working on cloud software and solutions.

The layoffs also claimed a general manager as well as an Intel fellow, the latter of which is the most prestigious title that can be given to a technical employee. CRN was unable to identify them.

Intel’s turnaround has increasingly faced an uphill battle, potentially tarnishing CEO Pat Gelsinger’s legacy in the process. The company turned in a surprise $500 million loss in one of its quarters last year, and its first-quarter 2023 results included the worst loss in the company’s history.

The fact that Intel is laying off the very type of engineers that may be crucial to its turnaround is sure to raise additional concerns.

Exploring the CI/CD Pipeline

As the demand for mobile apps continues to soar, there has never been a more pressing need for a strong CI/CD pipeline. With 7.33 billion mobile users globally, or almost the entire world’s population, mobile apps have become indispensable for a variety of functions, from playing mobile games to keeping up with social media posts. This massive demand is evident in the over 255 billion mobile app downloads worldwide in 2022 alone. As a result, it is anticipated that by 2026, demand for mobile app developers would rise from 17% to 24%.

Rapid creation is becoming more and more necessary in response to the rise in demand for mobile apps. Sixty percent of developers claim that code is released into production more quickly than in past years, with 15% releasing code three to five times quicker and 35% releasing code at a rate that is twice as quick as in 2021. Developers have considerably increased their coding pace in a relatively short amount of time, relying on CI/CD’s skills to stay on top of the game.

Challenges in Mobile App Production

However, several real-world challenges hinder mobile app production. There is a shortage of engineers with the highly specialized mobile development skills and experience required for Mobile DevOps. Additionally, evolving customer demands and expectations contribute to high uninstall rates. Buggy releases can quickly alienate customers, leaving little room for errors in the competitive mobile space. Furthermore, the industry is experiencing inflation, with rising costs associated with salaries, benefits, and even cloud-based service platforms. Surprisingly, 85% of SaaS companies have not adjusted their prices to match these increasing costs. This underscores the importance of error-free processes.

While 35% of developers claim to have fully integrated CI/CD pipelines within their organizations. This number should be higher given the immense benefits offered by these pipelines. Mobile app developers leveraging this technology can identify bugs long before the app reaches production. 50% of workflow failures occurring within an hour or less. By adopting CI/CD, developers can provide seamless mobile experiences. This surpass evolving customer expectations and release improvements at a faster pace. Consequently, this translates into higher ratings and more engaged customers.

Conclusion

Mobile CI/CD automation eliminates tedious manual tasks, freeing up developers’ mental resources to focus on creating superior apps at an accelerated rate. Elite developers are 3.7 times more likely to use continuous testing. They are 4.1 times more likely to adopt continuous delivery, and 5.8 times more likely to employ continuous integration if they meet their reliability targets. CI/CD simplifies maintenance and upgrades, enhances test reliability, increases developer satisfaction, boosts customer satisfaction, and reduces overall costs. The best CI/CD platforms offer cutting-edge services. These include advanced build pipeline management, release management, and support for both native and cross-platform development.

This blog post will provide details on various ways in which avionics software engineers can enhance their skills and stay at the forefront of this dynamic field.

Tips for Avionics Software Engineers to Improve Skills

Stay Updated with Industry Trends and Innovations

To improve as an avionics software engineer, it is important to stay up-to-date with the latest industry trends and innovations. Regularly reading technical journals, attending conferences, and following industry-leading blogs and publications can provide valuable insights into emerging technologies and best practices. By staying informed, engineers can apply new knowledge to their work and stay ahead of the curve.

Pursue Continuing Education

Continuing education is vital for avionics software engineers to enhance their skills and knowledge. Engineers can enroll in specific courses, workshops, or certification programs that focus on core areas like embedded systems, real-time operating systems, and safety-critical software development. These educational opportunities provide a deeper understanding of the domain and enable engineers to acquire new skills.

Engage in Collaborative Projects

Collaborating on projects with other engineers can significantly broaden an avionics software engineer’s skill set. By working closely with colleagues on complex tasks, they can learn from each other’s experiences, gain exposure to different development technique, and develop teamwork and problem-solving abilities. Collaborative projects also adopt innovation and encourage engineers to think creatively.

Stay Aware of Safety and Regulatory Standards

Safety and regulatory compliance are critical considerations in avionics software engineering. Engineers must stay up-to-date with industry-specific safety standards, such as DO-178C, and comply with regulatory requirements. Adhering to these standards ensures the development of safe and reliable software systems that meet aviation industry regulations.

Participate in Hackathons and Coding Competitions

Hackathons and coding competitions provide avionics software engineers with a platform to showcase their skills and creativity. These events often involve solving challenging problems within a limited timeframe, which fosters innovation and rapid skill development. Participating in such events can improve problem-solving abilities, expose engineers to new techniques and technologies, and encourage out-of-the-box thinking.

Seek Mentorship and Guidance

Avionics software engineers can greatly benefit from seeking mentorship and guidance from experienced professionals in the field. Mentors can provide valuable insights, share industry knowledge, and offer career advice. Engaging with mentors allows engineers to navigate challenges, make informed decisions, and accelerate their professional growth. Mentorship also provides a supportive network and encourages continuous learning.

Join Professional Associations and Communities

Being part of professional associations and communities enables avionics software engineers to connect with like-minded individuals and stay connected to the industry. These platforms provide opportunities for networking, knowledge sharing, and staying updated on the latest industry standards and practices. Engaging in discussions and attending events organized by these associations can broaden an engineer’s perspective and enhance their professional development.

Enhance Communication and Soft Skills

In addition to technical expertise, avionics software engineers should focus on improving their communication and soft skills. Effective communication is vital when collaborating with cross-functional teams, understanding client requirements, and conveying complex technical concepts to non-technical stakeholders. Developing strong interpersonal skills, leadership abilities, and adaptability can greatly enhance an engineer’s overall effectiveness and improve project outcomes.

Develop a Strong Foundation in Mathematics and Physics

Avionics software engineering often involves working with complex algorithms, control systems, and mathematical models. A solid understanding of mathematics and physics provides a strong foundation for designing and implementing efficient software solutions. They should continuously improve their knowledge in these areas to improve their problem-solving capabilities and ensure the accuracy and reliability of their work.

Embrace Agile Development Practices

Agile development methodologies, such as Scrum and Kanban, have gained popularity in software engineering. Avionics software engineers can benefit from adopting these practices, which promote iterative development, frequent collaboration, and flexibility in responding to changing requirements. Embracing agile practices can improve productivity, enhance teamwork, and deliver high-quality software solutions within the aviation industry’s fast-paced and evolving environment.

Utilize Code Review and Version Control Systems

Code reviews and version control systems are essential tools for improving software quality and collaboration. Avionics software engineers should actively participate in code reviews to receive feedback, identify potential issues, and learn from their peers. Version control systems help manage codebase changes, facilitate collaboration, and ensure proper documentation. Utilizing these tools enhances efficiency, promotes code quality, and maintains project integrity.

Emphasize Quality Assurance and Testing

Thorough testing and quality assurance processes are paramount in avionics software engineering. Engineers should prioritize testing at all stages of software development, including unit testing, integration testing, and system-level testing. Implementing automated testing frameworks and following best practices in software testing significantly improves the quality and reliability of avionics software. Rigorous quality assurance measures ensure that software systems function as intended and meet stringent safety requirements.

Invest in Professional Development Tools and Resources

Avionics software engineers should invest in professional development tools and resources to streamline their workflow and enhance productivity. Integrated development environments (IDEs), debuggers, modeling tools, and simulation software can assist engineers in designing, coding, and debugging complex software systems. Accessing the latest tools and staying updated on their usage can significantly improve an engineer’s efficiency and enable them to deliver high-quality work effectively.

Conclusion

Avionics software engineering is a dynamic and demanding field. To excel in this profession, avionics software engineers must continuously strive to improve their skills. By staying updated with industry trends, pursuing continuing education, engaging in collaborative projects, and embracing best practices, engineers can enhance their capabilities and contribute to the advancement of aviation technology.

According to verified posts on the anonymous forum Blind, it appears layoffs have impacted Cisco Application Centric Infrastructure (ACI), Cisco Collaboration, Data Center Services & Solutions, Experience Centers, Security Business Group, Cisco Servers, and Cisco Webex.

There appears to be a bit of confusion about the layoffs, with some employees reporting that this round coincides with the company’s annual July layoffs. It appears communication regarding the layoffs has also been somewhat sketchy.

One user described their experience:

Got to know that my name is in the layoff list through a known Senior Manager who was in meeting with my Director and frankly speaking, it’s such a toxic and controlling environment and I personally don’t want to work in that team. Little stressed as job market is very dull.

Another user said software engineers are being impacted:

Whosoever I know are software engineers and they are getting impacted. It’s a direct info from their managers. One manager fought hard to save some reports and he got some discount.

Still another user said there appear to be multiple dates for the layoffs:

Confirmed as well though I’ve heard 2 dates – 17th and 19th.

One of the groups is the one I got trolled about the “unannounced layoffs in RTP CxC”.

The decision was made weekend before July 4th to dissolve RTP CxC and shuffle jobs to MX CxC.

Those folks were all pulled from accounts unless they were escalated to be saved – USB and Wells Fargo are two on that list.

The folks in the CxC were told unsure of dates but packages were probably coming.

So there you go.

RTP CxC is all I can confirm for sure.

So GFYS trolls from last week.

More positive note – I feel for you OP and others affected… it could be any of us… seems it’s all on a whim and who’s leader’s arse you kiss the hardest.

Cisco’s last major round of layoffs impacted more than 4,000 employees in late 2022. With the current round, at least one employee said it fell below the threshold that would require a company to notify the SEC or Wall Street.

Apple Password Manager is the company’s tools to allow users to save their website passwords and sync them with iCloud. This makes the passwords available on all of a user’s Apple devices.

According to MacRumors, Apple Password Manager is about to get one of its biggest upgrades, adding the ability to work with third-party browsers.

Ricky Mondello, Software Engineering Manager at Apple, tweeted about the feature:

macOS Sonoma brings Apple’s password manager to Google Chrome, Microsoft Edge, and other browsers using their extensions stores with the “iCloud Passwords” browser extension.

If you’re running the macOS Sonoma public or developer beta, you can try it right now!

The announcement is good news for macOS users who prefer to use a different browser.

IBM unveiled watsonx in May, touting its ability to help customers become “AI advantaged,” with the tools necessary to train the AI for specific needs. The company says it is now rolling out watsonx in the form of three tools aimed at helping companies accelerate their AI adoption:

The watsonx.ai studio for new foundation models, generative AI and machine learning (now available); the watsonx.data fit-for-purpose data store, built on an open lakehouse architecture (now available); and the watsonx.governance toolkit to help enable AI workflows to be built with responsibility, transparency and explainability (coming later this year).

Watsonx is designed to allow customers to deploy the AI for specific use-case scenarios, or to custom train the model for their own needs. IBM says the platform has already been shaped by more than 150 users across a wide range of industries.

“IBM’s launch of watsonx was an awakening,” said Sean Im, Samsung SDS America, “and it has inspired us to explore the immense potential of watsonx.ai’s generative AI capabilities to deliver unprecedented innovations for our clients.”

“In an environment where the integration with our systems and seamless interconnection with various software are paramount, watsonx.ai emerges as a compelling solution,” said Atsushi Hasegawa, Chief Engineer, Honda R&D. “Its inherent flexibility and agile deployment capabilities, coupled with a robust commitment to information security, accentuates its appeal.”

IBM says it will continue to build on watsonx in the coming year, adding improved governance features and regulatory compliance.

Over the next year, watsonx will continue to evolve and we expect to make significant releases. We will be focused on expanding enterprise foundation model use cases beyond NLP and operationalizing 100B+ parameter models for bespoke, targeted use cases – opening the door to broader enterprise adoption.

We will also bring to bear the strength of our AI governance capabilities – helping organizations to implement end-to-end lifecycle governance, mitigate risk and manage compliance to the growing AI and industry regulations. AI governance should never be an afterthought, so we encourage our customers begin governance of their ML models and foundation models at the outset.