Firstly, public bodies should focus on outcomes rather than output. By identifying where an immediate impact can be made to address the challenges of legacy technology – rather than trying to fix everything at once – you can empower digital partners and discovery teams to identify issues and make key decisions without blockers from other teams, existing structures or business areas. Removing this red tape will mean decisions and actions will be taken at a pace, delivering greater value and results in the process, rather than creating complicated services that users struggle to navigate. The next focus to enhance digital discovery should be diversity, building and working with project teams that cover a wide range of disciplines and skill sets, as well as ages, races and genders. Increased diversity means that a discovery team benefits from different experiences and frames of reference, helping to avoid conformity and a groupthink mentality, which can result in issues being missed or solutions not being considered as everyone is thinking on the same page. For example, including people from non-digital backgrounds in a discovery team, such as service users, will help to identify problems that otherwise may be missed.
The global pandemic has accelerated enterprise IT teams’ desire to simplify the management of complex multi-cloud and edge environments and operate them holistically as a single WAN. It is also driving IT requirements for delivering the highest levels of application performance for all their cloud-hosted business applications, from any network in the emerging post-pandemic environment. This shift is intensifying the urgency to transform conventional data center and MPLS-centric and VPN-based networks to a more modern hybrid SD-WAN environment that combines MPLS and internet with secure managed internet-based cloud services. In a hybrid WAN environment, application performance across a WAN can vary considerably from site to site or region to region because of underlying factors such as latency, packet loss and jitter that must be taken into consideration, especially using a mix of MPLS and broadband connectivity services. The Aruba EdgeConnect SD-WAN edge platform, acquired with Silver Peak, supports advanced visibility, routing, control and intent-based policy management for any application – thereby improving the performance and availability of business applications by dynamically routing traffic to virtually any site, automatically adapting to real-time network conditions.
While theories governing corporate strategy have been debated (and sometimes overthrown) over the years, real time strategy focuses on modernizing an aspect that has practically been left untouched: methodology. AI techniques, which include machine learning, can import data from an abundance of sources, identify patterns and trends, and supply insights for decision-makers. In the process, AI-enabled planning upends traditional processes that depend on (and are affected by) human bias. Too often, the authors point out, current strategic decisions are based on information that is flawed across multiple dimensions (e.g., completeness, accuracy) and end up being unduly influenced by intuition and experience. During the exhaustive process of devising a plan, many assumptions and hypotheses are undeservedly promoted to “facts,” especially if they help dim uncertainty. The result: strategic plans that gain consensus, but emerge with a blandness akin to vision statements—and no mechanism for consistent follow-up. Without alignment among business units as to how each defines success, even companies that have embraced AI can end up stalled on the AI maturity curve, unable to progress beyond early victories in cost reductions and productivity gains.
Researchers claim to have discovered the identity of the operators of Hades ransomware, exposing the distinctive tactics, techniques, and procedures (TTPs) they employ in their attacks. Hades ransomware first appeared in December 2020 following attacks on a number of organizations, but to date there has been limited information regarding the perpetrators. ... The findings are a result of incident response engagements carried out by Secureworks in the first quarter of 2021. “Some third-party reporting attributes Hades to the Hafnium threat group, but CTU research does not support that attribution,” the researchers wrote. “Other reporting attributes Hades to the financially motivated Gold Drake threat group based on similarities to that group’s WastedLocker ransomware. Despite use of similar application programming interface (API) calls, the CryptOne crypter, and some of the same commands, CTU researchers attribute Hades and WastedLocker to two distinct groups as of this publication.” ... “Typically, when we see a variety of playbooks used around a particular ransomware, it points to the ransomware being delivered as ransomware-as-a-service (RaaS) with different pockets of threat actors using their own methods,"Marcelle Lee, senior security researcher, CTU-CIC at Secureworks, tells CSO.
“Previously, building models, building features, was extremely difficult” and typically required a data scientist. “But today, particularly for SMEs, this type of automation tool can help those aspects a lot…Our type of automation is definitely helping them to ramp up the speed of their AI journey.” Fujimaki noted how one of dotData’s smaller customers was able to build AI solutions without a huge investment. The company, Sticky.io, develops a subscription management service that is provided to other businesses as a SaaS offering. It wanted to add a predictive capability to identify payments that were likely to fail. “For them, the biggest barrier was…skill,” Fujimaki tells Datanami. “They are a cloud-native company, so the data is stored in AWS. On the AI side, they didn’t have data scientists, so they needed AutoML functionality.” Sticky.io’s product manager was able to use dotData to comb through their data and identify the right features that would go into the predictive model. Even though he didn’t posses preexisting talents in data science, the pilot was a success, and Sticky.io’s leadership recognized the value that it brought. “The most important skill that [customers] have to have is the input side and output side,” Fujimaki says.
The very first question is where to start the migration. Here, we can use domain-driven design to help us identify aggregates and the bounded contexts where each represents a potential unit of decomposition and a potential boundary for microservices. Or, we can use the event storming technique created by Antonio Brandolini to gain a shared understanding of the domain model. Other important considerations here would be how these models interact with the database and what work is required for database decomposition. Once we have a list of these factors, the next step is to identify the relationships and dependencies between the bounded contexts to get an idea of the relative difficulty of the extraction. Armed with this information, we can proceed with the next question: Do we want to start with the service that has the least amount of dependencies, for an easy win, or should we start with the most difficult part of the system? A good compromise is to pick a service that is representative of many others and can help us build a good technology foundation. That foundation can then serve as a base for estimating and migrating other modules.
AIOps is much more than another buzzword or a simple tool to correlate incidents. When implemented properly, AIOps can detect anomalies automatically and help remediate and prevent incidents before they impact end-users and customers. Once anomalies or incidents are detected, it takes a further step and provides structured analysis and detail on what these issues are and what the root cause is. This allows the IT team to understand the problem within minutes, and fix it faster, preserving user experience and avoiding disruptions to the business. This is observability in action. When working with telemetry data, AIOps can pick the right team to alert of issues it detects early, and provide actionable insights so that operations become more efficient and DevOps teams can focus on innovation, rather than spending non-productive time reactively troubleshooting problems. ... There is no real reason why a smaller teams could not use AIOps to differentiate their business and correct operational issues and also decrease human burden. In fact for small teams, AIOps can help to quickly discover issues and decrease pressure on already busy teams who need to eliminate toil to focus on value creation.
Data scientists will be extinct in 10 years (give or take), or at least the role title will be. Going forward, the skill set collectively known as data science will be borne by a new generation of data savvy business specialists and subject matter experts who are able to imbue analysis with their deep domain knowledge, irrespective of whether they can code or not. Their titles will reflect their expertise rather than the means by which they demonstrate it, be it compliance specialists, product managers or investment analysts. We don’t need to look back far to find historic precedents. During the advent of the spreadsheet, data entry specialists were highly coveted, but nowadays, as Cole Nussbaumer Knaflic (the author of “Storytelling With Data”) aptly observes, proficiency with Microsoft Office suite is a bare minimum. Before that, the ability to touch type with a typewriter was considered a specialist skill, however with the accessibility of personal computing it has also become assumed. Lastly, for those considering a career in data science or commencing their studies, it may serve you well to constantly refer back to the Venn diagram that you will undoubtedly come across.
As organizations accelerate digitization, they need a way to simplify management and security across the network and edge devices. "With our new routing portfolio, customers can have a united architecture across their diverse edge use cases from HQ to remote edges. The same rich functionality and robust security models across your entire business – from campuses and branch offices to substations, remote operating locations, fleets, on-the-go connected assets," wrote Butaney. "Now utilities can securely connect their edge to reduce outages, integrate renewables, and improve grid resiliency. Transportation systems providers can optimize routes for first responders and share real-time location and safety information with travelers. Whatever your business, you can connect all your networks with one common architecture and holistic enterprise-wide security approach," Butaney stated. The modular routers, including the Catalyst IR8100, IR8100 Heavy Duty Series and IR8300 Rugged Series Router, can be customized, and all can have storage or CPUs upgraded in the field.
The original mission of JReleaser is to streamline the release and publishing process of Java binaries in such a way that these binaries may be consumed by platform-specific package managers, that is, provide a ZIP, TAR, or JAR file. JReleaser will figure out the rest, letting you publish binaries to Homebrew, Scoop, Snapcraft, Chocolatey, and more. In other words, JReleaser shortens the distance between your binaries and your consumers by meeting them where they prefer to manage their packages and binaries. Early in JReleaser’s design, it became apparent that splitting the work into several steps that could be invoked, individually or as one single unit, would be a better approach than what GoReleaser offers today. This design choice allows developers to micromanage every step as needed to hook-in JReleaser at a specific point of their release process without having to rewrite everything. For example, you can fire up JReleaser and have it create a Git release (GitHub, GitLab, or Gitea) along with an automatically formatted changelog, or you can tell JReleaser to append assets to an existing Git release that was created by other means, or perhaps you’re only interested in packaging and publishing a package to Homebrew regardless of how the Git release was created.
Quote for the day:
"Whenever you see a successful business, someone once made a courageous decision." -- Peter F. Drucker