Like Agile, chaos engineering is more than a set of activities and workflows—it’s also a state of mind. Your people and your culture must be ready and able to adopt chaos principles, as well as chaos processes. For the DevOps leader, adopting a new mindset might sound a little, well, vague. But this shift is based on concrete actions, not just philosophical musings. Consider an example from the world of cloud infrastructure: a mission-critical application that is hosted within a cloud service could be at risk for failure if, say, that cloud service is centralized in a single location, or within a limited number of microservices within the cloud infrastructure. But if the app is hosted in a distributed way, you can create greater opportunity for application-level availability and resilience, and you can test for that resilience within the existing production environment. This kind of distributed architecture isn’t brand-new for most enterprises, and, therefore, the process of developing applications in way that tests for availability in a variety of infrastructure scenarios also shouldn’t be a foreign concept. As a DevOps leader, you can build a culture of resilience-centric thinking by empowering your teams with the tools they need to adopt chaos-style testing, and then showing them how to build that thinking into every sprint and every standup.
For Intel, the year 2020 was a roller coaster ride. The company saw more lows than highs. If Apple delivered the much dreaded news to the company, its rivals— NVIDIA and AMD chipped in with more bad news with mega acquisitions and advancements in technology. Intel’s woes didn’t end there. Last year, rockstar chip architect Jim Keller, who was hired to put Intel on top again, resigned after a brief stint at the company; this is Keller’s shortest tenure compared to his time at Apple and Tesla. Then there was Chief Engineer Venkata Murthy Renduchintala, who promised in 2019, that the Intel’s next gen 7nm chips were on track to start production in 2021. That didn’t happen. Intel parted ways with Renduchintala as part of a technical team shake up. Constant engineering hiccups and internal debates of whether Intel needs to outsource manufacturing further delayed the arrival of next gen CPUs. The top brass of the company moving in and out also signals Intel’s leadership vulnerabilities. Current chief Bob Swan who will be replaced soon, was also only appointed a couple of years ago. Swan was tasked with restructuring the company to adjust to the disrupting technologies like AI and cloud.
Microsoft reported a battle with North Korean-sponsored hackers who attacked security researchers with a most innovative technique: compromised Visual Studio projects. The attack was attributed to a group called ZINC, said to be associated with the Democratic People's Republic of Korea (DPRK). A Jan. 28 post titled "ZINC attacks against security researchers" described the organization as a DPRK-affiliated and state-sponsored group. That determination was based on "observed tradecraft, infrastructure, malware patterns, and account affiliations." "This ongoing campaign was reported by Google’s Threat Analysis Group (TAG) earlier this week, capturing the browser-facing impact of this attack," Microsoft said. "By sharing additional details of the attack, we hope to raise awareness in the cybersecurity community about additional techniques used in this campaign and serve as a reminder to security professionals that they are high-value targets for attackers." While such battles between hackers and enterprises and security organizations are obviously common and ongoing, one unusual aspect of this encounter was the choice of payloads for the bad code.
Innovating trustworthy AI/ML depends on the design, development and distribution of AI systems that learn from and work collaboratively with humans in a comprehensive and meaningful fashion. It's critical for security and privacy to be considered at the start of any new technology's architecture. They cannot be properly included as an afterthought; the absolute highest required level of security and protection of data must be incorporated in both hardware and software, which will ensure that it is already configured into all steps of the development and supply chain — beginning with design all the way through to the technology's business and utilization model. The Charter of Trust initiative for IoT cybersecurity (of which we're a partner) has also provided excellent guidelines for a risk-based methodology and verification that should be incorporated as core requirements throughout that supply chain. After we identify the core principles that will govern AI development, we must then determine how to ensure these ethical AI systems are not compromised. Machine learning can monitor data and pinpoint anomalies, but it unfortunately also can be used by hackers to increase the impact of their actual cyberattacks.
For those on the front lines, a restructuring can feel more like something done to them than with them. Managers might overlook the experience and insights of those expected to innovate, collaborate, and satisfy customers within the new structure. And there is often an explicit or implicit power dynamic that distorts functional considerations as executives jostle for control of prominence and resources. An alternative to the top-down approach is to let function drive form, supporting those most directly connected to creating value for customers. Think of it as bottom-up or outside-in. One discipline useful in such efforts is social design, a subspecialty of design that aspires to solve complex human issues by supporting, facilitating, and empowering cultures and communities. Its practitioners design systems, not simply beautiful things. I spoke with one of the pioneers in this area, Cheryl Heller, author of The Intergalactic Design Guide: Harnessing the Creative Potential of Social Design. Her current work at Arizona State University centers on integrating design thinking and practice into functions that don't typically utilize design principles. “People’s work is often their only source of stability right now,” she told me. “You have to be careful, because people are brittle.”
The initial tendency may be to install more APs in hopes of finding an easy fix, but doing so without careful analysis can make the situation even worse. Proper roaming requires more than just good signal strength throughout coverage areas; it takes a careful balance between the coverage of each AP on both 2.4 and 5GHz bands to make roaming work right. ... Getting the coverage overlap just right between all the APs in your network is one of the most important things you can do to help improve the roaming. At the same time, it is one of the toughest. You have to check the coverage throughout the coverage areas and analyze the overlapping. If issues are found you need to figure out how to address them, perform the fix, and then double-check that it’s actually fixed. Keep in mind you want about a 15% to 20% coverage overlap between AP cells, using -67dBm as the signal boundary for each cell. You want to look at both bands, too, keeping in mind 2.4GHz naturally provides longer range than 5GHz. Less overlap can result in spots with bad signals. If you have too much overlap between AP cells in either band, it can cause co-channel interference and “sticky” clients that don’t roam, which can result in APs that become overloaded with clients.
UK's leading AI startup and scaleup founders highlight the main pain points of running an AI business
Looking specifically at financial institutions, Hodgson says that they must ensure that their data foundations are fit for purpose. “Data is the raw material of our industry, and without it, the benefits and potential of AI are stunted and capped before the system even gets switched on. Many financial institutions already sit atop mountains of their own data in addition to buying more from vendors — yet they do not have the time, the resources or the staff expertise to sift through it,” Hodgson explains. Dr Richard Ahlfeld, founder and CEO at Monolith AI — a startup that builds new machine learning software to help engineers to improve the product development process, echoes this view. He says: “Any pain points tend to boil down to the data: getting the data, ensuring data security, making sure that you can trust the data. “There’s no standardisation of what makes data ‘valuable’ across the industry either, and not all engineers follow the same protocols and practices. For example, deciding what data to keep can be tricky as it’s hard to anticipate what might or might not be useful to have in the future. Even saving data from failed ventures (a practice which is often overlooked) can have its value, as it acts as a reference for future experiments.”
While it's positive that a higher percentage of these victims are choosing not to pay cyber criminals, there's still a large number of organisations that do give in – allowing ransomware to continue to be successful, even if those behind attacks have been making slightly less money. However, it might be enough for some ransomware operators to consider if the effort is worth it. "When fewer companies pay, regardless of the reason, it causes a long-term impact, that compounded over time can make a material difference in the volume of attacks," said a blog post by Coveware. The rise in organisations choosing not to give into extortion tactics around ransomware has also led the gangs to change their tactics, as shown by the increase in ransomware attacks where criminals threaten to leak stolen data if the victim doesn't pay. According to Coveware, these accounted for 70% of ransomware attacks in the final three months of 2020 – up from 50% during the previous three months. However, while almost three-quarters of organisations threatened with data being published between July and September paid ransoms, that dropped to 60% for organisations who fell victim between October and December.
Agrochemical companies are already experimenting with advanced data science techniques to overcome these challenges: they employ drones to capture high-resolution aerial images of the farms and apply computer vision techniques and other complex algorithms to process the images. However, challenges persist; leaf characteristics such as orientation, alignment, length, shape and twists are difficult to discern when viewed from above, particularly in crops that grow tall and narrow, such as maise. Further complexities are introduced by variability in ambient light conditions, soil terrain, cloud refraction, occlusion and other environmental factors. Finally, all these factors vary over time, which means that to get a clear picture of plant health and treatment performance, regular measurement is required. As deep learning and computer vision fields mature, scientists are beginning to use these technologies for such LAI measurements, and more. Tiger Analytics has collaborated with leading agrochemical companies to develop such solutions. In this article, we outline the possible approaches and challenges. The primary challenge in developing a deep learning solution is the near nonexistence of training data.
Provisioning blanket exemption to government agencies from the application of the data protection law and processing obligations (Section 35, PDP Bill) poses a challenge to reforming and upgrading the data access and surveillance regime. The importance of procedural safeguards, the right to effective recourse, and necessary and proportionate access principles has been reiterated by numerous Supreme Court judgments like PUCL v. Union of India and K.S. Puttaswamy v. Union of India. Such an exemption might inadvertently curtail the government’s stated vision of becoming the data processing and analytics hub of the world, and dent digital economy goals. According to the updated draft of the Standard Contractual Clauses (SCCs) by the European Commission on personal data transfers outside the European region, data exporters must take into account the laws and overall regime that enable public authorities to access personal data through binding requests in the destination country, and gauge if they meet “necessary and proportionate” requirements expected from a “democratic society”. If governments and businesses find the exemption under Section 35 of the PDP Bill excessive, digital trade and investments, and the ability to forge agreements, might be impacted.
Quote for the day:
"Trust is one of the greatest gifts that can be given and we should take creat care not to abuse it." --Gordon Tredgold