There’s no denying that the world is rapidly changing, with innovations such as artificial intelligence, robotics, blockchain, and the cloud. Each of the previous three industrial revolutions, including the most recent digital revolution, led to economic growth and helped eliminate mass poverty in many countries. However, these moments also concentrated wealth in the hands of those that control new technologies. VCs will play an increasing role in determining what tech factors into our daily lives over the next ten years and we must ensure that technology is used to modernize antiquated industries and can create a better standard of living worldwide. Ensuring that this new wave of technology benefits as many as possible is the challenge of our generation, especially considering that the pending climate crisis will disproportionately impact lower-income and marginalized communities. Bitcoin farms do not benefit maize farmers in Lagos who face deadly floods but VCs' obsession with crypto generates outsized investment and the wealthy get wealthier.
One of the barriers to assessing the cost of risks and opportunities in climate-change research is the lack of reliable and readily accessible data about climate. This data gap prevents financial sector stakeholders and others from assessing the financial stability of mitigation and resilience efforts and channeling global capital flows towards them. It also forces businesses to engage in costly, improvised ingestion and curation efforts without the benefit of shared data or open protocols. To address these problems, the Open Source Climate (OS-Climate) initiative is building an open data science platform that supports complex data ingestion, processing, and quality management requirements. It takes advantage of the latest advances in open source data platform tools and machine learning and the development of scenario-based predictive analytics by OS-Climate community members. To build a data platform that is open, auditable, and supports durable and repeatable deployments, the OS-Climate initiative leverages the Operate First program.
Managing security in the cloud is a daunting task, especially for a multicloud. For this reason, the recommended approach is to have Cloud Security Control Framework early in any cloud migration strategy. But what does this mean? Today the best practice is to change the security mentality from perimetral security to a more holistic approach, which considers cybersecurity risks from the very design of the multicloud deployment. It starts by allowing the DevSecOps team to build/automate modular guardrails around the infrastructure and application code right from the beginning. And you can consider these guardrails as cross-cloud security controls based on the current trend of implementing Zero Trust networking architecture. Under this new paradigm, all users and services are “mistrusted” even within the security perimeter. This approach requires a rethinking of access controls since the workloads may get distributed and deployed across different cloud providers. Implementing security controls at all levels is a key, from infrastructure to application code, services, networks, data, users’ access, etc.
Enterprise technology is always moving forward, and so, as more businesses move to a cloud-focused strategy, the boundaries of what that means are evolving. New models such as serverless and multi-cloud are redefining the ways in which companies will need to manage the flow and ownership of their data, and they’ll require new ways of thinking about how data is governed. According to Syed, these new models are going to make even more important the ability to decentralize data architecture while maintaining centralized governance policies. “A lot of companies are going to invest in trying to figure out, ‘How do I build something that combines not just my one data source, but my data warehouse, my data lake, my low-latency data store and pretty much any data object I have?’ How do you bring it all together under one umbrella? The tooling has to be very configurable and flexible to meet all the different lines of businesses’ unique requirements, but also ensure all the central policies are being enforced while you are producing and consuming the data.”
Organizations can be caught out by thinking that they can lift-and-shift their existing applications, services and data to the cloud, where they will be secure by default. The reality is that migrating workloads to the cloud requires significant planning and due diligence, and the addition of cloud management expertise to their workforce. Workloads in the cloud rely on a shared responsibility model, with the cloud provider assuming responsibility for the fabric of the cloud, and the customer assuming responsibility for the servers, services, applications and data within (assuming an IaaS model). However, these boundaries can seem somewhat fuzzy, especially as there isn’t a uniform shared responsibility model across cloud providers, which can result in misunderstandings for companies that use multi-cloud environments. With so much invested in cloud infrastructure – and with a general lack of awareness of cloud security issues and responsibilities, as well as a lack of skills to manage and secure these environments – there is much to be done.
Leaders who work with agile teams focus on ensuring that the teams have the support (tools, access, resources) and environment (culture, people, external processes) they need, and then trust them to get the job done. This principle can scare some leaders who have a more command-and-control management style. They wonder how they'll know if their team is succeeding and focusing on the right things. My response to these concerns is to focus on the team’s outcomes. Are they delivering working product frequently? Are they making progress towards their goals? Those are the metrics that warrant attention. It is a necessary shift in perspective and mindset, and it is one that leaders as well as agile teams need to make to achieve the best results. To learn more about how to support agile teams, leaders should consider attending the Professional Agile Leadership - Essential class. Successful agile leaders enable teams to deliver value by providing them with the tools that they need to be successful, providing guidance when needed, embracing servant leadership and focusing on outcomes.
With the beginning and end states clearly articulated, you can then specify a step-by-step journey, with projects sequenced according to which ones can do the most in early days to lay essential foundations for later initiatives. Here’s an example to illustrate how this approach can lead to better choices. At a construction equipment manufacturer, there are three tempting areas to automate. One is the solution a vendor is offering: a chatbot tool that can be fairly simply implemented in the internal IT help desk with immediate impact on wait times and headcount. A second possibility is in finance, where sales forecasting could be enhanced by predictive modeling boosted by AI pattern recognition. The third idea is a big one: if the company could use intelligent automation to create a “connected equipment” environment on customer job sites, its business model could shift to new revenue streams from digital services such as monitoring and controlling machinery remotely. If you’re going for a relatively easy implementation and fast ROI, the first option is a no-brainer. If instead you’re looking for big publicity for your organization’s bold new vision, the third one’s the ticket.
As the fallout of the Great Resignation is still being felt by many enterprises, there are four main concerns raised by Code42’s report. As 4.5 million employees left their jobs in November 2021 alone, this has created the first big challenge for industry leaders in protecting their data. Many employees leaving their roles have accidentally or intentionally taken data with them to competitors within the same industry, or even sometimes leveraged their former employers’ data for ransom. Business leaders are concerned with the types of data that are leaving, according to 49% of respondents, and 52% said they are concerned with what information is being saved on local machines and personal hard drives. Additionally, business leaders are more concerned with the content of the data that is exposed rather than how the data is exposed. Another major concern comes in the form of a disconnect when it comes to the problem of employees leaving in droves, creating uncertainty about ownership of data. Cybersecurity practitioners want more say in setting their company’s security policies and priorities to the company since they are dealing with the risks their employers face.
In addition to being time-consuming to build, once-off bridges are often highly centralized, acting as intermediaries between protocols. Built, owned, and operated by a single entity, these bridges become bottlenecks between different ecosystems. The controlling entity decides which tokens to support and which new networks to connect. ... Another impact of the siloed nature of the blockchain space is that developers are forced to choose between blockchain protocols, and end up building dapps that can be used on only one network, but not the others. This cuts the potential user base of any solution down significantly and prevents dapps from reaching mass adoption. Developers then have to spend resources deploying their apps across multiple networks which for many means to fragment their liquidity across their network-specific applications. From these struggles and drains on time and money, we know that a more universal solution for interoperability is the only way forward. Our industry, perhaps the most innovative in the world today and packed with the most talented minds, must prioritize the principles of universality, decentralization, security, and accessibility when it comes to interoperability.
Lean is a methodology for organizational management based on Toyota’s 1930 manufacturing model, which has been adapted for knowledge work. Where Agile was developed specifically for software development, Lean was developed for organizations, and focuses on continuous small improvement, combined with a sound management process in order to minimize waste and maximize value. Quality standards are maintained through collaborative work and repeatable processes. ... Eliminate anything not adding value as well as anything blocking the ability to deliver results quickly. At the same time, empower everyone in the process to take responsibility for quality. Automate processes wherever possible, especially those prone to human error, and get constant test-driven feedback throughout development. Improvement is only possible through learning, which requires proper documentation of the iterative process so knowledge is not lost. All aspects of communication, the way conflicts are handled, and the onboarding of team members should always occur within a culture of respect.
Quote for the day:
"Take time to deliberate; but when the time for action arrives, stop thinking and go in." -- Andrew Jackson