Daily Tech Digest - February 09, 2023

The role of the database in edge computing

In a distributed architecture, data storage and processing can occur in multiple tiers: at the central cloud data centers, at cloud-edge locations, and at the client/device tier. In the latter case, the device could be a mobile phone, a desktop system, or custom-embedded hardware. From cloud to client, each tier provides higher guarantees of service availability and responsiveness over the previous tier. Co-locating the database with the application on the device would guarantee the highest level of availability and responsiveness, with no reliance on network connectivity. A key aspect of distributed databases is the ability to keep the data consistent and in sync across these various tiers, subject to network availability. Data sync is not about bulk transfer or duplication of data across these distributed islands. It is the ability to transfer only the relevant subset of data at scale, in a manner that is resilient to network disruptions. For example, in retail, only store-specific data may need to be transferred downstream to store locations.

Data management in the digital age

To ensure effective data management, organisations can adopt various strategies and tactics that have proven their worth in modern organisations. The first of these is a comprehensive risk assessment. Performing risk assessments regularly will ensure that you can identify and prioritise vulnerabilities before they become gaping security holes that can be exploited. Ongoing risk assessments should be bolstered by robust and current security and data management policies that reflect the threat landscape. “You also need to implement employee training and communication because humans are often the weakest link in even the most advanced security system,” says Grimes. “You must ensure that security is understandable and accessible and that the lessons are driven home through constant reminders and training programmes. All it takes is one click to bring down the most sophisticated security system on the planet.” It’s also important to collaborate with vendors and partners that understand the security landscape and have the tools and expertise required to support the organisation’s security posture. 

Coaching IT pros for leadership roles

You can teach someone to code, manage money, and complete the tasks of being a manager. But teaching is limited. To develop a leader, you have to coach them to become someone who can make decisions on their own, communicate well, and plan strategically. But the transition from teacher to coach can be challenging. ... Then practice what Davis calls the “ask first, tell second” method of coaching. “Ask them what’s exciting about this. Then ask what’s scary?” And, since the core skill of coaching is listening, “give them the time and space to answer and listen to what they say,” she says. They might not want to give up the thing they are good at to learn something hard. They might feel jealous of team members who get to keep their hands on the technology. They might fear that others aren’t good enough to do the work they’ve been doing. And they might not yet see the benefits of a leadership role. In the “tell” portion, point out the influence they will have on larger issue in the company, the essential role of managers on the team, the pleasure of helping people grow into larger careers, and how this will give them a seat at the table.

4 characteristics of enterprise application platforms that support digital transformation

The need to deploy applications in various different cloud infrastructures—public cloud, private cloud, physical, virtual, and edge—based on business needs is a key requirement for most established enterprises. As more and more business value is created with the Internet of Things (IoT), edge computing, and artificial intelligence and machine learning (AI/ML), the need to deploy applications across these cloud providers from devices, edge datacenters, on-prem, and colocation providers to the public cloud ecosystem is growing exponentially. For an enterprise, a baseline application platform that can be deployed on all these cloud provider types is essential, if not vital, to support current and future business needs. Another aspect to consider is the growth and distribution of enterprise data. As the famous saying goes, "data is the new oil," and the amount and pace of enterprise data growth are unprecedented. Enterprises are looking at options to leverage this data to create meaningful business insights. 

How to Combine RPA and BPM the Smart Way

Seamless digital integration is more than just cobbling together the best digital solutions on the market. How these advanced technologies interact makes a huge difference. Technologies designed to work together are crucial to achieving the productivity gains promised by digital transformation. With a comprehensive platform, organizations don’t need to worry about building integrations because the platform already includes them. Moreover, a single platform is easier to buy and manage because it comes from the same licensor rather than going through the procurement process with multiple suppliers. Companies need to take care when determining which IA platform to adopt. The benefits of a comprehensive platform are increasingly recognized by vendors and their customers, pushing suppliers to put together multifeatured automation platforms. If companies choose a platform insufficient for their needs, they face reworking costs down the road. Nevertheless, suppose organizations have already taken on technical debt and are looking to rework their digital transformation journey.

5 Technologies Powering Cloud Optimization

Cloud cost management is a critical component of optimization that helps organizations to monitor and manage their cloud spend. The goal is to ensure that organizations are only paying for the cloud resources they actually need and that they are using those resources efficiently. ... Autoscaling is a technology that enables organizations to automatically scale their cloud resources up or down as needed to meet changing demands. The goal of autoscaling is to ensure that organizations always have the right amount of resources to support their workloads while minimizing costs and ensuring that their systems are always available when they are needed. Autoscaling works by monitoring the performance and usage of cloud resources, such as compute instances, storage and network traffic, and automatically adjusting the size of those resources to meet changing demand. ... An API gateway is a server that acts as an intermediary between an application and one or more microservices. The API gateway is responsible for request routing, composition and protocol translation, which enables microservices to communicate with each other securely and efficiently.

Streaming Data Management for the Edge

Managing data at the edge is actually quite easy. What’s hard is how you monetize it. How do you get value from it? How do you take the data that’s streaming into the organization and analyze it, inference on it, and act on it as it’s coming in? How do you use this data to help your customer or stakeholder Think about a retailer who’s trying to do in-store queue management, trying to identify situations where customers are abandoning their carts because the lines are too long, where you’re trying to watch for theft, for shrinkage. It isn’t the management of the data that’s as big a challenge. It is the ability to take that data and make better operational decisions at the point of customer interaction or operational execution. That’s the challenge. And so, we need a different mental frame as well as a different data and analytics architecture that is conducive to the fact that this data that’s coming in, in real time, has value as it’s coming in. Historically, in batch worlds, we didn’t care about real-time data. The data came in. 

DevOps isn’t dead: How platform engineering enables DevOps at scale

Platform engineers could automate almost all this work by building it into an IDP. For example, instead of manually setting up Git repositories, developers can request a repository from the IDP, which would then create it. The IDP would then assign the right user group and automatically integrate the correct CI/CD template. The same pattern applies to creating development environments and deploying core infrastructure. The IDP acts as a self-service platform for developers to request services and apply configurations, knowing security best practices and monitoring are built in by default. IDPs can also automatically set up projects in project tracking software and documentation templates. As you can see, platform engineers don’t replace DevOps processes. They enhance them by building a set of standardized patterns into a self-service internal development platform. This removes the burden of project initialization so teams can start providing business value immediately, rather than spending the first few weeks of a project setting up and working through teething issues.

The Dos and Don‘ts of API Monetization

Before diving into best practices and antipatterns, let’s go over the core technical requirements for enabling API monetization:Advanced metering: Because different customers may have different levels of access to APIs under varying pricing plans, it’s critical to be able to manage access to API requests in a highly granular way, based on factors like total allowed requests per minute, the time of day at which requests can be made and the geographic location where requests originate. Usage tracking: Developers must ensure that API requests can be measured on a customer-by-customer basis. In addition to basic metrics like total numbers of requests, more complex metrics, like request response time, might also be necessary for enforcing payment terms. Invoicing: Ideally, invoicing systems will be tightly integrated with APIs so that customers can be billed automatically. The alternative is to prepare invoices manually based on API usage or request logs, which is not a scalable or efficient approach. Financial analytics: The ability to track and assess the revenue generated by APIs in real time is essential to many businesses that sell APIs. 

How to unleash the power of an effective security engineering team

Security engineering teams should be able to build and operate the services they produce. You build it. You run it. This level of ownership within a group is vital from a technical competence standpoint and culturally, setting the tone around accountability. Technically speaking, a team that can own its services will proficiently manage infrastructure, CI/CD tooling, security tooling, application code, deployments, and the operational telemetry emitted from a service. In addition, the skills backing all that support as a team are likely to be highly transferable in support of other groups across the organization. Teams that understand, embrace, and optimize for DevX are likely more favored. Beyond that, it will have a particular focus on eliminating friction. Friction makes things take longer and cost more, creates longer learning cycles, and can lead to frustration. Less friction will lead to things generally running much smoother. Sometimes friction is necessary and should be intentional. An example is a forced code review on critical code before it's merged. 

Quote for the day:

"Leadership is liberating people to do what is required of them in the most effective and humane way possible." -- Max DePree

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