Articles

Monitoring and Governance for AKS Costs With Kubecost

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When running Azure Kubernetes Service (AKS), it can be hard to understand and allocate costs in environments with multiple teams, projects, or even departments. With Kubecost, you gain full transparency into your Kubernetes usage and cost within minutes of installation. Officially launched in 2019 and built on open source, Kubecost now monitors over one billion dollars in Kubernetes spend, and enables startups and global enterprises alike to understand their spend and identify cost savings ranging from 30% to over 50%. Kubecost supports a wide range of self-managed and hosted Kubernetes environments, including Azure Kubernetes Service, which we’ll cover today in this article.

The Microsoft Azure Kubernetes Service (AKS) is a popular fully managed Kubernetes service that offers embedded continuous integration and continuous delivery as well as enterprise-grade security and governance— powerful tools for teams adopting Kubernetes. As with any complex infrastructure, AKS requires proper governance and financial transparency for successful organizational adoption. Kubecost, an open source tool that provides teams with visibility into Kubernetes spend and supports environments hosted in Azure, is a widely recommended solution for engineers and finance teams facing this problem. Note: This documentation page for AKS provides helpful context for using Kubecost to implement a cost governance strategy.

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No-Code:  »It’s a Trap! »

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Gartner predicts that by 2023, over 50% of medium to large enterprises will have adopted a Low-code/No-code application as part of their platform development.
The proliferation of Low-code/No-code tooling can be partially attributed to the COVID-19 pandemic, which has put pressure on businesses around the world to rapidly implement digital solutions. However, adoption of these tools — while indeed accelerated by the pandemic — would have occurred either way.
Even before the pandemic, the largest, richest companies had already formed an oligopsony around the best tech talent and most advanced development tools. Low-Code/No-code, therefore, is an attractive solution for small and mid-sized organizations to level the playing field, and it does so by giving these smaller players the power to do more with their existing resources.
While these benefits are often realized in the short term, the long-term effect of these tools is often shockingly different. The promise of faster and cheaper delivery is the catch — or lure — inside this organizational mousetrap, whereas backlogs, vendor contracts, technical debts, and constant updates are the hammer.
So, what exactly is the No-Code trap, and how can we avoid it?

What is a No-Code Tool?

First, let’s make sure we clear up any confusion regarding naming. So far I have referred Low-Code and No-Code as if they were one term. It’s certainly easy to confuse them — even large analyst firms seem to have a hard time differentiating between the two — and in the broader context of this article, both can lead to the same set of development pitfalls.
Under the magnifying glass, however, there are lots of small details and capabilities that differentiate Low-code and No-code solutions. Most of them aren’t apparent at the UI level, leading to much of the confusion between where the two come from.
In this section, I will spend a little bit of time exploring the important differences between those two, but only to show that when it comes to the central premise of this article they are virtually equivalent.

Low-Code vs. No-Code Tools

The goal behind Low-Code is to minimize the amount of coding necessary for complex tasks through a visual interface (such as Drag ‘N’ Drop) that integrates existing blocks of code into a workflow.
Skilled professionals have the potential to work smarter and faster with Low-Code tools because repetitive coding or duplicating work is streamlined. Through this, they can spend less time on the 80% of work that builds the foundation and focuses more on optimizing the 20% that makes it different. It, therefore, takes on the role of an entry-level employee doing the grunt work for more senior developers/engineers.
No-Code has a very similar look and feel to Low-Code, but is different in one very important dimension. Where Low-Code is meant to optimize the productivity of developers or engineers that already know how to code (even if just a little), No-Code is built for business and product managers that may not know any actual programming languages. It is meant to equip non-technical workers with the tools they need to create applications without formal development training.
No-Code applications need to be self-contained and everything the No-Code vendor thinks the user may need is already built into the tool.
As a result, No-Code applications create a lot of restrictions for the long-term in exchange for quick results in the short-term. This is a great example of a ‘deliberate-prudent’ scenario in the context of the Technical Debt Quadrant, but more on this later.

Advantages of No-Code Solutions

The appeal of both Low-Code and No-Code is pretty obvious. By removing code organizations can remove those that write it — developers — because they are expensive, in short supply, and fundamentally don’t produce things quickly.
The benefits of these two forms of applications in their best forms can be pretty substantial:
  • Resources: Human Capital is becoming increasingly scarce — and therefore expensive. This can stop a lot of ambitious projects dead in their tracks. Low-Code and No-Code tools minimize the amount of specialized technical skills needed to get an application of the ground, which means things can get done more quickly and at a lower cost.
  • Low Risk/High ROI: Security processes, data integrations, and cross-platform support are all built into Low-Code and No-Code tools, meaning less risk and more time to focus on your business goals.
  • Moving to Production: Similarly, for both types of tools a single click is all it takes to send or deploy a model or application you built to production.
Looking at these advantages, it is no wonder that both Low-Code and No-Code have been taking industries by storm recently. While being distinctly different in terms of users, they serve the same goal — that is to say, faster, safer and cheaper deployment. Given these similarities, both terms will be grouped together under the ‘No-Code’ term for the rest of this article unless otherwise specified.

List of No-Code Data Tools

So far, we have covered the applications of No-Code in a very general way, but for the rest of this article, I would like to focus on data modeling. No-Code tools are prevalent in software development, but have also, in particular, started to take hold in this space, and some applications even claim to be an alternative to SQL and other querying languages (crazy, right?!). My reasons for focusing on this are two-fold: 
Firstly, there is a lot of existing analysis around this problem for software development and very little for data modeling. Secondly, this is also the area in which I have the most expertise.
Now let’s take a look at some of the vendors that provide No-Code solutions in this space. These in no way constitute a complete list and are, for the most part, not exclusively built for data modeling. 

1. No-Code Data Modeling in Power BI

Power BI was created by Microsoft and aims to provide interactive visualizations and business intelligence capabilities to all types of business users. Their simple interface is meant to allow end-users to create their own reports and dashboards through a number of features, including data mapping, transformation, and visualization through dashboards. Power BI does support some R coding capabilities for visualization, but when it comes to data modeling, it is a true No-Code tool.

2. Alteryx as a Low-Code Alternative

Alteryx is meant to make advanced analytics accessible to any data worker. To achieve this, it offers several data analytics solutions. Alteryx specializes in self-service analytics with an intuitive UI. Their offerings can be used as Extract, Transform, Load (ETL) Tools within their own framework. Alteryx allows data workers to organize their data pipelines through their custom features and SQL code blocks. As such, they are easily identified as a Low-Code solution.

3. Is Tableau a No-Code Data Modeling Solution?

Tableau is a visual analytics platform and a direct competitor to Power BI. They were recently acquired by Salesforce which is now hoping to ‘transform the way we use data to solve problems—empowering people and organizations to make the most of their data.’ It is also a pretty obvious No-Code platform that is supposed to appeal to all types of end-users. As of now, it offers fewer tools for data modeling than Power BI, but that is likely to change in the future.

4. Looker is a No-Code Alternative to SQL

Looker is a business intelligence software and big data analytics platform that promises to help you explore, analyze, and share real-time business analytics easily. Very much in line with Tableau and Power BI, it aims to make non-technical end-users proficient in a variety of data tasks such as transformation, modeling, and visualization.

You might be wondering why I am including so many BI/Visualization platforms when talking about potential alternatives to SQL. After all, these tools are only set up to address an organization’s reporting needs, which constitute only one of the use cases for data queries and SQL. This is certainly a valid point, so allow me to clarify my reasoning a bit more.

While it is true that reporting is only one of many potential uses for SQL, it is nevertheless an extremely important one. There is a good reason why there are so many No-Code BI tools in the market—to address heightening demand from enterprises around the world — and therefore, it is worth taking a closer look at their almost inevitable shortcomings.

Source de l’article sur DZONE

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Ebbs and Flows of DevOps Debugging

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Introduction

Ever since Patrick Debois coined the word DevOps back in 2009, teams and organizations have been clamoring to adopt relevant practices, tools, and a sense of culture in a bid to increase velocity while maintaining stability. However, this race to incorporate “DevOps” in software development practices has resulted in a perversion of the concept. This does not mean that there are no successful practices of teams adopting DevOps practices, but the word overall has become a buzzword. As per the DORA 2019 State of DevOps report, team managers are more likely to proclaim that their teams are practicing DevOps compared to the actual frontline engineers and developers.

Therefore, this piece aims to realign the meaning of DevOps as well as highlight the need for considering debugging as a core element of the practices and cultures that enable DevOps for teams. The argument for debugging as a core component in the DevOps pipeline is a result of the evident need for a shift-left in the way we build and release software, empowering developers to adhere to the intrinsic principle of you build it you run it.

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DevOps is not just automation!

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I was in the first week of a new job and the assignment was to install a company software on the local machine. In the beginning, I found that there are some documents on the internal website which I could follow to install. This was a very optimistic expectation of course. As soon as I started reading and doing the steps, I realized that there are many things that are not mentioned in the document and I began to ask a lot of questions that I do not have any answers to. I had to ask the current DevOps engineers for each unclear part. Later, I found that every day I am on a call for hours with these engineers and we achieve bit by bit of this installation together. I would say 20% of the operations were documented and automated, but the rest of the things should be done manually. Finally, I managed to install the software in a week but still, there were many things I did not know how I had done, and forgot many other details that were not in the document. 

It turns out every time we have a new hire, this situation happens again and again and there has been no update neither on the document nor in the software installation process. What amazed me was that the DevOps engineers were proud of what they have already created after years but they did not realize that no one can install that software without them. This situation created a huge amount of complexity around the software deployment and takes hours for employees to figure out things again and again. So, no matter how nice all those scripts were, it created a high overhead for the company which was quite hidden for the managers for years. 

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Technical Debt Affects Everyone

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If you’ve read our piece about the habits engineers need to beat tech debt, you might recall Conway’s law, which states that organizations which design systems […] are constrained to produce designs that are copies of the communication structures of these organizations.

It’s one of the forces that can push us towards technical bankruptcy because the systems designed by software engineers are constrained by their company’s organizational structure, over which they have little control. The right way to fight these forces is to talk about tech debt across the whole company so that everyone can understand why it’s vital to manage it carefully.

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10 Best Alternatives to Google Analytics in 2021

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When you think of installing analytics, you probably reach for Google Analytics. And you wouldn’t be alone. The platform’s tight integration with SEO and the implication that using Google products is beneficial to ranking means that Google Analytics is the most commonly installed analytics solution globally.

Google Analytics isn’t a bad choice: it’s free, it’s fairly comprehensive, and it does indeed tie most SEO efforts up with a nice bow.

But Google Analytics is also slow, extremely bad for privacy — both yours and your users’ — and for many people, it’s too unwieldy, having grown organically over the years into a relatively complex UI.

Some alternatives are fast, privacy-friendly, and geared towards different specialisms. Today we’re rounding up the best…

1. Heap

Heap is an event-based analytics platform. That means you can tell not just how many people visited your site but what actions they took when they were there. This isn’t a unique proposition, but Heap is one of the best implementations.

Heap offers an auto-track tool, which is ideal for new installations because you can get up and running immediately and fine-tune the details later. That makes it great for startups, although it’s also the choice of major corporations like Microsoft.

Heap’s free plan includes 60k sessions per year and 12 months of data history, but when you outgrow that, the business plans start at $12,000/year.

2 ChartMogul

ChartMogul is geared towards SaaS that offer subscription plans, staking a claim as the world’s first subscription data platform.

Services like Buffer and Webflow use ChartMogul to monitor their revenue and analyze the ROI of changes to their features, design, and user experience.

Ideally suited for startups, ChartMogul pricing is based on monthly recurring revenue; it has a free plan for up to $10,000 MMR; after that, pricing starts at $100/month.

3. Fathom

Fathom is an awesome, privacy-first analytics solution. It offers a simple dashboard and is ideal for anyone looking for simple analytics information to verify business decisions.

Fathom is ideally suited to freelancers, or entrepreneurs with multiple projects, as it allows you to run multiple domains from a single account. Fathom is entirely cookieless, meaning you can ditch that annoying cookie notice. It’s GDPR, ePrivacy, PECR, CCPA, and COPPA compliant.

There’s a seven-day free trial; after that, Fathom starts at $14/month.

4. FullStory

FullStory is designed to help you develop engaging online products with an emphasis on user experience.

FullStory is a set of tools, making it ideal for large in-house teams or in-house teams working with outside agencies or freelancers. It pitches itself as a single source of truth from which everyone from the marketing department to the database engineers can draw their insights, helping digital teams rapidly iterate by keeping everyone in the same loop.

FullStory uses AI to track and interpret unexpected events, from rage clicks to traffic spikes, and breaks those events down to a dollar-cost, so you can instantly see where your interventions will have the most impact.

There’s a free plan for up to 1k sessions per month; once you outgrow that, you need to talk to the sales team for a quote.

5. Amplitude

Amplitude has one of the most user-friendly dashboards on this list, with tons of power behind it. For project managers trying to make science-based decisions about future development, it’s a godsend.

The downside with Amplitude is that to make the most of its powerful data connections, you need to pump a lot of data in. For that reason, Amplitude is best suited to sites that already have a substantial volume of traffic — among those customers are Cisco and PayPal.

Amplitude provides a free plan, with its core analytics and up to 10m tracked actions per month. For premium plans, you have to contact their sales team for a quote.

6. Mixpanel

Mixpanel is a little bit more than an analytics program, aiming to be a whole suite of web tools it has ventured into split testing and notifications.

Mixpanel is laser-focused on maximizing your sales funnel. One look at the dashboard, and you can see that Mixpanel, while very well designed, has too many features to present them simply; Mixpanel is ideally suited to agencies and in-house development teams with time to invest — you probably want to keep the CEO away from this one.

Mixpanel has a generous free plan for up to 100k monthly users, with its business plans starting at $25/month.

7. Mode

Mode is a serious enterprise-level solution for product intelligence and decision making.

Ideally suited to in-house teams, Mode allows you to monitor financial flow and output the results in investor-friendly reports. You can monitor your entire tech stack and, of course, understand how users are interacting with your product. Wondering who handles the analytics for Shopify? That would be Mode.

Mode has a free plan aimed at individuals, but this tool’s scope is really beyond freelancers, and the free plan’s only likely to appeal to high-price consultants and tech trouble-shooters. For the full business plan, you need to contact Mode’s sales team for a quote.

8. Microanalytics

Microanalytics is a relatively new analytics program with a lightweight, privacy-focused approach.

Microanalytics provides a simple dashboard with acquisitions, user location, technology, and the all-important event tracking to monitor user behavior. Microanalytics is compliant with the web’s most stringent privacy laws, including GDPR, PECR, and CCPA. The tracking code is just 1kb in size, meaning that you’ll hardly notice its footprint in your stats.

Microanalytics is free for up to 10k pageviews/month; after that, the monthly plan starts at $9.

9. GoSquared

GoSquared is another suite of tools, this time aimed at SaaS. Its primary product is its analytics, but it also includes live chat, marketing tools, and a team inbox.

If you’re tired of comparing multiple tools to help make the most of your startup, GoSquared kills several birds with one stone. Perhaps most importantly, if you’re beginning to build a team and don’t have any engineers onboard yet, GoSquared has an award-winning support team and an idiot-proof setup process.

GoSquared has a free plan that’s fine for evaluating the suite and integrating data from day one. As you begin to grow, paid plans start at $40/month.

10. Segment

Segment is a little different from the other analytics tools on this list; Segment is a layer that sits between your site and your analytics. It integrates with many of the tools on this list.

There are several benefits to this approach. The main one is that different teams within your enterprise can access analytics data in a form that suits them — designers can access complex data, and management can stick to revenue flow. It also means that you can switch analytics programs with a single setting in Segment and even migrate historical data into new apps. If you’re an enterprise that wants to future-proof its customer intelligence gathering, Segment is worth considering.

Segment is trusted by some of the web’s best-known names, from IBM to Levis, and…ahem…Google.

Segment is free for up to 1k visitors per month, and after that, the team plan starts at $120/month.

Source

The post 10 Best Alternatives to Google Analytics in 2021 first appeared on Webdesigner Depot.


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How Engineers and CTOs Can Use a Simple, Universal Prioritization Technique Devised by Eisenhower

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Are you familiar with any of the following scenarios?

  • We are never doing anything significant, neither benefitting ourselves nor humankind
  • We are always firefighting, stressed out, and going through mental trauma
  • We are doing considerable work but never on time, so we are missing out on the rewards

Instead, we should be doing substantial work at the right time so that both you and humankind are benefitted from your work. The question is, how.

Source de l’article sur DZONE

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Best Tips to Manage Your Remote Software Development Teams

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For a few years now, remote software development has become quite the trend and favorite. Remote software development teams who constitute remote development are usually a team of designers, product engineers, scrum masters, developers, and product managers. All of them work individually over the project cumulatively, resulting in a product’s delivery. 

Generally, in outsourcing, the concerned remote software development company will have dedicated managers overseeing the projects. But post the outbreak of the dreaded pandemic, things are changing. Due to work from home, remote teams operate from different locations. For Business Owners, it is a tedious task to ensure the management of these teams. If you happen to be outsourcing your product development or hiring a remote team to design, develop, and deliver projects, here are a few coolest tips to help you manage them. 

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Agile Design Automation With Logic Bank

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Automation

As engineers, we are always mindful of the need to minimize cost and time.  Experience has taught us that while automation is valuable in reducing code, we must also preserve design flexibility and enable agile iterations.  Let’s break that down a bit, and then illustrate with an example.

Automation (Reduce Routine Code — Executable Specifications)

To warrant the learning curve, automation must significantly reduce routine coding.  25%  reduction in code is not compelling enough.

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Top 5 Reasons Presto Is the Foundation of the Data Analytics Stack

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The need for data engineers and analysts to run interactive, ad hoc analytics on large amounts of data continues to grow explosively. Data platform teams are increasingly using the federated SQL query engine PrestoDB to run such analytics for a variety of use cases across a wide range of data lakes and databases in-place, without the need to move data. PrestoDB is hosted by the Linux Foundation’s Presto Foundation and is the same project running at massive scale at Facebook, Uber and Twitter.

Let’s look at some important characteristics of Presto that account for its growing adoption.  

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