In concise words, ModelOps is a practice that introduces a modern set of tools and techniques that makes the process of developing, deploying, and managing predictive analytics models, including artificial intelligence and machine learning, more effective.
This article was originally published on The Chief I/O: What is ModelOps?
You’ve heard of DevOps, AIOps, MLOps, DevSecOps, and many other derivatives of the overused “Ops” suffix. So you’re wondering, is this ModelOps one of the many “Ops” terms?
ModelOps is a crucial term, technology and practice, branched from DevOps, that happens to share the infamous Ops suffix because of its implementation in Operations. We’ve explained what exactly it is, how it came about, and its goals in this article.
A survey by Gartner in 2018 recorded that 37% of the participants have deployed AI solutions in some form…
This post appeared first on FAUN: The 1st Crisis in Software Engineering, the Roots of Agile and the Short Story of DevOps
For some of us, the interest we have in software engineering started when we played our first video game when we were young, for others it started with coding bootcamps and others started having an interest in software engineering in college.
Whether you started this or that way, there’s a common thing that most of us share, we initially started with the intention of building visible code whether it’s a game, a website, or a mobile application.
…
Announcing our coming-soon FAUN Topic for Gophers: GoPa. The newsletter about the Go programming language.
After DevOpsLinks, Shipped, Kaptain, and PyDo (announced the last week), I’m happy to announce that FAUN is launching the 5th newsletter for software engineers: GoPa — The Gopher’s newsletter featuring must-read tutorials, news, and libraries every week!
This time, it’s about the fantastic programming language Golang. We know that many of you, especially in the DevOps space, are either learning or using Go on a daily basis. …
Training machine learning model for production use is a hectic and time-consuming process. With MLOps, this narrative is changing. MLOps, a descendent of DevOps, provides the automation and scalability required to develop, train, and continuously deliver modern agile machine learning applications. Machine learning lifecycle management tools are important to implement DevOps practices in your machine learning environment. Using popular, efficient open-source tools such as those mentioned in this article is an excellent start to your machine learning MLOps journey.
This article was originally published on The Chief I/O: 6 Open Source MLOps Platforms To Enable DevOps for your ML Project
Suppose you want to maximize the business potential of your production machine learning models and create new products. In that case, it’s important to equip your technical teams with the best tools and practices for an efficient and agile machine learning workflow.
Data scientists, machine learning experts, and developers are supposed to be spending time and resources researching, building, and innovating intuitive, modern business solutions. One of the concepts that bring about this result in machine learning is MLOps.
We’re launching the new FAUN Topic (weekly newsletter) dedicated to the Python ecosystem.
I’m happy to announce the imminent launch of PyDo, our 4th weekly newsletter, after DevOpsLinks, Shipped, and Kaptain. We’ll start the 1st issue of PyDo on May 6th. Don’t miss it!
Adopting AIOps solutions and choosing the right tool can be a game-changing decision for small and large organizations as the advantages are enormous. It reduces the workload on IT teams, increases their productivity, and makes your application faster, more innovative, efficient, and reliable.
This article was originally published on The Chief I/O: 5 Use Cases of AIOps
Today, many companies are transitioning from traditional on-premise infrastructure to a dynamic and hybrid mix of on-premise, private and public cloud environment which runs on various software that allows it to scale based on demands. Applications across this environment generate quintillions of data that keep growing.
Traditional IT management solutions cannot keep up with correlating and organizing this growing amount of data and often leaves IT operators, with a load of issues that leads to application inefficiency and, ultimately, downtime. …
These news articles were originally published on The Chief I/O Cloud-native news.
Devops Pros Salary on the Rise Despite the Effect of the Pandemic
Thanks to an all-time high in demand for fast digitization, DevOps professionals also saw an all-time high in salary increments. More than a third now earn $150,000 to $250,000 per annum in the US.
- Social Distancing ensured demand for digital initiatives increased globally.
- The worldwide rise wasn’t just about the United States of America, and Japan took the lead in percentage gain.
- DevOps professionals in the United States make more money than anywhere else in the world.
- IT managers and information security trail widely to engineering managers for income.
Continue reading this news on Devops Pros Salary on the Rise…
Advanced security of your cluster is one of the downsides of Kubernetes that requires serious attention. Attackers can take advantage of a loophole or misconfiguration in a Kubernetes cluster to exploit your application environment and probably force you out of business. Thankfully, there are third-party, free and open source Kubernetes security tools developed to help scan your cluster and identify potential loopholes before it’s being exploited.
This article was originally published on The Chief I/O: 7 Kubernetes Security Scanners to Use in Your DevSecOps Pipeline
With the growing number of organizations using Kubernetes as an orchestration tool due to its flexibility and other benefits, clusters’ security is becoming more vulnerable.
Even though Kubernetes provides basic IAM and role-based access control (RBAC) roles to secure the system, they are too basic and does not meet the security requirements of modern application and system breaches are on the rise like never before.
To address this issue and improve Kubernetes clusters’ security, many organizations have developed free open-source and…
These news articles were originally published on The Chief I/O Cloud-native news
Cloudflare Launches its 18th Data Center in Toronto, Canada
The reliability, security, and performance specialists have a new base in one of the fast-growing economies in the world. On April 19, 2021, the company announced that Toronto would house its new Canadian home of operations, allowing them to prove their commitment and show support to their increasing customer base.
- This is the cybersecurity firm’s second data center in Canada, the first was in 2012.
- Cloudflare’s global customer evaluation falls to 3.5 million coming from over 200 cities in over 100 countries.
- Out of 70 billion daily cyberattacks, 3.2 billion, which is about 4.6%, emanate from the Canadian internet.
When implemented accurately, DevSecOps significantly increases the productivity of developers and improves the efficiency, quality, and security of the whole software, allowing organizations to release new applications into production quickly. And as enterprises move from on-premises software to the cloud and the implementation of DevOps in their IT operations, the need for better DevSecOps tools and services is on the rise.
This article was originally published on The Chief I/O: 5 DevSecOps Platforms to Watch in 2021
Using some of the DevSecOps tools below will help in implementing and automating the required security measures for your IT infrastructure.
DevSecOps Platforms to Watch in 2021
Security in the cloud and cyberspace at large is and should always be one of the main concerns of software companies and every organization that uses technology to provide business solutions.
In the face of the Covid-19 pandemic, Cision, a PR software company reported a 400% increase in phishing, DDoS, malware, and other cyber threats compared to the pre-pandemic period.
The compulsory shift…
