Everyone’s talking about Platform Engineering these days. Even Gartner recently featured it in its Hype Cycle for Software Engineering 2022. But what is Platform Engineering really about? Is it the next stage in the evolution of DevOps? Is it just a fancy rebrand for DevOps or SRE? As a veteran of the PaaS (Platform as a Service) discipline about a decade ago, and a DevOps enthusiast at present, I decided to delve into this topic, peel off the hype, and see what it’s about in practice.

IT admins face pressure from all sides. Besides tracking and securing data across devices, they must also manage a changing inventory of physical and digital assets while adhering to an executive directive to make technology an enabler for growth. Software deployment can be a particularly daunting task. Deploying software through an automated solution is just a click of a button, but what are the don’ts to keep in mind?

Businesses need a new, more flexible solution to make digital transformation far easier, says Daniel Blackwell, Product Manager – Networks & Security, Pulsant Digital transformation can provide businesses with a more flexible approach to infrastructure that simplifies the delivery of services and applications. However, this journey to digital transformation can introduce its own complexities that require a new way of thinking.

The events over the past two and a half years have radically changed the world. Digital transformation initiatives went from being a priority to an urgent imperative. Enterprises that had not already migrated data to the cloud rushed to do so during the pandemic, and others accelerated their on-premise-to-cloud shifts. Hybrid and multi-cloud environments become the new reality for many organizations who want to get the most out of their on-premises and cloud investments.

Elastigroup predictive autoscaling uses a machine learning algorithm to accurately predict the CPU utilization pattern of your workloads and increase the number of instances based on the projected CPU utilization. Predictive autoscaling also helps in cases where your instances/applications take a lot of time to boot up. Predictive autoscaling can scale the instances in advance of the actual traffic and thus saving up to 30 minutes of startup time.

Monitoring KSM (Kernel Same-page Merging) performance at deduping memory shared across VMs.

Most software companies rely on DevOps at some scale to aid their software development and deployment processes. DevOps has recently seen a major increase in popularity due to the advent of cloud-based tools and automation possibilities. DevOps can help you completely forget the woes of deploying software and focus better on building better apps and providing a holistic experience for your end user. However, just like other things in tech, DevOps is not perfect.

Cyber Essentials is a UK government backed scheme, developed by the National Cyber Security Centre. Since its inception the scheme has become the benchmark for IT security, helping organizations to deploy technical controls to guard against the common types of cyber-attacks and improve data security.

For software development teams to make meaningful progress, they must invest in efficient monitoring, reporting practices, and tooling. This is because only by keeping track of select metrics, such as those pertaining to application performance, will you know whether you are on the right track. Without knowledge of whether the software is functioning and performing as it is supposed to, there is no way of knowing what, if any, changes need to be made.

Containers have been the buzz among developers in recent years with the adoption of cloud-native orchestration tools like Kubernetes and DevOps workflows centered around containers. At the same time, virtual machines (VMs) still power many enterprise workloads, whether they’re running in a public cloud provider like Azure or an on-premises data center running VMware. In one of my early jobs, we built a private cloud—in 2012. This was a ground-breaking project at the time.