Operations | Monitoring | ITSM | DevOps | Cloud

As technical professionals we spend a lot of time developing technical skills. Checking the right boxes of experience with languages, tools, and technologies is what typically lands us a job interview for our specialty. But what wins the job in DevOps — and carries you to success in it — are your human skills. Even more than technical chops, personal traits like mindset, communication skills, and work habits are your strongest assets in making DevOps work.

In my introduction to this blog series, I talked about why Unified Endpoint Management (UEM) is more relevant than ever before. While reading this blog put your own experiences into perspective with how you and your company were forced to work during COVID-19.

Modern applications enable enterprises to scale faster with better efficiency and resilience. The main advantage of a multi-cloud/hybrid cloud infrastructure is in its highly distributed architecture that offers proximity – bringing end users closer to the service provider.

The largest remote working experiment the world has ever faced is entering a new phase as the era of hybrid work begins. For IT and DevOps teams on the frontline, this is a time of enormous pressure. Along with its many benefits, hybrid working can also bring considerable disruption. Enabling and supporting the hybrid model is the next big challenge facing organizations around the globe. We wanted to find out what this new reality means for these teams.

But it’s better than nothing… Most of the industry is racing to adopt better observability practices, and they’re discovering lots of power in being able to see and measure what their systems are doing. High data availability is better than none, so for the time being, what we get is often impressive. There’s a qualitative difference between observability and data availability, and this post aims to highlight it and orient how we structure our telemetry.

A modified version of this blog post appeared in the June 2021 issue of Signal magazine. Decisions that need to be made in an instant require answers in real time, but existing big data systems are unable to return queries quickly enough for real-time analytics. And with growing data being queried by more connected users than ever before, it’s getting increasingly challenging to maintain fast reaction times.

TL;DR: We recommend that you use the new point-in-time functionality in Elasticsearch if you can. The scroll API is no longer recommended for deep pagination (even though it still works). Most data is constantly changing. When querying an index in Elasticsearch, you are essentially searching for data at a given point of time.

In a previous post, we described how we envision cloud-native initiatives reaching the 2.0 phase, where phase 1 was centered around providing clusters and running its underlying infrastructure effectively. Now that teams are starting to move some of their existing services to a microservices architecture, developers and platform engineers are being tasked with implementing the right policies and governance controls to ensure applications are running as securely as possible.

The ongoing news of massive cyberattacks on manufacturing and energy companies has been a wake-up call. Operational Technology (OT) Security had not been on the radar of many CISOs and plant managers until they got hit. After reacting in a defensive mode last year it is time to step up with a proactive security strategy including OT. Secure Factory by Splunk helps manufacturing companies better understand and address their unique security challenges.

As my colleague, Tim Frank, wrote about recently in his blog post, "The Department of Defense Data Strategy: An Important Start," in late 2020 the Department of Defense (DoD) released its new Data Strategy — providing focus and direction for the Department’s efforts to become data-centric at all levels of its enterprise.