As well as being a search engine, Elasticsearch is also a powerful analytics engine. However, in order to take full advantage of the near real-time analytics capabilities of Elasticsearch, it is often useful to add structure to your data as it is ingested into Elasticsearch. The reasons for this are explained very well in our schema on write vs. schema on read blog post, and for the remainder of this blog series, when I talk about structuring data, I am referring to schema on write.

There’s no getting around the prevalence of heterogeneous tools in IT operations and DevOps. Teams have built up ecosystems of tools over time for different infrastructure, workflows and applications – and while some of them are outdated or duplicitous – plenty still serve a useful purpose in the enterprise. Yet unfortunately tool sprawl adds to the complexity of monitoring a hybrid or multi-cloud environment.

I am spending a considerable amount of time recently on distributed tracing topics. In my previous blog, I discussed different pros and cons of various approaches to collecting distributed tracing data. Right now I would like to draw your attention to the analysis back-end: what does it take to be good at analyzing transaction traces?

Nexthink’s Chief Product Officer, Samuele Gantner, spoke recently with Digitalisation World, a popular tech news company to discuss the next generation of our Experience Platform. IT departments around the world are under considerable stress nowadays but there are several fast and practical solutions available in the Nexthink platform that our customers are using to help support their remote workers and flexible work environments.

SMEs struggle with keeping business processes running smoothly, from managing workflows to keeping records on sales and customer interactions. However, small businesses can make their life in business smarter and easier by integrating automation tools. Business automation is fast transforming how brands carry out their operations. In essence, the size of business does not matter when it comes to automation.

Monitoring the state of DevOps, multi-cloud, microservices and data centre environments is no easy task. You can’t manage what you can’t see. Gaps in your monitoring capability leave your enterprise vulnerable to catastrophic, customer impacting infrastructure blind-spots.

In January 2020, the UK recorded its first case of COVID-19. The world was facing the unknown, and the only apparent way to contain the virus was for every nation across the planet to shut down. As governments across the globe planned for the unknown, organizations rapidly began seeking ways to support efforts to save lives and restart the economies of these countries. One such endeavor was the vital role technology could play in contact tracing.

I’m excited that ServiceNow has been named a Leader in the 2020 Gartner Magic Quadrant for Software Asset Management Tools. We were recognized for our Software Asset Management (SAM) solution, which we believe helps reduce software costs and mitigate license compliance risk with actionable IT insights. We think It’s a great example of how ServiceNow makes work, work better for people. ServiceNow innovates by listening to our customers.

As an executive your focus is always on delivering the most value from every investment. Value for your customers, and of course value for yourself. Yet there are so many places in the value delivery process where things can – and do – go wrong. The term “value stream” describes the end- to-end process of developing and delivering software to your clients.

I recently spoke with Alex Skrivseth, the Operations Manager at The Shed App, and discovered how he’s using InfluxDB to monitor the current levels of gas and diesel at various gas stations. Simply by extracting IoT sensor data, he has been able to provide valuable previously inaccessible data to fuel truck drivers.