Log centralization is kind of like brushing your teeth: everyone tells you to do it. But until you step back and think about it, you might not appreciate why doing it is so important. If you’ve ever wondered why, exactly, teams benefit from centralized logging and analysis, keep reading. This article walks through five key advantages of log centralization for IT teams and the businesses they support.
Monitoring solutions are a vital component in managing an application’s environment. From the systems layer all the way up to the end user’s connection to the app, you want to find out how the platform is performing. Indicators like CPU, memory, the number of connections, and overall health help teams make informed decisions for guaranteeing uptime. Teams monitor metrics (short-term information) and logs (long-term information) mainly from a reactive perspective.
Site Reliability Engineering (SRE) and Operations (Ops) teams heavily rely on notifications. We use them to know what’s going on with application workloads and how applications are performing. Notifications are critical to ensuring SREs and Ops teams can resolve errors and reduce downtime. They’re also crucial when monitoring environments — not only when running in production but also during the dev-test or staging phase.
Ayyeka connects decision makers to their remote assets, so they can make better and timely decisions. Their Industrial IoT solutions for remote monitoring enable asset owners and operators to achieve enhanced compliance and improved efficiency across the board. Hardware, software, and digital services are merged to deliver an end-to-end experience and value when connecting asset and infrastructure networks to data systems.
Access to any airport is tightly governed. When you’re one of Europe’s busiest airports and a high-profile piece of national infrastructure, you cannot have unauthorized people wandering about. At Copenhagen Airport, we have more than 20,000 people cleared to access the airport. These might be security staff, baggage handlers, IT service providers, catering teams, and others. As the airport has grown, so has the number of on-site workers.
Building successful machine learning (ML) production systems requires a specialized re-interpretation of the traditional DevOps culture and methodologies. MLOps, short for machine learning operations, is a relatively new engineering discipline and a set of practices meant to improve the collaboration and communication between the various roles and teams that together manage the end-to-end lifecycle of machine learning projects.
I recently spoke to the IT Director and Head of End User Computing at a leading healthcare company who implemented Salesforce globally across their entire employee user base 9 months ago (before later becoming a Nexthink customer). She told me their Salesforce licensing model was similar to others you’ll see in market: a set of base licenses and then selected add-ons based on employee roles – with some at no charge and others priced ala carte. Her problem? License metering.
What do Google’s DevOps Research and Assessment (DORA) and Rollbar have to do with each other? DORA identified four key metrics to measure DevOps performance and identified four levels of DevOps performance from Low to Elite. One way for a team to become an Elite DevOps performer is by focusing on Continuous Code Improvement.
As everything good in life, serverless also comes with its downsides. One of them is the infamous “cold start”. In this article, we’ll cover what they are, what influences serverless startup latency, and how to mitigate its impacts in our applications.
Globally the impact of AI is increasingly growing year on year in every industry sector. Opening new scopes in construction & architecture sector, the global AImarket is estimated to grow at a CAGR of 29.4% (around) from 2019 to 2026 and is expected to reach around US$ 2.1 Billion by 2026.
