Operations | Monitoring | ITSM | DevOps | Cloud

IT teams in modern workplaces are no longer spending the bulk of their time troubleshooting and break/fixing issues. As in any service industry in the consumer world, IT service workers are now expected to deliver a great experience to their consumers – the employees. Managing the workplace has become much more like managing a theme park, where every aspect of its real estate should exhibit interest, joy, and fun; everything that makes up a great experience.

Legendary race car driver Carroll Smith once said, "until we have established reliability, there is no sense at all in wasting time trying to make the thing go faster." Even though he was referring to cars, the same goes for technology: no amount of code optimization or new features can replace stable systems. Unfortunately, much like race cars, it's hard to know that a system is unreliable until it blows a tire, the brakes stop working, or the steering wheel comes off the column.

This article was originally published in The New Stack and is reposted here with permission. You might need to perform anomaly detection or forecasting if you’re working with time-series data. The first step before working on your time series is finding the right data store. To effectively detect or forecast your data, you will require a data store that can handle a large volume of data at a high ingest rate. Therefore, you might want to look at using a purpose-built time-series database.

It’s already September! Time flies by when you’re getting things done, and we’ve been a busy bunch of bees here at Honeycomb. 🐝 We’re excited that we’ve gotten to share some of those changes with you already, like our relaunched interactive sandbox and the beta release of our OpenTelemetry log support and Go distribution, but that’s just the tip of the iceberg.

Cloud adoption has been on an upward trajectory for over a decade with no signs of slowing down. As widescale migration becomes the norm, organizations are realizing cloud financial management — also referred to as FinOps — is critical to creating long term value in the cloud. Building a culture of financial discipline requires visibility and a strategy for measuring success along the way.

Pranay, one of the the co-founders at SigNoz, was recently invited as a guest speaker by Jonah Kowall, CTO at Logz.io on his OpenObservability Podcast. In the podcast, Pranay talks about the mission behind SigNoz - unifying traces, metrics, and logs in a single platform and interface. He also shared anecdotes about the evolution of SigNoz since its inception, the community adoption, and its contribution to SigNoz.

If we’ve learned anything from the past few years, it’s the routines we used to consider normal—like being able to walk onto a college campus and attend class in-person each day—can change in an instant.

Database performance is critical to business revenue. Slow and non-responsive databases can result in hundreds of thousands or millions of dollars in lost revenue from poor customer experience and downtime. High expectations in performance require IT infrastructure to function at full speed. In 2006, an Amazon study found that every 100ms in added page load time cost them 1% in sales.

Companies can take big strides toward “preventing preventable” incidents by minding what they measure. What’s in a name? In Measuring what matters, one of the panels at our RESOLVE ‘22 event, the three words in the title reflect a plan successful IT Ops teams have embraced to reduce the complexity of their reporting systems—resulting in a faster path for companies to make more effective use of all the IT resources at their disposal.

The recipe for a delightful employee experience is all about adding heaps and heaps of delightful service desk experiences. Think about it, what good is a service desk if it doesn’t solve your employees’ day-to-day tech issues? According to Forrester’s The State Of The Service Desk, 2022 report, only 66% of employees contact their service desk more than once a year.