Streaming time series data from brokers and services that are on-premises or in the cloud to a cloud-based database is a resource-intensive process requiring third-party software and heavy customizations. Today we’re announcing InfluxDB Native Collectors to make it easy for developers to collect, process, and analyze data by subscribing directly to supported message brokers.
SAN FRANCISCO — August 23, 2022 – InfluxData, creator of the leading time series platform InfluxDB, today announced new serverless capabilities to expedite time series data collection, processing, and storage in InfluxDB Cloud. InfluxDB Native Collectors enable developers building with InfluxDB Cloud to subscribe to, process, transform, and store real-time data from messaging and other public and private brokers and queues with a click of a button.
Technology is the catalyst that propels business innovation. It’s the means of ridding inefficiency, delay, and inconsistency from business processes. Technology is the essential element of success for virtually every business in every industry. That’s why technology excellence ranks at the top of every business leader’s list of priorities. Maintaining the level and quality of technology service you need to be competitive comes with many challenges.
In this issue of the Calico Community Spotlight series, I’ve asked Burak Tahtacioglu from ParkLab Technology to share his experience with Kubernetes and Calico Open Source. Let’s take a look at how Burak started his Kubernetes journey, and the insights he gained from Calico Open Source. Q: Please tell us a little bit about yourself, including where you currently work and what you do there. I am a Sr. Software Developer in our Developer Experience team.
Back in May of this year, Verizon published its 15th annual Data Breach Investigation Report (DBIR) for 2022 which states that 82% of breaches involved the human element, whether it is the user of stolen credentials, phishing, misuse, or an error, people are the biggest contributors to security incidents and breaches. The past several months has also resulted in numerous phishing attacks via corporate email and SMS text messages.
The way organizations process logs have changed over the past decade. From random files, scattered amongst a handful of virtual machines, to JSON documents effortlessly streamed into platforms. Metrics, too, have seen great strides, as providers expose detailed measurements of every aspect of their system. Traces, too, have become increasingly sophisticated and can now highlight even the most precise details about interactions between our services. But alerts have remained stationary.
In the first portion of the underutilized RMM features series, we discussed the use of Site Concentrators and Data Overdue Cross-Checks. This time we’re going to discuss Monitoring Templates. MSPs have shied away from Monitoring Templates in the past because of the effort needed to set them up. I think this is the wrong way to look at them; we need to be thinking long-term here.
In the monitoring industry there’s a complicated and frustrating conversation that persisted over the years: how do you deal with the enormous volume of data generated by instrumentation? On one side of the aisle, you will find a cohort of vendors and developers telling you that you have to sample data, followed immediately by another group telling you that sampling will ruin the accuracy of incident analysis. They’re both right.
