Unexpected events make the healthcare profession one of the most challenging industries to navigate and plan for. Sudden, abrupt patient situations tend to occur, increasing the workload of healthcare providers. Similar, process efficiencies and productivity are a reflection of the care team’s ability to communicate. When teams are on the same page, patient wait times are significantly reduced and results are improved.
Nowadays, it’s not uncommon to see enterprise IT leaders in a situation that seems like a catch 22. Oftentimes, they are expected to be involved in making data-driven decisions for augmenting productivity and profitability. Paradoxically, they are preoccupied with what they consider as their core responsibilities – applying best practices to safeguard the IT infrastructure and expediting investigations when incidents occur.
You can’t really blame most people for thinking employee surveys are a lost cause. Survey fatigue is a real thing, and every organization has its unique red tape when it comes to data collection and HR policy. If you can even manage to convince your employees to respond to that well-crafted questionnaire, how do you separate the signal from the noise and operationalize this information for ITOps?
TL;DR: Fast-moving IT stacks see frequent, long and painful outages. Thousands of changes – planned, unplanned and shadow changes – are one of the main reasons behind this. Until now, IT Ops, NOC & DevOps teams didn’t have an easy way to get a real-time answer to the “What Changed?” question – the answer that can help reduce the duration of outages and incidents in these fast-moving IT stacks. Now, with BigPanda Root Cause Changes, they do.
If you have anything to do with the world of cloud computing or even programming for that matter, then I’m sure you’ve heard of different terms being tossed around such as “serverless computing” or “containers,” and even “monolithic architectures.” A lot of people who understand such computing methods can have a bad habit of using these terms without leaving any explanation as to what they are.
First time this year, multi-cloud enterprises, as a customer segment of Sumo Logic, have grown faster than any other segment: 50% Y/Y. What took so long? In my conversations with enterprises over the last 5 years, there was only one strategy for public cloud and it was multi-cloud. But evidence of multi-cloud usage was sparse at best. Data from our Continuous Intelligence Report in previous years didn’t find much to support that the strategy for multi-cloud was being implemented.
A Syslog server allows for the collection of logs into a centralized log repository. This centralized log repository allows for quick searching of your logs across your organization through different visualization tools. The Syslog web interface will provide the easiest access to the logs, and allows for easy secured remote access.
Whether you’re slinging code, managing developers, wrangling servers, or filling most other roles in the modern tech firm, you care about keeping your software running while bringing home the bacon. If your website or application is down, you’re not making money. (Or, if you aren’t in this for profit, your message isn’t getting to the people who need it.) Therefore, it’s everyone’s job to keep things running smoothly.
Logz.io was born out of a frustration with the realities of managing an open source monitoring and troubleshooting stack across distributed systems at cloud scale. Today, we introduce another tool to streamline log mamagement: Log Patterns.
BYOD stands for bring your own device, whereby your organization lets employees use personal devices for day-to-day work. Sounds simple, right? Unlike corporate devices where the enterprise has complete freedom to choose users’ device types and platforms, BYOD is a different case altogether. In BYOD environments, employees often use different devices manufactured by different OEMs running on multiple OS versions.
