In a previous post, I talked about the potential of AIOps and why true AI (Artificial Intelligence) hasn’t had much impact in the monitoring space yet. However, I believe Algorithmic IT Operations can help and will share the path LogicMonitor is taking to get there in this post.
NoSQL databases have always been regarded as a notch above SQL databases. The primary reason for the soaring popularity of NoSQL databases is their dynamic and cloud-friendly approach to seamlessly processing data across a large amount of commodity servers. With high scalability, availability, and reliability, AWS’s DynamoDB is a great example of a fully-managed NoSQL database.
Many teams choose Atlassian Server products because they want or need control over their data and infrastructure. But did you know that Atlassian offers another option for you to deploy on your own infrastructure? This alternative is called Atlassian Data Center, our self-managed enterprise offering, which provides the same functionality you know and love in our Server products, but has additional capabilities to better serve enterprise organizations.
Black Friday sales are not just for brick-and-mortar retailers anymore. In 2017, retail store visitors on the biggest shopping day of the year dropped four percent. Meanwhile, mobile and online Black Friday sales rose 17 percent last year, with customers spending almost $8 billion. The entire weekend (Black Friday through Cyber Monday) brought in almost $20 billion in online sales.
This week we released Grafana v5.3.4 which includes an important security fix, so we recommend you update your instance today. Also in this issue of TimeShift we share the first group of confirmed GrafanaCon LA speakers, and tell you about 5 plugins that have been recently updated.
Mattermost 5.5 includes several new features and improvements that will help your team get more done in less time.
In this blog miniseries, I’m talking about how to think about doing data analysis, the Honeycomb way. In Part I, I talked about how heatmaps help us understand how data analysis works. In Part II, I’d like to broaden the perspective to include the subject of actually analyzing data.
Red Hat OpenShift container platform enables enterprise/start-ups to develop, deploy, and manage existing container applications on-premise or in the cloud. Organizations can make use of proven, efficient, and powerful open-source technologies to create and deploy applications that are secured, scalable, highly available with minimal management and configuration.
Organizations that handle logging at scale eventually run into the same problem: too many events are being generated, and logging components can’t keep up. Even with persistent queues and other mitigating features enabled, there’s simply not enough of a buffer between log generators and log ingesters to handle the volume of log lines coming in.
We have a running joke at Stackery regarding our tiny little gong that’s used to mark the occasion when we get a new customer. And while I’m all about the sales team celebrating their successes (albeit with a far-too-small gong), I felt like the dev team needed its own way to commemorate major product releases and iterations.
