Operations | Monitoring | ITSM | DevOps | Cloud

At LogicMonitor, ingesting and processing time series metric data is arguably the most critical portion of our unified observability platform. In order to fully prepare for growth, scale, and fault-tolerance, we have evolved what we refer to as our Metrics Processing Pipeline from a monolith to a microservice-driven architecture.

Finding service relationships and diagnosing bottlenecks within an application can be incredibly difficult to accomplish, especially if your applications are spread across multiple services, with both internal and external service calls. Although users could get granular visibility into individual traces using our Distributed Tracing features, they couldn’t see how their services were connected across different traces.

A couple of weeks ago, I had the opportunity to attend AWS re:invent, one of the biggest cloud industry events of the year. An event so massive and big that only AWS can pull it off – 50,000 people marching across half a dozen of the finest hotels on the Las Vegas strip. The expo hall alone would have taken more than a couple of days to cover all the vendor booths spread across the expansive Venetian convention center.

FluentD is a free and open-source data collector. With its decentralized ecosystem, it’s known for its built-in reliability and cross-platform compatibility. One of the biggest challenges in big data collection is the lack of standardization between collection sources. They just aren’t able to talk to each other. With FluentD, you can address one of the biggest challenges to big data log collection.

NetApp, formerly Network Appliance Inc., is a computer technology company specializing in data storage and management software. NetApp provides cloud data services, primarily for the management of data. It also offers management solutions for applications.

Amazon Web Services (AWS) products can feel countless, and at LogicMonitor, we are working tirelessly to bring monitoring support to as many of them as possible. With so many products and tools already on your plate, we want to make sure that monitoring is not a hassle, but rather a trusted companion. AWS provides tools that help with application management, machine learning, end-user computing, and much more.

Today, data is invaluable. Many businesses store large amounts of it for everyday operations. Some information is stored in a hierarchical form, but companies must often hold significant amounts of data without any organization. The solution? Microsoft Azure’s Blob Storage. In this article, we’ll consider the key elements of Blob Storage, how it works, and why it’s important.

Google Cloud Provider (GCP) Storage uses buckets to store data. In GCP Storage, you can manage files and folders using the same tools and APIs you use to manage files in a standard container. Using GCP buckets, you can store any type of file, photo, video, or even projects. Essentially, GCP buckets are logical containers for your data. There is no limit to the number of buckets you can create; each bucket can hold any amount of data.